IMPORTANCE: The culture of academic medicine may foster mistreatment that disproportionately affects individuals who have been marginalized within a given society (minoritized groups) and compromises ...workforce vitality. Existing research has been limited by a lack of comprehensive, validated measures, low response rates, and narrow samples as well as comparisons limited to the binary gender categories of male or female assigned at birth (cisgender). OBJECTIVE: To evaluate academic medical culture, faculty mental health, and their relationship. DESIGN, SETTING, AND PARTICIPANTS: A total of 830 faculty members in the US received National Institutes of Health career development awards from 2006-2009, remained in academia, and responded to a 2021 survey that had a response rate of 64%. Experiences were compared by gender, race and ethnicity (using the categories of Asian, underrepresented in medicine defined as race and ethnicity other than Asian or non-Hispanic White, and White), and lesbian, gay, bisexual, transgender, queer (LGBTQ+) status. Multivariable models were used to explore associations between experiences of culture (climate, sexual harassment, and cyber incivility) with mental health. EXPOSURES: Minoritized identity based on gender, race and ethnicity, and LGBTQ+ status. MAIN OUTCOMES AND MEASURES: Three aspects of culture were measured as the primary outcomes: organizational climate, sexual harassment, and cyber incivility using previously developed instruments. The 5-item Mental Health Inventory (scored from 0 to 100 points with higher values indicating better mental health) was used to evaluate the secondary outcome of mental health. RESULTS: Of the 830 faculty members, there were 422 men, 385 women, 2 in nonbinary gender category, and 21 who did not identify gender; there were 169 Asian respondents, 66 respondents underrepresented in medicine, 572 White respondents, and 23 respondents who did not report their race and ethnicity; and there were 774 respondents who identified as cisgender and heterosexual, 31 as having LGBTQ+ status, and 25 who did not identify status. Women rated general climate (5-point scale) more negatively than men (mean, 3.68 95% CI, 3.59-3.77 vs 3.96 95% CI, 3.88-4.04, respectively, P < .001). Diversity climate ratings differed significantly by gender (mean, 3.72 95% CI, 3.64-3.80 for women vs 4.16 95% CI, 4.09-4.23 for men, P < .001) and by race and ethnicity (mean, 4.0 95% CI, 3.88-4.12 for Asian respondents, 3.71 95% CI, 3.50-3.92 for respondents underrepresented in medicine, and 3.96 95% CI, 3.90-4.02 for White respondents, P = .04). Women were more likely than men to report experiencing gender harassment (sexist remarks and crude behaviors) (71.9% 95% CI, 67.1%-76.4% vs 44.9% 95% CI, 40.1%-49.8%, respectively, P < .001). Respondents with LGBTQ+ status were more likely to report experiencing sexual harassment than cisgender and heterosexual respondents when using social media professionally (13.3% 95% CI, 1.7%-40.5% vs 2.5% 95% CI, 1.2%-4.6%, respectively, P = .01). Each of the 3 aspects of culture and gender were significantly associated with the secondary outcome of mental health in the multivariable analysis. CONCLUSIONS AND RELEVANCE: High rates of sexual harassment, cyber incivility, and negative organizational climate exist in academic medicine, disproportionately affecting minoritized groups and affecting mental health. Ongoing efforts to transform culture are necessary.
