{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,7,7]],"date-time":"2026-07-07T12:24:47Z","timestamp":1783427087370,"version":"3.54.6"},"reference-count":35,"publisher":"Frontiers Media SA","license":[{"start":{"date-parts":[[2025,1,23]],"date-time":"2025-01-23T00:00:00Z","timestamp":1737590400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":["frontiersin.org"],"crossmark-restriction":true},"short-container-title":["Front. Psychiatry"],"abstract":"<jats:sec><jats:title>Introduction<\/jats:title><jats:p>This study investigates how anxiety, depression, and sleep disorders impact heart rate variability (HRV) in the elderly, exploring the clinical implications of HRV changes.<\/jats:p><\/jats:sec><jats:sec><jats:title>Methods<\/jats:title><jats:p>We examined 355 patients (163 men, 192 women) at Xijing Hospital from July 2021 to December 2022 during health check-ups. Demographics were recorded, and emotional status was assessed using the Hamilton Anxiety Scale (HAMA) and the Hamilton Depression Scale (HAMD). The Pittsburgh Sleep Quality Scale (PSQI) evaluated sleep quality. Patients were categorized into groups A-G based on the presence of emotional states and sleep disorders. HRV indices\u2014SDNN, SDANN, RMSSD, PNN50, LF\/HF, LF, and HF\u2014were analyzed using ANOVA and multivariate logistic regression.<\/jats:p><\/jats:sec><jats:sec><jats:title>Results<\/jats:title><jats:p>No statistically significant differences were observed in demographic, clinical, and lifestyle factors across the eight groups. Variables assessed included age, sex, body mass index (BMI), fasting blood glucose, glycated hemoglobin (HbA1c), blood lipids, blood pressure, heart rate, and histories of smoking and alcohol consumption. Additionally, the presence of hypertension, diabetes, coronary heart disease, marital status, income, and education level were evaluated, with all showing equivalence (<jats:italic>P<\/jats:italic> &amp;gt; 0.05). Significant differences in HRV indices were observed across groups, particularly in group G (patients with anxiety, depression and sleep disorders), which showed decreased HRV parameters except LF\/HF, and group H (control group), which showed increased parameters, also except LF\/HF (<jats:italic>P<\/jats:italic> &amp;lt; 0.01). Anxiety was an independent risk factor for reduced SDNN, SDANN, and LF (<jats:italic>P<\/jats:italic> \u2264 0.01), and increased LF\/HF ratio (<jats:italic>P<\/jats:italic> &amp;lt; 0.01). Depression was linked to decreased SDNN, RMSSD, PNN50, and HF (<jats:italic>P<\/jats:italic> &amp;lt; 0.05). Sleep disorders independently predicted reduced PNN50 and SDANN (<jats:italic>P<\/jats:italic> &amp;lt; 0.01).<\/jats:p><\/jats:sec><jats:sec><jats:title>Conclusion<\/jats:title><jats:p>HRV indices of individuals with varying emotional states and sleep disorders exhibited varying degrees of decrease. Anxiety, depression, and sleep disorders presented a superimposed effect on HRV. SDNN, SDANN, RMSSD, PNN50, HF and LF of HRV are of great reference value in the diagnosis of emotional and sleep disorders. For elderly patients experiencing cognitive impairment, HRV is anticipated to serve as a convenient and effective tool for assessing mood and sleep disorders.<\/jats:p><\/jats:sec>","DOI":"10.3389\/fpsyt.2025.1485183","type":"journal-article","created":{"date-parts":[[2025,1,23]],"date-time":"2025-01-23T06:58:30Z","timestamp":1737615510000},"update-policy":"https:\/\/doi.org\/10.3389\/crossmark-policy","source":"Crossref","is-referenced-by-count":15,"title":["Heart rate variability, a potential assessment tool for identifying anxiety, depression, and sleep disorders in elderly 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