[Algorithm for the Classification of Type 1 and Type 2 Diabetes Mellitus for the Analysis of Routine Data]. / Algorithmus zur Unterscheidung von Diabetes mellitus Typ 1 und Typ 2 bei der Analyse von Routinedaten.

BACKGROUND: Diabetes mellitus is a disease of high public health relevance. To estimate the temporal development of prevalence, routine data of statutory health insurances (SHI) are being increasingly used. However, these data are primarily collected for billing purposes and the case definition of specific diseases remains challenging. In this study, we present an algorithm for differentiation of diabetes types analyzing SHI routine data. METHODS: The basis for the analysis was an age and sex-stratified random sample of persons of the Barmer SHI with a continuous insurance duration from 2010 to 2018 in the magnitude of 1% of the German population. Diabetes was defined in the reporting year 2018, as documentation of (1) a "confirmed" ICD diagnosis E10.- to E14.- in at least two quarters, (2) a "confirmed" ICD diagnosis E10.- to E14.- in one quarter with an additional prescription of an antidiabetic drug (ATC codes A10), or (3) an ICD diagnosis E10.- to E14.- in the inpatient sector, outpatient surgery, or work disability. Individuals were assigned to a diabetes type based on the specific ICD diagnosis E10.- to E14.- and prescribed medications, differentiated by insulin and other antidiabetics. Still unclear or conflicting constellations were assigned on the basis of the persons' age or the frequency and observation of the diagnosis documentation over more than one year. The participation in a disease management program was considered in a sensitivity analysis. RESULTS: The prevalence of documented diabetes in the Barmer sample was 8.8% in 2018. Applying the algorithm, 98.5% of individuals with diabetes could be classified as having type 1 diabetes (5.5%), type 2 diabetes (92.6%), or another specific form of diabetes (0.43%). Thus, the prevalence was 0.48% for type 1 diabetes and 8.1% for type 2 diabetes in 2018. CONCLUSION: The vast majority of people with diabetes can be classified by their diabetes type on the basis of just a few characteristics, such as diagnoses, drug prescription, and age. Further studies should assess the external validity by comparing the results with primary data. The algorithm enables the analysis of important epidemiological indicators and the frequency of comorbidities based on routine data differentiated by type 1 and type 2 diabetes, which should be considered in the surveillance of diabetes in the future.

Diabetes-related distress and associated factors among adults with diabetes in Germany: Results of the nationwide study "Disease knowledge and information needs - Diabetes mellitus 2017".

BACKGROUND: Diabetes-related distress (DRD) can affect diabetes management adversely. In lack of population-based data, the frequency and determinants of DRD among adults with diabetes in Germany remain controversial. METHODS: This study included 1367 adults with diabetes who participated in a nationwide health telephone survey conducted among German adults aged 18 years and older in 2017. The short form of the Problem Areas in Diabetes (PAID-5) scale was used to assess DRD. The associations of high DRD (PAID-5 sum score ≥ 8) with socio-demographics, diabetes-related risk factors, diabetes clinical characteristics as well as quality of self-care and chronic illness care assessed by patients were tested in multivariable logistic regression models. RESULTS: The overall DRD prevalence was 15.1% (95% confidence intervals, 95% CIs, 12.5-18.0%) with no significant difference between men (14.7%, 95% CIs 11.2-19.1%) and women (15.4%, 11.9-19.8%). In multivariable analyses, DRD was significantly associated with younger age (odds ratio 0.96, 95% CIs 0.94-0.98, per year), immigration background (2.26, 1.16-4.42), current smoking (2.06, 1.14-3.70), insulin use (2.57, 1.45-4.56), and the presence of diabetes-specific complications (1.80, 1.10-2.94) or depressive symptoms (5.34, 3.24-8.81). Among those with depressive symptoms (18,4% of the study population), 38.3% also had DRD, which accounted for 7.0% (95% CIs 5.3-9.3%) of the study population. CONCLUSION: DRD is a common health problem among adults with diabetes in Germany, and highly correlates with depressive symptoms, current smoking, immigration background, and insulin use. Addressing DRD needs to become an integrative part of ambulatory diabetes care.

German Diabetes Risk Score for the Determination of the Individual Type 2 Diabetes Risk.

