Evidence map›Paper›PMID 39106439›Full record

ArticleRevista medica del Instituto Mexicano del Seguro Social2024

[COVID-19 and the predominant groups of preventive behaviors and associated factors: semi-urban area].

Adriana Romero-Gomora, Laura Becerril-Díaz, Michelle Yesenia-Ávila, Adriana Díaz-Medina, María Guadalupe Berumen-Lechuga, Francisco Abraham Jiménez-Armenta, Jessica Camacho-Ruíz, Salvador Vázquez-Vega, Rosalinda Sánchez-Arenas

Abstract readEnglish Abstract
In one paragraph

Article in Revista medica del Instituto Mexicano del Seguro Social, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing 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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

9 authors.

Adriana Romero-GomoraInstituto Mexicano del Seguro Social, Centro Médico Siglo XXI, Módulo Central, Unidad de Investigación Epidemiológica y en Servicios de Salud. Ciudad de México, México.ORCID 0009-0003-2402-7152
Laura Becerril-DíazUniversidad Autónoma del Estado de México, Facultad de Enfermería, Coordinación de Extensión y Vinculación. Toluca, Estado de México, México.ORCID 0009-0008-7275-0595
Michelle Yesenia-ÁvilaInstituto Mexicano del Seguro Social, Centro Médico Siglo XXI, Módulo Central, Unidad de Investigación Epidemiológica y en Servicios de Salud. Ciudad de México, México.ORCID 0009-0000-9166-1581
Adriana Díaz-MedinaInstituto Mexicano del Seguro Social, Órgano de Operación Administrativa Desconcentrada Estado de México Poniente, Unidad de Medicina Familiar No. 226, Dirección General. Ixtlahuaca, Estado de México, México.ORCID 0009-0001-4414-5653
María Guadalupe Berumen-LechugaInstituto Mexicano del Seguro Social, Órgano de Operación Administrativa Desconcentrada Estado de México Poniente, Coordinación Auxiliar Médica en Investigación en Salud. Toluca, Estado de México, México.ORCID 0000-0002-0094-1308
Francisco Abraham Jiménez-ArmentaInstituto Mexicano del Seguro Social, Centro Médico Siglo XXI, Módulo Central, Unidad de Investigación Epidemiológica y en Servicios de Salud. Ciudad de México, México.ORCID 0009-0009-3554-508X
Jessica Camacho-RuízInstituto Mexicano del Seguro Social, Órgano de Operación Administrativa Desconcentrada CDMX Sur, Unidad de Medicina Familiar No. 28, Servicio de Urgencias. Ciudad de México, México.ORCID 0000-0003-4207-3251
Salvador Vázquez-VegaInstituto Mexicano del Seguro Social, Centro Médico Siglo XXI, Módulo Central, Unidad de Investigación Epidemiológica y en Servicios de Salud. Ciudad de México, México.ORCID 0000-0001-7544-0906
Rosalinda Sánchez-ArenasInstituto Mexicano del Seguro Social, Centro Médico Siglo XXI, Módulo Central, Unidad de Investigación Epidemiológica y en Servicios de Salud. Ciudad de México, México.ORCID 0000-0003-2043-9363

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Non-pharmacological interventions (NFI) or preventive actions (PA) are the best alternatives to control future pandemics, especially in vulnerable populations, such as semi-urban areas. Objective: To describe the predominant health behavior groups (HBG) and associated factors during the third wave of COVID-19 in a semi-urban area. Material and methods: A survey which included characteristics, factors related to COVID-19, perceptions of health behavior and PA was applied in a probabilistic sample in a first-level hospital in the State of Mexico. People of both sexes over 18 years of age were included. Using a hierarchical cluster analysis, HBGs were obtained and characterized with a descriptive and multivariate statistical analysis. Results: In a probabilistic sample (n = 260), 4 HBGs were identified: 2 of high-risk (HRG) and 2 of low-risk (LRG), and the proportions were 43.5% y 56.5%, respectively. The sociodemographic characteristics of both groups were similar. Perceptions of severity and COVID-19-related barriers significantly influenced health behaviors in LRG. In HRG, low security played a significant role, highlighting the importance of comorbidities as a clinical factor. Conclusions: In a semi-urban area, 2 crucial health behaviors were identified: one associated with low risk and the other with high risk. In the HRG, the perception of insecurity was particularly relevant, emphasizing the importance of comorbidities as a clinical factor.

Indexed as

COVID-19Health BehaviorAdolescentAdultAgedCross-Sectional StudiesFemaleHumansMaleMexicoMiddle AgedSuburban PopulationSurveys and QuestionnairesYoung AdultBehavior Health-RelatedCOVID-19Disease PreventionHealth BehaviorRisk Factors

Identifiers

PMID39106439
PMCPMC12092073

What OpenQuestion holds

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LicenceCC BY-NC-ND
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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.