This study aimed to investigate the spatial distribution and patterns of multimorbidity among the elderly in China. Data on the occurrence of 14 chronic diseases were collected for 9710 elderly participants in the 2015 waves of the China Health and Retirement Longitudinal Study (CHARLS). Web graph, Apriori algorithm, age-adjusted Charlson comorbidity index (AAC), and Spatial autocorrelation were used to perform the multimorbidity analysis. The multimorbidity prevalence rate was estimated as 49.64% in the elderly in China. Three major multimorbidity patterns were identified: [Asthma/Chronic lungs diseases]: (Support (S) = 6.17%, Confidence (C) = 63.77%, Lift (L) = 5.15); [Asthma, Arthritis, or rheumatism/ Chronic lungs diseases]: (S = 3.12%, C = 64.03%, L = 5.17); [Dyslipidemia, Hypertension, Arthritis or rheumatism/Heart attack]: (S = 3.96%, C = 51.56, L = 2.69). Results of the AAC analysis showed that the more chronic diseases an elderly has, the lower is the 10-year survival rate (P < 0.001). Global spatial autocorrelation showed a positive spatial correlation distribution for the prevalence of the third multimorbidity pattern in China (P = 0.032). The status of chronic diseases and multimorbidity among the elderly with a spatial correlation is a significant health issue in China.
Download full-text PDF |
Source |
---|---|
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8341534 | PMC |
http://journals.plos.org/plosone/article?id=10.1371/journal.pone.0255908 | PLOS |
Ann Med
December 2025
Department of Clinical Pharmacology, Flinders Medical Centre, Southern Adelaide Local Health Network, Adelaide, Australia.
Background: Most older patients with atrial fibrillation (AF) have comorbidities. However, it is unclear whether specific comorbidity patterns are associated with adverse outcomes. We identified comorbidity patterns and their association with mortality in multimorbid older AF patients with different multidimensional frailty.
View Article and Find Full Text PDFInt Nurs Rev
March 2025
College of Nursing, Keimyung University, Daegu, South Korea.
Aim: This study aimed to estimate the annual cost burden of productivity loss due to sickness presenteeism among hospital nurses in South Korea.
Background: Despite nurses being potentially more vulnerable to presenteeism, few studies have analyzed nurses' productivity losses due to sickness presenteeism.
Methods: This cross-sectional study employed an online survey in January 2023 with 607 nurses working in general/tertiary hospitals in South Korea.
Ann Med
December 2025
Department of Nursing, The Fourth Affiliated Hospital of School of Medicine, and International School of Medicine, International Institutes of Medicine, Zhejiang University, Yiwu, Zhejiang, China.
Introduction: Multimorbidity is increasing globally, emphasizing the need for effective self-management strategies. The Cumulative Complexity Model (CuCoM) offers a unique perspective on understanding self-management based on workload and capacity. This study aims to validate the CuCoM in multimorbid patients and identify tailored predictors of self-management.
View Article and Find Full Text PDFBackground: Much data informing sex differences in atrial fibrillation (AF) comes from Western cohorts. In this analysis, we describe sex differences in Kerala, India, using the Kerala-AF registry-the largest AF registry from the Indian subcontinent.
Methods: Patients aged ≥18 years were recruited from 53 hospitals across Kerala.
J Intellect Dev Disabil
September 2024
School of Nursing and Midwifery, Trinity College Dublin, Dublin, Ireland.
Constipation impacts health-related quality of life with a burden similar to other chronic conditions. This study characterises the prevalence of constipation and its associated factors in older adults with intellectual disability. Data from the Intellectual Disability Supplement of The Irish Longitudinal Study on Ageing was analysed using bivariate and multivariate approaches.
View Article and Find Full Text PDFEnter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!