BACKGROUND: The German Diabetes Risk Score (GDRS) currently enables prediction of the individual risk of developing type 2 diabetes (T2D) within five years. The aim of this study is to extend the prediction period of the GDRS, including its non-clinical version and its HbA1c extension, to 10 years, and to perform external validation. METHODS: In data from the European Prospective Investigation into Cancer and Nutrition (EPIC)-Potsdam study (n = 25 393), Cox proportional hazards regression was used to reweight the points that were used to calculate the five-year risk. Two population-based prospective cohorts (EPIC-Heidelberg n = 23 624, GNHIES98 cohort n = 3717) were used for external validation. Discrimination was represented by C-indices, and calibration by calibration plots and the expected-to-observed (E/O) ratio. RESULTS: Prediction performance in EPIC-Potsdam was very good (C-index for the non-clinical model: 0.834) and was confirmed in EPIC-Heidelberg (0.843) and in the GNHIES98 cohort (0.851). Among persons in the GNHIES98 cohort with a greater than 10% predicted probability of disease, 14.9% developed T2D within 10 years (positive predictive value). The models were very well calibrated in EPIC-Potsdam (E/O ratio for the non-clinical model: 1.08), slightly overestimated the risk in EPIC-Heidelberg (1.34), and predicted T2D very well in the GNHIES98 cohort after recalibration (1.06). CONCLUSION: The extended GDRS prediction period of 10 years, with a non-clinical version and an HbA1c extension that will soon be available in both German and English, enables the even longer-range, evidence-based identification of high-risk individuals with many different applications, including medical screening.

Sex-specific impact of major depressive disorder on 12-year change in glycaemic status: Results from a nationwide cohort study of adults without diabetes in Germany.

AIMS: There is evidence for an increased type 2 diabetes (T2D) risk associated with depression, but its role for diabetes prevention remains unclear. This study aimed to add insight by investigating the impact of major depressive disorder (MDD) on prospective glycaemic changes. METHODS: The study was based on a cohort of n = 1,766 adults without diabetes (776 men, 990 women; 18-65 years of age) who participated in the mental health supplement of the German National Health Interview and Examination Survey (GNHIES98-MHS, 1997-1999) and in a follow-up survey (DEGS1, 2008-2011). Glycaemic status was defined as normoglycaemia [HbA1c < 39 mmol/mol (<5.7%)], prediabetes [39 ≤ HbA1c < 48 mmol/mol (5.7-6.4%)] and diabetes [HbA1c ≥ 48 mmol/mol (≥ 6.5%), diagnosed diabetes, or antidiabetic medication], and glycaemic changes categorized as 'remission', 'stability' and 'progression'. Baseline MDD was assessed via a modified German version of the WHO Composite International Diagnostic Interview. Multivariable logistic regressions were applied to analyse the association of MDD with glycaemic changes and incident T2D, adjusting for socio-demographics, lifestyle conditions, chronic diseases, antidepressant use and mental health care. RESULTS: MDD prevalence was 21.4% for women and 8.9% for men. Among women, MDD was associated with a lower chance for remission (RRR 0.43; 95% CI 0.23, 0.82). Among men, MDD was not significantly related to glycaemic changes. MDD had no significant effect on incident T2D (men: OR 1.58; 0.55, 4.52; women: OR 0.76; 0.37, 1.58). CONCLUSIONS: Findings of the current study highlight the role of depression in T2D prevention, particularly among women.

Estimating the impact of tax policy interventions on the projected number and prevalence of adults with type 2 diabetes in Germany between 2020 and 2040.

INTRODUCTION: As a population-wide intervention, it has been proposed to raise taxes on unhealthy products to prevent diseases such as type 2 diabetes. In this study, we aimed to estimate the effect of tax policy interventions in 2020 on the projected prevalence and number of people with type 2 diabetes in the German adult population in 2040. RESEARCH DESIGN AND METHODS: We applied an illness-death model and the German Diabetes Risk Score (GDRS) to project the prevalence and number of adults with type 2 diabetes in Germany under a base case scenario and under a tax policy intervention scenario. For the base case scenario, we assumed constant age-specific incidence rates between 2020 and 2040. For the intervention scenario, we assumed a 50% price increase for sugar-sweetened beverages, tobacco and red meat products in the year 2020. Based on price elasticities, we estimated the impact on these risk factors alone and in combination, and calculated subsequent reductions in the age-specific and sex-specific GDRS. These reductions were used to determine reductions in the incidence rate and prevalence using a partial differential equation. RESULTS: Compared with the base case scenario, combined tax interventions in 2020 resulted in a 0.95 percentage point decrease in the prevalence of type 2 diabetes (16.2% vs 17.1%), which corresponds to 640 000 fewer prevalent cases of type 2 diabetes and a relative reduction by 6%. CONCLUSIONS: Taxation of sugar-sweetened beverages, tobacco products and red meat by 50% modestly lowered the projected number and prevalence of adults with type 2 diabetes in Germany in 2040. Raising taxes on unhealthy products as a stand-alone measure may not be enough to attenuate the future rise of type 2 diabetes.

