An epigenome-wide analysis of DNA methylation, racialized and economic inequities, and air pollution.

Importance: DNA methylation (DNAm) provides a plausible mechanism by which adverse exposures become embodied and contribute to health inequities, due to its role in genome regulation and responsiveness to social and biophysical exposures tied to societal context. However, scant epigenome-wide association studies (EWAS) have included structural and lifecourse measures of exposure, especially in relation to structural discrimination. Objective: Our study tests the hypothesis that DNAm is a mechanism by which racial discrimination, economic adversity, and air pollution become biologically embodied. Design: A series of cross-sectional EWAS, conducted in My Body My Story (MBMS, biological specimens collected 2008-2010, DNAm assayed in 2021); and the Multi Ethnic Study of Atherosclerosis (MESA; biological specimens collected 2010-2012, DNAm assayed in 2012-2013); using new georeferenced social exposure data for both studies (generated in 2022). Setting: MBMS was recruited from four community health centers in Boston; MESA was recruited from four field sites in: Baltimore, MD; Forsyth County, NC; New York City, NY; and St. Paul, MN. Participants: Two population-based samples of US-born Black non-Hispanic (Black NH), white non-Hispanic (white NH), and Hispanic individuals (MBMS; n=224 Black NH and 69 white NH) and (MESA; n=229 Black NH, n=555 white NH and n=191 Hispanic). Exposures: Eight social exposures encompassing racial discrimination, economic adversity, and air pollution. Main outcome: Genome-wide changes in DNAm, as measured using the Illumina EPIC BeadChip (MBMS; using frozen blood spots) and Illumina 450k BeadChip (MESA; using purified monocytes). Our hypothesis was formulated after data collection. Results: We observed the strongest associations with traffic-related air pollution (measured via black carbon and nitrogen oxides exposure), with evidence from both studies suggesting that air pollution exposure may induce epigenetic changes related to inflammatory processes. We also found suggestive associations of DNAm variation with measures of structural racial discrimination (e.g., for Black NH participants, born in a Jim Crow state; adult exposure to racialized economic residential segregation) situated in genes with plausible links to effects on health. Conclusions and Relevance: Overall, this work suggests that DNAm is a biological mechanism through which structural racism and air pollution become embodied and may lead to health inequities.

Epigenetic clocks and research implications of the lack of data on whom they have been developed: a review of reported and missing sociodemographic characteristics.

Epigenetic clocks are increasingly being used as a tool to assess the impact of a wide variety of phenotypes and exposures on healthy ageing, with a recent focus on social determinants of health. However, little attention has been paid to the sociodemographic characteristics of participants on whom these clocks have been based. Participant characteristics are important because sociodemographic and socioeconomic factors are known to be associated with both DNA methylation variation and healthy ageing. It is also well known that machine learning algorithms have the potential to exacerbate health inequities through the use of unrepresentative samples - prediction models may underperform in social groups that were poorly represented in the training data used to construct the model. To address this gap in the literature, we conducted a review of the sociodemographic characteristics of the participants whose data were used to construct 13 commonly used epigenetic clocks. We found that although some of the epigenetic clocks were created utilizing data provided by individuals from different ages, sexes/genders, and racialized groups, sociodemographic characteristics are generally poorly reported. Reported information is limited by inadequate conceptualization of the social dimensions and exposure implications of gender and racialized inequality, and socioeconomic data are infrequently reported. It is important for future work to ensure clear reporting of tangible data on the sociodemographic and socioeconomic characteristics of all the participants in the study to ensure that other researchers can make informed judgements about the appropriateness of the model for their study population.

Tabby2: a user-friendly web tool for forecasting state-level TB outcomes in the United States.

