Background: Cardiovascular diseases (CVDs) are prevalent in older people, but few studies focus on developmental patterns in CVD medication directly after transition to statutory retirement. We thus aimed to identify trajectories of CVD medication after retirement, and their sociodemographic, work and health-related determinants.
Methods: We used complete register data of former employees of the City of Helsinki, Finland. All who reached their statutory retirement in 2000-2013, with five-year follow-up data (n = 6,505, 73% women), were included. Trajectories of CVD medication were identified with group-based trajectory modelling using data from Finnish Social Insurance Institution's reimbursement register. Sociodemographic, work and health-related determinants of trajectory group membership were analysed using multinomial logistic regression.
Results: Six trajectories of CVD medication were distinguished: "constant low" (35%), "late increase" (6%), "early increase" (5%), "constant high" (39%), "high and decreasing " (8%), and "low and decreasing" (7%). The majority (74%) of the retirees fell into the "constant low" and "constant high" categories. Lower occupational class and increased pre-retirement sickness absence were associated with the "constant high" trajectory. Further, those with lower educational attainment were more prone to be in the "early increase" trajectory.
Conclusions: Individuals in lower socioeconomic positions or with a higher number of pre-retirement sickness absence may be considered at higher risk and might benefit from early interventions, e.g. lifestyle interventions and interventions targeting working conditions, or more frequent monitoring.
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http://dx.doi.org/10.1186/s12877-023-04272-8 | DOI Listing |
BMC Med Imaging
December 2024
Department of Radiology, Cardiothoracic Imaging, University of Utah, 30 N 1900 E #1A71, Salt Lake City, Utah, 84132, USA.
Background: Lung cancer is a leading cause of cancer-related mortality worldwide, with non-small cell lung cancer (NSCLC) comprising 85% of cases. Due to the lack of early clinical signs, metastasis often occurs before diagnosis, impacting treatment and prognosis. Cardiovascular disease (CVD) is a common comorbidity in lung cancer patients, with shared risk factors exacerbating outcomes.
View Article and Find Full Text PDFLipids Health Dis
December 2024
Department of Oncology, Liyuan Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei, P.R. China.
Background: Cardiometabolic index (CMI) is a comprehensive clinical parameter which integrates overweight and abnormal lipid metabolism. However, its relationship with all-cause, cardiovascular disease (CVD), and cancer mortality is still obscure. Thus, a large-scale cohort study was conducted to illustrate the causal relation between CMI and CVD, cancer, and all-cause mortality among the common American population.
View Article and Find Full Text PDFSci Rep
December 2024
General Practice Medical Center, West China Hospital, General Practice Ward/International Medical Center Ward, National Clinical Research Center for Geriatrics,, Sichuan University, Chengdu, Sichuan, China.
The triglyceride-glucose (TyG) index and the Atherogenic Index of Plasma (AIP) are both predictors of cardiovascular diseases (CVD). However, their combined and individual contributions to CVD risk are not well understood. This study evaluate the joint and individual associations of the TyG index and AIP with CVD events in middle-aged and older Chinese adults.
View Article and Find Full Text PDFSci Rep
December 2024
The Key Laboratory for Computer Systems of State Ethnic Affairs Commission, School of Computer and Artificial Intelligence, Southwest Minzu University, Chengdu, 610041, China.
Coronary artery disease represents a formidable health threat to middle-aged and elderly populations worldwide. This research introduces an advanced BP neural network algorithm, EPSOSA-BP, which integrates particle swarm optimization, simulated annealing, and a particle elimination mechanism to elevate the precision of heart disease prediction models. To address prior limitations in feature selection, the study employs single-hot encoding and Principal Component Analysis, thereby enhancing the model's feature learning capability.
View Article and Find Full Text PDFBMJ Open
December 2024
Nutrition and Food Engineering, Daffodil International University, Dhaka, Bangladesh.
Objective: The aim of this study is to evaluate diet quality and other associated factors with dyslipidaemia in cardiovascular disease (CVD) patients in Bangladesh.
Design: The study employed a cross-sectional design.
Setting: Data from medical records, dietary intake and socioeconomic factors were collected from January to October 2022 at the National Institute of Cardiovascular Disease, Dhaka, and Noakhali Sadar Hospital.
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