US Census Research Articles

Middle Eastern and North African: Recognizing the New US Census Category in Anesthesiology Research and Practice

Middle Eastern and North African: Recognizing the New US Census Category in Anesthesiology Research and Practice

Influenza Vaccination, Household Composition, and Race-Based Differences in Influenza Incidence: An Agent-Based Modeling Study.

Objectives. To estimate the effect of influenza vaccination disparities. Methods. We compared symptomatic influenza cases between Black and White races in 2 scenarios: (1) race- and age-specific vaccination coverage and (2) equal vaccination coverage. We also compared differences in household composition between races. We used the Framework for Reconstructing Epidemiological Dynamics, an agent-based model that assigns US Census‒based age, race, households, and geographic location to agents (individual people), in US counties of varying racial and age composition. Results. Influenza cases were highest in counties with higher proportions of children. Cases were up to 30% higher in Black agents with both race-based and race-equal vaccination coverage. Compared with corresponding categories of White households, cases in Black households without children were lower and with children were higher. Conclusions. Racial disparities in influenza cases persisted after equalizing vaccination coverage. The proportion of children in the population contributed to the number of influenza cases regardless of race. Differences in household composition may provide insight into racial differences and offer an opportunity to improve vaccination coverage to reduce influenza burden for both races. (Am J Public Health. Published online ahead of print November 14, 2024:e1-e8. https://doi.org/10.2105/AJPH.2024.307878).

Abstract 4140149: Differences in Interventional Treatment Outcomes of Peripheral Arterial Disease between African American Females, African American Males, and Caucasian Females

Introduction: Several recent publications demonstrated worse outcomes of interventional treatment of peripheral arterial disease (PAD) in patients of African American (AA) descent compared to Caucasians (C), and in female patients compared to male patients. However, studies addressing sex differences in outcomes, included predominantly white female patients. To our knowledge, there are no published studies specifically addressing outcomes of interventional treatment of PAD in female patients of African American descent. Aims: 1. To determine if the outcomes of interventional treatment of PAD in female patients of African American (FAA) descent differ from male African American patients (MAA), and Caucasian female patients (FC). If such differences exist, to identify factors associated with it. Methods: This study has a cross-sectional design with systematically retrospective data collection by the National Vascular Quality Initiative. Included in this study was data on patients treated with endovascular and open surgical options for symptomatic PAD. Statistical analysis was done using IBM Statistic SPSS V25. Results: 447,263 unique cases containing required data were available in the VQI database. Among them, 171,250 were female patients, of which 32,966 were FAA, 126,519 FC, and 39,461 MAA. This race and gender distribution is not significantly different from the US population structure (US Census Bureau 2023). 1 However, female to male ratio was higher in AA (0.83) compared to C (0.58, p<0.0001). FAA were younger (65.143+/-9.59) compared to FC (69.16+/-10.32, P<0.00001). Comparison of comorbidities, smoking rates, pre-interventional medications and post-interventional outcomes are listed in Table 1. Multivariate analysis confirmed higher amputation rate among FAA compared to FC and to MAA and showed no significant difference in mortality. Conclusions: FAA patients who require interventional treatment for PAD have significantly higher rate of hypertension and diabetes compared to FC and MAA patients and have higher amputation rates. It appears that differences in clinical outcomes of PAD treatment in FAA are related mostly if not entirely to poorly managed comorbidities existed prior to intervention.

Abstract 4130622: Neonatal Outcomes of Hypertensive Women Across US Races: 2016-2022

