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Hypertension is a very common comorbidity and major risk factor for cardiovascular complications, especially in people with Type 2 Diabetes (T2D). Nevertheless, studies in the past have shown that blood pressure is often insufficiently controlled in medical practice. For the DIAB-CARE study, we used longitudinal data based on the German DIAB-CORE Consortium to assess whether health care regarding hypertension has improved during the last decade in our participants. Data of the three regional population-based studies CARLA (baseline 2002-2006 and follow-up 2007-2010), KORA (baseline 1999-2001 and follow-up 2006-2008) and SHIP (baseline 1997-2001 and follow-up 2002-2006) were pooled. Stratified by T2D status we analysed changes in frequencies, degrees of awareness, treatment and control. Linear mixed models were conducted to assess the influence of sex, age, study, and T2D status on changes of systolic blood pressure between the baseline and follow-up examinations (mean observation time 5.7 years). We included 4,683 participants aged 45 to 74 years with complete data and accounted for 1,256 participants who were lost to follow-up by inverse probability weighting. Mean systolic blood pressure decreased in all groups from baseline to follow-up (e.g. - 8.5 mmHg in those with incident T2D). Pulse pressure (PP) was markedly higher in persons with T2D than in persons without T2D (64.14 mmHg in prevalent T2D compared to 52.87 mmHg in non-T2D at baseline) and did not change much between the two examinations. Awareness, treatment and control increased considerably in all subgroups however, the percentage of those with insufficiently controlled hypertension remained high (at about 50% of those with hypertension) especially in prevalent T2D. Particularly elderly people with T2D often had both, high blood pressure ≥140/90 mmHg and a PP of ≥60 mmHg. Blood pressure in men had improved more than in women at follow-up, however, men still had higher mean SBP than women at follow-up. Blood pressure management has developed positively during past years in Germany. While hypertension prevalence, awareness and treatment were substantially higher in participants with T2D than in those without T2D at follow-up, hypertension control was achieved only in about half the number of people in each T2D group leaving much room for further improvement.

The aim of this study was to identify the occupational risk for a SARS-CoV-2 infection in a nationwide sample of German workers during the first wave of the COVID-19 pandemic (1 February-31 August 2020). We used the data of 108 960 workers who participated in a COVID follow-up survey of the German National Cohort (NAKO). Occupational characteristics were derived from the German Classification of Occupations 2010 (Klassifikation der Berufe 2010). PCR-confirmed SARS-CoV-2 infections were assessed from self-reports. Incidence rates (IR) and incidence rate ratios (IRR) were estimated using robust Poisson regression, adjusted for person-time at risk, age, sex, migration background, study center, working hours, and employment relationship. The IR was 3.7 infections per 1000 workers [95% confidence interval (CI) 3.3-4.1]. IR differed by occupational sector, with the highest rates observed in personal (IR 4.8, 95% CI 4.0-5.6) and business administration (IR 3.4, 95% CI 2.8-3.9) services and the lowest rates in occupations related to the production of goods (IR 2.0, 95% CI 1.5-2.6). Infections were more frequent among essential workers compared with workers in non-essential occupations (IRR 1.95, 95% CI 1.59-2.40) and among highly skilled compared with skilled professions (IRR 1.36, 95% CI 1.07-1.72). The results emphasize higher infection risks in essential occupations and personal-related services, especially in the healthcare sector. Additionally, we found evidence that infections were more common in higher occupational status positions at the beginning of the pandemic.