IMPORTANCE: Clinical prediction models estimated with health records data may perpetuate inequities. OBJECTIVE: To evaluate racial/ethnic differences in the performance of statistical models that ...predict suicide. DESIGN, SETTING, AND PARTICIPANTS: In this diagnostic/prognostic study, performed from January 1, 2009, to September 30, 2017, with follow-up through December 31, 2017, all outpatient mental health visits to 7 large integrated health care systems by patients 13 years or older were evaluated. Prediction models were estimated using logistic regression with LASSO variable selection and random forest in a training set that contained all visits from a 50% random sample of patients (6 984 184 visits). Performance was evaluated in the remaining 6 996 386 visits, including visits from White (4 031 135 visits), Hispanic (1 664 166 visits), Black (578 508 visits), Asian (313 011 visits), and American Indian/Alaskan Native (48 025 visits) patients and patients without race/ethnicity recorded (274 702 visits). Data analysis was performed from January 1, 2019, to February 1, 2021. EXPOSURES: Demographic, diagnosis, prescription, and utilization variables and Patient Health Questionnaire 9 responses. MAIN OUTCOMES AND MEASURES: Suicide death in the 90 days after a visit. RESULTS: This study included 13 980 570 visits by 1 433 543 patients (64% female; mean SD age, 42 18 years. A total of 768 suicide deaths were observed within 90 days after 3143 visits. Suicide rates were highest for visits by patients with no race/ethnicity recorded (n = 313 visits followed by suicide within 90 days, rate = 5.71 per 10 000 visits), followed by visits by Asian (n = 187 visits followed by suicide within 90 days, rate = 2.99 per 10 000 visits), White (n = 2134 visits followed by suicide within 90 days, rate = 2.65 per 10 000 visits), American Indian/Alaskan Native (n = 21 visits followed by suicide within 90 days, rate = 2.18 per 10 000 visits), Hispanic (n = 392 visits followed by suicide within 90 days, rate = 1.18 per 10 000 visits), and Black (n = 65 visits followed by suicide within 90 days, rate = 0.56 per 10 000 visits) patients. The area under the curve (AUC) and sensitivity of both models were high for White, Hispanic, and Asian patients and poor for Black and American Indian/Alaskan Native patients and patients without race/ethnicity recorded. For example, the AUC for the logistic regression model was 0.828 (95% CI, 0.815-0.840) for White patients compared with 0.640 (95% CI, 0.598-0.681) for patients with unrecorded race/ethnicity and 0.599 (95% CI, 0.513-0.686) for American Indian/Alaskan Native patients. Sensitivity at the 90th percentile was 62.2% (95% CI, 59.2%-65.0%) for White patients compared with 27.5% (95% CI, 21.0%-34.7%) for patients with unrecorded race/ethnicity and 10.0% (95% CI, 0%-23.0%) for Black patients. Results were similar for random forest models, with an AUC of 0.812 (95% CI, 0.800-0.826) for White patients compared with 0.676 (95% CI, 0.638-0.714) for patients with unrecorded race/ethnicity and 0.642 (95% CI, 0.579-0.710) for American Indian/Alaskan Native patients and sensitivities at the 90th percentile of 52.8% (95% CI, 50.0%-55.8%) for White patients, 29.3% (95% CI, 22.8%-36.5%) for patients with unrecorded race/ethnicity, and 6.7% (95% CI, 0%-16.7%) for Black patients. CONCLUSIONS AND RELEVANCE: These suicide prediction models may provide fewer benefits and more potential harms to American Indian/Alaskan Native or Black patients or those with undrecorded race/ethnicity compared with White, Hispanic, and Asian patients. Improving predictive performance in disadvantaged populations should be prioritized to improve, rather than exacerbate, health disparities.
To compare racial and ethnic differences between obstetrician-gynecologists (ob-gyns) and other large groups of adult medical specialists who provide the predominant care of women. Whether physician ...diversity influences their practice locations in underserved areas was also sought.
This cross-sectional study reports an analysis of U.S. national data about racial and ethnic characteristics, gender, and specialty (obstetrics and gynecology, general internal medicine, family medicine, emergency medicine) of 190,379 physicians who came from three resources (Association of American Medical Colleges Student Records System, Association of American Medical Colleges Minority Physicians Database, American Medical Association Physician Masterfile). Underserved locations were identified as being rural, having 20% or more of the population living in poverty or being federally designated as areas of professional shortages or underserved populations. Bivariate measures of associations were performed to study the association between physician race and ethnicity and their practice location.
Female physicians in all specialties were more likely than males to be nonwhite, and ob-gyns were most likely to be female (61.9%). Compared with other studied specialists, ob-gyns had the highest proportion of underrepresented minorities (combined, 18.4%), especially black (11.1%) and Hispanic (6.7%) physicians. Underrepresented minority ob-gyns were more likely than white or Asians to practice in federally funded underserved areas or where poverty levels were high. Native Americans, Alaska Natives, and Pacific Islanders were the ob-gyn group with the highest proportion practicing in rural areas.
Compared with other adult medical specialists, ob-gyns have a relatively high proportion of black and Hispanic physicians. A higher proportion of underrepresented minority ob-gyns practiced at medically underserved areas.
Disparities in Access to Oral Health Care Northridge, Mary E; Kumar, Anjali; Kaur, Raghbir
Annual review of public health,
04/2020, Volume:
41, Issue:
1
Journal Article
Peer reviewed
Open access
In the United States, people are more likely to have poor oral health if they are low-income, uninsured, and or members of racial ethnic minority, immigrant, or rural populations who have suboptimal ...access to quality oral health care. As a result, poor oral health serves as the national symbol of social inequality. There is increasing recognition among those in public health that oral diseases such as dental caries and periodontal disease and general health conditions such as obesity and diabetes are closely linked by sharing common risk factors, including excess sugar consumption and tobacco use, as well as underlying infection and inflammatory pathways. Hence, efforts to integrate oral health and primary health care, incorporate interventions at multiple levels to improve access to and quality of services, and create health care teams that provide patient-centered care in both safety net clinics and community settings may narrow the gaps in access to oral health care across the life course.
