Evidence map›Paper›PMID 40080375›Full record

ArticleJournal of racial and ethnic health disparities2026

Geospatial Analysis of Tooth Loss Among the US Geriatric Population by Zip Code: The Role of Socioeconomic and Racial Factors.

Ravindra Rapaka, Richa Kaushik

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Article in Journal of racial and ethnic health disparities, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

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1 · What the graph read from it

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3 · Its place in the literature

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1 citing paper in PubMed.

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5 · Who and what money

Authors and funding

2 authors.

Ravindra RapakaUniversity of Connecticut, Storrs, CT, USA. ravindranath.rapaka@uconn.edu.ORCID 0009-0001-9549-8555
Richa KaushikUniversity of Connecticut, Storrs, CT, USA.ORCID 0000-0003-4376-3369

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

objectiveThis study investigates the prevalence of tooth loss among the US geriatric population (≥ 65 years) in relation to socioeconomic and demographic characteristics at the local level, specifically identified by ZIP code tabulation areas (ZCTAs).

methodsData obtained from the American Community Survey (ACS) and PLACES in collaboration with the Centers for Disease Control and Prevention (CDC) were evaluated. Geographical autocorrelation was examined using Moran's I, while geographically weighted regression (GWR) and geographical lag models were employed to analyze spatial patterns and relationships, accounting for spatial dependence. K-means clustering established several ZCTA typologies based on socioeconomic variables.

resultsA notable spatial autocorrelation was seen in the rates of total tooth loss (Moran's I = 0.64, p < 0.001). GWR demonstrated superior accuracy when compared with ordinary least squares (OLS) regression, accounting for 81.1% of the variance and indicating significant spatial heterogeneities in the associations between tooth loss and variables such as education, income, and poverty. Spatial lag models corroborated the impact of adjacent ZCTAs on the prevalence of tooth loss. Ethnic and racial discrepancies suggested that Black majority ZCTAs exhibited greater incidences of severe tooth loss. K-means clustering discovered distinct ZCTA typologies, one of which is a high-risk group marked by extreme poverty and lack of education, resulting in a higher rate of tooth loss.

conclusionThe findings emphasize the critical role of geographic context in understanding disparities in oral health care and underscore the necessity for localized primary preventive strategies targeted to the elderly, particularly those living in economically disadvantaged regions, to attain oral equality.

Indexed as

Health Status DisparitiesNeighborhood CharacteristicsTooth LossAgedAged, 80 and overBlack or African AmericanFemaleHumansMalePrevalenceSocioeconomic FactorsSpatial AnalysisUnited StatesWhiteGeographically weighted regressionGeriatric oral healthHealth disparitiesSocioeconomic factorsSpatial analysisTotal tooth loss

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