Identifying stroke risk and its association with multilevel factors among older people with uncontrolled hypertension in Chiang Rai, Thailand: a cross-sectional analytic study
Background: Stroke is a leading cause of death among older adults with uncontrolled hypertension. However, most studies focus on stroke patients rather than those at risk. This study examined stroke risk levels in older adults with uncontrolled hypertension in Chiang Rai, Thailand, and explored their associations with multilevel factors using an ecological model. Methods: A cross-sectional analytic study was conducted in a community of 238 individuals aged 60–69 years using multistage stratified random sampling. Data were collected through structured interviews and physical examinations (September-November 2023). The instruments were validated for reliability and met standard acceptance criteria. Binary logistic regression with adjusted odds ratio (AOR) was used to identify significant factors associated with a high risk of stroke. Results: Eighty-four percent of participants had a high 10-year risk of stroke. Eight factors were significantly associated with a high risk of stroke (p < 0.05), contributing to 45.3% of the risk. These factors included male gender, unemployment status, systolic blood pressure, body mass index, waist circumference exceeding the standard, number of cigarettes smoked daily, and perceived barriers to stroke prevention. Diastolic blood pressure was identified as a protective factor against stroke risk. Conclusions: Significant factors associated with a high risk of stroke were individual variables. The risk could be minimized by engaging individuals in regular exercise, educating them about healthier food choices, motivating smoking cessation, and regularly monitoring blood pressure and salt intake during home visits by village health volunteers. Keywords: Aging, Stroke, Hypertension, Health belief model, Social support, Thailand
Authors
- Sarunya Benjakul (ORCID: https://orcid.org/0000-0002-8396-8935)
- Jutatip Sillabutra (ORCID: https://orcid.org/0000-0002-9884-4193)
- Mondha Kengganpanich (ORCID: https://orcid.org/0000-0002-9144-6803)
- Sunaree Tanapek
Publication Details
- Journal
- Journal of Health Research
- Published
- 2025-05-07
- DOI
- https://doi.org/10.56808/2586-940x.1132
- Primary Topic
- Artificial Intelligence in Healthcare
- Type
- article
- Field-Weighted Citation Impact
- 0.00