Low cardiorespiratory fitness (CRF) and obesity are independent risk factors for dyslipidemia. We investigated the synergistic effects of CRF and obesity on the incidence of dyslipidemia among Japanese women. Of 7627 participants, 927 normolipidemic Japanese women completed a submaximal exercise test, medical examination, and a questionnaire on smoking and alcohol drinking. The incidence of dyslipidemia was defined as having at least one of the following: high-density lipoprotein cholesterol < 40 mg/dL, low-density lipoprotein cholesterol ≥ 140 mg/dL, fasting triglyceride ≥ 150 mg/dL, or physician-diagnosed dyslipidemia. Multivariable hazard ratios (HRs) and 95% confidence intervals (CI) were calculated using a Cox proportional hazard regression model. During the follow-up period of ≤16 years (median 1 year), 196 (21.1%) women developed dyslipidemia. Compared with those in the body mass index (BMI)-specific (< or ≥25.0 kg/m) lowest CRF tertile, the multivariable HRs for dyslipidemia in the highest CRF tertile were 1.36 (95% CI, 0.75-2.48) for women with BMI ≥ 25 kg/m and 0.70 (95% CI, 0.45-1.09) for those with BMI < 25 kg/m ( < 0.01 for interaction). These results suggest that CRF and BMI are interdependent and, together, they affect the incidence of dyslipidemia among Japanese women. CRF is inversely related to a lower incidence of dyslipidemia with low BMI.
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http://dx.doi.org/10.3390/ijerph16234647 | DOI Listing |
Eur Stroke J
January 2025
Department of Brain Repair and Rehabilitation, Stroke Research Centre, UCL Queen Square Institute of Neurology, London, UK.
Introduction: Stroke incidence in younger adults is increasing worldwide yet few comprehensive studies exist from a UK population. We investigated the risk factors, mechanisms, functional outcome and stroke recurrence rate in a cohort of young adults with stroke.
Patients And Methods: We included consecutive patients (<55 years) with ischaemic stroke or intracerebral haemorrhage (ICH) admitted to the University College London Hospitals Hyperacute Stroke Unit between 2017 and 2020.
Ann Surg
January 2025
Hubei Key Laboratory of Ischemic Cardiovascular Disease, Yichang, China.
Objective: The aim of this study is to explore the risk profiles associated with Abdominal aortic aneurysm (AAA) incidence in both the general population and diverse subpopulations.
Summary Background Data: AAA is a life-threatening arterial disease, and there is limited understanding of its etiological spectrum across the age, sex, and genetic risk subgroups, making early prevention efforts more complicated.
Methods: This study encompassed a sample size of 364399 participants from the UK.
Lipids Health Dis
January 2025
School of Health Service Management, Anhui Medical University, 81 Meishan Road, Shushan District, Hefei, Anhui, 230032, China.
Background: Primary healthcare (PHC) plays a key role in hyperlipidemia (HL) management yet lacks adequate monitoring and feedback. This study aims at identifying pragmatic measures out from routinely collected electronic records to enable automatic monitoring and inform continuous optimization of HL-management at PHC settings.
Methods: The study used randomly selected electronic records of PHC (from the province-wide data center of Anhui-province, China) as the main data source and generated both procedure-based and encounter-based measures for assessing HL-management.
Lipids Health Dis
January 2025
Department of Medical Biosciences, Clinical Chemistry, Umeå University, Building 6M 2:Nd Floor, 901 85, Umeå, Sweden.
Background: The ABO blood group system has shown an association with cardiovascular disease. The susceptibility to CVD is proposed to be partly mediated by dyslipidaemia in non-O individuals. Previous studies are scarce for the RhD blood group, but we recently showed that RhD - young individuals are associated with subclinical atherosclerosis.
View Article and Find Full Text PDFBMC Public Health
January 2025
Eli Lilly and Company, Indianapolis, IN, 46285, USA.
Background: Despite the substantial burden of obesity in the United States (US), data on the comprehensive range of comorbidities in different age groups is limited. This study assessed the prevalence of various comorbidities among people diagnosed with obesity (as per ICD-10 diagnosis code) across age cohorts and compared how they differ from people without obesity.
Methods: This cross-sectional study analyzed individuals from all four regions (Midwest, Northeast, South, and West) of the US who had continuous insurance coverage from 2018 to 2020, using a large health insurance claims database (Merative™ MarketScan).
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