To assess the effect of health check-ups on health among the elderly Chinese. The first dataset was panel data extracted from the 2011, 2014, and 2018 waves of the Chinese Longitudinal Health Longevity Survey (CLHLS). The second dataset was cross-sectional data come from CLHLS 2018 linked with the lagged term of health check-ups in CLHLS 2011. Health check-ups were measured by a binary variable annual health check-up (AHC). Health was assessed by a binary variable self-rated health (SRH). A coarsened exact matching method and individual fixed-effects models, as well as logistic regressions were employed. AHC attendance among the elderly increased from 2011 to 2018, with higher utilization of AHC also detected in the rural group. AHC had positive effects on SRH among rural respondents (short-term effect: OR = 1.567, < 0.05; long-term effect: OR = 3.385, < 0.001). This study highlights a higher utilization of AHC in rural area, and the effectiveness of AHC in SRH improvement among rural participants. It indicates enhanced access to public healthcare services in rural area and underlying implications of health check-ups for reducing urban-rural health inequalities.
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http://dx.doi.org/10.3389/ijph.2022.1604597 | DOI Listing |
J Inflamm Res
January 2025
Department of Vascular Surgery, Nanjing Drum Tower Hospital, Affiliated Hospital of Medical School, Nanjing University, Nanjing, People's Republic of China.
Purpose: Stanford Type B Aortic Dissection (TBAD), a critical aortic disease, has exhibited stable mortality rates over the past decade. However, diagnostic approaches for TBAD during routine health check-ups are currently lacking. This study focused on developing a model to improve the diagnosis in a population.
View Article and Find Full Text PDFJ Clin Med
December 2024
Division of Endocrinology and Metabolism, Department of Internal Medicine, Yeouido St. Mary's Hospital, College of Medicine, The Catholic University of Korea, 10, 63-ro, Yeongdeungpo-gu, Seoul 07345, Republic of Korea.
This national population-based study aimed to assess the cumulative burden of non-alcoholic fatty liver disease (NAFLD) measured via the fatty liver index (FLI) and its association with kidney cancer risk in young men aged 20-39. : Using the Korean National Health Insurance Service database, we examined a cohort of 1,007,906 men (age 20-39) who underwent four consecutive annual check-ups from 2009 to 2012. The FLI, calculated from body mass index values, waist circumference, triglyceride levels, and gamma-glutamyl transferase levels, was used to quantify the cumulative burden of NAFLD (FLI ≥ 60).
View Article and Find Full Text PDFSci Rep
January 2025
Department of Rehabilitation Medicine, Seoul National University Hospital, 101 Daehak-ro, Jongno-gu, Seoul, Republic of Korea.
Health-related behavioral changes may occur following traumatic brain injury. We focused on understanding the impact of mild traumatic brain injury (TBI) on health-related behaviors and identifying factors associated with such changes. We utilized health check-up records from the Korean National Health Insurance Service database spanning January 1, 2009, to December 31, 2017.
View Article and Find Full Text PDFBMC Public Health
January 2025
Department of Public Health, Faculty of Health Sciences, University of Venda, University Rd, Thohoyandou, South Africa.
Background: The reasons for men not to seek healthcare seem similar across the world. They avoid going for regular medical check-ups, and preventive care and often disregard symptoms or delay seeking medical attention when sick, in pain, or even when their lives are in danger.
Methods: This study sought to explore the views of men on factors contributing to poor health-seeking behavior among men in Mopani, Vhembe, and Capricorn district municipalities in Limpopo Province.
Gut Liver
January 2025
Department of Internal Medicine and Liver Research Institute, Seoul National University Hospital, Seoul National University College of Medicine, Seoul, Korea.
Background/aims: The incidence of steatotic liver disease (SLD) is increasing across all age groups as the incidence of obesity increases worldwide. The existing noninvasive prediction models for SLD require laboratory tests or imaging and perform poorly in the early diagnosis of infrequently screened populations such as young adults and individuals with healthcare disparities. We developed a machine learning-based point-of-care prediction model for SLD that is readily available to the broader population with the aim of facilitating early detection and timely intervention and ultimately reducing the burden of SLD.
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