Implications of Race Adjustment in Lung-Function Equations.

BACKGROUND: Adjustment for race is discouraged in lung-function testing, but the implications of adopting race-neutral equations have not been comprehensively quantified. METHODS: We obtained longitudinal data from 369,077 participants in the National Health and Nutrition Examination Survey, U.K. Biobank, the Multi-Ethnic Study of Atherosclerosis, and the Organ Procurement and Transplantation Network. Using these data, we compared the race-based 2012 Global Lung Function Initiative (GLI-2012) equations with race-neutral equations introduced in 2022 (GLI-Global). Evaluated outcomes included national projections of clinical, occupational, and financial reclassifications; individual lung-allocation scores for transplantation priority; and concordance statistics (C statistics) for clinical prediction tasks. RESULTS: Among the 249 million persons in the United States between 6 and 79 years of age who are able to produce high-quality spirometric results, the use of GLI-Global equations may reclassify ventilatory impairment for 12.5 million persons, medical impairment ratings for 8.16 million, occupational eligibility for 2.28 million, grading of chronic obstructive pulmonary disease for 2.05 million, and military disability compensation for 413,000. These potential changes differed according to race; for example, classifications of nonobstructive ventilatory impairment may change dramatically, increasing 141% (95% confidence interval [CI], 113 to 169) among Black persons and decreasing 69% (95% CI, 63 to 74) among White persons. Annual disability payments may increase by more than $1 billion among Black veterans and decrease by $0.5 billion among White veterans. GLI-2012 and GLI-Global equations had similar discriminative accuracy with regard to respiratory symptoms, health care utilization, new-onset disease, death from any cause, death related to respiratory disease, and death among persons on a transplant waiting list, with differences in C statistics ranging from -0.008 to 0.011. CONCLUSIONS: The use of race-based and race-neutral equations generated similarly accurate predictions of respiratory outcomes but assigned different disease classifications, occupational eligibility, and disability compensation for millions of persons, with effects diverging according to race. (Funded by the National Heart Lung and Blood Institute and the National Institute of Environmental Health Sciences.).

Differential effect of social mobility on tooth loss by race in adulthood: 1982 Pelotas Birth Cohort Study.

OBJECTIVES: To examine the association between social mobility and tooth loss in adults from the 1982 Pelotas Birth Cohort Study and whether race modifies this association. METHODS: The Oral Health Study used data from 541 individuals who were followed up to 31 years of age. Social mobility, composed of the participants' socioeconomic position (SEP) at birth and at age 30, was categorized as never poor, upwardly mobile, downwardly mobile and always poor. The outcome was the prevalence of at least one tooth lost due to dental caries when the participants were examined at 31 years of age. The effect modifier was race (Black/Brown versus white people). Log-binomial regression models were used to estimate crude and sex-adjusted prevalence ratios (PR) and to determine whether the association varied with race. Statistical interactions were tested using an additive scale. RESULTS: The prevalence of any tooth loss was 50.8% (n = 274). In social mobility groups, the prevalence of at least one tooth lost in the never-poor group was about 31% points higher for Black/Brown (68.2%) than for white people (37.4%). Antagonistic findings were found for the interaction between race and social mobility (Sinergy Index = 0.48; 95% CI 0.24, 0.99; and relative excess of risk due to the interaction = -1.38; 95% CI -2.34, -0.42), suggesting that the observed joint effect of race and social mobility on tooth loss was lower than the expected sum of these factors. The estimates for Black/Brown people were smaller for those who were always poor during their lives, relative to their white counterparts. CONCLUSIONS: The findings suggest a higher prevalence of at least one tooth lost among people in the downward mobile SEP group and Black/Brown people. Greater racial inequity was found among Black/Brown people who had never experienced episodes of poverty, with Black/Brown people having a greater prevalence of at least one tooth lost than their white counterparts.

Clarifications on the intersectional MAIHDA approach: A conceptual guide and response to Wilkes and Karimi (2024).