Excess mortality in adults with documented diabetes in Germany: routine data analysis of all insurance claims in Germany 2013-2014.

OBJECTIVES: Little is known about the age-specific excess mortality pattern of people with diagnosed diabetes in Germany. Thus, our goal was to determine the excess mortality in diagnosed diabetes overall and stratified by age and sex based on claims data. DESIGN: Routine data analysis using a claims dataset from all statutory health-insured persons in Germany in 2013, which accounts for about 90% of the population. PARTICIPANTS: We included persons who lived in Germany, were insured at least 360 days, were not self-paying any health services and were aged 30 years or older leading to a total number of 47.3 million insured persons for analyses. EXPOSURE: Diabetes was determined by the International Classification of Diseases-10 codes E10-E14, which were documented in 2013 in at least two-quarters on an outpatient setting or at least once on an inpatient setting. OUTCOME MEASURES: The vital status in the study population was drawn from the claims dataset for the year 2014. We derived the excess mortality estimated as an age-adjusted mortality rate ratio (MRR) by sex and for age groups using a Poisson model. MAIN RESULTS: We found age-adjusted MRRs (95% CI) for diabetes of 1.52 (1.51 to 1.52) for women and 1.56 (1.56 to 1.56) for men. These figures declined with increasing age and were highest for ages 30-34 years with 6.76 (4.99 to 9.15) for women and 6.87 (5.46 to 8.64) for men, and lowest for age 95 years and older with 1.13 (1.10 to 1.15) for women and 1.11 (1.05 to 1.17) for men. CONCLUSIONS: We derived deeply age-stratified figures on excess mortality in diabetes for Germany. Establishing a sustainable analysis of excess mortality is aimed at within the framework of diabetes surveillance.

Care for the chronically ill in Germany - The challenges during the COVID-19 pandemic.

The COVID-19 pandemic is posing major challenges to the health care sector. This scoping review compiles evidence concerning changes to health care service availability and utilisation as well as possible impacts on health for selected groups of chronically ill people in Germany. The focus is on cancer, cardiovascular diseases, diabetes mellitus and mental disorders. Most empirical data available concerned inpatient care and showed a clear decline in the utilisation of inpatient treatments in March and April 2020 in the areas of oncology and cardiology as well as in mental health. For cardiovascular emergencies such as heart attack and stroke, a decline was observed especially regarding less serious cases. Although there were indications of treatment delays, there was no evidence thus far that emergency care had been generally compromised due to adjustments to inpatient care capacities. In the outpatient setting, extensive adjustments to health care services availability were observed for all disease groups considered. Overall, very limited empirical data were available. In particular, hardly any data were available on how changes in care impacted population health. There is an urgent need for continuous surveillance and evaluation based on health care and epidemiological data.

Self-assessed quality of care among adults with diagnosed diabetes in Germany.

People who have diabetes require regular medical care. The views of patients about the quality of their care are becoming increasingly relevant when it comes to chronic diseases such as diabetes. As part of the nationwide study Disease Knowledge and Information Needs - Diabetes mellitus (2017), data on self-assessed quality of care by people with diagnosed diabetes was collected using the Patient Assessment of Chronic Illness Care - DAWN short form (PACIC-DSF, scale 1 to 5) and analysed for respondents aged 45 years or above. The average score for quality of care was 2.47 and was lower for women than for men (2.33 vs 2.58). The respondents assessed the quality of their care as being worse with rising age and size of the population in their residential area. No significant differences were observed by education group. Overall, people with diabetes in Germany consider the quality of their care to be moderate, which indicates a need for improvement in care.

Diabetes mellitus and comorbidities - A cross-sectional study with control group based on nationwide ambulatory claims data.

