Census Region Research Articles

Disparities in Penile Cancer Incidence, Mortality, and Place of Death Trends From 1999 to 2020

IntroductionPenile cancer is rare in the United States (US); however, disparities have been found in the incidence, treatment, and outcomes of penile cancer. There is a need for evaluation of recent trends in penile cancer mortality, incidence, and place of death across all demographics. Materials and MethodsUsing the CDC WONDER database, penile cancer-specific mortality (PNCSM) trends in the US were evaluated from 1999 to 2020 by race/ethnicity, age group, census region, and place of death. Penile cancer incidence trends for the US from 1995 to 2019 were gathered from the NAACCR database. Average annual percent changes for mortality and incidence rates were determined using Joinpoint regression modeling. Univariable and multivariable logistic regression were used to evaluate independent predictors associated with place of death. ResultsFrom 1999 to 2020, 5833 people died from penile cancer in the US. Overall PNCSM increased by 1.8% per year from 1999-2020 (95% CI, 1.3%, 2.2%). Non-Hispanic White patients and Hispanic patients had increasing PNCSM rates from 1999-2020 (2.1 [95% CI, 1.5%, 2.7%]; 1.9 [95% CI, 1.0%, 2.8%], respectively). From the place of death analysis, Hispanic patients were at higher odds of dying at home or hospice when compared to non-Hispanic White patients (adjusted odds ratio [aOR] = 1.19, P = .045). Age-adjusted incidence rates for all stages of penile cancer increased significantly from 1995-2016 (AAPC, 0.7% [95% CI, 0.4%, 1.0%]), driven by regional and distant penile cancer incidence rates (AAPC 1995-2019, regional: 2.0% [95% CI, 1.7%, 2.4%]; AAPC 1995-2019, distant: 2.5% [95% CI, 1.8%, 3.1%]). ConclusionThe increasing penile cancer-specific mortality and incidence rates indicate the need for further improvements in screening, diagnosis, and treatment. Widespread efforts across all demographics are needed to ensure early detection of the disease.

Accelerometer-Based Estimates of Physical Activity and Sedentary Time Among Samoan Adults.

The prevalence of obesity-related cardiometabolic disease in Samoa is among the highest globally. While physical activity is a modifiable risk factor for obesity-related disease, little is known about physical activity levels among adult Samoans. Using wrist-worn accelerometer-based devices, this study aimed to characterize physical activity among Samoan adults. Samoan adults (n = 385; 55% female, mean [SD] age 52 [10] y) wore Actigraph GT3X+ devices for 7 to 10days. General linear models were used to examine mean daily minutes of sedentary time, light physical activity, and moderate to vigorous physical activity by various participant characteristics. Time spent in moderate to vigorous physical activity did not differ statistically between men (88 [5]min; 95% confidence interval [CI], 80-97) and women (78 [4]min; 95% CI, 70-86; P = .08). Women, however, spent more time than men in light physical activity: 380 (7)minutes (95% CI, 367-393) versus 344 (7)minutes (95% CI, 329-358; P < .001). While there were no differences in physical activity by census region, education, or occupation among women, men in urban areas spent significantly less time in moderate to vigorous physical activity than those in peri-urban and rural areas (P = .015). Women with class II/III obesity spent more time in sedentary activities than those with healthy weight or overweight/class I obesity (P = .048). This study characterizes physical activity among Samoan adults and highlights variation by sex, urbanicity, and weight status. In providing initial device-measured estimates of physical activity in Samoa, this analysis establishes a baseline from which the success of future attempts to intervene on physical activity may be assessed.

Down Syndrome: Evaluating Disparities in Place of Death in the United States Using Centers for Disease Control and Prevention's Wide-Ranging Online Data for Epidemiologic Research (CDC-WONDER) Database Over 22 Years.

The Uniform Determination of Death Act(UDDA) ensures that individuals with irreversible cessation of circulatory, respiratory, or brain functions receive timely palliative care. Our research has focused on identifying disparities in mortality among individuals with Down syndrome (DS) based on gender, age, racial groups, and geographic regions within the United States over 22 years. This study aims to analyze differences in the location of death, including hospitals, nursing homes, hospice care facilities, and unspecified locations, considering demographic and regional variables. Utilizing a cross-sectional observational study design, we extracted data from the Centers for Disease Control and Prevention's Wide-ranging Online Data for Epidemiologic Research (CDC-WONDER) database, specifically targeting deaths coded under the International Classification of Diseases, 11th Revision (ICD-11) code "Q-90." This analysis, covering 1999 to 2020, segmented the data by age, gender, race, and United States Census regions. Death locations were categorized into home/hospice, medical facilities, and nursing/other facilities. Data analysis was conducted using Microsoft Excel, and the Autoregressive Integrated Moving Average (ARIMA) model was applied for statistical assessments. Our analysis included 22604 deaths related to DS, as recorded in the CDC-WONDER database from 1999 to 2020. The majority of these deaths occurred in medical or nursing facilities, with home or hospice deaths accounting for 6106 cases and other locations for 5.29% of deaths. Univariate logistic regression was used to identify predictors of home or hospice deaths, revealing a trend of increasing deaths in these settings over time. Between 1999 and 2020, there was a notable increase in the number of individuals with DS dying at home or in hospice care, especially among those aged 55-64. Female individuals and those identified as white experienced higher mortality rates than other demographic groups.This shift highlights the need to understand the disparity in places of death within this population, ensuring equitable access to quality end-of-life care for all individuals with DS.

