This study investigated the multidimensional clinical and health data of 874 elderly diabetic patients in northern Sichuan to support the development of a localized, multidimensional health assessment system for this population. The patients exhibited extremely suboptimal blood glucose control, widespread dyslipidemia, and high susceptibility to diabetic macrovascular complications. Over half of the patients suffered from renal impairment and elevated inflammatory and metabolic markers, indicating prevalent renal damage and chronic metabolic disorders. In terms of non-metabolic health conditions, skin abnormalities and sleep disorders were prevalent, whereas psychological abnormalities were rare. This study summarizes the unique demographic, biochemical, and multidimensional health characteristics of elderly diabetic patients in northern Sichuan, provides a reliable basis for establishing a targeted health assessment system to facilitate precise clinical intervention and standardized health management.

Biao Wang, Li Jiang, Yuanting Li, Xu Jia. Analysis of Clinical Characteristics and Health Status of Elderly Diabetic Patients in Northern Sichuan. Academic Journal of Medicine & Health Sciences (2026), Vol. 7, Issue 3: 58-65. https://doi.org/10.25236/AJMHS.2026.070308.

[1] Harreiter J, Roden M. Diabetes mellitus: definition, classification, diagnosis, screening and prevention (Update 2023)[J]. Wiener Klinische Wochenschrift, 2023,135(Suppl 1):7.

[2] Bergman M, Tuomilehto J. International Diabetes Federation Position Statement on the 1-hour post-load plasma glucose for the diagnosis of intermediate hyperglycaemia and type 2 diabetes[J]. Diabetes research and clinical practice, 2024,210:111636.

[3] Golmohammadi M, Attari V E, Salimi Y, et al. The effect of MIND diet on sleep status, mental health, and serum level of BDNF in overweight/obese diabetic women with insomnia: a randomized controlled trial[J]. Scientific reports, 2025,15(1):8214-8237.

[4] Alzahrani O, Fletcher J P, Hitos K. Quality of life and mental health measurements among patients with type 2 diabetes mellitus: a systematic review[J]. Health and quality of life outcomes, 2023,21(1):22-27.

[5] Yildirim D, Aras D. Evaluation of Complications, Peripheral Neuropathic Pain, and Sleep Quality in Patients With Diabetes Mellitus[J]. Brain and behavior, 2025,15(6):e70605.

[6] Sun XR, Sun JH, Chen LF, et al. Characteristics of health demands and health management strategies for elderly population[J]. Chin J Gerontol, 2018, 38(21): 5364-5367.

[7] Li M, Pan Q, Guo LX. Interpretation of Chinese guidelines for the diagnosis and treatment of elderly diabetes (2024 edition)[J]. Chin J Clin Healthc, 2024, 27(5): 577-581. 

[8] Yi J, Lin J, Feng Q, et al. Accurate screening of patients with diabetes based on physical examination: pancreas imaging features from chest CT and laboratory data[J]. Frontiers in endocrinology (Lausanne), 2025,16:1698247.

[9] Mokhtar S, Abbass J. Development and Evaluation of Machine Learning Models for Diabetes Risk Prediction Using BRFSS 2023 Data[C]. 2025 International Conference on Decision Aid Sciences and Applications (DASA). IEEE, 2025.

[10] Wu B, Niu Z, Hu F. Study on Risk Factors of Peripheral Neuropathy in Type 2 Diabetes Mellitus and Establishment of Prediction Model[J]. Diabetes Metab J, 2021,45(4):526-538.

[11] Eckert A J, Fritsche A P, Icks A P, et al. Common procedures and conditions leading to inpatient hospital admissions in adults with and without diabetes from 2015 to 2019 in Germany[J]. Wiener Klinische Wochenschrift, 2023,135(13-14):325-335.

[12] Hong J W, Noh J H, Kim D. Association between Alcohol Intake and Hemoglobin A1c in the Korean Adults: The 2011-2013 Korea National Health and Nutrition Examination Survey[J]. PloS one, 2016, 11(11):e167210.

[13] Paz-Graniel I, Kose J, Duquenne P, et al. Alcohol, Smoking, and Their Synergy as Risk Factors for Incident Type 2 Diabetes[J]. American journal of preventive medicine, 2025,69(5):108011.

[14] Zhang A, Wang J, Wan X, et al. Community-Based Intelligent Blood Glucose Management for Older Adults With Type 2 Diabetes Based on the Health Belief Model: Randomized Controlled Trial[J]. JMIR mHealth and uHealth, 2025,13:e60227.

[15] Karlsson S A, Franzén S, Svensson A, et al. Prescription of lipid-lowering medications for patients with type 2 diabetes mellitus and risk-associated LDL cholesterol: a nationwide study of guideline adherence from the Swedish National Diabetes Register[J]. BMC health services research, 2018,18(1):900-910.

[16] Liu J, Yasuno S, Oba K, et al. Long-term effects of antihypertensive therapy on cardiovascular events and new-onset diabetes mellitus in high-risk hypertensive patients in Japan[J]. Journal of hypertension, 2018,36(9):1921-1928.

[17] Basile J N. Antihypertensive therapy, new-onset diabetes, and cardiovascular disease[J]. International journal of clinical practice (Esher), 2009,63(4):656-666.

[18] Ma X, Liu R, Xi X, et al. Global burden of chronic kidney disease due to diabetes mellitus, 1990-2021, and projections to 2050[J]. Frontiers in endocrinology (Lausanne), 2025,16:1513008.

[19] Takamatsu K. Renal status in elderly patients with type 2 diabetes[J]. Clinical and experimental nephrology, 2020,24(1):53-62.

[20] Alvis B D, Hughes C G. Physiology Considerations in Geriatric Patients[J]. Anesthesiology clinics, 2015,33(3):447-456.

[21] Matwiejuk M, Myśliwiec H, Mikłosz A, et al. Common Skin Diseases and Metabolic Syndrome: A Proinflammatory Chemokine Perspective[J]. Metabolites, 2026,16(4):253.

[22] Schipper S B J, Van Veen M M, Elders P J M, et al. Sleep disorders in people with type 2 diabetes and associated health outcomes: a review of the literature[J]. Diabetologia, 2021,64(11):2367-2377.

[23] Liu Y, Qiu J, Li S, et al. Exploring psychological experiences of fear of complications among hospitalised people with type 2 diabetes in China: a qualitative phenomenological study[J]. BMJ open, 2026,16(5):e117522.