Comparative research on health and health inequalities has recently started to establish a welfare regime perspective. The objective of this study was to determine whether different welfare regimes are associated with health and health inequalities among adolescents. Data were collected from the 'Health Behaviour in School-aged Children' study in 2006, including 11- to 15-year-old students from 32 countries (N = 141,091). Prevalence rates and multilevel logistic regression models were calculated for self-rated health (SRH) and health complaints. The results show that between 4 per cent and 7 per cent of the variation in both health outcomes is attributable to differences between countries. Compared to the Scandinavian regime, the Southern regime had lower odds ratios for SRH, while for health complaints the Southern and Eastern regime showed high odds ratios. The association between subjective health and welfare regime was largely unaffected by adjusting for individual socioeconomic position. After adjustment for the welfare regime typology, the country-level variations were reduced to 4.6 per cent for SRH and to 2.9 per cent for health complaints. Regarding cross-level interaction effects between welfare regimes and socioeconomic position, no clear regime-specific pattern was found. Consistent with research on adults this study shows that welfare regimes are important in explaining variations in adolescent health across countries.
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http://dx.doi.org/10.1111/j.1467-9566.2011.01433.x | DOI Listing |
Sci Rep
December 2024
Department of Medical Microbiology, Radboudumc, Nijmegen, The Netherlands.
The aetiology of Alzheimer's disease (AD) and Parkinson's disease (PD) are unknown and tend to manifest at a late stage in life; even though these neurodegenerative diseases are caused by different affected proteins, they are both characterized by neuroinflammation. Links between bacterial and viral infection and AD/PD has been suggested in several studies, however, few have attempted to establish a link between fungal infection and AD/PD. In this study we adopted a nanopore-based sequencing approach to characterise the presence or absence of fungal genera in both human brain tissue and cerebrospinal fluid (CSF).
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December 2024
School of Physical Education, Southwest Petroleum University, Chengdu, 610500, China.
Stroke is one of the leading causes of death in developing countries, and China bears the largest global burden of stroke. This study aims to investigate the relationship between different dimensions of physical activity levels and stroke risk using a nationally representative database. We performed a cross-sectional analysis using data from the China Health and Retirement Longitudinal Study (CHARLS) 2020.
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December 2024
KAUST Center of Excellence for Smart Health (KCSH), King Abdullah University of Science and Technology, Thuwal, 23955, Saudi Arabia.
Analyzing microbial samples remains computationally challenging due to their diversity and complexity. The lack of robust de novo protein function prediction methods exacerbates the difficulty in deriving functional insights from these samples. Traditional prediction methods, dependent on homology and sequence similarity, often fail to predict functions for novel proteins and proteins without known homologs.
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December 2024
Department of Diagnostic Radiology, Dalhousie University, Halifax, Canada.
The goal of this study was to determine how radiologists' rating of image quality when using 0.5T Magnetic Resonance Imaging (MRI) compares to Computed Tomography (CT) for visualization of pathology and evaluation of specific anatomic regions within the paranasal sinuses. 42 patients with clinical CT scans opted to have a 0.
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December 2024
School of Mechanical Engineering, Liaoning Engineering Vocational College, Tieling, 112008, Liaoning, People's Republic of China.
The paper proposes a multi-rigid-body system state identification method based on self-healing model in order to improve the accuracy and reliability of CNC machine tools. Firstly, considering the influence of the joint surface, the Lagrange method is used to establish the mechanical model of the multi-rigid-body system. We input acceleration information and use the second-order modulation function to complete the online real-time identification of the joint surface parameters, thereby establishing the self-healing mechanical model of the multi-rigid-body system.
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