Multiple myeloma incidence and mortality trends in the United States, 1999–2020

Multiple myeloma (MM) is a plasma cell disorder accounting for approximately 10% of hematologic malignancies. There is limited epidemiological evidence regarding the long-term trends and disparities in MM in the US. We conducted a multiple time point cross-sectional study using MM incidence rate data from the Surveillance, Epidemiology, and End Results (SEER) database and mortality data from the CDC Wide-Ranging Online Data for Epidemiologic Research (CDC WONDER) Underlying Cause of Death database between 1999 and 2020. During this period, MM incidence has steadily increased, while MM mortality has steadily decreased, with substantial racial and ethnic disparities. Non-Hispanic Black individuals exhibited the highest incidence rates, which consistently rose from 12.02 (95% CI 10.54, 13.64) in 1999 to 14.20 (95% CI 12.93, 15.55) per 100,000 population by 2020. Non-Hispanic American Indian/Native Alaskans and Asian/Pacific Islanders demonstrated the lowest incidence rates of 5.59 (95% CI 2.69, 10.04) and 3.56 (95% CI 2.94, 4.27) per 100,000 population in 1999 to 5.76 (95% CI 3.49, 8.90) and 3.92 (95% CI 3.46, 4.42) per 100,000 population, respectively, by 2020. Disparities by gender, age, US census region, and rurality were observed, underscoring the importance of targeted, equity-centered interventions and MM screening initiatives for at-risk populations.

Descriptive Epidemiology of Female Suicides by Race and Ethnicity

Each year millions of females develop serious mental illnesses (SMI), which are major risk factors for suicides. Using the Web-Based Injury Statistics Query and Reporting System (WISQARS) for the years 2000, 2010 and 2020, we found in 2020 9,428 females (almost 190/week) committed suicide, losing 328,653 years off potential life before age 80 years. There were pronounced increases in female suicides from 2000 to 2020 across all racial and ethnic groups. The greatest number of suicides were in non-Hispanic white females, but the highest rate of suicides was in non-Hispanic American Indians /Alaska Natives, and in females 15–24 years of age. The West had the highest female suicide rates, with methods used to commit suicides varying by census regions and race and ethnicity. Suffocation to commit suicide increased for most racial and ethnic groups and poisonings decreased for most groups between 2000 and 2020, These underscore the need for targeted primary prevention of suicides for females based on age, geographic location and method of suicide, to mitigate female suicides improved access (e.g. geographically and financially) to mental health care services is essential.

Access to Prostate-Specific Antigen Testing and Mortality Among Men With Prostate Cancer

Prostate-specific antigen (PSA) screening for prostate cancer is controversial but may be associated with benefit for certain high-risk groups. To evaluate associations of county-level PSA screening prevalence with prostate cancer outcomes, as well as variation by sociodemographic and clinical factors. This cohort study used data from cancer registries based in 8 US states on Hispanic, non-Hispanic Black, and non-Hispanic White men aged 40 to 99 years who received a diagnosis of prostate cancer between January 1, 2000, and December 31, 2015. Participants were followed up until death or censored after 10 years or December 31, 2018, whichever end point came first. Data were analyzed between September 2023 and January 2024. County-level PSA screening prevalence was estimated using the Behavior Risk Factor Surveillance System survey data from 2004, 2006, 2008, 2010, and 2012 and weighted by population characteristics. Multivariable logistic, Cox proportional hazards regression, and competing risks models were fit to estimate adjusted odds ratios (AOR) and adjusted hazard ratios (AHR) for associations of county-level PSA screening prevalence at diagnosis with advanced stage (regional or distant), as well as all-cause and prostate cancer-specific survival. Of 814 987 men with prostate cancer, the mean (SD) age was 67.3 (9.8) years, 7.8% were Hispanic, 12.2% were non-Hispanic Black, and 80.0% were non-Hispanic White; 17.0% had advanced disease. There were 247 570 deaths over 5 716 703 person-years of follow-up. Men in the highest compared with lowest quintile of county-level PSA screening prevalence at diagnosis had lower odds of advanced vs localized stage (AOR, 0.86; 95% CI, 0.85-0.88), lower all-cause mortality (AHR, 0.86; 95% CI, 0.85-0.87), and lower prostate cancer-specific mortality (AHR, 0.83; 95% CI, 0.81-0.85). Inverse associations between PSA screening prevalence and advanced cancer were strongest among men of Hispanic ethnicity vs other ethnicities (AOR, 0.82; 95% CI, 0.78-0.87), older vs younger men (aged ≥70 years: AOR, 0.77; 95% CI, 0.75-0.79), and those in the Northeast vs other US Census regions (AOR, 0.81; 95% CI, 0.79-0.84). Inverse associations with all-cause mortality were strongest among men of Hispanic ethnicity vs other ethnicities (AHR, 0.82; 95% CI, 0.78-0.85), younger vs older men (AHR, 0.81; 95% CI, 0.77-0.85), those with advanced vs localized disease (AHR, 0.80; 95% CI, 0.78-0.82), and those in the West vs other US Census regions (AHR, 0.89; 95% CI, 0.87-0.90). This population-based cohort study of men with prostate cancer suggests that higher county-level prevalence of PSA screening was associated with lower odds of advanced disease, all-cause mortality, and prostate cancer-specific mortality. Associations varied by age, race and ethnicity, and US Census region.