As a condition, diabetes mellitus is associated with risk factors and diseases such as obesity. At the same time, cardiovascular diseases are a frequent consequence of diabetes. There have yet to be any findings on the Germany-wide prevalence of diabetes and diabetes comorbidities based on statutory health insurance data. This study estimates the documented prevalence of diabetes in 2019 on the basis of all ambulatory physicians' claims data of German statutory health insurance. In addition, the prevalence of obesity, high blood pressure, coronary heart disease, heart failure, stroke and depression is calculated for diabetes and non-diabetes patients, and the prevalence ratio (PR) is determined as a quotient. The approach used was a case-control design, which assigns a control person without diabetes to each diabetes patient who is similar in terms of age, region and sex. In diabetes patients, a PR greater than 1 was observed for all examined diseases across all age groups, thus demonstrating a higher prevalence compared to persons without diabetes. The highest PR across all age groups for women (3.8) and men (3.7) was found for obesity. In a comparison over time, documented prevalence figures of diabetes in Germany stagnate. With the exception of depression, the documented prevalences of comorbidities correspond well with the prevalences found in population-wide examination surveys.

Factors associated with undiagnosed type 2 diabetes in Germany: results from German Health Interview and Examination Survey for Adults 2008-2011.

INTRODUCTION: To identify characteristics of people with undiagnosed type 2 diabetes (T2D) among adults in Germany. RESEARCH DESIGN AND METHODS: The study population comprised participants aged 40-79 years of the German Health Interview and Examination Survey for Adults 2008-2011. Glycemic status was categorized as undiagnosed T2D (glycated hemoglobin A1c (HbA1c) ≥48 mmol/mol (6.5%), n=135), diagnosed T2D (n=518) and normoglycemia (HbA1c<48 mmol/mol (6.5%), n=4451). Multinomial logistic regression models including glycemic status as the outcome variable and sociodemographic characteristics, living alone, diabetes risk factors and healthcare services utilization as independent variables were used to identify factors associated with undiagnosed T2D compared with normoglycemia and diagnosed T2D. Odds ratios (ORs) and 95% confidence intervals (CIs) are reported as measure of association between the outcome and independent variables. RESULTS: The prevalence of undiagnosed T2D was 2.9% (95% CI 2.2% to 3.9%) at an overall prevalence of 12.3% (11.0% to 13.6%) of persons with undiagnosed or diagnosed T2D. In multivariable analyses, factors associated with undiagnosed as well as diagnosed T2D in comparison to normoglycemia were older age (OR 1.04, 95% CI 1.01 to 1.06, per year, for undiagnosed T2D; OR 1.08, 1.07 to 1.10 for diagnosed T2D), male sex (3.33, 2.18 to 5.07; 1.91, 1.43 to 2.56), obesity (3.47, 2.17 to 5.56; 2.68, 2.04 to 3.52), hypertension (1.66, 1.09 to 2.53; 2.04, 1.42 to 2.95) and parental history of diabetes (2.04, 1.24 to 3.35; 3.16, 2.30 to 4.34). Variables independently associated with undiagnosed T2D but not diagnosed T2D included living alone (2.20; 1.36 to 3.56) and not seeing a doctor within the past year (2.57; 1.34 to 4.93). People with undiagnosed T2D were further younger and more likely to be male sex and reside in the western part of Germany than people with diagnosed T2D. CONCLUSION: Apart from major known risk factors of diabetes, characteristics specific to undiagnosed diabetes among adults in Germany will serve to inform the national education and communication strategy on diabetes mellitus in Germany.

[Health reporting as part of public health surveillance: the example of diabetes]. / Gesundheitsberichterstattung im Rahmen von Public Health Surveillance: Das Beispiel Diabetes.

The continuous collection and analysis of health data on relevant diseases (surveillance) is at the core of public health. The surveillance enables the implementation of measures to protect the populations' health. Therefore, relevant information needs to be provided in a timely and target-group-specific manner to the respective stakeholders.A dissemination strategy supports the effective communication of results and considers three key questions: (1) "What content is relevant to the surveillance?", (2) "Who requires which information?" and (3) "How are the results disseminated to the target audience?" In this context, digitalisation allows for novel possibilities in the design of publication formats.Since 2015, diabetes surveillance has been established at the Robert Koch Institute. Within a structured process of consensus, we defined four fields of action relevant for health policy including 40 indicators. Thereafter, we developed the first publication formats in collaboration with the scientific advisory board of the project that reflected novel possibilities offered by digitalisation. In addition to articles in scientific journals, the essential formats of the first project phase comprise the report "Diabetes in Germany" and a website including interactive visualisations of results. Additional posts on Twitter and YouTube are used to increase coverage.In addition to the further development of the indicator set, the focus of the next project phase is the advancement of the dissemination towards user- and action-oriented reporting. In close exchange with the scientific advisory board, we aim to explore the requirements of the target audience and reflect them in the design of further publication formats.

