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In this large study, the mortality benefits of reducing levels of fine particulate matter air pollution were greater for low-income and higher-income Black persons and for low-income White persons than for higher-income White persons.

Differences in the incidence of cardiopulmonary resuscitation (CPR) provided by bystanders contribute to survival disparities among persons with out-of-hospital cardiac arrest. It is critical to understand whether the incidence of bystander CPR in witnessed out-of-hospital cardiac arrests at home and in public settings differs according to the race or ethnic group of the person with cardiac arrest in order to inform interventions. Within a large U.S. registry, we identified 110,054 witnessed out-of-hospital cardiac arrests during the period from 2013 through 2019. We used a hierarchical logistic regression model to analyze the incidence of bystander CPR in Black or Hispanic persons as compared with White persons with witnessed cardiac arrests at home and in public locations. We analyzed the overall incidence as well as the incidence according to neighborhood racial or ethnic makeup and income strata. Neighborhoods were classified as predominantly White (>80% of residents), majority Black or Hispanic (>50% of residents), or integrated, and as high income (an annual median household income of >$80,000), middle income ($40,000-$80,000), or low income (<$40,000). Overall, 35,469 of the witnessed out-of-hospital cardiac arrests (32.2%) occurred in Black or Hispanic persons. Black and Hispanic persons were less likely to receive bystander CPR at home (38.5%) than White persons (47.4%) (adjusted odds ratio, 0.74; 95% confidence interval [CI], 0.72 to 0.76) and less likely to receive bystander CPR in public locations than White persons (45.6% vs. 60.0%) (adjusted odds ratio, 0.63; 95% CI, 0.60 to 0.66). The incidence of bystander CPR among Black and Hispanic persons was less than that among White persons not only in predominantly White neighborhoods at home (adjusted odds ratio, 0.82; 95% CI, 0.74 to 0.90) and in public locations (adjusted odds ratio, 0.68; 95% CI, 0.60 to 0.75) but also in majority Black or Hispanic neighborhoods at home (adjusted odds ratio, 0.79; 95% CI, 0.75 to 0.83) and in public locations (adjusted odds ratio, 0.63; 95% CI, 0.59 to 0.68) and in integrated neighborhoods at home (adjusted odds ratio, 0.78; 95% CI, 0.74 to 0.81) and in public locations (adjusted odds ratio, 0.73; 95% CI, 0.68 to 0.77). Similarly, across all neighborhood income strata, the frequency of bystander CPR at home and in public locations was lower among Black and Hispanic persons with out-of-hospital cardiac arrest than among White persons. In witnessed out-of-hospital cardiac arrest, Black and Hispanic persons were less likely than White persons to receive potentially lifesaving bystander CPR at home and in public locations, regardless of the racial or ethnic makeup or income level of the neighborhood where the cardiac arrest occurred. (Funded by the National Heart, Lung, and Blood Institute.).

Underserved populations experience higher levels of pain. These disparities persist even after controlling for the objective severity of diseases like osteoarthritis, as graded by human physicians using medical images, raising the possibility that underserved patients’ pain stems from factors external to the knee, such as stress. Here we use a deep learning approach to measure the severity of osteoarthritis, by using knee X-rays to predict patients’ experienced pain. We show that this approach dramatically reduces unexplained racial disparities in pain. Relative to standard measures of severity graded by radiologists, which accounted for only 9% (95% confidence interval (CI), 3–16%) of racial disparities in pain, algorithmic predictions accounted for 43% of disparities, or 4.7× more (95% CI, 3.2–11.8×), with similar results for lower-income and less-educated patients. This suggests that much of underserved patients’ pain stems from factors within the knee not reflected in standard radiographic measures of severity. We show that the algorithm’s ability to reduce unexplained disparities is rooted in the racial and socioeconomic diversity of the training set. Because algorithmic severity measures better capture underserved patients’ pain, and severity measures influence treatment decisions, algorithmic predictions could potentially redress disparities in access to treatments like arthroplasty. An algorithmic, machine-learning approach to measuring severe pain from osteoarthritis applied to X-ray images of knees suggests that reported disparities in knee pain in underserved populations can be reduced by comparison with use of standard radiographic measures of disease severity.

This cross-sectional study examines trends in the suicide rate among racial and ethnic subgroups in the United States from 1999 to 2019.