Demographic Disparities in Lung Cancer Mortality and Trends in the United States From 1999 Through 2020: A Population-Based CDC Database Analysis.

Lung cancer is the leading cause of cancer-related mortality in the United States and is projected to account for 127,070 deaths in 2023. Although the lung cancer mortality rate has been decreasing over the last decade, demographic disparities in mortality still exist. We sought to determine the impact of demographic factors on lung cancer mortality and trends in the United States. We queried the Centers for Disease Control and Prevention (CDC) database for mortality statistics with an underlying cause of death of lung and bronchus cancer from 1999 through 2020. Age-adjusted mortality rates (AAMR) were calculated per 100,000 people. We assessed the AAMR by demographic variables, including race, geographic density, sex, age, and US census region. Temporal trends were evaluated using Joinpoint regression software, and average annual percent change (APC) was calculated. From 1999 through 2020, lung cancer led to 3,380,830 deaths. The AAMR decreased by 55.1 to 31.8, with an associated average APC of -2.6%. In 1999, men had an AAMR almost twice as high as women, but these differences became less pronounced over time. Rural populations experienced the highest AAMR and the slowest rate of decrease compared with urban populations, who experienced the lowest AAMR and fastest decrease. Non-Hispanic Black individuals experienced the highest AAMR, with an annual decrease of -3.0%. The West experienced the fastest decrease at -3.1% annually, whereas the Midwest experienced the slowest decrease at -2.0% annually. Although the mortality rate of lung cancer has been decreasing since 1999, not all demographic groups have experienced the same rates of decrease, and disparities in outcomes are still prevalent. Vulnerable subgroups need targeted interventions, such as the incorporation of patient navigators, improved screening chest CT scan access and follow-up, and telehealth expansion, which will improve the likelihood of earlier-stage diagnoses and the potential for curative treatments.

Asian and Pacific Islander cancer mortality trends in the United States between 1999-2020.

e23307 Background: The Asian and Pacific Islander (API) population is the fastest growing in the United States, composing nearly 7% of the US population. Although cancer is the second leading cause of death overall in the U.S., it is the leading cause of death in the API population. Despite this, no study has assessed trends in cancer mortality in API individuals in the US. Our aim was to analyze differences and trends in API cancer mortality in the U.S. between 1999 to 2020. Methods: The CDC WONDER database was used to determine mortality statistics for patients, classified as non-Hispanic Asian or Pacific Islander, with cancer (ICD-10 codes C00-C97) as the underlying cause of death between 1999 and 2020. Age-adjusted mortality rates (AAMR) were calculated per 100,000 deaths, and were stratified by cancer type, sex, population density, U.S. census region, and age. Joinpoint regression software was used to identify temporal trends. Average annual percent change (APC) was considered statistically significant if p &lt; 0.05. Results: Between 1999 and 2020, cancer accounted for 305,386 deaths in API individuals. During this period, there was a 30% decrease in mortality due cancer and a decrease in APC of -1.5% (p &lt; 0.05). When stratified by cancer site, the largest decrease in APC was in stomach cancer at -3.7% (p &lt; 0.05), and the largest increase was in uterine cancer at 2.6% (p &lt; 0.05). In 1999, males experienced an overall cancer-related AAMR of 151, 48% higher than females at 103; however, by 2020 these differences reduced, with males having a cancer-related AAMR of 105.6 vs API females of 80.9, a 25% difference. Males experienced a larger decrease in APC (-1.8%, p &lt; 0.05), compared with females (-1%, p &lt; 0.05). Rural populations had the largest cancer-related AAMR (113.0) and largest drop in APC (-2%, p &lt; 0.05), compared with urban groups with a cancer-related AAMR of 106.7 and APC drop (-1.3%, p &lt; 0.05). The highest cancer related AAMRs was seen in lung cancer (24.3 in urban vs 25.4 in rural). Liver-cancer related AAMR was highest in urban populations at 10.4 and lowest in rural populations at 8.2. Western census regions had the highest AAMR at 113.7 with an APC decrease of –1.4% and Southern census regions had the lowest AAMR at 90.5 with an APC decrease of –1.2%. Adults aged &gt; 65 experienced the highest cancer related AAMR at 588.2, and adults aged 25-44 demonstrated the lowest AAMR at 14.7. However, adults aged 25-44 experienced the largest decrease in APC at -2% (p &lt; 0.05), compared with adults aged &gt; 65 at -1.4% (p &lt; 0.05). Conclusions: Our study identifies a significant decrease in cancer mortality in API individuals between 1999 and 2020. The largest decrease seen was in stomach cancer; however, uterine cancer mortality has increased. Notably, liver cancer mortality was higher in urban rather than rural groups. Further studies may examine differences amongst API and other racial groups, and potential sources for the disparities seen amongst API individuals.