Background Although most deaths among patients with type 2 diabetes (T2D) are attributable to cardiovascular disease, modifiable cardiovascular risk factors appear to be inadequately treated in medical practice. The aim of this study was to describe hypertension, dyslipidemia and medical treatment of these conditions in a large population-based sample. Methods The present analysis was based on the DIAB-CORE project, in which data from five regional population-based studies and one nationwide German study were pooled. All studies were conducted between 1997 and 2006. We assessed the frequencies of risk factors and co-morbidities, especially hypertension and dyslipidemia, in participants with and without T2D. The odds of no or insufficient treatment and the odds of pharmacotherapy were computed using multivariable logistic regression models. Types of medication regimens were described. Results The pooled data set comprised individual data of 15, 071 participants aged 45–74 years, including 1287 (8.5%) participants with T2D. Subjects with T2D were significantly more likely to have untreated or insufficiently treated hypertension, i.e. blood pressure of > = 140/90 mmHg (OR = 1.43, 95% CI 1.26-1.61) and dyslipidemia i.e. a total cholesterol/HDL-cholesterol ratio > = 5 (OR = 1.80, 95% CI 1.59-2.04) than participants without T2D. Untreated or insufficiently treated blood pressure was observed in 48.9% of participants without T2D and in 63.6% of participants with T2D. In this latter group, 28.0% did not receive anti-hypertensive medication and 72.0% were insufficiently treated. In non-T2D participants, 28.8% had untreated or insufficiently treated dyslipidemia. Of all participants with T2D 42.5% had currently elevated lipids, 80.3% of these were untreated and 19.7% were insufficiently treated. Conclusions Blood pressure and lipid management fall short especially in persons with T2D across Germany. The importance of sufficient risk factor control besides blood glucose monitoring in diabetes care needs to be emphasized in order to prevent cardiovascular sequelae and premature death.

Background In humans, uric acid is a product of purine metabolism that impacts the vascular system. In addition to effects on arterial vascular tone, associations between serum uric acid concentrations—even in the physiological range—and arterial hypertension and vascular-mediated end-organ damage due to an impact on vascular stiffness have been postulated. Methods Therefore, we aim to investigate a possible cross-sectional association between serum uric acid concentrations in the physiological range and differences in arterial pulse wave velocity (PWV), an indicator of vascular remodeling, with a focus on possible differences between female and male individuals. We analyzed cross-sectional phenotypic and laboratory parameters, including PWV from 70,649 individuals in the population-based German National Cohort (NAKO) in a sex-specific manner. In parallel, we applied a machine learning approach to identify and quantify factors associated with PWV in a hypothesis-free manner. Results Our analysis uncovered a positive association between serum uric and PWV which was detected even if only individuals with urate values in the physiological range were included ( n  = 64,095). This correlation was more pronounced in women than in men. In multivariable linear regression models, we observed an association of uric acid (mmol/l) with PWV (m/s) of β  = 1.12 (95% confidence interval (CI): 0.78; 1.45) in males and β  = 1.35 (1.05; 1.66) in females, independent of other factors known to affect vascular stiffness. In addition, the machine learning approach identified uric acid as a major factor associated with PWV. The positive association was not restricted to hyperuricemia but evident even in the physiological concentration range. Based on the data from studies on the impact of aging on PWV, it is estimated that an increase in serum uric acid concentration by 0.1 mmol/l corresponds to an increase of approx. 7 years of age in females and of 4 years in males. Conclusions Already in the physiological concentration range, uric acid is positively associated with parameters of arterial stiffness. This association is more pronounced in females as compared to males. This finding provides a mechanistic explanation for the increased risk of vascular end-organ damage associated with higher serum uric acid concentrations and supports the observed greater benefit of therapeutic uric acid lowering in female. Future intervention studies have to address the mechanistic causality of the observed effect.

Background During the COVID-19 pandemic, non-COVID-19 related healthcare utilization declined in Germany, resulting in care delay, including delays and cancellations of routine, chronic, and even acute care. The aim of this study was to investigate factors (i.e. regional differences and participant characteristics) associated with care delay during the pandemic in Germany using a cross-sectional survey. Methods In October 2022, a total of 117,466 participants from the German National Cohort (NAKO) study completed an online questionnaire on pandemic-related topics, including care delay during the COVID-19 pandemic. Regional differences and participant characteristics associated with care delay were assessed using (multilevel) logistic regression. Results One third of participants reported having experienced care delay. Care delay did not differ across the 13 federal states or 32 districts in Germany for which sufficient data were available. In the medical practice setting, care delay was nearly equally provider- and patient-related and was reported mostly for routine check-ups. In the hospital setting, care delay was predominantly provider-related and reported for newly occurring conditions. The odds for care delay were higher in females vs. males (odds ratio (OR): 1.30; 95% confidence interval (CI): 1.27–1.34), and in participants with vs. without chronic conditions (e.g. mental disorders, OR: 1.41, 95%CI: 1.36–1.46 or cardiovascular diseases, OR: 1.20 95%CI: 1.16–1.24) and decreased with age (e.g. 70 + vs. 50–59 years, OR: 0.59, 95%CI: 0.57–0.62). Conclusion Care delay during the COVID-19 pandemic depended on participant characteristics including age, sex, and preexisting chronic conditions but not on regional (i.e. state and district-level) differences in Germany.

