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1.
JAMA ; 329(19): 1682-1692, 2023 05 16.
Artículo en Inglés | MEDLINE | ID: mdl-37191700

RESUMEN

Importance: Health inequities exist for racial and ethnic minorities and persons with lower educational attainment due to differential exposure to economic, social, structural, and environmental health risks and limited access to health care. Objective: To estimate the economic burden of health inequities for racial and ethnic minority populations (American Indian and Alaska Native, Asian, Black, Latino, and Native Hawaiian and Other Pacific Islander) and adults 25 years and older with less than a 4-year college degree in the US. Outcomes include the sum of excess medical care expenditures, lost labor market productivity, and the value of excess premature death (younger than 78 years) by race and ethnicity and the highest level of educational attainment compared with health equity goals. Evidence Review: Analysis of 2016-2019 data from the Medical Expenditure Panel Survey (MEPS) and state-level Behavioral Risk Factor Surveillance System (BRFSS) and 2016-2018 mortality data from the National Vital Statistics System and 2018 IPUMS American Community Survey. There were 87 855 survey respondents to MEPS, 1 792 023 survey respondents to the BRFSS, and 8 416 203 death records from the National Vital Statistics System. Findings: In 2018, the estimated economic burden of racial and ethnic health inequities was $421 billion (using MEPS) or $451 billion (using BRFSS data) and the estimated burden of education-related health inequities was $940 billion (using MEPS) or $978 billion (using BRFSS). Most of the economic burden was attributable to the poor health of the Black population; however, the burden attributable to American Indian or Alaska Native and Native Hawaiian or Other Pacific Islander populations was disproportionately greater than their share of the population. Most of the education-related economic burden was incurred by adults with a high school diploma or General Educational Development equivalency credential. However, adults with less than a high school diploma accounted for a disproportionate share of the burden. Although they make up only 9% of the population, they bore 26% of the costs. Conclusions and Relevance: The economic burden of racial and ethnic and educational health inequities is unacceptably high. Federal, state, and local policy makers should continue to invest resources to develop research, policies, and practices to eliminate health inequities in the US.


Asunto(s)
Escolaridad , Estrés Financiero , Inequidades en Salud , Accesibilidad a los Servicios de Salud , Determinantes Sociales de la Salud , Adulto , Humanos , Etnicidad/estadística & datos numéricos , Estrés Financiero/epidemiología , Estrés Financiero/etnología , Estrés Financiero/etiología , Grupos Minoritarios/estadística & datos numéricos , Estados Unidos/epidemiología , Accesibilidad a los Servicios de Salud/economía , Accesibilidad a los Servicios de Salud/estadística & datos numéricos , Determinantes Sociales de la Salud/economía , Determinantes Sociales de la Salud/etnología , Determinantes Sociales de la Salud/estadística & datos numéricos , Costo de Enfermedad , Indio Americano o Nativo de Alaska/estadística & datos numéricos , Asiático Americano Nativo Hawáiano y de las Islas del Pacífico/estadística & datos numéricos , Hispánicos o Latinos/estadística & datos numéricos , Negro o Afroamericano/estadística & datos numéricos
2.
Am J Prev Med ; 2024 Jul 05.
Artículo en Inglés | MEDLINE | ID: mdl-38971453

RESUMEN

INTRODUCTION: Social determinants of health (SDOH) contribute to differences in health outcomes and exacerbate health disparities. This study characterizes the National Institute on Minority Health and Health Disparities' (NIMHD) portfolio of funded grants in SDOH research, identifies gaps, and provides suggestions for future research. METHODS: Using the National Institutes of Health's SDOH Research, Condition, and Disease Categorization, research projects funded from 2019 to 2023 were identified and linked with NIMHD's internal coding system to extract in-depth study characteristics, including sociodemographics of study participants, disease and condition focus, and alignment with strategic priorities. Natural Language Processing methods were used to categorize projects into five Healthy People 2030 SDOH domains. RESULTS: The resulting sample included 675 unique research projects. Most projects included racial and ethnic minority groups (89%), followed by people with lower socioeconomic status (33%), underserved rural communities (16%), and sexual and gender minority groups (13%). Most projects focused on the Etiology of health disparities (61%), followed by Interventions (54%), and Methods and Measurement (39%). Of the Healthy People 2030 domains, Social and Community Context had the greatest representation (61%) whereas Education Access and Quality had the least (6%). Variation in research project characteristics across SDOH domains is also presented. CONCLUSIONS: This study documents characteristics of SDOH research funded by NIMHD and explores how they differ across Healthy People 2030 SDOH domains. Findings highlight how study characteristics and foci align with strategic priorities and suggest opportunities for future research.

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