Evidence map›Paper›PMID 41360840›Full record

ArticleScientific reports2025

Effect of information motivation behavioral skills model based dietary patterns on carotid atherosclerosis in elderly hypertensive patients.

Beiguang Yu, Linlin Pu, Shuai Liu, Shanshan Lu, Guochao Han, Dongruo He

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Article in Scientific reports, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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1 · What the graph read from it

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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

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3 · Its place in the literature

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4 · The record

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5 · Who and what money

Authors and funding

6 authors.

Beiguang YuDepartment of Electrophysiology, The First Hospital of Qiqihar, No. 30, Park Road, Longsha District, Qiqihar, 161000, Heilongjiang, China. yubeiguang@qmu.edu.cn.
Linlin PuDepartment of Respiratory Medicine I, The Second Affiliated Hospital of Qiqihar Medical University, Qiqihar, China.
Shuai LiuDepartment of Electrophysiology, , The Second Affiliated Hospital of Qiqihar Medical University, Qiqihar, China.
Shanshan LuDepartment of Electrophysiology, , The Second Affiliated Hospital of Qiqihar Medical University, Qiqihar, China.
Guochao HanDepartment of Electrophysiology, , The Second Affiliated Hospital of Qiqihar Medical University, Qiqihar, China.
Dongruo HeDepartment of Electrophysiology, , The Second Affiliated Hospital of Qiqihar Medical University, Qiqihar, China.

Funding

Qiqihar Science and Technology Program Joint Guidance Project LSFGG-2024064
6 · The paper itself

Abstract

Since hypertension exacerbates carotid arteries atherosclerosis among the elderly, this study aimed to find whether dietary pattern alteration can alleviate this effect using the Information-Motivation-Behavioral (IMB) Skills Model. In a retrospective cohort study with a 3-month follow-up, 1000 elderly hypertensive patients admitted between June 2022 and June 2023 were categorized into two groups: a Non-IMB group (n = 480) following a standard low-salt, low-fat diet and an IMB model-based diet group (n = 520). Propensity score matching ensured comparable baseline characteristics. Over three months, the IMB group received comprehensive dietary education and support. Primary outcomes measured were changes in CIMT and plaque scores, assessed via carotid ultrasound. Secondary measures included motivation for health-related behaviors, cardiovascular health, and quality of life. The IMB group showed a significant reduction in CIMT (1.05 ± 0.30 mm) compared to the Non-IMB group (1.20 ± 0.35 mm, P < 0.001). Plaque scores decreased significantly in the IMB group (1.80 ± 0.32) versus the Non-IMB group (1.97 ± 0.41, P < 0.001). Multivariate analysis highlighted adherence to the IMB dietary pattern as the strongest predictor of improved CIMT and plaque scores, with an odds ratio of 7.807 (95% CI 5.851 to 10.417, P < 0.001). While significant improvements were noted in dietary intake patterns and blood pressure parameters, motivational and cardiovascular health metrics showed no statistically significant differences between groups. The potential applicability of the IMB dietary framework in clinical strategies aimed at mitigating atherosclerosis progression and managing cardiovascular risk in this demographic.

Indexed as

Carotid Artery DiseasesHypertensionMotivationAgedAged, 80 and overCarotid Intima-Media ThicknessFemaleHealth BehaviorHumansInformation Motivation Behavioral Skills ModelMaleMiddle AgedQuality of LifeRetrospective StudiesCarotid artery atherosclerosisCarotid vascular ultrasoundDietary patternElderly hypertensive patientsInformation-motivation-behavioral modelRetrospective cohort study

Identifiers

PMID41360840
PMCPMC12685943

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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.