Intersectional Multilevel Analysis of Individual Heterogeneity and Discriminatory Accuracy (MAIHDA) has been welcomed as a new gold standard for quantitative evaluation of intersectional inequalities, and it is being rapidly adopted across the health and social sciences. In their commentary "What does the MAIHDA method explain?", Wilkes and Karimi (2024) raise methodological concerns with this approach, leading them to advocate for the continued use of conventional single-level linear regression models with fixed-effects interaction parameters for quantitative intersectional analysis. In this response, we systematically address these concerns, and ultimately find them to be unfounded, arising from a series of subtle but important misunderstandings of the MAIHDA approach and literature. Since readers new to MAIHDA may share confusion on these points, we take this opportunity to provide clarifications. Our response is organized around four important clarifications: (1) At what level are the additive main effect variables defined in intersectional MAIHDA models? (2) Do MAIHDA models have problems with collinearity? (3) Why does the Variance Partitioning Coefficient (VPC) tend to be small, and the Proportional Change in Variance (PCV) tend to be large in MAIHDA? and (4) What are the goals of MAIHDA analysis?

The clustering effects of current smoking status, overweight/obesity, and physical inactivity with all-cause and cause-specific mortality risks in U.S. adults.

Objective: To estimate the associations of smoking, weight status and physical inactivity with all-cause and cause-specific deaths, and the advanced rate period (RAP) to determine how early death was advanced among United States (U.S.) adults aged 18 years or older. Methods: We used data from the third National Health and Nutrition Examination Survey (NHANES III) and the 2019 Linked Mortality File (LMF) with a follow-up period of 21.6 years (n = 16,612, including 7,278 deaths). Smoking, weight status, and physical inactivity were obtained from NHANES III and mortality outcomes from the 2019 LMF. Cox regression was used to estimate hazard ratios, RAPs and their corresponding confidence intervals. Results: For adults who currently smoke, were obese and physically inactive, the rate of dying from all-cause, CVD, and cancer was at least 231 % greater than for those who never smoked, were normal weight and physically active. The RAPs associated with the clustering of these risk factors for all cause, CVD- and cancer-specific cause of deaths were 13.0, 12.1 and 18.9 years older, respectively. Conclusions: Our findings underscore the need to focus on modifiable risk factors for illness prevention and health promotion and call attention to the increasing clustering of unhealthy risk factors in the U.S. population.

Mental Health Concerns During COVID-19: An Observational Study Among a Predominantly Black Community in New York City.

PURPOSE: This study examined the prevalence of mental health concerns and its association with COVID-19, selected social determinants of health, and psychosocial risk factors in a predominantly racial/ethnic minoritized neighborhood in New York City. METHODS: Adult Harlem residents (N = 393) completed an online cross-sectional survey from April to September 2021. The Patient Health Questionnaire (PHQ-4) and the Post-Traumatic Stress Disorder (PC-PTSD) were used to evaluate mental health concerns. Poisson regression with robust variance quantified the associations of interests via prevalence ratios (PR) and 95% confidence intervals (CI). RESULTS: Two-thirds (66.4%) of the residents reported experiencing mental health concerns, including PTSD (25.7%), depression (41.2%), and anxiety (48.1%). Residents with low-income housing status (PR = 1.16; 95% CI 1.01, 1.34), alcohol misuse (PR = 1.68; 95% CI 1.40, 2.01), food insecurity (PR = 1.23; 95% CI 1.07, 1.42), exposure to interpersonal violence (PR = 1.33; 95% CI 1.08, 2.65), and experience of discrimination (PR = 1.53, 95% CI 1.23-1.92) were more likely to report mental health concerns. Better community perception of the police (PR = 0.97, 95% CI 0.95, 0.99) was associated with fewer mental health concerns. No associations were observed for employment insecurity, housing insecurity, or household COVID-19 positivity with mental health concerns. CONCLUSIONS: This study showed a high prevalence of mental health concerns in a low-income racial/ethnic minoritized community, where COVID-19 and social risk factors compounded these concerns. Harlem residents face mental health risks including increased financial precarity, interpersonal violence, and discrimination exposure. Interventions are needed to address these concurrent mental health and psychosocial risk factors, particularly in racial/ethnic minoritized residents.

Asthma prevalence among US 9th-12th graders who report past 30-day cannabis use in 2019.