BACKGROUND: In the United States, the tuberculosis (TB) disease burden and associated factors vary substantially across states. While public health agencies must choose how to deploy resources to combat TB and latent tuberculosis infection (LTBI), state-level modeling analyses to inform policy decisions have not been widely available. METHODS: We developed a mathematical model of TB epidemiology linked to a web-based user interface - Tabby2. The model is calibrated to epidemiological and demographic data for the United States, each U.S. state, and the District of Columbia. Users can simulate pre-defined scenarios describing approaches to TB prevention and treatment or create their own intervention scenarios. Location-specific results for epidemiological outcomes, service utilization, costs, and cost-effectiveness are reported as downloadable tables and customizable visualizations. To demonstrate the tool's functionality, we projected trends in TB outcomes without additional intervention for all 50 states and the District of Columbia. We further undertook a case study of expanded treatment of LTBI among non-U.S.-born individuals in Massachusetts, covering 10% of the target population annually over 2025-2029. RESULTS: Between 2022 and 2050, TB incidence rates were projected to decline in all states and the District of Columbia. Incidence projections for the year 2050 ranged from 0.03 to 3.8 cases (median 0.95) per 100,000 persons. By 2050, we project that majority (> 50%) of TB will be diagnosed among non-U.S.-born persons in 46 states and the District of Columbia; per state percentages range from 17.4% to 96.7% (median 83.0%). In Massachusetts, expanded testing and treatment for LTBI in this population was projected to reduce cumulative TB cases between 2025 and 2050 by 6.3% and TB-related deaths by 8.4%, relative to base case projections. This intervention had an incremental cost-effectiveness ratio of $180,951 (2020 USD) per quality-adjusted life year gained from the societal perspective. CONCLUSIONS: Tabby2 allows users to estimate the costs, impact, and cost-effectiveness of different TB prevention approaches for multiple geographic areas in the United States. Expanded testing and treatment for LTBI could accelerate declines in TB incidence in the United States, as demonstrated in the Massachusetts case study.

Contextualizing Response Rates During the COVID-19 Pandemic: Experiences From a Boston-Based Community Health Centers Study.

OBJECTIVES: The focus of this study was to calculate and contextualize response rates for a community-based study conducted during the COVID-19 pandemic, a topic on which scant data exist, and to share lessons learned from recruiting and enrolling for implementation of future studies. DESIGN: The Life+Health Study, a cross-sectional population-based study designed to advance novel methods to measure and analyze multiple forms of discrimination for population health research. SETTING: The study recruited participants from 3 community health centers in Boston, Massachusetts, between May 2020 and July 2022. PARTICIPANTS: A total of 699 adult participants between the ages of 25 and 64 years who were born in the United States and had visited one of the health centers within the last 2 years. MAIN OUTCOME MEASURES: The response rate was calculated as follows: (number of completions + number of dropouts)/(dropouts + enrollments). To contextualize this response rate, we synthesized evidence pertaining to local COVID-19 case counts, sociopolitical events, pandemic-related restrictions and project protocol adjustments, and examples of interactions with patients. RESULTS: Our study had a lower-than-expected response rate (48.4%), with the lowest rates from the community health centers serving primarily low-income patients of color. Completion rates were lower during periods of higher COVID-19 case counts. We describe contextual factors that led to challenges and lessons learned from recruiting during the pandemic, including the impact of US sociopolitical events. CONCLUSIONS: The Life+Health Study concluded recruitment during the pandemic with a lower-than-expected response rate, as also reported in 4 other US publications focused on the impact of COVID-19 on response rates in community-based studies. Our results provide an example of the impact of the pandemic and related US sociopolitical events on response rates that can serve as a framework for contextualizing other research conducted during the pandemic and highlight the importance of best practices in research recruitment with underserved populations.

Decreasing Survey Response Rates in the Time of COVID-19: Implications for Analyses of Population Health and Health Inequities.

Objectives. To examine whether, and if so how, US national and state survey response rates changed after the onset of the COVID-19 pandemic. Methods. We compared the change in response rates between 2020 and 2019 of 6 (3 social and economic, 3 health focused) major US national surveys (2 with state response rates). Results. All the ongoing surveys except 1 reported relative decreases (∼29%) in response rates. For example, the household response rate to the US Census American Community Survey decreased from 86.0% in 2019 to 71.2% in 2020, and the response rate of the US National Health Interview Survey decreased from 60.0% to 42.7% from the first to the second quarter of 2020. For all surveys, the greatest decreases in response rates occurred among persons with lower income and lower education. Conclusions. Socially patterned decreases in response rates pose serious challenges and must be addressed explicitly in all studies relying on data obtained since the onset of the pandemic. Public Health Implications. Artifactual reduction of estimates of the magnitude of health inequities attributable to differential response rates could adversely affect efforts to reduce these inequities. (Am J Public Health. 2023;113(6):667-670. https://doi.org/10.2105/AJPH.2023.307267).