Trends in hospice utilization and place of death preferences in multiple myeloma-related deaths from 2003 to 2020: Analysis of CDC Wonder database.

e24039 Background: Multiple myeloma (MM) is an incurable hematological malignancy of plasma cells with high disease-related morbidity and mortality. Modern treatment has revolutionized the care of MM patients. However, a significant proportion of patients will eventually succumb to the disease. Place of Death (POD) is an important determinant of patient and caregiver preference, access to home-based supportive care, and cost of caregiving at EOL. We evaluate trends in POD for patients and hospice utilization with MM in the U.S. from 2003 to 2020. Methods: We analyzed data using the Centers for Disease Control and Prevention WONDER (Wide-Ranging Online Data for Epidemiologic Research) database. The data for deaths due to MM was pooled using the International Classification of Diseases-10th Revision code C 90.0. We included adult patients (age &gt; 18 years), diagnosed with MM during 2003-2020. The demographic data was obtained to calculate descriptive statistics using age, gender, place of death, census region, and utilization of hospice mortality. Annual percentage change (APC) in mortality was calculated using the joinpoint model. Results: There were 205,472 deaths in MM patients in the era 2003-2020, of which 88,245 (42.95%) deaths were in the decedent home and hospice facility (H&amp;H) and107,275 (52.12%) deaths were reported in medical facilities and nursing homes. There was a significant increase in the trend of H&amp;H [29% to 58%, average annual percentage (AAPC) 4.6404, p &lt; 0.001] and a decline in medical facility/nursing home (M&amp;N) deaths [64.9% to 37.7%, AAPC-2.1059, p &lt; 0.001]. When stratified by census regions, all regions in the US depicted significantly increased utilization of H&amp;H (p &lt; 0.001), with the highest H&amp;H utilization in the West region (CENS-R4) of 47.97%, while the highest M&amp;N mortality of 60.4% was observed in North-East region. There is a significant increase in H&amp;H utilization reported in the age group 45-64 years (AAPC 3.544) and age group 65+ (AAPC 5.0277) with p &lt; 0.0001 for both groups. The younger patients (Age &lt; 45) tend to use hospice less, but the number of deaths in the group was small. Furthermore, we saw increased H&amp;H utilization in both genders, with female AAPC at 4.0951 and male AAPC at 5.1393, p &lt; 0.0001 With regards to race, the highest H&amp;H utilization was seen in whites (44.66%), then American Indian or Alaska Native (40.12%), Asian or Pacific Islander (36.76%), and African American (36.05%). However, the trend analysis from 2003-2020 depicts the highest AAPC change in AAPI (8.8409). Conclusions: Over the past two decades, there has been a trend in increased utilization of hospice facilities in end-of-life care among MM patients. However, there is still opportunities to expand its utility especially in the North-East and among African American patients to reduce the psychological and cost of end-of-life care.

A real-world study on biomarker retesting among patients with non-small cell lung cancer and disparity in outcomes.

