Racial Disparities In Mortality Rates Research Articles

Emerging trends and demographic disparities in anal cancer mortality across the United States census regions: An analysis of National Center for Health Statistics mortality data.

Anal cancer, despite its rarity, is a matter of serious concern in the United States, with an uptrend in recent years and marked racial disparities in mortality rates. The aim of this work was to investigate anal cancer mortality trends and sex race disparities in the United States from 1999 to 2020. This is a retrospective study using data from the CDC WONDER database (1999-2020). We investigated deaths attributed to anal cancer, identified by the ICD-10 code C21.1, and excluded individuals aged 14 years and under. The Mann-Kendall trend test was used to investigate temporal trends and a t-test was used to compare continuous variables. Both male and female age-adjusted mortality attributed to anal cancer increased significantly during the study period across all subgroups, including race (Black and White), US Census region (Northeast, Midwest, South and West) and age (15-64 and ≥65 years) (p < 0.001 for all comparisons). For each subgroup, women demonstrated significantly higher rates of mortality than men, except in the Black population, where Black men had higher rates than Black women (0.40 vs. 0.29, p < 0.001). Additionally, Black men had significantly higher mean mortality rates than White men (0.40 vs. 0.27, p < 0.001). The highest rates of anal cancer mortality were among geriatric individuals, especially women aged ≥65 years, at 1.18 per 100 000. The rise in anal cancer mortality and racial and sex disparities present a significant challenge for healthcare providers and policy makers. Further studies are required to devise evidence-based strategies to effectively tackle this challenge.

Heart disease and heart failure: Trends and disparities in mortality rates in the United States from 2000 to 2020

Study objectiveTo describe the age, sex and racial disparities in mortality rates for heart disease (HD) and heart failure (HF) in the United States (US) between 2000 and 2020. DesignThis was an ecological study with trend analysis of mortality rates. SettingUnited States. ParticipantsAdults aged 18 years and above. Main outcomes measuresMortality rates per 100,000 for HD and HF. ResultsThere was a significant decrease in the age-standardized mortality rate for HD over the past two decades (from 343.5 per 100,000 cases to 215.1 per 100,000 cases, p < 0.001). HD mortality rates were significantly higher in males (p < 0.001), non-Hispanic blacks (p < 0.001) and in adults aged 65+ (p < 0.001) and 75+ (p < 0.001). There was no significant change in the age-standardized mortality rate for HF (from 26.9 per 100,000 cases to 25.7 per 100,000 cases (p = 0.706)) due to a reversal in the trend beyond 2011. Though the HF mortality rates were significantly lower in males (p = 0.001), and not significantly different in non-Hispanic blacks and non-Hispanic whites, there were shifts in trends beyond 2016, with higher rates in males and in non-Hispanic blacks compared to non-Hispanic whites. ConclusionsIn summary, this study underscores significant reductions in heart disease mortality rates over the past two decades, alongside persistent disparities among different demographic groups. It also highlights emerging trends in heart failure mortality rates in particular population subgroups in recent years, necessitating further exploration to inform targeted interventions and policies.

Racial disparities in COVID-19 and gastrointestinal diseases–related mortality: analysis from CDC-WONDER databases, 2020–2022

Background The COVID-19 pandemic represents an unprecedented global health challenge. Gastrointestinal diseases (GID) have been shown to increase morbidity and mortality in COVID-19 patients, warranting a comprehensive investigation of their combined impact and racial disparities in mortality rates within the United States. Methods Data from the Centers for Disease Control and Prevention Wide-Ranging Online Data for Epidemiologic Research (CDC WONDER) mortality statistics database were analyzed for the period from January 1, 2020, to December 31, 2022. This study focused on adults, considering all deaths related to COVID-19 and GID. Age-adjusted mortality rates (AAMR) per 100,000 population were reported. Sociodemographic data, including age, sex, race/ethnicity, and region of residence, were collected. Results Among 9,925,729 total deaths in the US between 2020 and 2022, 3.9% were GID related only, 9.6% were COVID-19 related only, and 0.4% were attributed to both COVID-19 and GID as underlying causes of death. AAMR for COVID-19 was 121.3 per 100,000, significantly higher than the AAMR for GID (50.3 per 100,000). Age-wise, elderly individuals had the highest AAMR for both COVID-19 and GID-related deaths. Stratified by race/ethnicity, Hispanics exhibited the highest AAMR, nearly twice that of Non-Hispanic Black patients and substantially higher than Non-Hispanic White and Asian patients. Conclusion Our findings reveal substantial disparities in race/ethnicity-specific AAMR associated with both COVID-19 and GID in the US. Further research is crucial to delve deeper into their root causes and develop targeted interventions to strive for health equity for all.