Use of Correct and Incorrect Methods of Accounting for Age in Studies of Epigenetic Accelerated Aging: Implications and Recommendations for Best Practices.

Motivated by our conduct of a literature review on social exposures and accelerated aging as measured by a growing number of epigenetic "clocks" (which estimate age via DNA methylation (DNAm) patterns), we report on 3 different approaches in the epidemiologic literature-1 incorrect and 2 correct-on the treatment of age in these and other studies using other common exposures (i.e., body mass index and alcohol consumption). Among the 50 empirical articles reviewed, the majority (n = 29; 58%) used the incorrect method of analyzing accelerated aging detrended for age as the outcome and did not control for age as a covariate. By contrast, only 42% used correct methods, which are either to analyze accelerated aging detrended for age as the outcome and control for age as a covariate (n = 16; 32%) or to analyze raw DNAm age as the outcome and control for age as a covariate (n = 5; 10%). In accord with prior demonstrations of bias introduced by use of the incorrect approach, we provide simulation analyses and additional empirical analyses to illustrate how the incorrect method can lead to bias towards the null, and we discuss implications for extant research and recommendations for best practices.

Addressing spatial misalignment in population health research: a case study of US congressional district political metrics and county health data.

Areal spatial misalignment, which occurs when data on multiple variables are collected using mismatched boundary definitions, is a ubiquitous obstacle to data analysis in public health and social science research. As one example, the emerging sub-field studying the links between political context and health in the United States faces significant spatial misalignment-related challenges, as the congressional districts (CDs) over which political metrics are measured and administrative units, e.g., counties, for which health data are typically released, have a complex misalignment structure. Standard population-weighted data realignment procedures can induce measurement error and invalidate inference, which has prompted the development of fully model-based approaches for analyzing spatially misaligned data. One such approach, atom-based regression models (ABRM), holds particular promise but has scarcely been used in practice due to the lack of appropriate software or examples of implementation. ABRM use "atoms", the areas created by intersecting all sets of units on which variables of interest are measured, as the units of analysis and build models for the atom-level data, treating the atom-level variables (generally unmeasured) as latent variables. In this paper, we demonstrate the feasibility and strengths of the ABRM in a case study of the association between political representatives' voting behavior (CD-level) and COVID-19 mortality rates (county-level) in a post-vaccine period. The adjusted ABRM results suggest that more conservative voting record is associated with an increase in COVID-19 mortality rates, with estimated associations smaller in magnitude but consistent in direction with those of standard realignment methods. The results also indicate that ABRM may enable more robust confounding adjustment and more realistic uncertainty estimates, properly representing the uncertainties arising from all analytic procedures. We also implement the ABRM in modern optimized Bayesian computing programs and make our code publicly available, which may enable these methods to be more widely adopted.

Using Implicit Measures of Discrimination: White, Black, and Hispanic Participants Respond Differently to Group-Specific Racial/Ethnic Categories vs. the General Category "People of Color" in the USA.

Recent studies showed that implicit measures are valuable instruments for assessing exposure to discrimination and predicting negative physical conditions. Between March 10, 2020, and April 1, 2020, we conducted three experiments (577 participants) in the USA to evaluate the use of group-specific vs. general race/ethnicity categories in implicit measures of discrimination. We measured implicit discrimination and attitudes towards the general race/ethnicity category "people of color" (POC) and two specific race/ethnicity categories (i.e., "Black people" and "Hispanic people"). Implicit discrimination and attitudes were assessed using the Brief Implicit Association Test (B-IAT). Among participants (mean age = 37, standard deviation = 10.5), 50% identified as White non-Hispanic (NH), 33.3% as Black NH, and 16.7% as Hispanic; 71.7% were female and 72.2% had a bachelor's degree or higher. We found an implicit discrimination towards target groups and an in-group preference among all participant groups only when specific race/ethnicity categories were used in the B-IAT. When the general category POC was used, we observed a discrimination towards POC only for Black NH participants, while White NH participants showed no discrimination. Similarly, Black NH participants showed no in-group preference for POC, but did show an in-group preference for Black people. These results suggest that using the category POC in implicit measures may be inappropriate when evaluating discrimination and attitudes towards Black and Hispanic individuals as it may not capture specific experiences of discrimination and identity in these groups.