8590 Background: Prior studies revealed sociodemographic disparities in biomarker testing among patients (pts) with advanced/metastatic non-small cell lung cancer (a/mNSCLC). However, the association of testing disparities with clinical outcomes among real-world pts requires further characterization. Methods: This retrospective study used ConcertAI Patient360™ US dataset to assess biomarker testing disparities and their association with median overall survival (mOS) among adults with a/mNSCLC (2017–2022) who received ≥1 line of therapy with ≥90-day follow-up. Analyses were conducted in pts who initiated first-line (1L) treatment and stratified by setting (community vs academic) and race. Biomarker testing is a curated data element in this database, leveraging structured and unstructured electronic medical record data and includes the following biomarkers ALK, BRAF, EGFR, KRAS, MET amp, MET exon 14, NTRK, PD-L1, RET, and ROS1. Biomarker testing to inform 1L decision was defined as testing before 1L start. Testing to inform second-line (2L) decision was defined as testing after 1L start and before 2L start. Variables were compared using chi-square or ANOVA tests. Unadjusted and adjusted OS using multivariate Cox proportional hazards are reported. Results: Of 3678 pts included in the 1L cohort, 3127 (85%) received 1L testing. In community settings, 22% of Black pts vs 15% of White pts did not receive 1L testing (P=0.002), whereas 1L testing rates between races were similar in academic settings (Table). In 2L community setting among pts who received 1L but not 2L testing, mOS was 5.9 vs 9.9 months in Black (n=54) vs White (n=529) pts, respectively (P=0.35). In 2L community setting among pts who were and were not tested prior to 1L and not tested at 2L, mOS was 5.9 vs 10.1 months in Black (n=62) vs White (n=613) pts, respectively (P=0.27). Accounting for recorded sociodemographic and clinical characteristics at baseline, differences in OS by testing setting and status start to normalize to the reference group. Disparities within groups appear to potentially exist despite no statistical significance (except for ECOG score of 2+). Conclusions: Despite small 2L sample sizes and lack of significance, disparities in testing rates and outcomes were observed, which may be overcome by normalizing testing across race and treatment setting to potentially improve pt outcomes. Further analysis can be performed across census regions. Further research is needed to confirm the impact of lack of biomarker testing on pt outcomes on a broader scale, particularly around characteristics that may impact outcomes but were undetected in this dataset. [Table: see text]

Trends of pancreatic cancer-related mortality among patients with type 2 diabetes mellitus in the United States, 1999-2020.

e22523 Background: The relationship between pancreatic cancer (PC) and type 2 diabetes mellitus (T2DM) is complex and bidirectional. While T2DM can be a risk factor for PC, pancreatic cancer can also lead to the onset or exacerbation of T2DM. Especially when these conditions coexist, individuals confront heightened mortality risks due to the compounded effects of both. Thus, our CDC analysis delves into mortality trends among patients affected by both conditions from “1999 to 2020”. By analyzing extensive datasets we scrutinized how factors such as gender, race, region of residence, and level of urbanization intersect with mortality rates. Our trend analysis highlights the need for effective strategies and interventions for individuals facing these complex health challenges simultaneously. Methods: We used the CDC Wonder database to analyze trends in PC-related mortality in patients with T2DM from 1999 to 2020. Age-adjusted mortality rate (AAMR) per 100,000 people with 95% confidence intervals was calculated for the total population, stratified by gender, race, urban/rural status, and census region. We used the Joinpoint regression software to calculate annual percentage change (APC) trend for each stratification. Results: In the US between 1999 and 2020, there were 20,980 deaths from PC in patients with T2DM. The overall AAMR showed a gradual rise from 0.15 per 100,000 in 1999 to 0.27 in 2008 (APC: 6.23), a relatively constant rate of 0.27 till 2013 (APC: -0.79), followed by a more recent sharp rise to 0.48 in 2020 (APC: 8.86). While both genders showed an increase in AAMR, men showed consistently higher AAMR than women in 1999 (AAMR Men: 0.20 vs Women: 0.12) and 2020 (AAMR Men: 0.60 vs Women: 0.37). Moreover, when stratified by race NH Blacks showed higher AAMR than NH Whites in 1999 (AAMR Black: 0.22 vs White: 0.14) and 2020 (AAMR Black: 0.51 vs White:0.48). Rural areas showed consistently higher AAMR than urban areas throughout the study period, from 1999 (AAMR Rural: 0.22 vs Urban: 0.14) till 2020 (AAMR Rural: 0.64 vs Urban:0.44). Finally, the highest mortality rate was observed in Western region (AAMR: 0.39), followed by the Midwestern region (AAMR: 0.36), Southern region (AAMR: 0.26), and Northeastern region (AAMR: 0.20). Conclusions: PC remains one of the leading causes of cancer-related deaths in developed high-income countries and despite the advancements in medicine, the median survival rate remains low. Considering the high risk of PC in patients with T2DM, it is imperative to devise regulations for regular screening to avoid delays in diagnosis and ensuing treatments. Our study underscores the need for larger population-based studies to further understand the primary factors influencing the observed geographical, racial, and gender disparities.

