Purpose This paper examined the impacts of artificial intelligence (AI)-assisted health management on blood pressure control and self-management effectiveness in older adults with hypertension.Materials and Methods Two hundred hypertensive patients were randomly assigned to a usual care group (routine health management) or an intervention group (AI-assisted health management, including aspects such as intelligent monitoring, early warning and proactive intervention, among others) (n = 100 each). Primary outcomes included blood pressure control rate (<140/<90 mm Hg) and systolic and diastolic blood pressure (SBP and DBP). Secondary outcomes included improvement in lifestyle behaviors, level of hypertension knowledge awareness, self-management efficacy, medication beliefs, quality of life, and management satisfaction.Results Following one year intervention, the intervention group demonstrated a higher blood pressure control rate than the usual care group (88.66% vs. 64.89%), along with lower SBP (128.49 ± 6.63 vs. 135.38 ± 7.31 mmHg) and DBP (77.49 ± 6.07 vs. 81.84 ± 5.44 mmHg) (all P < 0.05). Additionally, the intervention group showed superior improvements in smoking behavior change, alcohol consumption behavior change, low-salt and low-fat diet adherence, and regular exercise attainment, as well as higher scores on the Hypertension Knowledge-Level Scale, Hypertension Patient Self-Management Behavior Rating Scale, Modified Beliefs about Medicines Questionnaire, physical component summary and the mental component summary, and Client Satisfaction Questionnaire-8 (all P < 0.05).Conclusion AI-assisted health management enhances blood pressure control, and improves self-management capacity, quality of life, and service satisfaction in older adults with hypertension.
Environmental and psychosocial factors are increasingly recognized as important contributors to the development, progression, and control of hypertension (HTN) and cardiovascular (CV) disease. Within the exposome framework, these exposures converge on shared neuroendocrine, oxidative, and inflammatory pathways leading to endothelial dysfunction and blood pressure (BP) elevation. Among environmental pollutants, air pollution, particularly fine particulate matter (PM2.5), is a major modifiable risk factor; each 10 µg/m³ increase in PM2.5 is associated with a 4% rise in HTN prevalence. Transportation noise from road traffic and aircraft independently increases HTN risk through stress-related neurohormonal activation, oxidative stress, and sleep disruption. Artificial light at night and heavy metals are additional contributors, whereas micro- and nanoplastics remain an emerging concern awaiting robust human data. Physical and climatic stressors also influence BP regulation. Both heat and cold are associated with increased CV morbidity and mortality, with cold exerting the greater impact, and hypobaric hypoxia at high altitude activates sympathetic and neurohormonal pathways that promote BP elevation, particularly in hypertensive individuals. Among psychosocial and behavioral factors, sleep disturbances, including obstructive sleep apnea, short sleep duration, and poor sleep quality, are associated with incident and resistant HTN. Post-traumatic stress disorder (PTSD) is an underrecognized determinant of HTN, especially among refugees, migrants, war veterans, and other trauma-exposed populations, through chronic sympathetic activation, inflammation, and adverse behavioral pathways. Finally, spaceflight provides a unique model of extreme environmental stress, inducing CV adaptations ranging from transient BP dysregulation and orthostatic intolerance to vascular remodeling resembling accelerated CV aging. Recognizing these determinants is essential to improve HTN prevention, optimize BP control, and reduce long-term CV risk.