Abstract 6141: Understanding the role of gp78 in breast cancer health disparities

Abstract Background: Breast cancer is a devastating disease where death rates for women of African ancestry (AA) are 40% higher than that of European ancestry (EA), demonstrating racial disparity in mortality. gp78 protein is an independent predictor of poor outcomes in women of AA that is over-expressed in aggressive breast cancers. The purpose of this research was to understand how gp78 is associated with poor survival rates by studying tumor biology and gene expression. We hypothesize a positive correlation between the overexpression of gp78 protein in higher amounts for AA women than that of European ancestry women which may correlate with specific functional pathways. Methods: Medical data was collected from a health disparities cohort in Eastern North Carolina. The patient’s race, ethnicity/ancestry were self-reported at the initial visit; the study cohort was reported as 50% AA. Immunohistochemistry to measure protein expression, DNA mutation &amp; gene expression used with Gene Set Enrichment Analysis(GSEA) of 147 patients to identify functional pathway differences in tumor biology between high versus low gp78 expression versus gp78 expression based on patient race. Hierarchical clustered heatmaps were used to compare overlapping genes that were differentially expressed. Results: 49 common genes were identified as the overlap between the genes in the differential gene expression list for gp78 and the two different gene set enrichment analyses compared: GSEA based on patients expressing high versus low gp78 protein by IHC versus GSEA based on white vs black patients (race). The hierarchical cluster analysis of the gene expression patterns identified two prominent clusters: association by extracellular factors in the tumor microenvironment and association by mitochondrial regulation and proliferation. Conclusions: This study suggests that gp78 differences based on race may be linked to tumor microenvironment, mitochondrial function, &amp; proliferation linking gp78 as a biomarker that is differentially expressed based on race and more highly correlated with breast cancer aggressiveness to functional properties of mitochondrial metabolism &amp; tumor microenvironment. We will explore this gene signature/biomarker that may predict survival based on race. This discovery provides new areas of research to explore the relationship of extracellular factors in the tumor microenvironment, mitochondria regulation, &amp; proliferation. Clinical &amp; nonclinical interventions addressing racial health disparity in mortality should target breast cancer-specific health determinants (both environmental and biological) among those of AA with efforts to decrease racial disparities in mortality rates. These new observations indicate gp78 may be a biomarker that can predict survival based on race using tumor biology, which can contribute to new strategies for reducing the rate at which women of AA disproportionately suffer from breast cancer mortality. Citation Format: Sediqua Sherese Bufford. Understanding the role of gp78 in breast cancer health disparities [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2022; 2022 Apr 8-13. Philadelphia (PA): AACR; Cancer Res 2022;82(12_Suppl):Abstract nr 6141.

Genetic Contributions to Prostate Cancer Disparities in Men of West African Descent.

Prostate cancer (PCa) is the second most frequently diagnosed malignancy and the second leading cause of death in men worldwide, after adjusting for age. According to the International Agency for Research on Cancer, continents such as North America and Europe report higher incidence of PCa; however, mortality rates are highest among men of African ancestry in the western, southern, and central regions of Africa and the Caribbean. The American Cancer Society reports, African Americans (AAs), in the United States, have a 1.7 increased incidence and 2.4 times higher mortality rate, compared to European American’s (EAs). Hence, early population history in west Africa and the subsequent African Diaspora may play an important role in understanding the global disproportionate burden of PCa shared among Africans and other men of African descent. Nonetheless, disparities involved in diagnosis, treatment, and survival of PCa patients has also been correlated to socioeconomic status, education and access to healthcare. Although recent studies suggest equal PCa treatments yield equal outcomes among patients, data illuminates an unsettling reality of disparities in treatment and care in both, developed and developing countries, especially for men of African descent. Yet, even after adjusting for the effects of the aforementioned factors; racial disparities in mortality rates remain significant. This suggests that molecular and genomic factors may account for much of PCa disparities.

Mediators of racial disparities in mortality rates after traumatic brain injury in childhood: data from the Trauma Quality Improvement Program.