BACKGROUND AND PURPOSE—Substantial variability exists in the use of life-prolonging treatments for patients with stroke, especially near the end of life. This study explores patterns of palliative ...care utilization and death in hospitalized patients with stroke across the United States.
METHODS—Using the 2010 to 2012 nationwide inpatient sample databases, we included all patients discharged with stroke identified by International Classification of Diseases-Ninth Revision codes. Strokes were subclassified as ischemic, intracerebral, and subarachnoid hemorrhage. We compared demographics, comorbidities, procedures, and outcomes between patients with and without a palliative care encounter (PCE) as defined by the International Classification of Diseases-Ninth Revision code V66.7. Pearson χ test was used for categorical variables. Multivariate logistic regression was used to account for hospital, regional, payer, and medical severity factors to predict PCE use and death.
RESULTS—Among 395 411 patients with stroke, PCE was used in 6.2% with an increasing trend over time (P<0.05). We found a wide range in PCE use with higher rates in patients with older age, hemorrhagic stroke types, women, and white race (all P<0.001). Smaller and for-profit hospitals saw lower rates. Overall, 9.2% of hospitalized patients with stroke died, and PCE was significantly associated with death. Length of stay in decedents was shorter for patients who received PCE.
CONCLUSIONS—Palliative care use is increasing nationally for patients with stroke, especially in larger hospitals. Persistent disparities in PCE use and mortality exist in regards to age, sex, race, region, and hospital characteristics. Given the variations in PCE use, especially at the end of life, the use of mortality rates as a hospital quality measure is questioned.
IMPORTANCE: Workplace mistreatment can manifest as microaggressions that cause chronic, severe distress. As physician burnout becomes a global crisis, quantitative research to delineate the impact of ...microaggressions is imperative. OBJECTIVES: To examine the prevalence and nature of sexist and racial/ethnic microaggressions against female and racial/ethnic–minority surgeons and anesthesiologists and assess the association with physician burnout. DESIGN, SETTING, AND PARTICIPANTS: This cross-sectional survey evaluated microaggressions and physician burnout within a diverse cohort of surgeons and anesthesiologists in a large health maintenance organization. A total of 1643 eligible participants were sent a recruitment email on January 8, 2020, 1609 received the email, and 652 replied, for a response rate of 41%. The study survey remained open until February 20, 2020. A total of 588 individuals (37%) were included in the study after exclusion criteria were applied. EXPOSURES: The Maslach Burnout Inventory, the Racial Microaggression Scale, and the Sexist Microaggression Experience and Stress Scale. MAIN OUTCOMES AND MEASURES: The primary outcomes were prevalence and nature of sexist and racial/ethnic microaggressions against female and racial/ethnic–minority surgeons and anesthesiologists using the Sexist Microaggression Experience and Stress Scale and Racial Microaggression Scale. Secondary outcomes were frequency and severity of microaggressions, prevalence of physician burnout, and associations between microaggressions and physician burnout. RESULTS: Data obtained from 588 respondents (249 44% female, 367 62% racial/ethnic minority, 224 38.1% 40-49 years of age) were analyzed. A total of 245 of 259 female respondents (94%) experienced sexist microaggressions, most commonly overhearing or seeing degrading female terms or images. Racial/ethnic microaggressions were experienced by 299 of 367 racial/ethnic–minority physicians (81%), most commonly reporting few leaders or coworkers of the same race/ethnicity. Criminality was rare (18 of 367 5%) but unique to and significantly higher for Hispanic and Black physicians. Individuals who identified as underrepresented minorities were more likely to experience environmental inequities (odds ratio OR, 4.21; 95% CI, 1.6-10.75; P = .002) and criminality (OR, 14.93; 95% CI, 4.5-48.5; P < .001). The prevalence of physician burnout was 47% (280 of 588 physicians) and higher among female physicians (OR, 1.60; 95% CI, 1.03-2.47; P = .04) and racial/ethnic–minority physicians (OR, 2.08; 95% CI, 1.31-3.30; P = .002). Female physicians who experienced sexist microaggressions (racial/ethnic–minority female physicians: OR, 1.84; 95% CI, 1.04-3.25; P = .04; White female physicians: OR, 1.99; 95% CI, 1.07-3.69; P = .03) were more likely to experience burnout. Racial/ethnic–minority female physicians (OR, 1.86; 95% CI, 1.03-3.35; P = .04) who experienced racial microaggressions were more likely to report burnout. Racial/ethnic–minority female physicians who had the compound experience of sexist and racial/ethnic microaggressions (OR, 2.05; 95% CI, 1.14-3.69; P = .02) were more likely to experience burnout. CONCLUSIONS AND RELEVANCE: The prevalence of sexist and racial/ethnic microaggressions against female and racial/ethnic–minority surgeons and anesthesiologists was high and associated with physician burnout. This study provides a valuable response to the increasing call for evidence-based data on surgical workplace mistreatment.