Trends of stroke-related mortality among patients with cancer in the United States, 1999-2020.

e24021 Background: Patients with cancer are at an increased risk of stroke and stroke-related mortality via various mechanisms such as hypercoagulability, direct tumor effects, and largely as side effects of treatments. Enhancement of thrombin release from chemotherapy induced release of extracellular vesicles and cell-free DNA, and the use of angiogenesis inhibitors are some of the proposed mechanisms for stroke development in patients with cancer. Despite this, current guidelines lack clarity in identifying patients with cancer as having moderate to high risk of mortality from stroke. Recognizing this complex relationship is pivotal for crafting comprehensive care plans that address the dual challenges of cancer and stroke risks. Hence, our CDC analysis focuses on unraveling mortality trends among patients grappling with both conditions from “1999 to 2020”. Methods: We analyzed national mortality data from the multiple causes of death files in the CDC WONDER database from 1999 to 2020. Age-adjusted mortality rates (AAMRs) per 100,000 people were calculated for the total population, stratified by gender, race, urban/rural metro status, and census region. Annual percent change (APC) was calculated using the Joinpoint regression software. Results: A total of 36,648 stroke-related deaths among patients with cancer occurred between 1999 and 2020. The APC trends are as follows: a major decrease of -6.8 (95% CI: -11.8 to -1.5) from 2002 to 2009, a slight decline of -1.23 (95% CI: -13.8 to 13.2) from 2009 to 2014, a significant decrease of -6.71 (95% CI: -46.2 to 61.7) from 2014 to 2017, and an increase of 2.07 (95% CI: -26.1 to 41.1) from 2017 to 2020. Men consistently showed higher mortality rates compared to women in 1999 (AAMR Men: 1.0 vs Women: 0.63) and 2020 (AAMR Men: 0.94 vs Women: 0.69). Moreover, when stratified by race non-hispanic (NH) Black showed the highest mortality rate, followed by NH Whites, and Hispanics throughout the study period between 1999 (AAMR NH Black: 0.96 vs NH White: 0.75 vs Hispanic: 0.32) and 2020 (AAMR NH Black: 0.85 vs NH White: 0.81 vs Hispanic: 0.53). Rural areas compared to urban areas showed consistently higher mortality rates over the study period. Conclusions: Despite more than a decade-long decline, stroke-related mortality among cancer patients has significantly increased since 2015. Targeted therapy and investigations into the role of social determinants of health may improve care for these patients. Further investigation is warranted to elucidate the mechanisms for the increase in stroke-related mortality among people with cancer, particularly those with the following demographics: Men, Black or African American, and residents of rural areas and Midwestern regions.

Use of CAR T cell vs non-CAR T cell therapy in the treatment of patients (pts) with multiple myeloma (MM) in the Medicare population.

e23310 Background: Chimeric antigen receptor T-cell therapy (CAR T) is FDA-approved in pts with triple-class exposed (TCE) relapsed/refractory (RR) MM after four or more prior lines of therapy (LOTs). Real-world access to CAR T remains challenging due to manufacturing capacity, financial barriers, and pt fitness. Pts with certain pre-existing comorbidities (e.g., central nervous system disease, heart disease, secondary malignancies) are commonly excluded from clinical trials, including those investigating CAR T. The objective of this study was to identify the factors associated with the use of CAR T in pts with TCE RRMM to better understand the unmet need in this population. Methods: We conducted an observational cohort study using Medicare fee-for-service data; each pt in the CAR T intention-to-treat (ITT) population between 2021 and 2023 was matched to three non-CAR T pts, without replacement. Pts were eligible if they had an initial MM diagnosis, were continuously enrolled, were TCE, and did not receive treatment in a clinical trial. The index date was the ITT date. Baseline characteristics included age, sex, race/ethnicity, census region, three comorbidity indexes (Charlson, Elixhauser, CMS hierarchical condition categories [HCCs]), a claims-based frailty index (CFI), and dual enrollment in Medicare and Medicaid (as a proxy to social economic status [SES]). Logistic regression was used to derive odds ratios (ORs) and 95% confidence intervals (CIs) comparing the characteristics of CAR T vs non-CAR T pts. Results: Seventy-three ITT CAR T pts (nine underwent apheresis but did not receive CAR T) were matched to 219 non-CAR T pts by LOT and index year. Matched pts were treated with varied standard regimens (daratumumab-containing: 63%). Median prior LOTs were similar in the two cohorts (8; range 2–13). Median time from MM diagnosis to index date was 44.6 and 51.9 months for CAR T and non-CAR T pts, respectively. Compared with non-CAR T pts, pts in the CAR T population were younger (aged &lt; 75 years: 59% CAR T vs 36% non-CAR T), less frail (mean CFI: 0.18 vs 0.20) and had higher SES (without dual enrollment in Medicare and Medicaid: 96% vs 81%), but were similar in terms of sex, region, and race/ethnicity. Variation in individual comorbidity prevalence was observed between CAR T and non-CAR T pts. In a multivariable regression analysis, factors strongly associated with lower odds of CAR T use included age ≥75 years (OR 0.29; 95% CI 0.16–0.53), comorbidities (lung/other severe cancers [OR 0.39; 95% CI 0.20–0.74] and chronic obstructive pulmonary disease [OR 0.32; 95% CI 0.10–0.99] defined by HCCs), and SES (OR 0.09; 95% CI 0.02–0.37). Conclusions: Older age, certain comorbidities, and lower SES are associated with lower odds of receiving CAR T in real-world pts with TCE RRMM, demonstrating an unmet need for more accessible and effective treatment options with acceptable safety profiles for these pts.