Epigenetic aging & embodying injustice: US My Body My Story and Multi-Ethnic Atherosclerosis Study.

Importance: Epigenetic accelerated aging is associated with exposure to social and economic adversity and may increase risk of premature morbidity and mortality. However, no studies have included measures of structural racism and few have compared estimates within or across the 1st and 2nd generation of epigenetic clocks (the latter additionally trained on phenotypic data). Objective: To determine if accelerated epigenetic aging is associated with exposures to diverse measures of racialized, economic, and environmental injustice measured at different levels and time periods. Design: Cross-sectional My Body My Story Study (MBMS; US, 2008-2010) and Exam 5 Multi-Ethnic Atherosclerosis Study (MESA; US, 2010-2012). MBMS DNA extraction: 2021; linkage of structural measures to MBMS and MESA: 2022. Setting: MBMS recruited a random sample of US-born Black non-Hispanic (BNH) and white non-Hispanic (WNH) participants from 4 community health centers in Boston, MA. The MESA Exam 5 epigenetic component included 975 randomly selected US-born BNH, WNH, and Hispanic participants from four field sites: Baltimore, MD; Forsyth County, NC; New York City, NY; St. Paul, MN. Participants: US-born persons (MBMS: 224 BNH, 69 WNH; MESA: 229 BNH, 555 WNH, 191 Hispanic). Main outcome and measures: 10 epigenetic clocks (six 1st generation; four 2nd generation), computed using DNA methylation data (DNAm) from blood spots (MBMS; N = 293) and purified monocytes (MESA; N = 975). Results: Among Black non-Hispanic MBMS participants, epigenetic age acceleration was associated with being born in a Jim Crow state by 0.14 standard deviations (95% confidence interval [CI] 0.00, 0.27) and with birth state conservatism (0.06, 95% CI 0.00, 0.05), pooling across all clocks, as was low parental education for both Black non-Hispanic and white non-Hispanic MBMS participants (respectively: 0.24, 95% CI 0.08, 0.39, and 0.27, 95% CI 0.03, 0.51. Adult impoverishment was positively associated with the pooled 2nd generation clocks among the MESA participants (Black non-Hispanic: 0.06, 95% CI 0.01, 0.12; white non-Hispanic: 0.05, 95% CI 0.01, 0.08; Hispanic: 0.07, 95% CI 0.01, 0.14). Conclusions and Relevance: Epigenetic accelerated aging may be one of the biological mechanisms linking exposure to racialized and economic injustice to well-documented inequities in premature morbidity and mortality.

Relationship of political ideology of US federal and state elected officials and key COVID pandemic outcomes following vaccine rollout to adults: April 2021-March 2022.

Background: Scant research, including in the United States, has quantified relationships between the political ideologies of elected representatives and COVID-19 outcomes among their constituents. Methods: We analyzed observational cross-sectional data on COVID-19 mortality rates (age-standardized) and stress on hospital intensive care unit (ICU) capacity for all 435 US Congressional Districts (CDs) in a period of adult vaccine availability (April 2021-March 2022). Political metrics comprised: (1) ideological scores based on each US Representative's and Senator's concurrent overall voting record and their specific COVID-19 votes, and (2) state trifectas (Governor, State House, and State Senate under the same political party control). Analyses controlled for CD social metrics, population density, vaccination rates, the prevalence of diabetes and obesity, and voter political lean. Findings: During the study period, the higher the exposure to conservatism across several political metrics, the higher the COVID-19 age-standardized mortality rates, even after taking into account the CD's social characteristics; similar patterns occurred for stress on hospital ICU capacity for Republican trifectas and US Senator political ideology scores. For example, in models mutually adjusting for CD political and social metrics and vaccination rates, Republican trifecta and conservative voter political lean independently remained significantly associated with an 11%-26% higher COVID-19 mortality rate. Interpretation: Associations between the political ideologies of US federal elected officials and state concentrations of political party power with population health warrant greater consideration in public health analyses and monitoring dashboards. Funding: This research received no specific grant from any funding agency in the public, commercial or not-for-profit sectors.

