Evidence map›Paper›PMID 42010579›Full record

ArticleBMC public health2026

Active health behaviors and their influencing factors among community-dwelling elderly hypertensive patients: a cross-sectional study in Zhengzhou, China.

XinWen, Yan Zhang, Shiwei Ma, Qi Li, Xinqi Wu

Abstract read
In one paragraph

Article in BMC public health, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

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

What it found

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2 · The registry

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3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

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4 · The record

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5 · Who and what money

Authors and funding

5 authors.

XinWenSchool of Nursing and Health, Zhengzhou University, Zhengzhou, Henan, China.
Yan ZhangSchool of Nursing and Health, Zhengzhou University, Zhengzhou, Henan, China. zhangyanmy@126.com.
Shiwei MaSchool of Nursing and Health, Zhengzhou University, Zhengzhou, Henan, China.
Qi LiSchool of Nursing and Health, Zhengzhou University, Zhengzhou, Henan, China.
Xinqi WuSchool of Nursing and Health, Zhengzhou University, Zhengzhou, Henan, China.

Funding

Chinese Nursing Association ZHKY202414
6 · The paper itself

Abstract

backgroundHypertension is a common chronic disease among older adults, and active health behaviors are important for disease management and health promotion in this population. However, evidence on the current status of active health behaviors and their influencing factors among community-dwelling older adults with hypertension remains limited. This study aimed to investigate the current status of active health behaviors among community-dwelling older adults with hypertension and explore the factors influencing these behaviors, thereby providing a basis for improving active health behaviors in this population.To investigate the current status of active health behaviors among elderly hypertensive patients in the community and explore the factors influencing these behaviors, providing a basis for improving the active health behaviors of this population.

methodsIn this community-based cross-sectional study, convenience sampling was used to recruit 401 community-dwelling elderly hypertensive patients in Zhengzhou, Henan Province, China, from November 2023 to December 2023. Data were collected using a general information questionnaire, the Active Health Behavior Scale, the Digital Health Literacy Assessment Scale for Community Elderly, and the Brief Illness Perception Questionnaire. Descriptive statistics, univariate analyses, Pearson correlation analysis, and multiple linear regression were used to analyze the data.

resultsThe average score of active health behaviors among elderly hypertensive patients in the community was 109.86(21.64). Multiple linear regression showed that age, per capita monthly household income, health status, form of medical payment, digital health literacy, and illness perception were factors influencing active health behaviors in elderly hypertensive patients in the community (P<0.05), explaining 60.6% of the total variance.

conclusionThe level of active health behaviors among elderly hypertensive patients in the community needs improvement. Higher levels of active health behaviors were associated with older age, higher per capita monthly household income, better self-assessed health status, and having medical insurance as the form of payment. Positive illness perception and digital health literacy also had a favorable impact on the active health behaviors of elderly hypertensive patients in the community.

trial registrationNot applicable.

Indexed as

Health BehaviorHypertensionIndependent LivingAgedAged, 80 and overChinaCross-Sectional StudiesFemaleHealth LiteracyHumansMaleMiddle AgedSurveys and QuestionnairesActive health behaviorsDigital health literacyElderlyHypertensionIllness perception

Identifiers

PMID42010579
PMCPMC13227720

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LicenceCC BY-NC-ND
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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.