The water footprint of humanity Hoekstra, Arjen Y.; Mekonnen, Mesfin M.
Proceedings of the National Academy of Sciences - PNAS,
02/2012, Volume:
109, Issue:
9
Journal Article
Peer reviewed
Open access
This study quantifies and maps the water footprint (WF) of humanity at a high spatial resolution. It reports on consumptive use of rainwater (green WF) and ground and surface water (blue WF) and ...volumes of water polluted (gray WF). Water footprints are estimated per nation from both a production and consumption perspective. International virtual water flows are estimated based on trade in agricultural and industrial commodities. The global annual average WF in the period 1996-2005 was 9,087 Gm³ /y (74% green, 11% blue, 15% gray). Agricultural production contributes 92%. About one-fifth of the global WF relates to production for export. The total volume of international virtual water flows related to trade in agricultural and industrial products was 2,320 Gm³ /y (68% green, 13% blue, 19% gray). The WF of the global average consumer was 1,385 m³ /y. The average consumer in the United States has a WF of 2,842 m³ /y, whereas the average citizens in China and India have WFs of 1,071 and 1,089 m³ /y, respectively. Consumption of cereal products gives the largest contribution to the WF of the average consumer (27%), followed by meat (22%) and milk products (7%). The volume and pattern of consumption and the WF per ton of product of the products consumed are the main factors determining the WF of a consumer. The study illustrates the global dimension of water consumption and pollution by showing that several countries heavily rely on foreign water resources and that many countries have significant impacts on water consumption and pollution elsewhere.
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BFBNIB, NMLJ, NUK, PNG, SAZU, UL, UM, UPUK
Prior efforts to characterize disparities in radiation therapy access and receipt have not comprehensively investigated interplay between race, socioeconomic status, and geography relative to ...oncologic outcomes. This study sought to define these complex relationships at the US county level for prostate cancer (PC) and invasive breast (BC) cancer to build a tool that facilitates identification of “radiotherapy deserts”—regions with mismatch between radiation therapy resources and oncologic need.
An ecologic study model was constructed using national databases to evaluate 3,141 US counties. Radiation therapy resources and use densities were operationalized as physicians to persons at risk (PPR) and use to persons at risk (UPR): the number of attending radiation oncologists and Medicare beneficiaries per 100,000 persons at risk, respectively. Oncologic need was defined by “hot zone” counties with ≥2 standard deviations (SDs) above mean incidence and death rates. Univariable and multivariable logistic regressions examined links between PPR and UPR densities, epidemiologic variables, and hot zones for oncologic outcomes. Statistics are reported at a significance level of P < .05.
The mean (SD) PPR and UPR densities were 2.1 (5.9) and 192.6 (557.6) for PC and 1.9 (5.3) and 174.4 (501.0) for BC, respectively. Counties with high PPR and UPR densities were predominately metropolitan (odds ratio OR, 2.9-4.4), generally with a higher percentage of Black non-Hispanic constituents (OR, 1.5-2.3). Incidence and death rate hot zones were largely nonmetropolitan (OR, 0.3-0.6), generally with a higher percentage of Black non-Hispanic constituents (OR, 3.2-6.3). Lower PPR density was associated with death rate hot zones for both types of cancer (OR, 0.8-0.9); UPR density was generally not linked to oncologic outcomes on multivariable analysis.
The study found that mismatch between oncologic need with PPR and UPR disproportionately affects nonmetropolitan communities with a higher percentage of Black non-Hispanic constituents. An interactive web platform (bit.ly/densitymaps) was developed to visualize “radiotherapy deserts” and drive targeted investigation of underlying barriers to care in areas of highest need, with the goal of reducing health inequities in this context.
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