Regional variation in financial hardship among US veterans during the COVID-19 pandemic.

Geographic variation in hardship, especially health-related hardship, was identified prior to and during the pandemic, but we do not know whether this variation is consistent among Veterans Health Administration (VHA)-enrolled veterans, who reported markedly high rates of financial hardship during the pandemic, despite general and veteran-specific federal policy efforts aimed at reducing hardship. In a nationwide, regionally stratified sample of VHA-enrolled veterans, we examined whether the prevalence of financial hardship during the pandemic varied by US Census region. We found veterans in the South, compared with those in other census regions, reported higher rates of severe-to-extreme financial strain, using up all or most of their savings, being unable to pay for necessities, being contacted by collections, and changing their employment due to the kind of work they could perform. Regional variation in veteran financial hardship demonstrates a need for further research about the role and interaction of federal and state financial-assistance policies in shaping risks for financial hardship as well as potential opportunities to mitigate risks among veterans and reduce variation across regions.

Regional and rural-urban patterns in the prevalence of diagnosed hypertension among older U.S. adults with diabetes, 2005–2017

BackgroundHypertension prevalence among the overall US adult population has been relatively stable during the last two decades. However, whether this stabilization has occurred across rural-urban communities and across different geographic regions is unknown, particularly among older adults with diabetes who are likely to have concomitant cardiovascular risk factors.MethodsThis serial cross-sectional analysis used the 5% national sample of Medicare administrative claims data (n = 3,516,541) to examine temporal trends (2005–2017) in diagnosed hypertension among older adults with diabetes, across urban-rural communities and US census regions (Northeast, Midwest, South, and West). Joinpoint regression was used to obtain annual percent change (APC) in hypertension prevalence across rural-urban communities and geographic regions, and multivariable adjusted regression was used to assess associations between rural-urban communities and hypertension prevalence.ResultsThe APC in the prevalence of hypertension was higher during 2005–2010, and there was a slowdown in the increase during 2011–2017 across all regions, with significant variations across rural-urban communities within each of the regions. In the regression analysis, in the adjusted model, older adults living in non-core (most rural) areas in the Midwest (PR = 0.988, 95% CI: 0.981–0.995) and West (PR = 0.935, 95% CI: 0.923–0.946) had lower hypertension prevalence than their regional counterparts living in large central metro areas.ConclusionsAlthough the magnitudes of these associations are small, differences in hypertension prevalence across rural-urban areas and geographic regions may have implications for targeted interventions to improve chronic disease prevention and management.

The Spatial–Racial Patterns of U.S. Dam Removals Since 2010

Dam removal in the United States has grown exponentially, yet we do not know whether the pattern of such removals comports with principles of environmental justice. This exploratory study investigates the spatial pattern of dam removals across the United States to ascertain whether there were any geographic areas where the probability of removal was correlated with the racial or ethnic composition of the environs. We analyze dam removals since 2010 using national data on existing dams, removed dams, and demographics. We estimate multivariate probability models of dam removal stratified by census region and dam ownership to pinpoint contexts where significant spatial-racial patterns occur that cannot be attributed to dam characteristics. Our exploration reveals only a few such contexts. After controlling for dam purpose, construction type, age, and height, the probability of a dam being removed since 2010 is positively associated with the proportion of nearby White residents for dams owned by local or state governments in the South. The probability of removal is negatively associated with the proportion of nearby White residents for dams owned privately or by state or local governments in the West. Future case studies should probe these contexts of clear spatial–racial patterns from an environmental justice perspective.

Examining business cycles and optimal monetary policy in a regional DSGE model

I construct a dynamic stochastic general equilibrium (DSGE) model consisting of geographic regions and use state level data to estimate the effects that monetary policy and financial shocks have on the four census regions of the United States. The DSGE model I use is constructed around a centralized monetary authority and financial market with regional output, labor and investment markets. I find significant heterogeneity amongst the regional structural parameters of the model, creating different business cycle dynamics for the four regions. The estimated model aligns with other economic studies that suggest that monetary shocks have a greater impact in certain geographic regions in terms of employment, inflation, wages, and consumption. Simulating the estimated model, I find that monetary policy that considers the regional variation in output and inflation can significantly lower the volatility around national output and inflation. The paper’s results suggest that regional macroeconomic conditions should be considered in monetary policy decisions.