The impact of low input DNA on the reliability of DNA methylation as measured by the Illumina Infinium MethylationEPIC BeadChip.

DNA methylation (DNAm) is commonly assayed using the Illumina Infinium MethylationEPIC BeadChip, but there is currently little published evidence to define the lower limits of the amount of DNA that can be used whilst preserving data quality. Such evidence is valuable for analyses utilizing precious or limited DNA sources. We used a single pooled sample of DNA in quadruplicate at three dilutions to define replicability and noise, and an independent population dataset of 328 individuals (from a community-based study including US-born non-Hispanic Black and white persons) to assess the impact of total DNA input on the quality of data generated using the Illumina Infinium MethylationEPIC BeadChip. We found that data are less reliable and more noisy as DNA input decreases to 40ng, with clear reductions in data quality; and that low DNA input is associated with a reduction in power to detect EWAS associations, requiring larger sample sizes. We conclude that DNA input as low as 40ng can be used with the Illumina Infinium MethylationEPIC BeadChip, provided quality checks and sensitivity analyses are undertaken.

Breast Cancer Incidence, Hormone Receptor Status, Historical Redlining, and Current Neighborhood Characteristics in Massachusetts, 2005-2015.

BACKGROUND: Scant research has analyzed contemporary US cancer incidence rates in relation to historical redlining (ie, 1930s US federally imposed residential segregation), implemented via the color-coded federal Home Owners' Loan Corporation (HOLC) maps. METHODS: We analyzed Massachusetts Cancer Registry data for all patients with primary invasive breast cancer (BC) diagnosed in 2005-2015 among women in the 28 Massachusetts municipalities with digitized 1930s HOLC maps. Multilevel Poisson regression estimated BC incidence rate ratios (IRR), overall and by tumor estrogen receptor (ER-positive, ER-negative) and progesterone receptor (PR-positive, PR-negative) status, in relation to HOLC grade and contemporary census tract (CT) social characteristics. RESULTS: Net of age and racialized group, the extremes of BC incidence were detected by combinations of HOLC grade and contemporary CT racialized economic segregation. Compared with CTs with the best HOLC grade (A + B) and most privileged contemporary characteristics (T1), for all, ER-positive and PR-positive BC, incidence was highest in T1 and mixed HOLC grade CTs (eg, IRRER+; Mixed-T1 = 1.10, 95% confidence interval [CI] = 1.01 to 1.21) and lowest in CTs with most concentrated racialized economic deprivation (T3) and no HOLC grade (eg, IRRER+; No Grade-T3 = 0.85, 95% CI = 0.75 to 0.95). For ER-negative and PR-negative BC, incidence was highest in CTs with the most contemporary deprivation, but the best HOLC grade (eg, IRRER-; A+B-T3 = 1.27, 95% CI = 0.93 to 1.75) and lowest in T1 and worst HOLC-graded CTs (eg, IRRER-; D-T1 = 0.84, 95% CI = 0.56 to 1.25). CONCLUSION: Breast cancer risk may be shaped by combined histories of redlining and present-day CT characteristics.

Estimated costs and quality-adjusted life-years lost due to N. gonorrhoeae infections acquired in 2015 in the United States: A modelling study of overall burden and disparities by age, race/ethnicity, and other factors.

Background: Disparities in the health and economic burden of gonorrhoea have not been systematically quantified. We estimated population-level health losses and costs associated with gonococcal infection and sequelae in the United States. Methods: We used probability-tree models to capture gonorrhoea sequelae and to estimate attributable disease burden in terms of the discounted lifetime costs and quality-adjusted life-years (QALYs) lost due to incident infections acquired during 2015 from the healthcare system perspective. Numbers of infections in 2015 were obtained from a published gonorrhoea transmission model. We evaluated population-level disease burden, disaggregated by sex, age, race/ethnicity, and for men who have sex with men (MSM). We conducted a multivariate sensitivity analysis for key parameters. Findings: Discounted lifetime QALYs lost per incident gonococcal infection were estimated as 0.093 (95% uncertainty interval [UI] 0.022-0.22) for women, 0.0020 (0.0015-0.0024) for heterosexual men, and 0.0015 (0.00070-0.0021) for MSM. Discounted lifetime costs per incident infection were USD 261 (109-480), 169 (88-263), and 133 (50-239), respectively. At the population level, total discounted lifetime QALYs lost due to infections acquired during 2015 were 53,293 (12,326-125,366) for women, 621 (430-872) for heterosexual men, and 1,078 (427-1,870) for MSM. Total discounted lifetime costs were USD 150 million (64-277 million), 54 million (25-92 million), and 97 million (34-197 million), respectively. The highest total burden of both QALYs and costs at the population-level was observed in Non-Hispanic Black women, and highest burden per 1,000 person-years was identified in MSM among men and American Indian/Alaska Native among women. Interpretation: Gonorrhoea causes substantial health losses and costs in the United States. These results can inform planning and prioritization of prevention services. Funding: Centers for Disease Control and Prevention, Charles A. King Trust.