Social disparities in healthcare outcomes are almost ubiquitous, and trauma care is no exception. Because social factors cannot cause a trauma outcome directly, there must exist mediating causal factors related to the nature and severity of the injury, the robustness of the victim, access to care, or processes of care. Identification of these causal factors is the first step in the movement toward health equity. A noninferiority analysis was undertaken to compare mortality rates between Black children and White children after traumatic brain injury (TBI). Data were derived from the Trauma Quality Improvement Program (TQIP) registries for the years 2014 through 2017. Inclusion criteria were age younger than 19 years and head Abbreviated Injury Scale scores of 4, 5, or 6. A noninferiority margin of 10% was preselected. A logistic regression propensity score model was developed to distinguish Black and White children based on all available covariates associated with race at p < 0.10. Stabilized inverse probability weighting and a one-tailed 95% CI were used to test the noninferiority hypothesis. There were 7273 observations of White children and 2320 observations of Black children. The raw mortality rates were 15.6% and 22.8% for White and Black children, respectively. The final propensity score model included 31 covariates. It had good fit (Hosmer-Lemeshow χ2 = 7.1604, df = 8; p = 0.5194) and good discrimination (c-statistic = 0.752). The adjusted mortality rates were 17.82% and 17.79% for White and Black children, respectively. The relative risk was 0.9986, with a confidence interval upper limit of 1.0865. The relative risk corresponding to the noninferiority margin was 1.1. The hypothesis of noninferiority was supported. Data captured in the TQIP registries are sufficient to explain the observed racial disparities in mortality after TBI in childhood. Speculations about genetic or epigenetic factors are not supported by this analysis. Discriminatory care may still be a factor in TBI mortality disparities, but it is not occult. If it exists, evidence for it can be sought among the data included in the TQIP registries.

The Economic Benefits of Reducing Racial Disparities in Health: The Case of Minnesota.

This paper estimates the benefits of eliminating racial disparities in mortality rates and work weeks lost due to illness. Using data from the American Community Survey (2005–2007) and Minnesota vital statistics (2011–2015), we explore economic methodologies for estimating the costs of health disparities. The data reveal large racial disparities in both mortality and labor market non-participation arising from preventable diseases and illnesses. Estimates show that if racial disparities in preventable deaths were eliminated, the annualized number of lives saved ranges from 475 to 812, which translates into $1.2 billion to $2.9 billion per year in economic savings (in 2017 medical care inflation-adjusted dollars). After eliminating the unexplained racial disparities in labor market participation, an additional 4,217 to 9185 Minnesota residents would have worked each year, which equals $247.43 million to $538.85 million in yearly net benefits to Minnesota.

Nonverbal synchrony as a behavioural marker of patient and physician race-related attitudes and a predictor of outcomes in oncology interactions: protocol for a secondary analysis of video-recorded cancer treatment discussions

IntroductionRacial disparities in cancer treatment contribute to racial disparities in mortality rates. The quality of patient–physician communication during clinical interactions with black patients and non-black physicians (racially discordant) is poorer...

Age at cancer diagnosis, amenability to medical interventions, and racial/ethnic disparities in cancer mortality.

Racial disparities in cancer mortality may be greater for cancers that are amenable to available early detection and treatment (amenability level). We investigated whether these patterns vary by age at cancer diagnosis. Using 5-year relative survival rates (5Y-RSR), we classified 51 cancer sites into least amenable, partly amenable, and mostly amenable cancers (<40%, 40-69%, ≥70% 5-YRS, respectively). We examined whether racial disparities in mortality rates (African-Americans, Asian/Pacific Islanders, Hispanics, whites), as estimated through Cox regression models, were modified by age at diagnosis and amenability level in 516,939 cancer cases diagnosed in 1995-1999. As compared with whites, all racial minority groups experienced higher cancer mortality rates in the youngest age group of 20-34 years. African-Americans and Hispanics diagnosed with partly and mostly amenable cancers had higher mortality rates relative to whites with cancers of the same amenability levels; further, these differences decreased in magnitude or reversed in direction with increasing age. In contrast, the racial differences in mortality were smaller and remained fairly constant across age groups for least amenable cancers. For example, in the youngest (20-34) and oldest (80-99) age groups, the adjusted hazard ratios (HRs) for African-Americans versus whites with least amenable cancers were, respectively, 1.26 (95% CI 1.02, 1.55) and 0.90 (95% CI 0.85, 0.96), while the HRs for African-Americans versus whites with mostly amenable cancers were 2.77 (95% CI 2.38, 3.22) and 1.07 (95% CI 0.98, 1.17). Cancer survival disadvantage for racial minorities is larger in younger age groups for cancers that are more amenable to medical interventions.