Health App Use and Its Correlates Among Individuals With and Without Type 2 Diabetes: Nationwide Population-Based Survey.

BACKGROUND: Evidence suggests that mobile health app use is beneficial for the prevention and management of type 2 diabetes (T2D) and its associated complications; however, population-based research on specific determinants of health app use in people with and without T2D is scarce. OBJECTIVE: This cross-sectional study aimed to provide population-based evidence on rates and determinants of health app use among adults with and without T2D, thereby covering a prevention perspective and a diabetes management perspective, respectively. METHODS: The study population included 2327 adults without a known diabetes diagnosis and 1149 adults with known T2D from a nationwide telephone survey in Germany conducted in 2017. Rates of smartphone ownership and health app use were estimated based on weighted sample proportions. Among smartphone owners, determinants of health app use were identified for both groups separately in multivariable logistic regression models. Sociodemographic factors, diabetes-related factors or indicators, psychological and health-related factors, and physician-provided information were selected as potential determinants. RESULTS: Among participants without known diabetes, 74.72% (1690/2327) were smartphone owners. Of those, 49.27% (717/1690) used health apps, most often to improve regular physical activity. Among participants with T2D, 42.26% (481/1149) were smartphone owners. Of those, 41.1% (171/481) used health apps, most commonly to target a healthy diet. Among people without known diabetes, determinants significantly (all P values <.05) associated with an increased likelihood of health app use compared with their reference group were as follows: younger and middle age of 18 to 44 or 45 to 64 years (odds ratios [ORs] 3.89; P<.001 and 1.76; P=.004, respectively), overweight or obesity (ORs 1.58; P<.001 and 2.07; P<.001, respectively), hypertension diagnosis (OR 1.31; P=.045), former or current smoking (ORs 1.51; P=.002 and 1.58; P<.001, respectively), perceiving health as very good (OR 2.21; P<.001), other chronic diseases (OR 1.48; P=.002), and having received health advice from a physician (OR 1.48; P<.001). A slight or high perceived diabetes risk (ORs 0.78; P=.04 and 0.23; P<.001, respectively) was significantly associated with a decreased likelihood of health app use. Among people with T2D, younger and middle age (18-64 years; OR 1.84; P=.007), female gender (OR 1.61; P=.02), and using a glucose sensor in addition or instead of a glucose meter (OR 2.74; P=.04) were significantly positively associated with health app use. CONCLUSIONS: In terms of T2D prevention, age, diabetes-related risk factors, psychological and health-related factors, and medical health advice may inform app development for specific target groups. In addition, health professionals may encourage health app use when giving advice on health behaviors. Concerning T2D management, only a few determinants seem relevant for explaining health app use among people with T2D, indicating a need for more future research on which people with T2D use health apps and why.

Psychometric properties of a nationwide survey for adults with and without diabetes: the "disease knowledge and information needs - diabetes mellitus (2017)" survey.

BACKGROUND: In order to close existing information gaps on diabetes-related health perceptions, diabetes knowledge, and information-seeking behaviors among adults in Germany, a representative population-based survey targeting the German-speaking population 18 years and older with and without diabetes was conducted. The aim of the present work was to analyze the psychometric properties of the multi-item scales, applied in the survey in order to provide guidance for decisions on the use of these measurements for future research. METHODS: Based on data from participants who completed the final survey (N = 1479 with known diabetes; N = 2327 without known diabetes) reliability and unidimensionality of multi-item scales were tested using Cronbach's Alpha and confirmatory factor analysis (CFA). RESULTS: Psychometric properties and model fit varied across scales. Cronbach's alpha values ranged from very good to unacceptable. Model fit indices suggested evidence of a single underlying factor in some but not all scales. Adequate reliability and at least mediocre model fit were found for diabetes distress and patient-provider-relationship in people with diabetes and for perceived level of information in individuals without diabetes. Scales revealing inacceptable reliability values or not suggesting unidimensionality were e.g. diabetes-related stigmatization in both individuals with and without diabetes, self-efficacy in individuals with diabetes, and perceived personal control in those without diabetes. CONCLUSION: Based on results of the current study, some of the scales applied in the survey can be recommended for present and future analyses of the survey data and for future surveys (e.g. diabetes distress, patient-provider-relationship in people with diabetes). Other scales should be interpreted and used with caution (e.g. depressive symptoms in people with diabetes) while others should be reformulated, interpreted only as single items, or need further investigation (e.g. diabetes-related stigmatization in people with and without diabetes). Findings provide researchers the opportunity to evaluate diabetes-specific scales in population-based studies of adults with and without diabetes.