Among the 50+ million informal caregivers in the US, substantial gender, racial/ethnic, and socioeconomic disparities in caregiving intensity are well-documented. However, those disparities may be more nuanced: gender disparities in caregiving intensity may vary by race/ethnicity (White, Black, and Hispanic) and socioeconomic status (SES). We used data from the 2011 National Study of Caregiving and applied generalized linear models to estimate associations between three measures of caregiver intensity (ADLs, IADLs, and hours caregiving/month) and the three sociodemographic factors with their interaction terms. Black female caregivers provided significantly higher levels of care than White females and males for both IADL caregiving and hours/month spent caregiving. Black caregivers spent an average of 28.5 more hours/month (95%CI 1.7–45.2) caregiving than White caregivers. These findings highlight the need to understand the complex disparities within population subgroups and how intersections between gender, race/ethnicity, and SES can be used to develop effective policies to reduce disparities and improve caregiver quality-of-life.

Since its founding, the US government has sorted people into racial/ethnic categories for the purpose of allowing or disallowing their access to social services and protections. The current Office of Management and Budget racial/ethnic categories originated in a dominant racial narrative that assumed a binary biological difference between Whites and non-Whites, with a hard-edged separation between them. There is debate about their continued use in researching group differences in mortality profiles and health outcomes: should we use them with modifications, cease using them entirely, or develop a new epistemology of human similarities and differences? This essay offers a research framework for including in these debates the daily lived experiences of the 110 million racialized non-White Americans whose lived experiences are the legacy of historically limited access to society’s services and protections. The experience of Latinos in California is used to illustrate the major elements of this framework that may have an effect on mortality and health outcomes: a subaltern fuzzy-edged multivalent racial narrative, agency, voice, and community and cultural resilience.

Background An established body of literature has shown evidence of implicit bias in the health care system on the basis of patient race and ethnicity that contributes to well documented disparities in outcomes. However, little is known about the influence of patient race and ethnicity on the decision to order diagnostic radiology exams in the acute care setting. This study examines the role of patient race and ethnicity on the likelihood of diagnostic imaging exams being ordered during United States emergency department encounters. Methods Publicly available data from the National Hospital Ambulatory Medical Care Survey Emergency Department sample for the years 2006–2016 was compiled. The proportion of patient encounters where diagnostic imaging was ordered was tabulated by race/ethnicity, sub-divided by imaging modality. A multivariable logistic regression model was used to evaluate the influence of patient race/ethnicity on the ordering of diagnostic imaging controlling for other patient and hospital characteristics. Survey weighting variables were used to formulate national-level estimates. Results Using the weighted data, an average of 131,558,553 patient encounters were included each year for the 11-year study period. Imaging was used at 46% of all visits although this varied significantly by patient race and ethnicity with white patients receiving medical imaging at 49% of visits and non-white patients at 41% of visits ( p  < 0.001). This effect persisted in the controlled regression model and across all imaging modalities with the exception of ultrasound. Other factors with a significant influence on imaging use included patient age, gender, insurance status, number of co-morbidities, hospital setting (urban vs non-urban) and hospital region. There was no evidence to suggest that the disparate use of imaging by patient race and ethnicity changed over the 11-year study time period. Conclusion The likelihood that a diagnostic imaging exam will be ordered during United States emergency department encounters differs significantly by patient race and ethnicity even when controlling for other patient and hospital characteristics. Further work must be done to understand and mitigate what may represent systematic bias and ensure equitable use of health care resources.

