No previous review has formally modelled the decline in IHD risk following quitting smoking. From PubMed searches and other sources we identified 15 prospective and eight case-control studies that compared IHD risk in current smokers, never smokers, and quitters by time period of quit, some studies providing separate blocks of results by sex, age or amount smoked. For each of 41 independent blocks, we estimated, using the negative exponential model, the time, H, when the excess risk reduced to half that caused by smoking. Goodness-of-fit to the model was adequate for 35 blocks, others showing a non-monotonic pattern of decline following quitting, with a variable pattern of misfit. After omitting one block with a current smoker RR 1.0, the combined H estimate was 4.40 (95% CI 3.26-5.95) years. There was considerable heterogeneity, H being <2years for 10 blocks and >10years for 12. H increased (p<0.001) with mean age at study start, but not clearly with other factors. Sensitivity analyses allowing for reverse causation, or varying assumed midpoint times for the final open-ended quitting period little affected goodness-of-fit of the combined estimate. The US Surgeon-General's view that excess risk approximately halves after a year's abstinence seems over-optimistic.
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http://dx.doi.org/10.1016/j.yrtph.2012.06.009 | DOI Listing |
Biomolecules
January 2025
Department of Medicine, School of Medicine, Nazarbayev University, Astana 010000, Kazakhstan.
Chronic kidney disease (CKD) is a progressive condition characterized by declining renal function, with limited biomarkers to predict its progression. The early identification of prognostic biomarkers is crucial for improving patient care and therapeutic strategies. This follow-up study investigated urinary proteomics and clinical outcomes in 18 CKD patients (stages 1-3) and 15 healthy controls using liquid chromatography-mass spectrometry and Mascot-SwissProt for protein identification.
View Article and Find Full Text PDFJ Environ Radioact
January 2025
Department of Soil and Environment, Swedish University of Agricultural Sciences, Box 7070, 750 07, Uppsala, Sweden.
In this study, the long-term transfer of Cs from soil to grass on Swedish farms and fields, heavily contaminated after the 1986 radioactive fallout, was investigated. The study spans over 8-14 years, beginning in June 1986, and covers various soil types and agricultural practices. The transfer of Cs from soil to grass was highly variable, with transfer factors ranging from 1.
View Article and Find Full Text PDFHealth Expect
February 2025
Population Health Sciences Institute, Faculty of Medical Sciences, Newcastle University, Newcastle Upon Tyne, UK.
Objective: Public Involvement (PI) in applied health and social care research has grown exponentially in the UK. This review aims to synthesise published UK evidence that evaluates the process and/or outcome(s) of PI in applied health and social care research to identify key contextual factors, effective strategies, outcomes and public partner experiences underpinning meaningful PI in research.
Methods: Following a pre-registered protocol, we systematically searched four databases and two key journals for studies conducted within the UK between January 2006 and July 2024.
Sci Rep
January 2025
Leiden University, Leiden, Netherlands.
This paper introduces a novel approach for identifying dynamic triadic transformation processes, applied to five networks: three undirected and two directed. Our method significantly enhances the prediction accuracy of network ties. While balance theory offers insights into evolving patterns of triadic structures, its effects on overall network dynamics remain underexplored.
View Article and Find Full Text PDFSoc Networks
January 2024
Departments of Sociology, Statistics, Computer Science, and EECS, University of California, Irvine, CA, United States.
The exponential-family random graph models (ERGMs) have emerged as an important framework for modeling social networks for a wide variety of relational types. ERGMs for valued networks are less well-developed than their unvalued counterparts, and pose particular computational challenges. Network data with edge values on the non-negative integers (count-valued networks) is an important such case, with examples ranging from the magnitude of migration and trade flows between places to the frequency of interactions and encounters between individuals.
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