INTRODUCTION: Little is known about the relationship between cannabis use and asthma among youth in the US. The aims of this study were to estimate prevalence of asthma among youth who reported any cannabis use in the past 30 days, relative to those who did not, and to investigate the relationship between frequency of cannabis use and prevalence of asthma, adjusting for demographic characteristics and cigarette use. METHODS: Data were drawn from the 2019 Youth Risk Behavior Surveillance System (YRBSS), a CDC national high school survey, which collects data from students in grades 9-12 across the US bi-annually. Logistic regression was used to examine the prevalence of asthma among youth who reported any past 30-day cannabis use, relative to no use, and by frequency of cannabis use, adjusting for demographic characteristics and cigarette use. RESULTS: Asthma was more common among youth who reported any cannabis use, relative to youth who reported no use (29.07% vs. 23.62%; AOR = 1.25 (1.20, 1.30)). Asthma was greater among youth who reported more frequent cannabis use; asthma was highest among youth who reported having used cannabis "40 or more times" in the month (31.38%; AOR = 1.35 (1.25, 1.45)) CONCLUSION: Asthma is more common among youth who use cannabis, relative to those who do not, and the prevalence of asthma increases with frequency of use among 9th-12th graders in the US. More public health and clinical research is needed quickly to produce scientific data that can inform clinical guidelines and public health policy, as well as parents and youth, on the potential relationship between cannabis use and respiratory health among youth.

Mental Health Service Use, Barriers, and Service Preferences During COVID-19 among Low-Income Housing and Market-Rate Housing Residents of Harlem in New York City.

This study examined the differences in mental health service use, barriers, and service preferences among 393 low-income housing (LIH) and market-rate housing (MRH) Harlem residents in New York City. One-third (34.6%) endorsed the need for professional support for psychological issues, 27.2% and 15.8% reported using counseling services and psychotropic medication, with no differences between housing types. LIH residents (21.6-38.8%) reported significantly higher use of all types of mental health resources (e.g., websites, anonymous hotlines, self-help tools) compared with MRH residents (16.1-26.4%). Eighty-six percent reported barriers to mental health access, with LIH residents reporting more than double the barriers. Particularly, LIH residents reported greater difficulty getting time off work (34.1% vs. 14%), lack of health insurance (18.7% vs. 9.8%), lack of trust in mental health providers (14.6% vs. 4.7%), and stigma (12.2% vs. 5.1%) compared with MRH residents. Residents most preferred places of services were health clinics and houses of worship; provided by healthcare and mental health providers; and services delivered in-person and phone-based counseling. In contrast, residents least preferred getting support at mental health clinics; from family/friends; and by the Internet. No differences were found between service preferences by housing type. LIH residents reported higher use of mental health services and resources, but they face significantly more barriers to mental health care, suggesting a need to address specific barriers. Preferences for mental health services suggest a need for expanding mental health services to different settings given the low preference for services to be delivered at mental health clinics.

Is there an association between family members' season of birth that could influence birth seasonality? Evidence from Spain and France.

The number of births varies by season. Research on birth seasonality has shown that women's season of birth somehow influences that of their children, but factors underlying the intergenerational transmission of birth seasonality remain unknown. With data from Spain and France, we analysed the possibility of transmission of birth season between generations, testing whether relatives tended to be born in the same season. Results indicated that there was an association-a similarity-between parents' and children's birth seasons, partially explaining the stability of seasonal patterns over time. This association also existed between parents' birth seasons. While parents' association is directly explained by an excess of marriages with spouses born in the same month, the overall association may be explained by two facts: different socio-demographic groups show differentiated birth patterns, and relatives share socio-demographic features. Birth season seems to be related to family characteristics, which should be controlled for when assessing birth-month effects on subsequent social/health outcomes.

Cannabis use and the prevalence of current asthma among adolescents and adults in the United States.

OBJECTIVES: Cannabis use has increased among adolescents and adults in the United States (US) in recent years. Few data are available on the prevalence of asthma by frequency of cannabis use. This study aimed to estimate the prevalence of asthma by frequency of past 30-day cannabis use among US individuals. METHODS: Data were drawn from the 2020 National Survey on Drug Use and Health (NSDUH), a nationally representative, annual cross-sectional survey of US individuals aged 12 and older in the United States (N = 32,893). Logistic regression models were used to examine the relationship between frequency of any cannabis and/or blunt (i.e., cannabis smoked in a hollowed-out cigar) use in the past 30 days and current asthma, adjusting for demographics and current cigarette smoking. RESULTS: Current asthma was more common among US individuals who reported cannabis use in the past 30-days, relative to those who did not (9.8% vs. 7.4%, p < 0.0001). The odds of asthma was significantly greater among individuals reporting cannabis use 20-30 days/month (Adjusted Odds Ratio [AOR] = 1.67, 95% CI:1.21, 2.31), blunt use 6-15 and 20-30 days/month (AOR = 1.9, 95% CI:1.1, 3.2; AOR = 2.2, 95% CI:1.4, 3.6), respectively, than among those without. A positive linear relationship was observed between frequency of a) cannabis use (p < 0.0001) and b) blunt use (p < 0.0001) and current asthma prevalence. CONCLUSIONS: Findings suggest a dose-response relationship between frequency of current cannabis use and the prevalence of current asthma in the US individuals.