Background: Maternal hypertension, a major pregnancy complication, can adversely affect newborn health. We aim to evaluate the racial and ethnic disparities in neonatal outcomes among hypertensive pregnant women in the United States. Methods: Using data from the CDC WONDER Natality database, we conducted a retrospective cohort study focusing on live births to hypertensive mothers from 2016 to 2022. Neonatal outcomes, including NICU admissions, low birth weight, infant mortality, and assisted ventilation, were analyzed by calculating rates [95% CIs] per 1000 live births across maternal racial/ethnic groups and the US Census Bureau's regional classification: Northeast, Midwest, South, and West. Results: We analyzed 2,336,679 live births to hypertensive women (23% pre-pregnancy; 77% gestational). This cohort comprised: 0.2% infants born to Native Hawaiian/other Pacific Islander women (NH/PI), 0.9% to American Indian/Alaska Native women (AI/AN), 3.8% to Asian American women (AA), 19.6% to Hispanic/Latino women (H/L), 20.0% to Black/African American women (BA), and 55.4% to White American women (WA). Infant mortality rates were highest in BA (3.6 [3.5, 3.8]), followed by AA (2.1 [1.8, 2.4]), AI/AN (2.1 [1.6, 2.7]), H/L (1.9 [1.8, 2.0]), NH/PI (1.9 [1.0, 3.3]), and lowest in WA (1.5 [1.4, 1.6]). Similarly, NICU admission rates were highest in BA (217.2 [216.1, 218.4]) and lowest in WA (156 [155.4, 156.6]). Assisted ventilation rates were highest in NH/PI (131.8 [123.4, 140.7]) and lowest in AA (87.8 [86.0, 89.7]). Low birth weight rates were highest in BA (235.1 [233.9, 236.3]) and lowest in WA (121.8 [121.2, 122.4]). The Midwest had the highest rates for NICU admissions in NH/PI (254.2 [217.2, 295.2]), assisted ventilation in AI/AN (143.8 [133.2, 155.1]), and mortality in BA (4.1 [3.7, 4.5]). The South had the highest rate of low birth weight for BA (244.4 [242.9, 246.0]). Conclusion: Significant racial and regional disparities exist in neonatal outcomes among hypertensive women in the US. BA mothers consistently experienced the poorest outcomes, while WA mothers had the best. Further research is crucial to understand the reasons behind these disparities and develop targeted interventions for high-risk populations.

Abstract 4134079: Neighborhood-Level Indices of Social Disadvantage and Cardiovascular-Kidney-Metabolic Health

Background: Several area-level indices exist that integrate a variety of social drivers of health. However, whether certain indices better capture neighborhood-level variability in cardiovascular-kidney-metabolic (CKM) outcomes is not well known. Aims: We sought to examine the associations of census tract-level indices of social disadvantage with CKM outcomes. Methods: Exposures for the analysis included seven indices of social disadvantage (ADI, COI, EJI, NDI, SDI, SREI, SVI) based on census tract-level data from the 2010-2019 American Community Survey (ACS) and census tract-level median household income from the 2015-2019 ACS data. Outcomes included the census tract-level prevalence of CKM outcomes (obesity, hypertension, diabetes, hyperlipidemia, chronic kidney disease, coronary heart disease [CHD], and stroke) from the 2019 Behavioral Risk Factor Surveillance System. All indices and median income were standardized, and we used linear regression to examine the associations between each census tract-level social measure and CKM outcomes, adjusted for population size and median age. Next, we calculated the △r 2 in adjusted models for the association of median income with each CKM outcome when each index was added. Results: Among 65,476 US census tracts, median (IQR) population size was 4068 (2969, 5374), age was 39 years (35, 44), and household income was $58,870 (44276, 79802). Median income as well as each index was significantly associated with census tract-level prevalence of each CKM outcome assessed (p < 0.05). The r 2 (Panel A) and △r 2 values (Panel B) varied for each of the social measures and CKM outcomes, with higher r 2 values when each index was individually added to median income compared with income alone. For example, for CHD, the r 2 ranged between 0.39 to 0.67 and △r 2 ranged from 0.01 to 0.10. Conclusions: Neighborhood-level measures of social disadvantage are differentially associated with CKM outcomes, with a large proportion of the variability explained by median income. Identifying the advantages and disadvantages of each index and comparison with median income can inform the prioritization of measures for specific outcomes.