Disparities in cervical cancer mortality rates as determined by the longitudinal hyperbolastic mixed-effects type II model.

BackgroundThe main purpose of this study was to model and analyze the dynamics of cervical cancer mortality rates for African American (Black) and White women residing in 13 states located in the eastern half of the United States of America from 1975 through 2010.MethodsThe cervical cancer mortality rates of the Surveillance, Epidemiology, and End Results (SEER) were used to model and analyze the dynamics of cervical cancer mortality. A longitudinal hyperbolastic mixed-effects type II model was used to model the cervical cancer mortality data and SAS PROC NLMIXED and Mathematica were utilized to perform the computations.ResultsDespite decreasing trends in cervical cancer mortality rates for both races, racial disparities in mortality rates still exist. In all 13 states, Black women had higher mortality rates at all times. The degree of disparities and pace of decline in mortality rates over time differed among these states. Determining the paces of decline over 36 years showed that Tennessee had the most rapid decline in cervical cancer mortality for Black women, and Mississippi had the most rapid decline for White Women. In contrast, slow declines in cervical cancer mortality were noted for Black women in Florida and for White women in Maryland.ConclusionsIn all 13 states, cervical cancer mortality rates for both racial groups have fallen. Disparities in the pace of decline in mortality rates in these states may be due to differences in the rates of screening for cervical cancers. Of note, the gap in cervical cancer mortality rates between Black women and White women is narrowing.

Explaining Racial Disparities in Outcomes After Cardiac Surgery

Racial disparities in mortality rates after coronary artery bypass graft (CABG) surgery are well established. We have yet to fully understand how care at high-mortality, low-quality hospitals contributes to racial disparities in surgical outcomes. To determine the effects of hospital quality on racial disparities in mortality rates after CABG surgery. The national Medicare database (2007-2008) was used to identify 173,925 patients undergoing CABG surgery in US hospitals. Our primary measure of quality was the risk-adjusted mortality rate for each hospital. Logistic regression was used to determine the relationship between race and mortality rates, accounting for patient characteristics, socioeconomic status, and hospital quality. Nonwhite patients had 33% higher risk-adjusted mortality rates after CABG surgery than white patients (odds ratio [OR], 1.33; 95% CI, 1.23-1.45). In hospitals treating the highest proportion of nonwhite patients (>17.7%), the mortality was 4.8% in nonwhite and 3.8% in white patients. When assessed independently, differences in hospital quality explained 35% of the observed disparity in mortality rates (OR, 1.22; 95% CI, 1.12-1.34). We were able to explain 53% of the observed disparity after adjusting for differences in socioeconomic status and hospital quality. However, even after these factors were taken into account, nonwhite patients had a 16% higher mortality (OR, 1.16; 95% CI, 1.05-1.27). Hospital quality contributes significantly to racial disparities in outcomes after CABG surgery. However, a significant fraction of this racial disparity remains unexplained. Efforts to decrease racial disparities in health care should focus on underperforming centers of care treating disproportionately high numbers of nonwhite patients.

A smoothing approach for masking spatial data

Individual-level health data are often not publicly available due to confidentiality; masked data are released instead. Therefore, it is important to evaluate the utility of using the masked data in statistical analyses such as regression. In this paper we propose a data masking method which is based on spatial smoothing techniques. The proposed method allows for selecting both the form and the degree of masking, thus resulting in a large degree of flexibility. We investigate the utility of the masked data sets in terms of the mean square error (MSE) of regression parameter estimates when fitting a Generalized Linear Model (GLM) to the masked data. We also show that incorporating prior knowledge on the spatial pattern of the exposure into the data masking may reduce the bias and MSE of the parameter estimates. By evaluating both utility and disclosure risk as functions of the form and the degree of masking, our method produces a risk-utility profile which can facilitate the selection of masking parameters. We apply the method to a study of racial disparities in mortality rates using data on more than 4 million Medicare enrollees residing in 2095 zip codes in the Northeast region of the United States.