Association of smart elderly care and quality of life among older adults: the mediating role of social support.

BACKGROUND: In the current context of ageing, the field of smart elderly care has gradually developed, contributing to the promotion of health among older adults. While the positive impact on health has been established, there is a scarcity of research examining its impact on the quality of life (QoL). This study aims to investigate the mediating role of social support in the relationship between smart elderly care and QoL among older adults. METHODS: A total of 1313 older adults from Zhejiang Province, China, participated in the study. Questionnaires were used to collect data on participants' basic demographic information, smart elderly care, social support, and QoL. The descriptive analyses of the demographic characteristics and correlation analyses of the three variables were calculated. Indirect effects were tested using bootstrapped confidence intervals (CI). RESULTS: The analysis revealed a positive association between smart elderly care and social support (ß = 0.42, p < 0.01), as well as a positive correlation between social support and QoL (ß = 0.65, p < 0.01). Notably, social support emerged as an important independent mediator (effect size = 0.28, 95% bootstrap CI 0.24 to 0.32) in the relationship between smart elderly care and QoL. CONCLUSIONS: The results of this study underscore the importance of promoting the utilization of smart elderly care and improving multi-faceted social support for older adults, as these factors positively contribute to the overall QoL.

Association between incorrect postures and curve magnitude of adolescent idiopathic scoliosis in china.

BACKGROUND: Despite advancements in school scoliosis screening (SSS), there are still no effective indicators to estimate the severity of spinal curvature. We aim to investigate the association between incorrect postures and curve magnitude of adolescent idiopathic scoliosis (AIS) among Chinese adolescents. METHODS: In this SSS program, we examined the incorrect posture, Adam's forward bending test (FBT) results, and angle of trunk rotation (ATR) in adolescents. Those with suspected scoliosis were referred for a standing anteroposterior whole-spine radiography as outpatients. The radiographic data of 426 students with lateral Cobb angles were collected from 2016 to 2022 and the associations were studied using logistic regression (LR) models and receiver operating characteristic (ROC) curves. RESULTS: Univariate LR revealed that female gender [odds ratio (OR) = 2.92, 95% confidence interval (CI) 1.67-5.09, P < 0.001], age 16-19y (OR = 2.83, 95%CI 1.10-7.28, P = 0.031), right shoulder height (OR = 2.15, 95%CI 1.23-3.75, P = 0.007), right scapula tilt (OR = 2.03, 95%CI 1.18-3.50, P = 0.010), right rib hump (OR = 1.88, 95%CI 1.23-2.85, P = 0.003), right thoracic rotation ≥ 5° (OR = 2.14, 95%CI 1.43-3.20, P < 0.001), and left thoracolumbar kyphosis (OR = 3.79, 95%CI 1.06-13.56, P = 0.041) were all significantly associated with the severity of the curve magnitude. Multivariate LR showed that female gender [adjusted OR (AOR) = 3.23, 95%CI 1.81-5.73, P < 0.001], those aged 16-19y (AOR = 5.08, 95%CI 1.86-13.91, P = 0.002), and with a right rib hump (AOR = 1.72, 95%CI 1.11-2.64, P = 0.015) presented with a higher risk of severe curve magnitude than men, those aged 7-12y, and without a rib hump, respectively. ROC curves further proved that sex, age, shoulder-height difference, scapula tilt, flat back, rib hump, angle of thoracic rotation were the risk predictors for curve magnitude. CONCLUSION: Incorrect posture and ATR, especially the right rib hump, were significantly associated with the curve magnitude of AIS. Early screening for incorrect postures and ATR could be an effective and economical strategy to predict the severity of AIS through SSS in Chinese adolescents.

Comparative mathematical modeling of causal association between metal exposure and development of chronic kidney disease.

Background: Previous studies have identified several genetic and environmental risk factors for chronic kidney disease (CKD). However, little is known about the relationship between serum metals and CKD risk. Methods: We investigated associations between serum metals levels and CKD risk among 100 medical examiners and 443 CKD patients in the medical center of the First Hospital Affiliated to China Medical University. Serum metal concentrations were measured using inductively coupled plasma mass spectrometry (ICP-MS). We analyzed factors influencing CKD, including abnormalities in Creatine and Cystatin C, using univariate and multiple analysis such as Lasso and Logistic regression. Metal levels among CKD patients at different stages were also explored. The study utilized machine learning and Bayesian Kernel Machine Regression (BKMR) to assess associations and predict CKD risk based on serum metals. A chained mediation model was applied to investigate how interventions with different heavy metals influence renal function indicators (creatinine and cystatin C) and their impact on diagnosing and treating renal impairment. Results: Serum potassium (K), sodium (Na), and calcium (Ca) showed positive trends with CKD, while selenium (Se) and molybdenum (Mo) showed negative trends. Metal mixtures had a significant negative effect on CKD when concentrations were all from 30th to 45th percentiles compared to the median, but the opposite was observed for the 55th to 60th percentiles. For example, a change in serum K concentration from the 25th to the 75th percentile was associated with a significant increase in CKD risk of 5.15(1.77,8.53), 13.62(8.91,18.33) and 31.81(14.03,49.58) when other metals were fixed at the 25th, 50th and 75th percentiles, respectively. Conclusions: Cumulative metal exposures, especially double-exposure to serum K and Se may impact CKD risk. Machine learning methods validated the external relevance of the metal factors. Our study highlights the importance of employing diverse methodologies to evaluate health effects of metal mixtures.