The burden of overweight/obesity and weight-related behaviors attributable to food addiction in emerging adults

While food addiction has been positively associated with excess weight and disordered eating behaviors, this has not been examined in representative samples of emerging adults, who are at elevated risk for these outcomes. This study investigated relationships of food addiction with weight outcomes, weight perception, and weight-control behaviors in emerging adults and estimated the population attributable fraction to food addiction. Data from an observational cohort study were collected in seven annual waves from 2010 to 2016. A nationally representative sample of 2785 10th grade students was recruited from schools within each U.S. census region (73% participation) (mean ± SD baseline age = 16.3 ± 0.5years). Wave 7 retention was 81% (n = 2323, 60% female, mean ± SD = 22.6 ± 0.5 years). Outcomes included current BMI, BMI change from baseline – wave 7, increased weight status in wave 7 (increased weight status from baseline-wave 7), perceived overweight, dieting, any weight-control behavior, and extreme weight-control behaviors. Food addiction was measured in wave 7 using the modified Yale Food Addiction Scale. Relative risk of the outcomes associated with food addiction, and population attributable fraction, were estimated using adjusted log-binomial or robust Poisson regression analyses accounting for the complex survey design. Food addiction prevalence was 4.7%. Participants with food addiction were primarily females (91%); food addiction was uncorrelated with other sociodemographics. Food addiction was associated with 48%–167% increased RR for all outcomes, but these were attenuated after adjustment for confounders (31%–64%). The population attributable fraction for food addiction ranged from 2% (high wave 7 BMI) – 5% (extreme weight-control behaviors). Although the population attributable fraction estimates indicate that the public health burden of these outcomes attributable to food addiction may be relatively minor, food addiction may signal the presence of several adverse mental health symptoms.

Comparison of Hospital Volume and Risk-Standardized Mortality Rate as a Proxy for Hospital Quality in Complex Oncologic Hepatopancreatobiliary Surgery

BackgroundCentralization of hepatopancreatobiliary procedures to more experienced centers has been recommended but remains controversial. Hospital volume and risk-stratified mortality rates (RSMR) are metrics for interhospital comparison. We compared facility operative volume with facility RSMR as a proxy for hospital quality.Patients and MethodsPatients who underwent surgery for liver (LC), biliary tract (BTC), and pancreatic (PDAC) cancer were identified in the National Cancer Database (2004–2018). Hierarchical logistic regression was used to create facility-specific models for RSMR. Volume (high versus low) was determined by quintile. Performance (high versus low) was determined by RSMR tercile. Primary outcomes included median facility RSMR and RSMR distributions. Volume- and RSMR-based redistribution was simulated and compared for reductions in 90-day mortality.ResultsA total of 106,217 patients treated at 1282 facilities were included; 17,695 had LC, 23,075 had BTC, and 65,447 had PDAC. High-volume centers (HVC) had lower RSMR compared with medium-volume centers and low-volume centers for LC, BTC, and PDAC (all p < 0.001). High-performance centers (HPC) had lower RSMR compared with medium-performance centers and low-performance centers for LC, BTC, and PDAC (all p < 0.001). Volume-based redistribution required 16.0 patients for LC, 11.2 for BTC, and 14.9 for PDAC reassigned to 15, 22, and 20 centers, respectively, per life saved within each US census region. RSMR-based redistribution required 4.7 patients for LC, 4.2 for BTC, and 4.9 for PDAC reassigned to 316, 403, and 418 centers, respectively, per life saved within each US census region.ConclusionsHVC and HPC have the lowest overall and risk-standardized 90-day mortality after oncologic hepatopancreatobiliary procedures, but RSMR may outperform volume as a measure of hospital quality.

CDC-WONDER Database Analysis of Maternal Morbidity in Florida [ID 2683410

INTRODUCTION: The CDC's WONDER Natality database was updated in 2016 to include comprehensive pregnancy data, encompassing maternal morbidity, a growing concern in the United States. Using the WONDER Natality database, we can better understand risk factors and trends associated with maternal morbidity. The aim of this research is to investigate the variations in maternal morbidity in Florida, focusing on maternal demographics and pregnancy characteristics. METHODS: This cross-sectional descriptive study used results from the CDC’s WONDER Natality 2016–2021 expanded-results database. Five categories of maternal morbidity were analyzed. Maternal morbidity and pregnancy characteristics were analyzed for statistical significance using χ2 and unpaired t-tests. RESULTS: 92,680 (1.04%) births in Census Region 3 (the South) were found to be associated with maternal morbidity. This prompted an in-depth examination of this region, with a particular focus on Florida. Notably, Asian mothers experienced the highest rate of maternal morbidity (1.49%), whereas Black mothers faced the lowest statistical rate (0.67%). Asian mothers experiencing maternal morbidity tended to be older, have lower pre-pregnancy body mass indexes, more prenatal visits, and shorter intervals since their last live births. CONCLUSION: This study underscores statistically significant maternal morbidity disparities in Florida, with Asian mothers being particularly vulnerable. It identifies several pregnancy characteristics linked to increased morbidity. Further exploration, including a county-level analysis in Florida and examination of other states in Census Region 3, could reveal or consolidate emerging trends. Moreover, the absence of a universally accepted definition for severe maternal morbidity calls for the establishment of a clear standard to guide future research and obstetric practices.