Abstract 4123373: Estimating obesity-attributable cardiovascular disease burden in the United States: a Bayesian network analysis

Background: Obesity is a known contributor to the development of cardiovascular disease (CVD) and increases the risk of subsequent mortality. To fully understand the burden of obesity, accurate information regarding its effects on CVD is necessary. Current estimates are limited by a focus on direct effects, use of non-representative data sources, and a reliance on inaccurate diagnosis codes. Aim: To determine the size of CVD burden attributable to obesity in the US and identify the mechanisms through which obesity affects CVD. Methods: This study used data collected from US adults (aged ≥35 years) participating in the National Health and Nutrition Examination Survey (NHANES) from 1999 to 2020 and US Census projections. NHANES data were longitudinally adapted, and participants were excluded if they had missing data for weight history, risk factors, or a given outcome of interest. Bayesian networks (BNs) mapping out the relationship between risk factors and each outcome were constructed to estimate current CVD risk and expected CVD risk in the absence of obesity. Obesity-attributable CVD burden was then calculated for each outcome, and the direct and indirect pathways through which changes in CVD risk occur were characterized. A subgroup analysis was conducted in non-smoking participants aged ≤65 years for whom obesity is likely the primary CVD risk factor. Results: The final sample included data from approximately 29,000 participants. Of these, 1286 (4.3%) had a history of myocardial infarction (MI), 1283 (4.4%) had a history of stroke, 1092 (3.7%) had a history of heart failure (HF), and 1992 (6.7%) had a history of CVD (composite of MI, stroke, angina, coronary heart disease, and HF). Results from the fitted BN indicate that 21% of MI, 16% of stroke, 38% of HF, and 19% of CVD cases were attributable to obesity, with ≥80% of this burden due to the effect of obesity on intermediate risk factors (hypertension, type 2 diabetes, and prior cardiovascular events). In the subgroup analysis, the obesity-attributable CVD burden was approximately twice as high for non-smokers aged ≤65 years, with 39% of MI, 32% of stroke, 65% of HF, and 38% of CVD cases attributable to obesity. Conclusion: Through a sophisticated network modeling approach, we generated estimates of obesity-attributable CVD burden in the US. Results highlight the importance of obesity as a CVD risk factor, particularly in younger non-smokers, and provide insight into the nature of this relationship.

Abstract 4136636: Analysis of Racial Disparities in the Training Path to Cardiology: Trends from 2012 to 2022

Introduction: Substantial evidence indicates that racial and ethnic diversity among the physician workforce bridges cultural gaps and improves patient care. Trends in racial diversity across the full training pipeline from undergraduate to practicing cardiologist are not yet well-characterized. Aims: We analyze racial disparities at each stage of training towards becoming a practicing cardiologist, and identify changes in these disparities between 2012 and 2022. Methods: We conducted a retrospective analysis of data specifying the racial composition of medical trainees acquired from the Association of American Medical Colleges, Accreditation Council for Graduate Medical Education, and Electronic Residency Application Service. Population data was acquired from the US Census Bureau. We computed the representation quotient (RQ) for each racial group at each stage to compare representation among the trainees or physicians to age-matched segments of the US population. Results: RQ decreases from undergraduate to active cardiologist for African Americans (0.719 to 0.314), Hispanics (0.660 to 0.359), American Indians (0.551 to 0.221), and Native Hawaiians (1.121 to 0.512). The lowest RQs of 0.133 and 0.137 were observed for American Indian active internal medicine residents and cardiology fellows, respectively. Racial disparities in medical education declined between 2012 and 2022, with RQs increasing from 0.541 to 0.735 for African American medical school matriculants and from 0.444 to 0.578 for Hispanic medical school matriculants. Similar increases were seen in the active cardiologist population for African Americans (2013 RQ: 0.227, 2022 RQ: 0.342) and Hispanics (2013 RQ: 0.283, 2022 RQ: 0.375). Conclusion: While racial diversity in the cardiology training pipeline has increased over the last decade, significant disparities persist for under-represented minorities. Addressing these barriers will help achieve a cardiology workforce reflective of the diverse population it serves.