Perceived diabetes risk and related determinants in individuals with high actual diabetes risk: results from a nationwide population-based survey.

Objective: The purpose of this study was first, to examine perceived diabetes risk compared with actual diabetes risk in the general population and second, to investigate which factors determine whether persons at increased actual risk also perceive themselves at elevated risk. Research design and methods: The study comprised adults (aged 18-97 years) without known diabetes from a nationwide survey on diabetes-related knowledge and information needs in Germany in 2017. Actual diabetes risk was calculated by an established risk score estimating the 5-year probability of developing type 2 diabetes and was compared with perceived risk of getting diabetes over the next 5 years (response options: 'almost no risk', 'slight risk', 'moderate risk', 'high risk'; n = 2327). Among adults with an increased actual diabetes risk (n=639), determinants of perceived risk were investigated using multivariable logistic regression analysis. Results: Across groups with a 'low' (<2%), 'still low' (2% to<5%), 'elevated' (5% to <10%), and 'high' (≥10%) actual diabetes risk, a proportion of 89.0%, 84.5%, 79.3%, and 78.9%, respectively, perceived their diabetes risk as almost absent or slight. Among those with an increased (elevated/high) actual risk, independent determinants of an increased (moderate/high) perceived risk included younger age (OR 0.92 (95% CI 0.88 to 0.96) per year), family history of diabetes (2.10 (1.06-4.16)), and being informed about an increased diabetes risk by a physician (3.27 (1.51-7.07)), but none of further diabetes risk factors, healthcare behaviors or beliefs about diabetes. Conclusions: Across categories of actual diabetes risk, perceived diabetes risk was low, even if actual diabetes risk was high. For effective strategies of primary diabetes prevention, attention should be directed to risk communication at the population level as well as in primary care practice.

Social inequality and diabetes mellitus - developments over time among the adult population in Germany.

The connection between social disadvantage and the presence of known diabetes and specific risk factors is well documented. This article summarises the results from the Robert Koch Institute examination surveys that were conducted between 1997 and 1999 as well as 2008 and 2011 to address social inequality - operationalised by level of education - with regard to prevalences of known and unknown diabetes, risk of diabetes and care of diabetes as well as their development over time. Both survey periods showed that the low education group has higher prevalences of known and unkown diabetes as well as a higher risk of developing diabetes within the next five years compared to the medium and high education group. Over time, prevalence tended to increase for known diabetes and to decrease for unknown diabetes for all education groups. For the 5-year diabetes risk, only the high education group showed a clear decrease over time. The chosen indicators of diabetes care indicated no clear differences between education groups and an improvement of diabetes care over time. For some indicators of care (foot examination, statins), improvements were only seen in the low education group. In conclusion, social inequalities in the prevalence of known and unknown diabetes as well as in diabetes risk remain in Germany; for the indicators of care, however, no clear education gradient is evident. Over time, inequality regarding the prevalence of diabetes has not increased further. However, with regard to diabetes risk, inequality has become slightly more evident. For individual care indicators, improvements are limited to specific education groups.

Secondary data in diabetes surveillance - co-operation projects and definition of references on the documented prevalence of diabetes.