Novel insights into the whole-blood DNA methylome of asthma in ethnically diverse children and youth.

BACKGROUND: The epigenetic mechanisms of asthma remain largely understudied in African Americans and Hispanics/Latinos, two populations disproportionately affected by asthma. We aimed to identify markers, regions and processes with differential patterns of DNA methylation (DNAm) in whole blood by asthma status in ethnically diverse children and youth, and to assess their functional consequences. METHODS: DNAm levels were profiled with the Infinium MethylationEPIC or HumanMethylation450 BeadChip arrays among 1226 African Americans or Hispanics/Latinos and assessed for differential methylation per asthma status at the CpG and region (differentially methylated region (DMR)) level. Novel associations were validated in blood and/or nasal epithelium from ethnically diverse children and youth. The functional and biological implications of the markers identified were investigated by combining epigenomics with transcriptomics from study participants. RESULTS: 128 CpGs and 196 DMRs were differentially methylated after multiple testing corrections, including 92.3% and 92.8% novel associations, respectively. 41 CpGs were replicated in other Hispanics/Latinos, prioritising cg17647904 (NCOR2) and cg16412914 (AXIN1) as asthma DNAm markers. Significant DNAm markers were enriched in previous associations for asthma, fractional exhaled nitric oxide, bacterial infections, immune regulation or eosinophilia. Functional annotation highlighted epigenetically regulated gene networks involved in corticosteroid response, host defence and immune regulation. Several implicated genes are targets for approved or experimental drugs, including TNNC1 and NDUFA12. Many differentially methylated loci previously associated with asthma were validated in our study. CONCLUSIONS: We report novel whole-blood DNAm markers for asthma underlying key processes of the disease pathophysiology and confirm the transferability of previous asthma DNAm associations to ethnically diverse populations.

Research on racial/ethnic inequities in oral health over the past 80 years: The role of racism.

AIM: This study aims to (1) describe trends in explanations provided for racial/ethnic inequities in dental caries and periodontitis, and (2) explore the patterns of relatedness among explanations for these inequities. MATERIALS AND METHODS: Highly cited publications based on studies indexed in the Scopus database were retrieved and assessed for eligibility. Explanations for racial/ethnic inequities were classified into eight different, but interrelated domains. We assessed trends and examined the relations among explanations using multiple correspondence analysis. RESULTS: A total of 200 articles among the most cited publications were selected. The proportion of studies invoking racism as an explanation for racial inequities in oral health increased from 0% to 14.3%, from 1937 to 2020. The proportions of individual socio-economic factors increased from 52.0% to 82.9%, and dental care from 28.0% to 62.9%. The remaining explanations were stable: psychological/behavioural processes (62.5%), biological factors (49.5%), contextual/area-level effects (24.0%) and immigrant paradox (4.0%). Multiple correspondence analysis revealed a smaller axial distance between racism and the following categories: studies from Brazil, recent publications and Blacks/Hispanics/mixed-race groups. Publications about immigrants were axially closer to the high-income countries category. CONCLUSIONS: Our findings call on dental researchers to consider racism as a cause for existing racial/ethnic inequities in oral health.

Intersectional inequities in the birthweight gap between twin and singleton births: A random effects MAIHDA analysis of 2012-2018 New York City birth data.

Birthweight is a widely-used biomarker of infant health, with inequities patterned intersectionally by maternal age, race/ethnicity, nativity/immigration status, and socioeconomic status in the United States. However, studies of birthweight inequities almost exclusively focus on singleton births, neglecting high-risk twin births. We address this gap using a large sample (N = 753,180) of birth records, obtained from the 2012-2018 New York City (NYC) Department of Health and Mental Hygiene, Bureau of Vital Statistics, representing 99% of all births registered in NYC, and a novel random coefficients intersectional MAIHDA (Multilevel Analysis of Individual Heterogeneity and Discriminatory Accuracy) model. Our results show evidence of intersectional inequities in birthweight outcomes for both twin and singleton births by maternal age, race/ethnicity, education, and nativity status. Twins have considerably lower predicted birthweights than singletons overall (-930 g on average), and this is especially true for babies born to mothers who are younger (11-19 years), older (40+), racial/ethnic minoritized, foreign-born, and have lower education. However, the magnitude of this birthweight 'gap' between twins and singletons varies considerably across social identity strata, ranging between 830.8 g (observed among 40+ year old Black foreign-born mothers with high school degrees) and 1013.7 g (observed among 30-39 year old Hispanic/Latina foreign-born mothers with less than high school degrees). This study underscored the needs of a high-risk population and the need for aggressive social policies to address health inequities and dismantle intersectional systems of marginalization, oppression, and socioeconomic inequality. In addition to our substantive contributions, we add to the growing methods literature on intersectional quantitative analysis by demonstrating how to apply intersectional MAIHDA with random coefficients and random slopes. We conclude with a discussion of the significant potential for this methodological extension in future research on inequities.