Machine learning insights into regional dynamics and prevalence of COVID-19 variants in US health and human services regions

BackgroundThe COVID-19 pandemic arising from the emergence of SARS-CoV-2 in late 2019 has led to global devastation with millions of lives lost by January 2024. Despite the WHO’s declaration of the end of the global health emergency in May 2023, the virus persists, propelled by mutations. Variants continue to challenge vaccination efforts, underscoring the necessity for ongoing vigilance. This study aimed at contributing to a more data-driven approach to pandemic management by employing random forest regression to analyze regional variant prevalence.MethodsThis study utilized data from various sources including National COVID Cohort Collaborative database, Bureau of Transportation Statistics, World Weather Online, EPA, and US Census. Key variables include pollution, weather, travel patterns, and demographics. Preprocessing steps involved merging and normalization of datasets. Training data spanned from January 2021 to February 2023. The Random Forest (RF) Regressor was chosen for its accuracy in modeling. To prevent data leakage, time series splits were employed. Model performance was evaluated using metrics such as MSE and R-squared.ResultsThe Alpha variant was predominant in the Southeast, with less than 80% share even at its peak. Delta surged initially in Kansas City and maintained dominance there for over 5 months. Omicron subvariant BA.5 spread nationwide, becoming predominant across all Health and Human Services regions simultaneously, with New York seeing the earliest and fastest decline in its share. Variant XBB.1.5 concentrated more in the Northeast, but limited data hindered full analysis. Using RF Regressor, key features affecting spread patterns were identified, with high predictive accuracy. Each variant showed specific environmental correlations; for instance, Alpha with air quality index, Delta with ozone density, BA.5 with UV index, and XBB.1.5 with land area and income. Correlation analysis further highlighted variant-specific associations.ConclusionsThis research provides a comprehensive analysis of the regional distribution of COVID-19 variants, offering critical insights for devising targeted public health strategies. By utilizing machine learning, the study uncovers the complex factors contributing to variant spread and reveals how specific factors contribute to variant prevalence, offering insights crucial for pandemic management.

State and Local Government Expenditures and Infant Mortality.

A previous study reported that increased state and local government expenditures were associated with decreased infant mortality rates (IMRs). However, reported estimates of the association between expenditures and IMR represented the degree to which the association changed each year, not the main effect. We reproduced the original results, reporting this main effect and replicated the analysis using improved methodology and updated data. For the reproduction analysis, we used methods and data identical to the original study: A publicly-posted, state-level data set of expenditures from 2000 to 2014 US Census Bureau survey data linked to 2-year lagged IMR data with a random intercept model including an interaction between time and expenditures. For the replication analysis, we added 5 years of data and adjusted for fixed state differences and inflation. In the reproduction, the main effects of total, environmental, and educational expenditures on IMR were much larger than the interaction effects previously reported as the main effects. For example, a 1-SD increase in per-capita total expenditures was associated with a reduction of 0.35 infant deaths per 1000 live births instead of 0.02 deaths per 1000 live births originally reported. In the updated replication, the main effects were generally even larger (eg, -0.51 deaths per 1000 per SD increase in total expenditures). Increased total expenditures were associated with absolute but not relative reductions in Black-white IMR gaps. State and local government expenditures are associated with greater reductions in IMR than previously reported, underscoring the importance of continued public investment.

