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. 2024 Jan 26;10(4):eadf9033.
doi: 10.1126/sciadv.adf9033. Epub 2024 Jan 24.

Mining the health disparities and minority health bibliome: A computational scoping review and gap analysis of 200,000+ articles

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Mining the health disparities and minority health bibliome: A computational scoping review and gap analysis of 200,000+ articles

Harry Reyes Nieva et al. Sci Adv. .

Abstract

Without comprehensive examination of available literature on health disparities and minority health (HDMH), the field is left vulnerable to disproportionately focus on specific populations or conditions, curtailing our ability to fully advance health equity. Using scalable open-source methods, we conducted a computational scoping review of more than 200,000 articles to investigate major populations, conditions, and themes as well as notable gaps. We also compared trends in studied conditions to their relative prevalence using insurance claims (42 million Americans). HDMH publications represent 1% of articles in Medical Literature Analysis and Retrieval System Online (MEDLINE). Most studies are observational in nature, although randomized trial reporting has increased fivefold in the past 20 years. Half of HDMH articles concentrate on only three disease groups (cancer, mental health, and endocrine/metabolic disorders), while hearing, vision, and skin-related conditions are among the least well represented despite substantial prevalence. To support further investigation, we present HDMH Monitor, an interactive dashboard and repository generated from the HDMH bibliome.

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Figures

Fig. 1.
Fig. 1.. Graphical abstract.
We identified HDMH articles using the MEDLINE/PubMed Health Disparities and Minority Health Search Strategy and indexed them via MeSH terms, conditions mentioned, and themes derived from topic modeling. We also compared trends in studied conditions to their relative prevalence in the general population using data from external insurance claims databases. CCAE, Commercial Claims and Encounters; HDMH, health disparities and minority health; MDCD, Medicaid; MDCR, Medicare; MEDLINE, Medical Literature Analysis and Retrieval System Online; MeSH, Medical Subject Headings.
Fig. 2.
Fig. 2.. HDMH publication output, 1975–2020 (n = 206,011).
(A) HDMH article count by year. (B) Percentage of HDMH articles in MEDLINE by year. Between 1975 and 2020, HDMH research publications in MEDLINE, the NLM bibliographic database containing more than 28 million biomedical references from more than 5200 journals, rose annually from 0.5% (408 articles) to 1% (13,180 articles). HDMH, health disparities and minority health; MEDLINE, Medical Literature Analysis and Retrieval System Online; NLM, National Library of Medicine.
Fig. 3.
Fig. 3.. HDMH article counts by ICD-10 chapter and population category.
Conditions across all ICD-10 chapters (see Table 1 for full descriptions) were identified among minority groups (based on MeSH population categories) with high variability in condition coverage within and across populations. Disabled, persons with disabilities; HDMH, health disparities and minority health; ICD-10, International Classification of Diseases, 10th Revision; Latino, Hispanic or Latina/e/o/x; MeSH, Medical Subject Heading; NAAN, Native American or Alaska Native; NHPI, Native Hawaiian or other Pacific Islander; SGM, sexual and gender minorities.
Fig. 4.
Fig. 4.. Word clouds for maternal-child health (Topic 11) and reproductive health (Topic 33).
Topic modeling of HDMH article titles and abstract text enabled nuanced analysis capable of distinguishing between seemingly similar themes such as maternal-child health and reproductive health despite shared terms (e.g., "woman" and "pregnancy"). Word size indicates relative frequency among topic terms. HDMH, health disparities and minority health.
Fig. 5.
Fig. 5.. Topics generated from titles and abstracts of HDMH articles (n = 206,011).
Topics spanned 50 themes that ranged in discussion of populations (e.g., racial and ethnic groups, sexual and gender minorities, adolescents, and immigrants), conditions (e.g., cancer, cardiovascular disease, diabetes mellitus, infectious diseases, and overweight/obesity), and study methods (e.g., community-based research and assessments of knowledge, attitudes, and perceptions). For each topic, we present the percentage of articles for which that topic was the dominant theme of the article. HDMH, health disparities and minority health.
Fig. 6.
Fig. 6.. Topics generated from the HDMH bibliome (206,011 articles) by publication year, 1975–2020.
(A) Cancer incidence and mortality, cancer screening, cancer treatment and outcomes, environmental health, and genetics and epigenetics. (B) Household environment, maternal-child health, reproductive health, sexual and gender minorities, and sexual health and behavior. (C) Adolescents and youth; child development; immigrant health; race, ethnicity, and neighborhood; and urban-rural status. (D) Access to care and services; health insurance and utilization; health policy and government; health care costs; and race, ethnicity, and socioeconomic status. (E) Diagnosis and treatment delay; disease prevalence; economic policy; medical education; population trends; and race, ethnicity, and education. (F) Beliefs and culture; communication and decision-making; community-based research; cultural competence; knowledge, attitudes, and perceptions; and survey-based studies. (G) Diabetes and cardiovascular disease, diet and nutrition, medications, overweight and obesity, and physical activity and disability. (H) Mental health; mortality, injury, and suicide; sleep and stress; substance use and criminalization; and tobacco use and cessation. (I) Global health, hospital-based care, infectious diseases, oral health, patient satisfaction, and primary and specialist care. Trend lines representing annual percentage of articles based on the dominant topic of each article are graphed using LOESS. Themes in the literature have changed over the past half century, ranging in discussions of groups and subgroups (e.g., racial and ethnic groups, sexual and gender minorities, adolescents, and immigrants), conditions (e.g., cancer, cardiovascular disease, diabetes mellitus, infectious diseases, and overweight/obesity), and study approaches (e.g., community-based research; assessments of knowledge, attitudes, and perceptions). SES, socioeconomic status.

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