Substance Use Patterns and Their Association with Depression and Social Factors During COVID-19 Among Harlem Residents in New York City.

This study aimed to identify the prevalence of substance use before and during COVID-19; and examined its association with depression and social factors among 437 residents from the neighborhood of Harlem in Northern Manhattan, New York City. Over a third of respondents reported using any substance before COVID-19, and initiating/increasing substance use during COVID-19. The most common substances used before COVID-19 and initiated/increased during COVID-19 were smoking (20.8% vs. 18.3%), marijuana (18.8% vs. 15.3%), and vaping (14.2% and 11.4%). The percentages of any hard drug use were 7.3% and 3.4%, respectively. After adjustment, residents with mild (Prevalence Ratio [PR] = 2.86, 95% CI 1.65, 4.92) and moderate (PR = 3.21, 95% CI 1.86, 5.56) symptoms of depression, and housing insecurity (PR = 1.47, 95% CI 1.12, 1.91) had at least a 47% greater probability of initiating and/or increasing substance use. Conversely, respondents with employment insecurity (PR = 0.71, 95% CI 0.57, 0.88) were 29% less likely to report such patterns. No association was found between substance use initiation and/or increase and food insecurity. High prevalence of substance use during COVID-19 may lead residents to turn to substance use as a coping mechanism for psychosocial stressors. Thus, it is essential to provide accessible and culturally sensitive mental health and substance use services.

The prevalence of SARS-CoV-2 infection and other public health outcomes during the BA.2/BA.2.12.1 surge, New York City, April-May 2022.

BACKGROUND: Routine case surveillance data for SARS-CoV-2 are incomplete, unrepresentative, missing key variables of interest, and may be increasingly unreliable for timely surge detection and understanding the true burden of infection. METHODS: We conducted a cross-sectional survey of a representative sample of 1030 New York City (NYC) adult residents ≥18 years on May 7-8, 2022. We estimated the prevalence of SARS-CoV-2 infection during the preceding 14-day period. Respondents were asked about SARS-CoV-2 testing, testing outcomes, COVID-like symptoms, and contact with SARS-CoV-2 cases. SARS-CoV-2 prevalence estimates were age- and sex-adjusted to the 2020 U.S. POPULATION: We triangulated survey-based prevalence estimates with contemporaneous official SARS-CoV-2 counts of cases, hospitalizations, and deaths, as well as SARS-CoV-2 wastewater concentrations. RESULTS: We show that 22.1% (95% CI 17.9-26.2%) of respondents had SARS-CoV-2 infection during the two-week study period, corresponding to ~1.5 million adults (95% CI 1.3-1.8 million). The official SARS-CoV-2 case count during the study period is 51,218. Prevalence is estimated at 36.6% (95% CI 28.3-45.8%) among individuals with co-morbidities, 13.7% (95% CI 10.4-17.9%) among those 65+ years, and 15.3% (95% CI 9.6-23.5%) among unvaccinated persons. Among individuals with a SARS-CoV-2 infection, hybrid immunity (history of both vaccination and infection) is 66.2% (95% CI 55.7-76.7%), 44.1% (95% CI 33.0-55.1%) were aware of the antiviral nirmatrelvir/ritonavir, and 15.1% (95% CI 7.1-23.1%) reported receiving it. Hospitalizations, deaths and SARS-CoV-2 virus concentrations in wastewater remained well below that during the BA.1 surge. CONCLUSIONS: Our findings suggest that the true magnitude of NYC's BA.2/BA.2.12.1 surge may have been vastly underestimated by routine case counts and wastewater surveillance. Hybrid immunity, bolstered by the recent BA.1 surge, likely limited the severity of the BA.2/BA.2.12.1 surge.