US Cancer Mortality Trends Among Asian and Pacific Islander Populations

Cancer is the leading cause of death among Asian American individuals and the second leading cause of death among Native Hawaiian and Pacific Islander people. To evaluate longitudinal cancer mortality trends from 1999 to 2020 among Asian American and Pacific Islander populations in the US by demographic characteristics. This cross-sectional study used the Centers for Disease Control and Prevention Wide-Ranging Online Data for Epidemiologic Research database to obtain age-adjusted cancer death rates among Asian American and Pacific Islander individuals of all ages between January 1, 1999, and December 31, 2020. Data were analyzed from January 12 to March 19, 2024. Age, sex, cancer type, and US census regions. Trends and average annual percent changes (AAPCs) in age-adjusted cancer-specific mortality (CSM) rates for non-Hispanic Asian American and Pacific Islander populations were estimated by cancer type, age, sex, and region using Joinpoint regression. Between 1999 and 2020, 305 386 Asian American and Pacific Islander individuals (median [IQR] age, 69.5 [58.5-79.2] years; 51.1% male) died of cancer in the US. Overall, the CSM rate decreased by 1.5% annually. Men experienced a greater CSM rate decrease (AAPC, -1.8%; 95% CI, -2.2% to -1.3%) compared with women (AAPC, -1.1%; 95% CI: -1.2% to -1.0%). For women, death rates decreased for most cancer types but increased for uterine (AAPC, 2.5%; 95% CI, 2.0%-3.0%) and brain and central nervous system (AAPC, 1.4%; 95% CI: 0.7%-2.1%) cancers. Colorectal cancer mortality rates increased among men aged 45 to 54 years (AAPC, 1.3%; 95% CI, 0.5%-2.1%). Liver and intrahepatic bile duct cancer mortality increased for both men and women in all US census regions, uterine cancer mortality increased in all regions for women, and pancreatic cancer mortality increased in the Midwest for both men and women. Although these findings show an overall decrease in CSM among Asian American and Pacific Islander populations, specific cancer types exhibited increased mortality rates, with further disparities by sex and age. Targeted, culturally adapted clinical and public health interventions are needed to narrow disparities in cancer mortality.

Spatial Patterns of Emergency Dental Care Utilization: Assessing the Influence of Social Vulnerability and Dental Provider Availability.

Our aim was to examine the association between emergency dental care use and dental providers' availability and ZIP code social vulnerability index. This cross-sectional observational study mapped variations in emergency dental care and analyzed their association with social vulnerability using generalized spatial two-stage least-squares to address spatial correlation. To perform spatial autoregressive modeling to examine how dental provider capacity and social vulnerability influence emergency care use across neighboring counties, accounting for ZIP Code Tabulation Area (ZCTA) spillover effects, we used secondary data from the Maryland Health Services Cost Review Commission, InfoUSA, and the US Census American Community Survey. We focused on emergency dental care usage in ZIP Code Tabulation Areas, using emergency department visits and inpatient stays per 1000 residents for dental conditions, as the dependent variable. Highly vulnerable ZCTAs saw 5.9× more non-traumatic dental condition (NTDC) ED visits, 5.3× more chronic dental ED visits, 3.3× more NTDC inpatient stays, and 1.3× more chronic dental inpatient stays than less vulnerable areas. For all four measures of emergency dental care use, increased dental provider availability was associated with reductions in use of emergency dental care (ED), while higher social vulnerability was associated with increased use. For example, an increase of one dental provider per 1000 residents was associated with a reduction of 28.2 non-traumatic dental ED visits, while a high social vulnerability index was associated with an increase of 88.6 non-traumatic dental ED visits. There was an association among dental provider availability, social vulnerability, and the use of emergency dental care.

Regional Distribution of Foreign-Born Medical Graduates in US Primary Care Specialty Residencies from 2010 to 2022.

The United States has more foreign-born (FB) individuals than any other country and a large international medical graduate (IMG) workforce. Yet little is known about the trends of FB IMGs matching into primary care specialties residency programs or the alignment between FB individuals and FB IMGs. This study examined the recent trends in FB IMGs entry into primary care specialty residency programs and their distribution in relation to the US FB population. In this retrospective study, we used archives of National Resident Matching Program (NRMP) data on the main residency match from 2010 to 2022. We extracted match data and program directors' policies for internal medicine, pediatrics, family medicine, and internal medicine/pediatrics. We also extracted data on the total population and FB individuals from the US Census Bureau for each US state from 2010 to 2022. From 2010 to 2022, 17.2% of primary care specialty positions were filled by FB IMGs, with 22.1% for internal medicine, 11.3% for pediatrics, 10.7% for family medicine, and 3.2% for internal medicine/pediatrics. The percentage of primary care specialty positions filled by FB IMGs was significantly higher than the percentage of FB people in the US overall and 7 of 9 US regions (p < 0.001) (excepting Pacific and Mountain). The percentage of family medicine, pediatrics, and internal medicine/pediatrics positions filled by FB IMGs was significantly lower than the proportion of FB people (p < 0.001). Internal medicine had a higher proportion of positions filled by FB IMGs compared to the proportion of FB individuals in the general population (p < 0.001). Distribution of FB IMGs varies in primary care specialties compared to FB people in the US. Given the importance of aligning medical education with patients' needs, programs could take into account population demographics while assessing and admitting the applicants.

