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All Journal SRIWIJAYA JOURNAL OF MEDICINE Journal of Applied Data Sciences
Alexander Halim Santoso
Department of Nutrition, Faculty of Medicine, Universitas Tarumanagara
Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Health Professions Immunology & microbiology Medicine & Pharmacology Neuroscience Public Health

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The Role of Blood Pressure, Diabetes Panel, Vitamin D, and Albumin in Sleep Quality Among the Elderly Population Anastasia Ratnawati Biromo; Paskalis Andrew Gunawan; Alexander Halim Santoso; Bryan Anna Wijaya; Raden Seliwat Agung Aditya; Anthon Eka Prayoga Khoto
Sriwijaya Journal of Medicine Vol. 9 No. 1 (2026): Vol 9, No 1, 2026
Publisher : Fakultas Kedokteran Universitas Sriwijaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32539/sjm.v9i1.369

Abstract

Sleep disturbances are common among the elderly, influenced by multiple physiological factors, including blood pressure regulation, metabolic markers, nutritional status, and inflammation. Poor sleep quality has been linked to cardiovascular diseases, cognitive decline, and reduced overall well-being. Understanding the relationship between blood pressure, diabetes markers, vitamin D, and albumin levels with sleep quality may provide insights into potential interventions to improve sleep health in older adults. This study aims to analyze the correlation between blood pressure, diabetes panel (fasting blood glucose, fasting insulin, and HbA1c), vitamin D, and albumin levels with sleep quality in the elderly population. This Cross-sectional study was conducted at Bina Bhakti Nursing Home in 2024 to 58 elderly participants selected through total sampling. Sleep quality was assessed with the Pittsburgh Sleep Quality Index (PSQI), while physiological parameters were measured using validated clinical and laboratory methods. Data were analyzed using Spearman’s Rho test to determine correlations between these factors and sleep disturbances. This study found that diastolic blood pressure and HbA1c level showed weak correlations with sleep quality. Low diastolic blood pressure and poor glycemic control demonstrated weak but statistically significant correlations with sleep quality among older adults. These findings indicate that certain physiological and metabolic factors, particularly diastolic blood pressure and HbA1c, may be associated with variations in sleep regulation among the elderly. Future research should explore targeted interventions, such as blood pressure management and metabolic regulation, that may improve sleep quality and overall health in the aging population.  
Remote Photoplethysmography-Based HbA1c Estimation for Community Screening of Type 2 Diabetes Mellitus: Screening Tool or Diagnostic Alternative? Ernawati Ernawati; Yohanes Firmansyah; Alexander Halim Santoso; David Wongso; Diana Dinali; Muhammad Fikri Dzakwan; Bryan Anna Wijaya; Sri Tiatri; Putu Tommy Yudha Sumatera Suyasa; Meiske Yunithree Suparman
Journal of Applied Data Sciences Vol 7, No 4: December 2026
Publisher : Bright Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47738/jads.v7i4.1433

Abstract

Type 2 diabetes mellitus (T2DM) remains a major global health burden, with a high proportion of undiagnosed cases, particularly in community settings with limited access to laboratory testing. Remote photoplethysmography (rPPG) has emerged as a non-invasive, camera-based technology with potential for scalable screening. This study aimed to evaluate the agreement, diagnostic performance, and clinical role of rPPG-derived HbA1c as a screening tool or diagnostic alternative for T2DM. A cross-sectional diagnostic validation study was conducted among adults in a community setting in Semanan Subdistrict, Jakarta. Participants underwent non-contact facial scanning using an rPPG system alongside standard laboratory measurements of HbA1c and blood glucose. Agreement was assessed using Bland–Altman analysis and Cohen’s Kappa. Diagnostic performance was evaluated using sensitivity, specificity, predictive values, and receiver operating characteristic (ROC) curve analysis. rPPG-derived HbA1c showed a significant mean difference compared with laboratory measurements (0.63%; p 0.001; 95% CI: 0.34–0.93), indicating systematic bias. Categorical agreement was poor (κ = 0.029; p = 0.403). In screening analysis, sensitivity ranged from 65.38% to 97.37%, while specificity ranged from 8.91% to 59.55%, with consistently high negative predictive values (≥82%). ROC analysis demonstrated an AUC of 0.668 (p = 0.008) for diabetes and 0.711 (p 0.001) for prediabetes, indicating modest to acceptable discriminative ability. rPPG-based HbA1c estimation lacks sufficient agreement for diagnostic use. However, its relatively high sensitivity and scalability suggest that it may warrant further evaluation as a non-invasive screening tool for early detection and population-level risk stratification within mobile health settings.
Co-Authors Anastasia Ratnawati Biromo Anthon Eka Prayoga Khoto Bryan Anna Wijaya Bryan Anna Wijaya David Wongso Diana Dinali Ernawati Ernawati Meiske Yunithree Suparman Muhammad Fikri Dzakwan Paskalis Andrew Gunawan Putu Tommy Yudha Sumatera Suyasa Raden Seliwat Agung Aditya Sri Tiatri Yohanes Firmansyah