Chronic heart failure (CHF) is one of the most important public health concerns in the industrialized world having increasing incidence and prevalence. Although there are several studies describing the prevalence of heart failure with reduced ejection fraction (HFREF) and heart failure with normal ejection fraction (HFNEF) in selected populations, there are few data regarding the prevalence and the determinants of symptomatic heart failure in the general population. Cross-sectional data of a population-based German sample (1,779 subjects aged 45-83 years) were analyzed to determine the prevalence and determinants of chronic SHF and HFNEF defined according to the European Society of Cardiology using symptoms, echocardiography and serum NT-proBNP. Prevalence was age-standardized to the German population as of December 31st, 2005. The overall age-standardized prevalence of symptomatic CHF was 7.7% (95%CI 6.0-9.8) for men and 9.0% (95%CI 7.0-11.5) for women. The prevalence of CHF strongly increased with age from 3.0% among 45-54- year-old subjects to 22.0% among 75-83- year-old subjects. Symptomatic HFREF could be shown in 48% (n = 78), symptomatic HFNEF in 52% (n = 85) of subjects with CHF. The age-standardized prevalence of HFREF was 3.8 % (95%CI 2.4-5.8) for women and 4.6 % (95%CI 3.6-6.3) for men. The age-standardized prevalence of HFNEF for women and men was 5.1 % (95%CI 3.8-7.0) and 3.0 % (95%CI 2.1-4.5), respectively. Persons with CHF were more likely to have hypertension (PR = 3.4; 95%CI 1.6-7.3) or to have had a previous myocardial infarction (PR = 2.5, 95%CI 1.8-3.5). The prevalence of symptomatic CHF appears high in this population compared with other studies. While more women were affected by HFNEF than men, more male subjects suffered from HFREF. The high prevalence of symptomatic CHF seems likely to be mainly due to the high prevalence of cardiovascular risk factors in this population.

Background Advanced glycation end products (AGEs), modifications of proteins or amino acids, are increasingly produced and accumulated with age-related diseases. Recent studies suggested that the ratio of AGEs and their soluble receptor (sRAGE) is a more accurate biomarker for age-related diseases than each separately. We aim to investigate whether this also applies for physical functioning in a broad age-spectrum. Methods AGE and sRAGE levels, and physical functioning (SF-12 questionnaire) of 967 men and 812 women (45–83 years) were measured in the CARLA study. We used ordinal logistic regression to examine associations between AGEs, sRAGE, and AGE/sRAGE ratio with physical functioning in sex- and age-stratified models. Results Higher levels of AGEs and AGE/sRAGE ratio were associated with lower physical functioning only in women, even after consideration of classical lifestyle and age-related factors (education, BMI, smoking, alcohol consumption, diet, creatinine clearance, diabetes mellitus, lipid lowering and antihypertensive drugs) (odds ratio (OR) =0.86, 95%confidence interval = 0.74–0.98 and OR = 0.86, 95%CI = 0.75–0.98 for AGEs and AGE/sRAGE ratio respectively). We could not demonstrate a significant difference across age. Conclusions We showed a sex-specific association between physical functioning and AGEs and AGE/sRAGE, but no stronger associations of the latter with physical functioning. Further investigation is needed in the pathophysiology of this association.

