Background: Smoking worsens the prognosis of patients with coronary heart disease (CHD). Only limited population-based data are available on smoking cessation and its characteristics in people with CHD. We compared smokers with and without CHD. Methods: We analyzed pooled data from nine waves (June 2023-August 2024) of two representative cross-sectional surveys in Germany (DEBRA and OptiCor). We included adults aged 35 years and above who provided information on their smoking behavior and CHD status (n = 11 069; 994 [9%] with CHD). The endpoints included smoking status, tobacco dependence, motivation to quit smoking, and attempts to do so, as well as the use of electronic inhalation products (e-cigarettes, tobacco heaters). Regression models with CHD as an independent variable were adjusted for age, sex, education, and income. Results: People with CHD were less likely to be current smokers (23.8%, 95% confidence interval [21.2; 26.6], versus 29.3% [28.5; 30.2]), but they were more likely to be former smokers (32.2% [29.3; 35.3] versus 18.9% [18.1; 19.6]). Being a smoker with CHD was associated with the use of electronic inhalation products (odds ratio [OR] = 2.53 [1.43; 4.48]), higher motivation to quit smoking (OR = 1.41 [1.02; 1.96]), and greater tobacco dependence (OR = 1.63 [1.05; 2.53]). Among current smokers and those who smoked in the past year, those with CHD were also more likely than those without CHD to have made at least one attempt to quit in the past year (OR = 2.90 [1.98; 4.25]). Conclusion: One-quarter of people with CHD smoke. Despite a greater degree of tobacco depen-dence, they show higher motivation and make more attempts to quit smoking compared with smokers without CHD. As smoking cessation is crucial in this group, healthcare professionals should consistently assess the smoking status of people with CHD and offer them evidence-based support for smoking cessation.
Background: Recent years have seen an increase in reported violent crime involving knives. Valid case numbers of severe stabbing injuries have not been available to date, and the poor state of the evidence hinders consideration of the matter not only on the medical level, but on the political level as well. In this study, we provide the first data on the evolution of case numbers of severe injury from knife crime in Germany. Methods: We retrospectively analyzed data from the trauma registry of the German Society for Trauma Surgery (Deutsche Gesellschaft f & uuml;r Unfallchirurgie, DGU).Additional data from the Academy of Trauma Surgery (Akademie f & uuml;r Unfallchirurgie, AUC) were used for an analysis of geographic distribution. Patients were included if they sustained a documented severe stab injury that was suspected to be due to a violent crime in the period January 2013 to December 2024. The number of hospitals contributing data remained stable over the study period, with only small fluctuations. Results: 291 752 cases of severe injury were registered, of which 3664 (1.28%) involved stabbing in a suspected violent crime. The lowest number of such cases (212) was in 2013, and the highest (382) in 2023; there were 336 cases in 2024. The mean age of the patients was 34.2 +/- 14.3 years; 85.6% were male. Emergency surgery was performed in 72% of cases. Conclusion: The absolute incidence of severe stab injuries of suspected criminal origin (212 to 382 cases per year) is low but on the rise, as is the percentage of such injuries among all severe injuries. Persons who died before reaching a hospital were not included in the data.
Background: The German National Cohort (NAKO Gesundheitsstudie) is a prospective cohort study with 205 053 participants. Its goal is to investigate risk factors for chronic diseases, including cancer. Methods: We describe the methods of ascertaining cancer cases in NAKO (linkage with cancer registries and self-reporting), the incidence and prevalence figures obtained so far, and the ratio of observed to expected (O/E) case numbers. Results: Altogether, 2774 prevalent (diagnosed within the 5 years prior to study enrollment) and 4295 incident (diagnosed up to 5 years after enrollment) cancer cases were identified. Breast, prostate, lung, and colorectal cancers made up 55% of the incident cases. Fewer incident cases were found than would have been expected on the basis of incidence rates in the general population (O/E ratio 0.80, 95% confidence interval [0.76;0.83] for the first 2 years of prospective follow-up). The O/E ratio varied, however, across tumor sites (breast 1.02, prostate 1.12, lung 0.38, colorectal 0.62). Possible explanations include bias caused by the fact that most study participants were healthy, delayed tumor reporting, incomplete data linkage, and incomplete self-reporting. Conclusion: Rising case numbers for the most commonly occurring types of cancer are expected in the next few years. This will enable comprehensive epidemiological analysis of the risk factors for cancer.
BACKGROUND Common diseases are largely caused by the combined contributions of genetic and environmental risk factors. On the genetic side, numerous variants contribute to disease susceptibility, resulting in a substantial polygenic component of disease risk. Many such variants have already been identified. Polygenic risk scores (PRS), which aggregate the effects of these variants, enable more precise estimation of an individual's disease risk. We review the current state of bench-to-bedside translation of PRS. METHODS This review is based on publications retrieved by a selective PubMed literature search using predefined search terms relevant to PRS. RESULTS Studies across a range of diseases have shown that PRS can markedly influence the assessment of disease risk, enabling the identification of individuals at high risk. The predictive value of PRS can be improved by integrating them into established clinical risk models; this is the area of application in which the implementation of PRS in clinical practice is currently most advanced. For example, studies on coronary heart disease (CHD) and on breast and pancreatic cancer have shown that integrating PRS into clinical risk models changes personalized recommendations for primary and secondary prevention. Depending on the study, this affects 24% (CHD) to 25% (breast cancer) of individuals in the respective clinical risk groups. A major limitation is that most PRS are based on data from European populations, and their predictive value may be lower in individuals of other ancestral backgrounds. Moreover, quality standards must be established to ensure that the potential of PRS can be effectively translated into routine clinical practice. CONCLUSION As genetic data continue to grow, the predictive value of PRS is expected to increase further. PRS are therefore likely to become an integral component of risk prediction in preventive and precision medicine.