It is difficult to assess the true prevalence of SARS-CoV-2, the virus that causes COVID-19, due to changes in testing practices and behaviors, including increasing at-home testing and decreasing healthcare provider-based testing. We conducted a population-representative survey in New York City to estimate the prevalence of SARS-CoV-2 during the second Omicron surge in spring 2022. We compared survey-based SARS-CoV-2 prevalence estimates with data on diagnosed cases, hospitalizations, deaths, and SARS-CoV-2 concentration in wastewater. Our survey-based estimates were nearly 30 times higher than official case counts and estimates of immunity among those with active infection were high. Taken together, our results suggest that the magnitude of the second Omicron surge was likely significantly underestimated, and high levels of immunity likely prevented a major surge in hospitalizations/deaths. Our findings might inform future work on COVID-19 surveillance and how to mitigate its spread.

Enhancing physicians' radiology diagnostics of COVID-19's effects on lung health by leveraging artificial intelligence.

Introduction: This study aimed to develop an individualized artificial intelligence model to help radiologists assess the severity of COVID-19's effects on patients' lung health. Methods: Data was collected from medical records of 1103 patients diagnosed with COVID-19 using RT- qPCR between March and June 2020, in Hospital Madrid-Group (HM-Group, Spain). By using Convolutional Neural Networks, we determine the effects of COVID-19 in terms of lung area, opacities, and pulmonary air density. We then combine these variables with age and sex in a regression model to assess the severity of these conditions with respect to fatality risk (death or ICU). Results: Our model can predict high effect with an AUC of 0.736. Finally, we compare the performance of the model with respect to six physicians' diagnosis, and test for improvements on physicians' performance when using the prediction algorithm. Discussion: We find that the algorithm outperforms physicians (39.5% less error), and thus, physicians can significantly benefit from the information provided by the algorithm by reducing error by almost 30%.

Alcohol Misuse, Binge Drinking, and their Associations with Psychosocial Factors during COVID-19 among Harlem Residents in New York City.

This study examined alcohol misuse and binge drinking prevalence among Harlem residents, in New York City, and their associations with psycho-social factors such as substance use, depression symptom severity, and perception of community policing during COVID-19. An online cross-sectional study was conducted among 398 adult residents between April and September 2021. Participants with a score of at least 3 for females or at least 4 for males out of 12 on the Alcohol Use Disorders Identification Test were considered to have alcohol misuse. Binge drinking was defined as self-reporting having six or more drinks on one occasion. Modified Poisson regression models were used to examine associations. Results showed that 42.7% used alcohol before COVID-19, 69.1% used it during COVID-19, with 39% initiating or increasing alcohol use during COVID-19. Alcohol misuse and binge drinking prevalence during COVID-19 were 52.3% and 57.0%, respectively. Higher severity of depression symptomatology, history of drug use and smoking cigarettes, and experiencing housing insecurity were positively associated with both alcohol misuse and binge drinking. Lower satisfaction with community policing was only associated with alcohol misuse, while no significant associations were found between employment insecurity and food insecurity with alcohol misuse or binge drinking. The findings suggest that Harlem residents may have resorted to alcohol use as a coping mechanism to deal with the impacts of depression and social stressors during COVID-19. To mitigate alcohol misuse, improving access to mental health and substance use disorder services, and addressing public safety through improving relations with police could be beneficial.

Gene expression in African Americans, Puerto Ricans and Mexican Americans reveals ancestry-specific patterns of genetic architecture.

We explored ancestry-related differences in the genetic architecture of whole-blood gene expression using whole-genome and RNA sequencing data from 2,733 African Americans, Puerto Ricans and Mexican Americans. We found that heritability of gene expression significantly increased with greater proportions of African genetic ancestry and decreased with higher proportions of Indigenous American ancestry, reflecting the relationship between heterozygosity and genetic variance. Among heritable protein-coding genes, the prevalence of ancestry-specific expression quantitative trait loci (anc-eQTLs) was 30% in African ancestry and 8% for Indigenous American ancestry segments. Most anc-eQTLs (89%) were driven by population differences in allele frequency. Transcriptome-wide association analyses of multi-ancestry summary statistics for 28 traits identified 79% more gene-trait associations using transcriptome prediction models trained in our admixed population than models trained using data from the Genotype-Tissue Expression project. Our study highlights the importance of measuring gene expression across large and ancestrally diverse populations for enabling new discoveries and reducing disparities.