Background Frailty is a geriatric syndrome associated with increased morbidity, disability, and mortality. While its prevalence has been studied extensively in individual cohorts and patient populations, national prevalence data are scarce and regional variations within Germany remain largely unexplored. This study examined the frequency of frailty and its regional variation across the 18 NAKO (German National Cohort) study centers using a uniform frailty index. Methods We analysed baseline data collected between 2014 and 2019 from 39,248 participants aged 61–75 years enrolled in the NAKO study, a large population-based cohort recruited across 18 study centers in Germany. Frailty was measured using a 40-item Frailty Index (FI), with FI ≥ 0.25 indicating frailty. Regional variations in frailty were first examined using crude frequencies and subsequently analysed with logistic regression, adjusting for key confounders, including age, sex, and sociodemographic and socioeconomic factors, to account for compositional differences across centers. Results The crude frequency of frailty in the total sample was 7.7% (95% CI: 7.5–8.0), while 34.1% were prefrail. Frailty frequencies showed a nearly twofold spread (5.4%–10.2%) across study sites, being highest in Essen, Düsseldorf, Regensburg, Saarbrücken, and Berlin, and lowest in Freiburg, Münster, and northern German centers. Higher age, lower socioeconomic status and weaker social networks were all independently associated with frailty status. However, while these compositional factors contributed to the variability observed across centers, they did not fully account for it. Conclusion Notable regional differences in frailty are evident across NAKO study centers in Germany, even after accounting for population composition (age, sex, and socioeconomic factors). This residual heterogeneity suggests that contextual factors - such as regional healthcare access, environmental exposures, or structural policies - contribute to frailty development beyond individual risk factors.

We thank van Tongeren et al for responding to our study on occupational disparities in SARS-CoV-2 infection risks during the first pandemic wave in Germany (1). The authors address the potential for bias resulting from differential testing between occupational groups and propose an alternative analytical strategy for dealing with selective testing. In the following, we want to discuss two aspects of this issue, namely (i) the extent and reasons of differential testing in our cohort and (ii) the advantages and disadvantages of different analytical approaches to study risk factors for SARS-CoV-2 infection. Our study relied on nationwide prospective cohort data including more than 100 000 workers in order to compare the incidence of infections between different occupations and occupational status positions. We found elevated infection risks in personal services and business administration, in essential occupations (including health care) and among people in higher occupational status positions (ie, managers and highly skilled workers) during the first pandemic wave in Germany (2). Van Tongeren's et al main concern is that the correlations found could be affected by a systematic bias because people in healthcare professions get tested more often than employees in other professions. A second argument is that better-off people could be more likely to use testing as they are less affected by direct costs (prices for testing) and the economic hardship associated with a positive test result (eg, loss of earnings in the event of sick leave). We share the authors' view that differential testing must be considered when analysing and interpreting the data. Thus, in our study, we examined the proportion of tests conducted in each occupational group as part of the sensitivity analyses (see supplementary figure S1, accessible at www.sjweh.fi/article/4037). As expected, testing proportions were exceptionally high in medical occupations (due to employer requirements). However, we did not observe systematic differences among non-medical occupations or when categorising by skill-level or managerial responsibility. This might be explained by several reasons. First, SARS-CoV-2 testing was free of charge during the first pandemic wave in Germany, but reporting a risk contact or having symptoms was a necessary condition for testing ( https://www.bundesgesundheitsministerium.de/coronavirus/chronik-coronavirus.html (accessed 5 September 2022). The newspaper article cited by van Tongeren et al is misleading as it refers to a calendar date after our study period. Second, different motivation for testing due to economic hardship in case of a positive test result is an