Associations between neighbourhood-level median household income and outpatients' risk of antibiotic non-susceptible uropathogens in a major urban centre, USA.

Resistance to first-line antibiotics among urinary tract infections continues to rise, but how neighbourhood-level socioeconomic status impacts this risk remains unclear. We examined the effect of neighbourhood-level income on a patient's risk of having a uropathogen non-susceptible to trimethoprim/sulfamethoxazole (TMP/SMX) or nitrofurantoin. We used electronic health record data and antibiotic susceptibility test results for urinary Escherichia coli and Klebsiella pneumoniae collected at Emory Healthcare outpatient facilities in greater Atlanta between October 2022 and September 2023. We determined patients' block group median household income (MHI) using their residential addresses and 2017-21 US census data. We performed a logistic regression with a priori risk factors using a generalized estimating equation, with subgroup analysis by organism and for patients with diabetes mellitus. We included 9325 urine E. coli and K. pneumoniae isolates from 3867 outpatients. Compared to uropathogenic E. coli, K. pneumoniae were more likely to be non-susceptible to nitrofurantoin (P < 0.001) and less likely to be non-susceptible to TMP/SMX (P < 0.001). Compared to the lowest MHI quintile, patients in the highest MHI quintile neighbourhoods had 0.78 odds of harbouring a non-susceptible uropathogen (95% CI: 0.64, 0.95) after controlling for patient age, sex and race/ethnicity, along with neighbourhood-level characteristics. This association was stronger for K. pneumoniae infections and non-significant among people with diabetes. Higher neighbourhood-level MHI was associated with lower individual risk of harbouring a first-line antibiotic-non-susceptible uropathogen.

Identifying Partisan Gerrymandering and its Consequences: Evidence from the 1990 US Census Redistricting

Identifying Partisan Gerrymandering and its Consequences: Evidence from the 1990 US Census Redistricting

Peripartum Cardiomyopathy and Social Vulnerability: An Epidemiological Analysis of Mortality Outcomes.

Peripartum cardiomyopathy (PPCM) outcomes have been previously linked to demographic and social factors. The social vulnerability index (SVI) is a measure of social vulnerability in the United States. We explored PPCM disparities and the impact of SVI on PPCM mortality. Mortality from 1999 to 2020, SVI, and demographic data were obtained from CDC databases. County-specific SVI rankings were linked to PPCM age-adjusted mortality rates (AAMRs), allowing for a comparative analysis of AAMRs across both cumulative populations and subpopulations to identify disparities. All US counties were then stratified into low- and high-SVI groups, facilitating comparison of SVI rankings by estimation of excess-deaths per 1 000 000 person-years attributable to greater social vulnerability and rate ratios (RR) through univariable Poisson regression. We identified a total of 1026 deaths related to PPCM between 1999 and 2020. Overall AAMR increased from 0.180 in 1999 to 0.326 in 2020. Black populations (AAMR: 1.081) and Southern US counties (AAMR: 0.444) had the highest AAMRs compared with other racial and US census groups, respectively. Higher SVI accounted for 0.172 excess deaths per 1 000 000 person-years (RR=1.800). Among Black and White populations, higher SVI also accounted for 0.248 and 0.071 excess deaths per 1 000 000 person-years, respectively. Similar impacts of greater social vulnerability were observed when comparing the US census regions (Northeast RR=1.609, Midwest RR=1.819, South RR=1.934, West RR=1.776). PPCM mortality disparities exist across racial and geographic populations in the United States. A greater burden of social vulnerability is associated with higher PPCM mortality on a national level.

Sex, Racial/Ethnic, and Regional Disparities in Pulmonary Embolism Mortality Trends in the USA, 1999-2020.