The evolving roles of US political partisanship and social vulnerability in the COVID-19 pandemic from February 2020-February 2021.

The COVID-19 pandemic has had intense, heterogeneous impacts on different communities and geographies in the United States. We explore county-level associations between COVID-19 attributed deaths and social, demographic, vulnerability, and political variables to develop a better understanding of the evolving roles these variables have played in relation to mortality. We focus on the role of political variables, as captured by support for either the Republican or Democratic presidential candidates in the 2020 elections and the stringency of state-wide governor mandates, during three non-overlapping time periods between February 2020 and February 2021. We find that during the first three months of the pandemic, Democratic-leaning and internationally-connected urban counties were affected. During subsequent months (between May and September 2020), Republican counties with high percentages of Hispanic and Black populations were most hardly hit. In the third time period -between October 2020 and February 2021- we find that Republican-leaning counties with loose mask mandates experienced up to 3 times higher death rates than Democratic-leaning counties, even after controlling for multiple social vulnerability factors. Some of these deaths could perhaps have been avoided given that the effectiveness of non-pharmaceutical interventions in preventing uncontrolled disease transmission, such as social distancing and wearing masks indoors, had been well-established at this point in time.

Modeling the Cost-Effectiveness of Express Multisite Gonorrhea Screening Among Men Who Have Sex With Men in the United States.

BACKGROUND: Men who have sex with men (MSM) experience high rates of gonococcal infection at extragenital (rectal and pharyngeal) anatomic sites, which often are missed without asymptomatic screening and may be important for onward transmission. Implementing an express pathway for asymptomatic MSM seeking routine screening at their clinic may be a cost-effective way to improve extragenital screening by allowing patients to be screened at more anatomic sites through a streamlined, less costly process. METHODS: We modified an agent-based model of anatomic site-specific gonococcal infection in US MSM to assess the cost-effectiveness of an express screening pathway in which all asymptomatic MSM presenting at their clinic were screened at the urogenital, rectal, and pharyngeal sites but forewent a provider consultation and physical examination and self-collected their own samples. We calculated the cumulative health effects expressed as gonococcal infections and cases averted over 5 years, labor and material costs, and incremental cost-effectiveness ratios for express versus traditional scenarios. RESULTS: The express scenario averted more infections and cases in each intervention year. The increased diagnostic costs of triple-site screening were largely offset by the lowered visit costs of the express pathway and, from the end of year 3 onward, this pathway generated small cost savings. However, in a sensitivity analysis of assumed overhead costs, cost savings under the express scenario disappeared in the majority of simulations once overhead costs exceeded 7% of total annual costs. CONCLUSIONS: Express screening may be a cost-effective option for improving multisite anatomic screening among US MSM.

The target/perpetrator brief-implicit association test (B-IAT): an implicit instrument for efficiently measuring discrimination based on race/ethnicity, sex, gender identity, sexual orientation, weight, and age.