unlikely explanation, because Germany has a universal healthcare system, including paid sick leave and sickness benefits for all workers (3). Self-employed people carry greater financial risks in case of sickness. We therefore included self-employment in the multivariable analyses to address this potential source of bias. While the observed inverse social gradient may be surprising, it actually matches with findings of ecological studies from Germany (4, 5), the United States (6, 7) as well as Spain, Portugal, Sweden, The Netherlands, Israel, and Hong Kong (8), all of which observed higher infection rates in wealthier neighbourhoods during the initial outbreak phase of the pandemic. One possible explanation is the higher mobility of managers and better educated workers, who are more likely to participate in meetings and engage in business travel and holiday trips like skiing. Given the increasing number of studies providing evidence for this hypothesis, we conclude that the inverse social gradient in our study likely reflects different exposure probabilities and is not a result of systematic bias. This also holds true for the elevated infection risks in essential workers, which is actually corroborated by a large body of research (9-11). Regarding differential likelihood of testing, van Tongeren et al state that \"[i]t is relatively simple to address this problem by using a test-negative design\" (1). As van Tongeren et al describe, this is a case-control approach only including individuals who were tested (without considering those who were not tested). However, the proposed analytical strategy can lead to another (more serious) selection bias if testing proportions and/or testing criteria differ between groups (12). This can be easily illustrated when comparing the results based on a time-incidence design with those obtained by a test-negative design as shown in table 1 (see PDF). Both approaches show similar results in terms of vertical occupational differences. Infection was more common if individuals had a high skill level or had a managerial position, but associations were stronger in the time-incidence design and did not reach statistical significance in the test-negative design (as indicated by the confidence intervals overlapping \"1\"). Unfortunately, the test-negative approach relies on a strongly reduced sample size and thus results in greater statistical uncertainty and loss of statistical power (13). In contrast, the test-negative design yields a different picture when estimating the association between essential occupation and infection risk: In this analysis, essential workers did not differ from non-essential workers in their chance of being infected with SARS-CoV-2 (the test-negative design even exhibits a lower chance for essential workers). This is rather counter-intuitive and is not in accordance with what we know about the occupational hazards of healthcare workers during the pandemic (14). The main problem is that proportions of positive tests are highly unreliable when testing proportions and/or testing criteria differ between groups. As essential workers were tested more often without being symptomatic (due to employer requirements), a lower proportion of positive tests in this group does not necessarily correspond to a lower risk of infection. Consequently, we are not convinced that the test-negative design should be the 'gold standard' for studying risk factors for SARS-CoV-2 infections (15). Especially problematic is the loss of statistical power (increasing the probability of a type II error) and the low validity of the test-positivity when test criteria and/or test proportions differ between groups. References 1. van Tongeren M, Rhodes S, Pearce N. Occupation and SARS-CoV-2 infection risk among workers during the first pandemic wave in Germany: potential for bias. Scand J Work Environ Health 2022;48(7):586-587. https://doi.org/10.5271/sjweh.4052. 2. Reuter M, Rigó M, Formazin M, Liebers F, Latza U, Castell S, et al. Occupation and SARS-CoV-2 infection risk among 108 960 workers during the first pandemic wave in Germany. Scand J Work Environ Health 2022;48:446-56. https://doi.org/10.5271/sjweh.4037. 3. Busse R, Blümel M, Knieps F, Bärnighausen T. Statutory health insurance in Germany: a health system shaped by 135 years of solidarity, self-governance, and competition. Lancet 2017;390:882-97. https://doi.org/10.1016/S0140-6736(17)31280-1. 4. Wachtler B, Michalski N, Nowossadeck E, Diercke M, Wahrendorf M, Santos-Hövener C, et al. Socioeconomic inequalities in the risk of SARS-CoV-2 infection - First results from an analysis of surveillance data from Germany. J Heal Monit 2020;5:18-29. https://doi.org/10.25646/7057. 