Evidence map›Paper›PMID 40245404›Full record

ArticleJMIR aging2025

Unveiling the Frailty Spatial Patterns Among Chilean Older Persons by Exploring Sociodemographic and Urbanistic Influences Based on Geographic Information Systems: Cross-Sectional Study.

Yony Ormazábal, Diego Arauna, Juan Carlos Cantillana, Iván Palomo, Eduardo Fuentes, Carlos Mena

Abstract read
In one paragraph

Article in JMIR aging, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

2 citing papers in PubMed.

  1. Review
  2. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

6 authors.

Yony Ormazábal *Longevity Center VITALIS, Faculty of Economics and Business, University of Talca, Universidad de Talca, Avenida Lircay S/N, Talca, 3460000, Chile, 56 712200200.ORCID http://orcid.org/0000-0001-9947-3024
Diego Arauna *Thrombosis Research Center, Department of Clinical Biochemistry and Immunohematology, Faculty of Health Sciences, Interuniversity Center of Healthy Aging (CIES), Longevity Center VITALIS, University of Talca, Talca, Chile.ORCID http://orcid.org/0000-0001-7132-991X
Juan Carlos CantillanaFacultad de Administración y Economía, Universidad Tecnológica Metropolitana, Santiago, Chile.ORCID http://orcid.org/0000-0002-4872-1478
Iván PalomoThrombosis Research Center, Department of Clinical Biochemistry and Immunohematology, Faculty of Health Sciences, Interuniversity Center of Healthy Aging (CIES), Longevity Center VITALIS, University of Talca, Talca, Chile.ORCID http://orcid.org/0000-0002-9618-8778
Eduardo FuentesThrombosis Research Center, Department of Clinical Biochemistry and Immunohematology, Faculty of Health Sciences, Interuniversity Center of Healthy Aging (CIES), Longevity Center VITALIS, University of Talca, Talca, Chile.ORCID http://orcid.org/0000-0003-0099-4108
Carlos MenaLongevity Center VITALIS, Faculty of Economics and Business, University of Talca, Universidad de Talca, Avenida Lircay S/N, Talca, 3460000, Chile, 56 712200200.ORCID http://orcid.org/0000-0001-7780-9092

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Frailty syndrome increases the vulnerability of older adults. The growing proportion of older adults highlights the need to better understand the factors contributing to the prevalence of frailty. Current evidence suggests that geomatic tools integrating geolocation can provide valuable information for implementing preventive measures by enhancing the urban physical environment. Objective: The aim of this study was to analyze the relationship between various elements of the urban physical environment and the level of frailty syndrome in older Chilean people. Methods: A cohort of 251 adults aged 65 years or older from Talca City, Chile, underwent comprehensive medical assessments and were geographically mapped within a Geographic Information Systems database. Frailty was determined using the Fried frailty criteria. The spatial analysis of the frailty was conducted in conjunction with layers depicting urban physical facilities within the city, including vegetables and fruit shops, senior centers or communities, pharmacies, emergency health centers, main squares and parks, family or community health centers, and sports facilities such as stadiums. Results: The studied cohort was composed of 187 women and 64 men, with no significant differences in age and BMI between genders. Frailty prevalence varied significantly across clusters, with Cluster 3 showing the highest prevalence (14/47, P=.01). Frail individuals resided significantly closer to emergency health centers (960 [SE 904] m vs 1352 [SE 936] m, P=.04), main squares/parks (1550 [SE 130] m vs. 2048 [SE 105] m, P=.03), and sports fields (3040 [SE 236] m vs 4457 [SE 322]m, P=.04) compared with nonfrail individuals. There were no significant differences in urban quality index across frailty groups, but frail individuals lived in areas with higher population density (0.013 [SE 0.001] vs 0.01 [SE 0.0007], P=.03). Conclusions: Frail individuals exhibit geospatial patterns suggesting intentional proximity to health facilities, sports venues, and urban facilities, revealing associations with adaptive responses to frailty and socioeconomic factors. This highlights the crucial intersection of urban environments and frailty, which is important for geriatric medicine and public health initiatives.

Indexed as

Frail ElderlyFrailtyGeographic Information SystemsUrban PopulationAgedAged, 80 and overChileCross-Sectional StudiesFemaleHumansMalePrevalenceSociodemographic FactorsSocioeconomic FactorsSpatial Analysisagingfrailtygeospatial clusteringneighborhood conditions.urban factors

Identifiers

PMID40245404
PMCPMC12021301

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.