BACKGROUND: To date, research assessing discrimination has employed primarily explicit measures (i.e., self-reports), which can be subject to intentional and social desirability processes. Only a few studies, focusing on sex and race/ethnicity discrimination, have relied on implicit measures (i.e., Implicit Association Test, IAT), which permit assessing mental representations that are outside of conscious control. This study aims to advance measurement of discrimination by extending the application of implicit measures to multiple types of discrimination and optimizing the time required for the administration of these instruments. METHODS: Between September 27th 2019 and February 9th 2020, we conducted six experiments (984 participants) to assess implicit and explicit discrimination based on race/ethnicity, sex, gender identity, sexual orientation, weight, and age. Implicit discrimination was measured by using the Brief-Implicit Association Test (B-IAT), a new validated version of the IAT developed to shorten the time needed (from ≈15 to ≈2 min) to assess implicit mental representations, while explicit discrimination was assessed using self-reported items. RESULTS: Among participants (mean age = 37.8), 68.6% were White Non-Hispanic; 69% were females; 76.1% were heterosexual; 90.7% were gender conforming; 52.8% were medium weight; and 41.5% had an advanced level of education. Overall, we found implicit and explicit recognition of discrimination towards all the target groups (stronger for members of the target than dominant groups). Some exceptions emerged in experiments investigating race/ethnicity and weight discrimination. In the racism experiment, only people of Color showed an implicit recognition of discrimination towards the target group, while White people were neutral. In the fatphobia experiment, participants who were not heavy showed a slight implicit recognition of discrimination towards the dominant group, while heavy participants were neutral. CONCLUSIONS: This study provides evidence that the B-IAT is a valuable tool for quickly assessing multiple types of implicit discrimination. It shows also that implicit and explicit measures can display diverging results, thus indicating that research would benefit from the use of both these instruments. These results have important implications for the assessment of discrimination in health research as well as in social and psychological science.

Time Since Infection and Risks of Future Disease for Individuals with Mycobacterium tuberculosis Infection in the United States.

BACKGROUND: Risk of tuberculosis (TB) declines over time since Mycobacterium tuberculosis infection, but progression to clinical disease is still possible decades later. In the United States, most TB cases result from the progression of latent TB infection acquired over 2 years ago. METHODS: We synthesized evidence on TB natural history and incidence trends using a transmission-dynamic model. For the 2020 US population, we estimated average time since infection and annual, cumulative, and remaining lifetime risks of progression to TB, by nativity and age. RESULTS: For a newly infected adult with no other risk factors for progression to TB, estimated rates of progression declined from 38 (95% uncertainty interval: 33, 46) to 0.38 (0.32, 0.45) per 1000 person-years between the first and 25th year since infection. Cumulative risk over 25 years from new infection was 7.9% (7.0, 8.9). In 2020, an estimated average age of individuals with prevalent infection was 62 (61, 63) for the US-born population, 55 (54, 55) for non-US-born, and 57 (56, 58) overall. Average risks of developing TB over the remaining lifetime were 1.2% (1.0, 1.4) for US-born, 2.2% (1.8, 2.6) for non-US-born, and 1.9% (1.6, 2.2) for the general population. Risk estimates were higher for younger age groups. CONCLUSIONS: Our analysis suggests that, although newly infected individuals face appreciable lifetime TB risks, most US individuals with latent TB infection were infected long ago, and face low future risks of developing TB. Better approaches are needed for identifying recently infected individuals and those with elevated progression risks.

COVID-19: US federal accountability for entry, spread, and inequities-lessons for the future.

The United States (US) has been among those nations most severely affected by the first-and subsequent-phases of the pandemic of COVID-19, the disease caused by SARS-CoV-2. With only 4% of the worldwide population, the US has seen about 22% of COVID-19 deaths. Despite formidable advantages in resources and expertise, presently the per capita mortality rate is over 585/million, respectively 2.4 and 5 times higher compared to Canada and Germany. As we enter Fall 2020, the US is enduring ongoing outbreaks across large regions of the country. Moreover, within the US, an early and persistent feature of the pandemic has been the disproportionate impact on populations already made vulnerable by racism and dangerous jobs, inadequate wages, and unaffordable housing, and this is true for both the headline public health threat and the additional disastrous economic impacts. In this article we assess the impact of missteps by the Federal Government in three specific areas: the introduction of the virus to the US and the establishment of community transmission; the lack of national COVID-19 workplace standards and enforcement, and lack of personal protective equipment (PPE) for workplaces as represented by complaints to the Occupational Safety and Health Administration (OSHA) which we find are correlated with deaths 16 days later (ρ = 0.83); and the total excess deaths in 2020 to date already total more than 230,000, while COVID-19 mortality rates exhibit severe-and rising-inequities in race/ethnicity, including among working age adults.