While the National Institutes of Health emphasize integrating sex as a biological variable into research, specific considerations of sex-related differences in pulmonary embolism (PE) mortality trends remain scarce. This study examines sex-based PE mortality trends across regional and demographic groups in the USA from 1999 to 2020. A retrospective analysis of National Center for Health Statistics mortality data from 1999 to 2020 was conducted. Using ICD-10 code I26, PE decedents were identified. Piecewise linear regression assessed sex-based temporal trends in PE mortality by age, race/ethnicity, and census region. Annual percentage changes and average annual percentage changes were derived using Weighted Bayesian Information Criteria. The 95% confidence intervals were estimated using the empirical quantile method. From 1999 to 2020, a total of 179,273 individuals died in the USA due to PE, resulting in an age-adjusted mortality rate of 2.5 per 100,000 persons (95% CI, 2.5-2.5). While men and women exhibited comparable rates in recent time segments and across most subcategories, a higher mortality trend among males compared to females was observed among non-Hispanic White and Hispanic individuals and residents of the Western US census region. These results remained robust even after excluding data from 2020, accounting for the potential impact of the COVID-19 pandemic. Our study highlights sex-based disparities in PE mortality trends in the USA from 1999 to 2020. Despite overall stable mortality rates, higher trends among males were evident in specific demographic groups and regions. These findings emphasize the importance of targeted interventions to mitigate PE-related mortality discrepancies across diverse populations.

Sociodemographic disparities in antibiotic-resistant outpatient urine cultures in a Boston hospital, 2015–2020: a cross-sectional analysis

BackgroundAntibiotic resistance in uropathogens has rapidly escalated over time, complicating treatment and increasing morbidity and mortality. Few studies have explored how the social determinants of health may be associated with patients’ risks for acquiring antibiotic-resistant (AR) uropathogens.MethodsWe identified urine cultures collected from outpatients presenting to Tufts Medical Center Primary Care Practices between 2015 and 2020. Specimens were included if patients’ age, sex, and residential address were recorded in the electronic medical record (EMR) and if their urine culture yielded Enterococcus spp. or one or more gram-negative bacterial organism(s) or for which antibiotic susceptibility profiling and species identification was conducted. We abstracted patients’ sociodemographic characteristics from the EMR and used US Census Bureau data to identify characteristics about patients’ census tracts of residence. We evaluated associations between individual- and neighborhood-level characteristics and patients’ risk of having a urine culture resistant to (1) three or more antibiotic classes (i.e., multidrug resistant [MDR]), (2) first-line treatments, (3) fluoroquinolones, (4) aminoglycosides, or (5) ceftriaxone using logistic regression models and a Bonferroni correction to account for multiple hypothesis testing.ResultsWe included urine cultures from 1,306 unique outpatients, most of whom were female (89%). Patients largely self-identified as Non-Hispanic White (36%), Asian (15%), or Non-Hispanic Black (11%). Over 60% lived in an environmental justice-designated census tract. Most included isolates were Escherichia coli (76%) or Klebsiella pneumoniae (7%). Using public insurance increased patients’ odds of having a uropathogen resistant to first-line antibiotics, but living in a limited-income neighborhood reduced patients’ odds of having a MDR uropathogen by 47%. We noted a strong but non-significant positive trend between speaking a language other than English and having an aminoglycoside-resistant uropathogen (p-value = 0.02). Most notably, after controlling for other factors, we observed no statistically significant associations between race or ethnicity and AR uropathogens.ConclusionThe social determinants of health may play important and intersecting roles in determining a patient’s risk of having a resistant uropathogens that is more challenging or expensive to treat. It is crucial to acknowledge how race is likely to be a proxy for other factors affecting health, and to consider that some groups may be disproportionately impacted by antibiotic resistance.

US Primary Care WorkforceGrowth: A Decade of Limited Progress, and Projected Needs Through 2040.

