Early detection of diabetes and prediabetic states is beneficial for patients, but may be delayed by patients´ being overly optimistic about their own health. Therefore, we assessed how persons without known diabetes perceive their risk of having or developing diabetes, and we identified factors associated with perception of diabetes risk. 1,953 participants without previously known diabetes from the population-based, German KORA FF4 Study (59.1 years, 47.8% men) had an oral glucose tolerance test. They estimated their probability of having undiagnosed diabetes mellitus (UDM) on a six category scale, and assessed whether they were at risk of developing diabetes in the future. We cross-tabulated glycemic status with risk perception, and fitted robust Poisson regression models to identify determinants of diabetes risk perception. 74% (95% CI: 65–82) of persons with UDM believed that their probability of having undetected diabetes was low or very low. 72% (95% CI: 69–75) of persons with prediabetes believed that they were not at risk of developing diabetes. In people with prediabetes, seeing oneself at risk of diabetes was associated with self-rated poor general health (prevalence ratio (PR) = 3.1 (95% CI: 1.4–6.8), parental diabetes (PR = 2.6, 1.9–3.4), high educational level (PR = 1.9 (1.4–2.5)), lower age (PR = 0.7, 0.6–0.8, per 1 standard deviation increase), female sex (PR = 1.2, 0.9–1.5) and obesity (PR = 1.5, 1.2–2.0). People with undiagnosed diabetes or prediabetes considerably underestimate their probability of having or developing diabetes. Contrary to associations with actual diabetes risk, perceived diabetes risk was lower in men, lower educated and older persons.

Introduction: Excess mortality is a suitable indicator of health consequences of COVID-19 because death from any cause is clearly defined contrary to death from Covid-19. We compared the overall mortality in 2020 with the overall mortality in 2016 to 2019 in Germany, Sweden and Spain. Contrary to other studies, we also took the demographic development between 2016 and 2020 and increasing life expectancy into account. Methods: Using death and population figures from the EUROSTAT database, we estimated weekly and cumulative Standardized Mortality Ratios (SMR) with 95% confidence intervals (CI) for the year 2020. We applied two approaches to calculate weekly numbers of death expected in 2020: first, we used mean weekly mortality rates from 2016 to 2019 as expected mortality rates for 2020, and, second, to consider increasing life expectancy, we calculated expected mortality rates for 2020 by extrapolation from mortality rates from 2016 to 2019. Results: In the first approach, the cumulative SMRs show that in Germany and Sweden there was no or little excess mortality in 2020 (SMR = 0.976 (95% CI: 0.974–0.978), and 1.030 (1.023–1.036), respectively), while in Spain the excess mortality was 14.8% (1.148 (1.144–1.151)). In the second approach, the corresponding SMRs for Germany and Sweden increased to 1.009 (1.007–1.011) and 1.083 (1.076–1.090), respectively, whereas results for Spain were virtually unchanged. Conclusion: In 2020, there was barely any excess mortality in Germany for both approaches. In Sweden, excess mortality was 3% without, and 8% with consideration of increasing life expectancy.

Mortality rates for coronary heart disease (CHD) experience a longstanding decline, attributed to progress in prevention, diagnostics and therapy. However, CHD mortality rates vary between countries. To estimate whether national patterns of causes of death impact CHD mortality, data from the WHO “European detailed mortality database” for 2000 and 2013 for populations aged ≥ 80 years was analyzed. We extracted mortality rates for total mortality, cardiovascular diseases, neoplasms, dementia and ill-defined causes. We calculated proportions of selected causes of death among all deaths, and proportions of selected cardiovascular causes among cardiovascular deaths. CHD mortality rates were recalculated after re-coding ill-defined causes of death. Association between CHD mortality rates and proportions of CHD deaths was estimated by population-weighted linear regression. National patterns of causes of death were divers. In 2000, CHD was assigned as cause of death in 13–53% of all cardiovascular deaths. Until 2013, this proportion changed between − 65% (Czech Republic) and + 57% (Georgia). Dementia was increasingly assigned as underlying cause of death in Western Europe, but rarely in eastern European countries. Ill-defined causes accounted for between < 1% and 53% of all cardiovascular deaths. CHD mortality rates were closely linked to a countries’ proportion of cardiovascular deaths assigned to CHD (R² = 0.95 for 2000 and 0.99 for 2013). We show that CHD mortality is considerably influenced by national particularities in certifying death. Changes in CHD mortality rates reflect changes in certifying competing underlying causes of death. This must be accounted for when discussing reasons for the CHD mortality decline.