In addition to the Robert Koch Institute's health surveys, analyses of secondary data are essential to successfully developing a regular and comprehensive description of the progression of diabetes as part of the Robert Koch Institute's diabetes surveillance. Mainly, this is due to the large sample size and the fact that secondary data are routinely collected, which allows for highly stratified analyses in short time intervals. The fragmented availability of data means that various sources of secondary data are required in order to provide data for the indicators in the four fields of action for diabetes surveillance. Thus, a milestone in the project was to check the suitability of different data sources for their usability and to carry out analyses. Against this backdrop, co-operation projects were specifically funded in the context of diabetes surveillance. This article presents the results that were achieved in co-operation projects between 2016 and 2018 that focused on a range of topics: from evaluating the usability of secondary data to statistically modelling the development of epidemiological indices. Moreover, based on the data of the around 70 million people covered by statutory health insurance, an initial estimate was calculated for the documented prevalence of type 2 diabetes for the years 2010 and 2011. To comparably integrate these prevalences over the years in diabetes surveillance, a reference definition was established with external expertise.

Association between random glucose and all-cause mortality: findings from the mortality follow-up of the German National Health Interview and Examination Survey 1998.

BACKGROUND: Random glucose is widely measured in epidemiological studies and in the clinical setting when standardized fasting protocols and oral glucose tolerance testing or HbA1c measuring are not feasible. The relationship between random glucose and all-cause mortality has hardly been studied so far and was examined in the present study. METHODS: We ascertained mortality status among 5955 persons aged 18-79 years and free of known diabetes when participating in the German National Health Interview and Examination Survey 1998 (mean observation time 11.7 years, 458 deaths). Cox regression was applied to analyze the association of random serum glucose with all-cause mortality taken potential confounders into account. Relative mortality risks were estimated as hazard ratios (HRs) with 95% confidence intervals (CIs) modeling random glucose as categorical or continuous variable. RESULTS: Compared to random glucose levels of 4.3 - < 5.3 mmol/L, HRs (95% CIs) were 1.94 (0.85-4.45) for levels < 4.3 mmol/L and 1.16 (0.89-1.50), 1.20 (0.91-1.58), 1.42 (0.88-2.29), 2.02 (1.26-3.25) and 4.71 (2.20-10.10) for levels 5.3 - < 5.8, 5.8 - < 6.8, 6.8 - < 7.8, 7.8 - < 11.1 and ≥ 11.1 mmol/L, adjusted for age, sex, lifestyle, anthropometry and chronic diseases. An additional adjustment for fasting time or HbA1c yielded similar estimates. Modeling continuous random glucose by restricted cubic spline functions revealed comparable findings. CONCLUSIONS: In the present epidemiological study drawn from the general population, random glucose showed a significant association with all-cause mortality, independent of main potential confounders. Thus, random glucose measures are highly relevant to health risk assessment among people without known diabetes when fasting glucose or HbA1c are difficult to obtain.

Determinants of Change in Glycemic Status in Individuals with Prediabetes: Results from a Nationwide Cohort Study in Germany.

Previous studies investigating determinants of changes in glycemic status among individuals with prediabetes mainly focused on glucose-defined prediabetes. In this study, we examined determinants of a regression to normoglycemia or a progression to diabetes among individuals with HbA1c-defined prediabetes. The study included 817 participants (18-79 years) with prediabetes (HbA1c 5.7-6.4% (39-47 mmol/mol)) at baseline. Glycemic status at follow-up was categorized as diagnosed diabetes (self-reported physician diagnosis or antidiabetic medication), undiagnosed diabetes (HbA1c ≥ 6.5% (≥48 mmol/mol)), prediabetes (as defined at baseline), and normoglycemia (HbA1c < 5.7% (<39 mmol/mol)). Determinants of glycemic changes were identified by multinomial logistic regression (OR (95% CI)), with those remaining in the prediabetic state as reference. During a mean follow-up time of 12.0 years, 33.8% of the participants reverted to normoglycemia, 7.2% progressed to undiagnosed diabetes, 12.8% progressed to diagnosed diabetes, and 46.2% remained prediabetic. Determinants of a regression to normoglycemia were female sex (male vs. female: 0.67 (0.46; 0.98)) and higher HDL cholesterol levels (1.17 (1.02; 1.35) per 10 mg/dl). Determinants of a progression to undiagnosed or diagnosed diabetes were higher values of BMI (1.10 (1.02; 1.18); 1.13 (1.06; 1.21) per kg/m2), waist circumference (1.04 (1.01; 1.07); 1.06 (1.03; 1.09) per cm), alanine aminotransferase (1.06 (1.03; 1.09); 1.07 (1.03; 1.10) per U/l), and gamma-glutamyl transferase (1.02 (1.00; 1.03); 1.03 (1.01; 1.04) per U/l). Higher age (1.04 (1.02; 1.06) per year), female sex (male vs. female: 0.56 (0.33; 0.97)), and parental history of diabetes (yes vs. no: 1.82 (1.05; 3.15)) were further associated with a progression to diagnosed diabetes, whereas higher triglyceride levels (1.03 (1.01; 1.06) per 10 mg/dl) were associated with a progression to undiagnosed diabetes. In conclusion, among the investigated determinants, potentially modifiable anthropometric and metabolic markers were associated with glycemic changes in individuals with HbA1c-defined prediabetes. The findings of this study demonstrate the need for more refined case finding strategies for diabetes prevention.