5. Plümper T, Neumayer E. The pandemic predominantly hits poor neighbourhoods? SARS-CoV-2 infections and COVID-19 fatalities in German districts. Eur J Public Health 2020;30:1176-80. https://doi.org/10.1093/eurpub/ckaa168. 6. Abedi V, Olulana O, Avula V, Chaudhary D, Khan A, Shahjouei S, et al. Racial, Economic, and Health Inequality and COVID-19 Infection in the United States. J Racial Ethn Heal Disparities 2021;8:732-42. https://doi.org/10.1007/s40615-020-00833-4. 7. Mukherji N. The Social and Economic Factors Underlying the Incidence of COVID-19 Cases and Deaths in US Counties During the Initial Outbreak Phase. Rev Reg Stud 2022;52. https://doi.org/10.52324/001c.35255. 8. Beese F, Waldhauer J, Wollgast L, Pförtner T, Wahrendorf M, Haller S, et al. Temporal Dynamics of Socioeconomic Inequalities in COVID-19 Outcomes Over the Course of the Pandemic-A Scoping Review. Int J Public Health 2022;67:1-14. https://doi.org/10.3389/ijph.2022.1605128. 9. Nguyen LH, Drew DA, Graham MS, Joshi AD, Guo C-G, Ma W, et al. Risk of COVID-19 among front-line health-care workers and the general community: a prospective cohort study. Lancet Public Heal 2020;5:e475-83. https://doi.org/10.1016/S2468-2667(20)30164-X. 10. Chou R, Dana T, Buckley DI, Selph S, Fu R, Totten AM. Epidemiology of and Risk Factors for Coronavirus Infection in Health Care Workers. Ann Intern Med 2020;173:120-36. https://doi.org/10.7326/M20-1632. 11. Stringhini S, Zaballa M-E, Pullen N, de Mestral C, Perez-Saez J, Dumont R, et al. Large variation in anti-SARS-CoV-2 antibody prevalence among essential workers in Geneva, Switzerland. Nat Commun 2021;12:3455. https://doi.org/10.1038/s41467-021-23796-4. 12. Accorsi EK, Qiu X, Rumpler E, Kennedy-Shaffer L, Kahn R, Joshi K, et al. How to detect and reduce potential sources of biases in studies of SARS-CoV-2 and COVID-19. Eur J Epidemiol 2021;36:179-96. https://doi.org/10.1007/s10654-021-00727-7. 13. Cohen J. Statistical Power Analysis for the Behavioral Sciences. 2nd Editio. New York: Routledge; 2013. https://doi.org/10.4324/9780203771587. 14. The Lancet. The plight of essential workers during the COVID-19 pandemic. Lancet 2020;395:1587. https://doi.org/10.1016/S0140-6736(20)31200-9. 15. Vandenbroucke JP, Brickley EB, Pearce N, Vandenbroucke-Grauls CMJE. The Evolving Usefulness of the Test-negative Design in Studying Risk Factors for COVID-19. Epidemiology 2022;33:e7-8. https://doi.org/10.1097/EDE.0000000000001438.We thank van Tongeren et al for responding to our study on occupational disparities in SARS-CoV-2 infection risks during the first p

Background Hypertension and dyslipidemia are often insufficiently controlled in persons with type 2 diabetes (T2D) in Germany. In the current study we evaluated individual characteristics that are assumed to influence the adequate treatment and control of hypertension and dyslipidemia and aimed to identify the patient group with the most urgent need for improved health care. Methods The analysis was based on the DIAB-CORE project in which cross-sectional data from five regional population-based studies and one nationwide German study, conducted between 1997 and 2006, were pooled. We compared the frequencies of socio-economic and lifestyle factors along with comorbidities in hypertensive participants with or without the blood pressure target of < 140/90 mmHg. Similar studies were also performed in participants with dyslipidemia with and without the target of total cholesterol/HDL cholesterol ratio < 5. Furthermore, we compared participants who received antihypertensive/lipid lowering treatment with those who were untreated. Univariable and multivariable logistic regression models were used to assess the odds of potentially influential factors. Results We included 1287 participants with T2D of whom n = 1048 had hypertension and n = 636 had dyslipidemia. Uncontrolled blood pressure was associated with male sex, low body mass index (BMI), no history of myocardial infarction (MI) and study site. Uncontrolled blood lipid levels were associated with male sex, no history of MI and study site. The odds of receiving no pharmacotherapy for hypertension were significantly greater in men, younger participants, those with BMI < 30 kg/m2 and those without previous MI or stroke. Participants with dyslipidemia received lipid lowering medication less frequently if they were male and had not previously had an MI. The more recent studies HNR and CARLA had the greatest numbers of well controlled and treated participants. Conclusion In the DIAB-CORE study, the patient group with the greatest odds of uncontrolled co-morbidities and no pharmacotherapy was more likely comprised of younger men with low BMI and no history of cardiovascular disease.