Racial and ethnic minority groups, such as Black, Hispanic, American Indian or Alaska Native, and Asian or Pacific Islander persons, often experience higher rates of severe influenza disease. To describe rates of influenza-associated hospitalization, intensive care unit (ICU) admission, and in-hospital death by race and ethnicity over 10 influenza seasons. This cross-sectional study used data from the Influenza-Associated Hospitalization Surveillance Network (FluSurv-NET), which conducts population-based surveillance for laboratory-confirmed influenza-associated hospitalizations in selected counties, representing approximately 9% of the US population. Influenza hospitalizations from the 2009 to 2010 season to the 2018 to 2019 season were analyzed. Data were analyzed from October 2020 to July 2021. The main outcomes were age-adjusted and age-stratified rates of influenza-associated hospitalization, ICU admission, and in-hospital death by race and ethnicity overall and by influenza season. Among 113 352 persons with an influenza-associated hospitalization (34 436 persons [32.0%] aged ≥75 years; 61 009 [53.8%] women), 70 225 persons (62.3%) were non-Hispanic White (White), 24 850 persons (21.6%) were non-Hispanic Black (Black), 11 903 persons (10.3%) were Hispanic, 5517 persons (5.1%) were non-Hispanic Asian or Pacific Islander, and 857 persons (0.7%) were non-Hispanic American Indian or Alaska Native. Among persons aged younger than 75 years and compared with White persons of the same ages, Black persons were more likely to be hospitalized (eg, age 50-64 years: rate ratio [RR], 2.50 95% CI, 2.43-2.57) and to be admitted to an ICU (eg, age 50-64 years: RR, 2.09; 95% CI, 1.96-2.23). Among persons aged younger than 50 years and compared with White persons of the same ages, American Indian or Alaska Native persons were more likely to be hospitalized (eg, age 18-49 years: RR, 1.72; 95% CI, 1.51-1.96) and to be admitted to an ICU (eg, age 18-49 years: RR, 1.84; 95% CI, 1.40-2.42). Among children aged 4 years or younger and compared with White children, hospitalization rates were higher in Black children (RR, 2.21; 95% CI, 2.10-2.33), Hispanic children (RR, 1.87; 95% CI, 1.77-1.97), American Indian or Alaska Native children (RR, 3.00; 95% CI, 2.55-3.53), and Asian or Pacific Islander children (RR, 1.26; 95% CI, 1.16-1.38), as were rates of ICU admission (Black children: RR, 2.74; 95% CI, 2.43-3.09; Hispanic children: RR, 1.96; 95% CI, 1.73-2.23; American Indian and Alaska Native children: RR, 3.51; 95% CI, 2.45-5.05). In this age group and compared with White children, in-hospital death rates were higher among Hispanic children (RR, 2.98; 95% CI, 1.23-7.19), Black children (RR, 3.39; 95% CI, 1.40-8.18), and Asian or Pacific Islander children (RR, 4.35; 95% CI, 1.55-12.22). Few differences were observed in rates of severe influenza-associated outcomes by race and ethnicity among adults aged 75 years or older. For example, in this age group, compared with White adults, hospitalization rates were slightly higher only among Black adults (RR, 1.05; 95% CI 1.02-1.09). Overall, Black persons had the highest age-adjusted hospitalization rate (68.8 [95% CI, 68.0-69.7] hospitalizations per 100 000 population) and ICU admission rate (11.6 [95% CI, 11.2-11.9] admissions per 100 000 population). This cross-sectional study found racial and ethnic disparities in rates of severe influenza-associated disease. These data identified subgroups for whom improvements in influenza prevention efforts could be targeted.

Background Colorectal cancer is a leading cause of morbidity and mortality across U.S. racial/ethnic groups. Existing studies often focus on a particular race/ethnicity or single domain within the care continuum. Granular exploration of disparities among different racial/ethnic groups across the entire colon cancer care continuum is needed. We aimed to characterize differences in colon cancer outcomes by race/ethnicity across each stage of the care continuum. Methods We used the 2010–2017 National Cancer Database to examine differences in outcomes by race/ethnicity across six domains: clinical stage at presentation; timing of surgery; access to minimally invasive surgery; post-operative outcomes; utilization of chemotherapy; and cumulative incidence of death. Analysis was via multivariable logistic or median regression, with select demographics, hospital factors, and treatment details as covariates. Results 326,003 patients (49.6% female, 24.0% non-White, including 12.7% Black, 6.1% Hispanic/Spanish, 1.3% East Asian, 0.9% Southeast Asian, 0.4% South Asian, 0.3% AIAE, and 0.2% NHOPI) met inclusion criteria. Relative to non-Hispanic White patients: Southeast Asian (OR 1.39, p  < 0.01), Hispanic/Spanish (OR 1.11 p  < 0.01), and Black (OR 1.09, p  < 0.01) patients had increased odds of presenting with advanced clinical stage. Southeast Asian (OR 1.37, p  < 0.01), East Asian (OR 1.27, p  = 0.05), Hispanic/Spanish (OR 1.05 p  = 0.02), and Black (OR 1.05, p  < 0.01) patients had increased odds of advanced pathologic stage. Black patients had increased odds of experiencing a surgical delay (OR 1.33, p  < 0.01); receiving non-robotic surgery (OR 1.12, p  < 0.01); having post-surgical complications (OR 1.29, p  < 0.01); initiating chemotherapy more than 90 days post-surgery (OR 1.24, p  < 0.01); and omitting chemotherapy altogether (OR 1.12, p  = 0.05). Black patients had significantly higher cumulative incidence of death at every pathologic stage relative to non-Hispanic White patients when adjusting for non-modifiable patient factors ( p  < 0.05, all stages), but these differences were no longer statistically significant when also adjusting for modifiable factors such as insurance status and income. Conclusions Non-White patients disproportionately experience advanced stage at presentation. Disparities for Black patients are seen across the entire colon cancer care continuum. Targeted interventions may be appropriate for some groups; however, major system-level transformation is needed to address disparities experienced by Black patients.

This cross-sectional study evaluates changes in reporting practices for race, sex, and socioeconomic status in randomized clinical trials in 2015 vs 2019.