National public health system responses to diabetes and other important noncommunicable diseases : Background, goals, and results of an international workshop at the Robert Koch Institute.

Diabetes mellitus and other noncommunicable diseases (NCDs) represent an emerging global public health challenge. In Germany, about 6.7 million adults are affected by diabetes according to national health surveys, including 1.3 million with undiagnosed diabetes. Complications of diabetes result in an increasing burden for individuals and society as well as enormous costs for the health care system. In response, the Federal Ministry of Health commissioned the Robert Koch Institute (RKI) to implement a diabetes surveillance system and the Federal Center for Health Education (BZgA) to develop a diabetes prevention strategy. In a two-day workshop jointly organized by the RKI and the BZgA, representatives from public health institutes in seven countries shared their expertise and knowledge on diabetes prevention and surveillance. Day one focused on NCD surveillance systems and emphasized both the strengthening of sustainable data sources and the timely and targeted dissemination of results using innovative formats. The second day focused on diabetes prevention strategies and highlighted the importance of involving all relevant stakeholders in the development process to facilitate its acceptance and implementation. Furthermore, the effective translation of prevention measures into real-world settings requires data from surveillance systems to identify high-risk groups and evaluate the effect of measures at the population level based on analyses of time trends in risk factors and disease outcomes. Overall, the workshop highlighted the close link between diabetes prevention strategies and surveillance systems. It was generally stated that only robust data enables effective prevention measures to encounter the increasing burden from diabetes and other NCDs.

Derivation and external validation of a clinical version of the German Diabetes Risk Score (GDRS) including measures of HbA1c.

OBJECTIVE: The German Diabetes Risk Score (GDRS) is a diabetes prediction model which only includes non-invasively measured risk factors. The aim of this study was to extend the original GDRS by hemoglobin A1c (HbA1c) and validate this clinical GDRS in the nationwide German National Health Interview and Examination Survey 1998 (GNHIES98) cohort. RESEARCH DESIGN AND METHODS: Extension of the GDRS was based on the European Prospective Investigation into Cancer and Nutrition (EPIC)-Potsdam study with baseline assessment conducted between 1994 and 1998 (N=27 548, main age range 35-65 years). Cox regression was applied with the original GDRS and HbA1c as independent variables. The extended model was evaluated by discrimination (C-index (95% CI)), calibration (calibration plots and expected to observed (E:O) ratios (95% CI)), and reclassification (net reclassification improvement, NRI (95% CI)). For validation, data from the GNHIES98 cohort with baseline assessment conducted between 1997 and 1999 were used (N=3717, age range 18-79 years). Missing data were handled with multiple imputation. RESULTS: After 5 years of follow-up 593 incident cases of type 2 diabetes occurred in EPIC-Potsdam and 86 in the GNHIES98 cohort. In EPIC-Potsdam, the C-index for the clinical GDRS was 0.87 (0.81 to 0.92) and the overall NRI was 0.26 (0.21 to 0.30), with a stronger improvement among cases compared with non-cases (NRIcases: 0.24 (0.19 to 0.28); NRInon-cases: 0.02 (0.01 to 0.02)). Almost perfect calibration was observed with a slight tendency toward overestimation, which was also reflected by an E:O ratio of 1.07 (0.99 to 1.16). In the GNHIES98 cohort, discrimination was excellent with a C-index of 0.91 (0.88 to 0.94). After recalibration, the calibration plot showed underestimation of diabetes risk in the highest risk group, while the E:O ratio indicated overall perfect calibration (1.02 (0.83 to 1.26)). CONCLUSIONS: The clinical GDRS provides the opportunity to apply the original GDRS as a first step in risk assessment, which can then be extended in clinical practice with HbA1c whenever it was measured.