Despite efforts to mitigate a projected primary care physician (PCP) shortage required to meet an aging, growing, and increasingly insured population, shortages remain, compounded by the COVID-19 pandemic, growing inequity, and persistent underinvestment. We examined primary care workforce trends over the past decade and revisited projected primary care clinician workforce needs through the year 2040. Using data from the AMA Masterfile and Medical Expenditure Panel Survey (MEPS), we analyzed trends in the number of primary care physicians (PCPs) and in outpatient PCP visits by age and gender over the past decade. We then used the Medicare PECOS and Physician & Other Practitioners datasets to identify nurse practitioners (NPs) and physician assistants (PAs) in primary care. Using these baseline clinician enumerations and projected population growth estimates from the US Census Bureau for the years 2020-2040, we calculated estimated primary care workforce needs by 2040. The effects of aging and population growth and baseline shortages in the primary care workforce call for significant increases in the primary care workforce to accommodate rising demands. Office visits to primary care clinicians are projected to increase from 773,606 in 2020 to 893,098 in 2040. We project a need for an additional 57,559primary care clinicians by 2040. Workforce shortages in primary care continue to expand due to populationaging, growth, and heightened rates of clinicianburnout& egress.

Black Women in Medical Education Publishing: Bibliometric and Testimonio Accounts Using Intersectionality Methodology.

Black women in academic medicine experience racial and gender discrimination, all while being tasked with improving a flawed system. Representation of Black women in medicine remains low, yet they bear the burden of fostering diversity and mentoring trainees, exacerbating their minority tax and emotional labor, and negatively impacting career progression. To complement qualitative accounts of Black women authors in the medical education literature with a quantitative account of their representation. We used statistical modeling to estimate the representation of Black women authors in medical education publishing as compared to other groups. An intersectional methodology employing bibliometric analysis and testimonio reflection. US-based authors of journal articles published in medical education journals between 2000 and 2020. Author race was determined using a probability-based algorithm incorporating US Census data, and author gender was ascribed using Social Security Administration records. We conducted two negative binomial generalized linear models by first and last author publications. Metadata for each article was retrieved from Web of Science and PubMed to include author names, country of institutional affiliation, and Medical Subject Headings (MeSH). Results were contextualized via the "testimonio" account of a Black woman author. Of 21,945 unique authors, Black women (and other racially minoritized groups) published far fewer first and last author papers than white women and men. In addition, major MeSH terms used by Black women authors reveal little overlap with highly ranked medical education topics. The testimonio further narrated struggles with belonging and racial identity. This study revealed that Black women are underrepresented in medical education publishing. We believe that dismantling oppressive structures in the publishing ecosystem and the field is imperative for achieving equity. Additionally, further experiential accounts are needed to contextualize this quantitative account and understand underrepresentation in medical education publishing.

Prevalence of Hearing Loss and Hearing Aid Use Among Persons Living With Dementia in the US

Dementia and hearing loss are prevalent and represent public health priorities, but little is known about the prevalence of hearing loss among persons living with dementia at a population level. To estimate the prevalence of hearing loss and hearing aid use among a nationally representative sample of persons living with dementia. In this cross-sectional study, we analyzed data from Medicare beneficiaries who participated in round 11 of the National Health and Aging Trends Study (NHATS). The analytic sample included participants who had complete audiometric data and a dementia classification, and survey weights were applied to yield nationally representative estimates. Data were collected from June to November 2021, and analyzed from October 12, 2023, to February 27, 2024. Audiometric measures of hearing loss and self-reported hearing aid use. National prevalence estimates of possible and probable dementia and hearing loss were estimated by applying NHATS survey weights of sex and age to the population aged 71 years or older based on the US Census Bureau's 2020 American Community Survey data. The analytic sample comprised 2613 NHATS participants (74.6% aged 71-79 years and 25.4% aged ≥80 years; 52.9% female). Overall prevalence of hearing loss among participants with dementia was estimated at 79.4% (95% CI, 72.1%-85.3%). The prevalence of hearing loss increased with age, from 61.1% (95% CI, 37.7%-80.2%) among participants aged 71 to 74 years to 94.2% (95% CI, 88.8%-97.0%) among those aged 85 years or older. Among participants with hearing loss, 21.7% (95% CI, 16.2%-28.3%) reported hearing aid use. In this cross-sectional study, the findings suggest that hearing loss is highly prevalent among individuals with dementia, with a low prevalence of hearing aid use. These findings reveal a potential opportunity for intervention.