Diabetes free life expectancy and years of life lost associated with type 2 diabetes: projected trends in Germany between 2015 and 2040

Background: Type 2 diabetes (T2D) causes substantial disease burden and is projected to affect an increasing number of people in coming decades. This study provides projected estimates of life years free of type 2 diabetes (T2D) and years of life lost (YLL) associated with T2D for Germany in the years 2015 and 2040. Methods: Based on an illness-death model and the associated mathematical relation between prevalence, incidence and mortality, we projected the prevalence of diagnosed T2D using currently available data on the incidence rate of diagnosed T2D and mortality rates of people with and without diagnosed T2D. Projection of prevalence was achieved by integration of a partial differential equation, which governs the illness-death model. These projected parameters were used as input values to calculate life years free of T2D and YLL associated with T2D for the German population aged 40 to 100 years in the years 2015 and 2040, while accounting for different assumptions on future trends in T2D incidence and mortality. Results: Assuming a constant incidence rate, women and men at age 40 years in 2015 will live approximately 38 years and 33 years free of T2D, respectively. Up to the year 2040, these numbers are projected to increase by 1.0 years and 1.3 years. Assuming a decrease in T2D-associated excess mortality of 2% per year, women and men aged 40 years with T2D in 2015 will be expected to lose 1.6 and 2.7 years of life, respectively, compared to a same aged person without T2D. In 2040, these numbers would reduce by approximately 0.9 years and 1.6 years. This translates to 10.8 million and 6.4 million YLL in the German population aged 40–100 years with prevalent T2D in 2015 and 2040, respectively. Conclusions: Given expected trends in mortality and no increase in T2D incidence, the burden due to premature mortality associated with T2D will decrease on the individual as well as on the population level. In addition, the expected lifetime without T2D is likely to increase. However, these trends strongly depend on future improvements of excess mortality associated with T2D and future incidence of T2D, which should motivate increased efforts of primary and tertiary prevention.Peer Reviewe

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.Peer Reviewe

Productivity-adjusted life years lost due to type 2 diabetes in Germany in 2020 and 2040

Aims/hypothesis!#!Type 2 diabetes can lead to reduced productivity during working age. We aimed to estimate productive life years lost associated with type 2 diabetes on the individual and population level in Germany in 2020 and 2040, while accounting for future trends in mortality.!##!Methods!#!Based on a mathematical projection model, we estimated age- and sex-specific productivity losses associated with type 2 diabetes during working age (20-69 years) in Germany in 2020 and 2040. Productivity losses in terms of excess mortality (years of life lost, YLL) and reductions in labour force participation, presenteeism and absenteeism (years of productivity lost, YPL) were summed to calculate productivity-adjusted life years (PALY) lost. Input data for the projection were based on meta-analyses, representative population-based studies and population projections to account for future trends in mortality.!##!Results!#!Compared with a person without type 2 diabetes, mean PALY lost per person with type 2 diabetes in 2020 was 2.6 years (95% CI 2.3, 3.0). Of these 2.6 years, 0.4 (95% CI 0.3, 0.4) years were lost due to YLL and 2.3 (95% CI 1.9, 2.6) years were lost due to YPL. Age- and sex-specific results show that younger age groups and women are expected to lose more productive life years than older age groups and men. Population-wide estimates suggest that 4.60 (95% CI 4.58, 4.63) million people with prevalent type 2 diabetes in 2020 are expected to lose 12.06 (95% CI 10.42, 13.76) million PALY (1.62 million years due to YLL and 10.44 million years due to YPL). In 2040, individual-level PALY lost are projected to slightly decrease due to reductions in YLL. In contrast, population-wide PALY lost are projected to increase to 15.39 (95% CI 13.19, 17.64) million due to an increase in the number of people with type 2 diabetes to 5.45 (95% CI 5.41, 5.50) million.!##!Conclusions/interpretation!#!On the population level, a substantial increase in productivity burden associated with type 2 diabetes was projected for Germany between 2020 and 2040. Efforts to reduce the incidence rate of type 2 diabetes and diabetes-related complications may attenuate this increase

Importance of Diagnostic Accuracy in Big Data: False-Positive Diagnoses of Type 2 Diabetes in Health Insurance Claims Data of 70 Million Germans

Brinks R, Tönnies T, Hoyer A. Importance of Diagnostic Accuracy in Big Data: False-Positive Diagnoses of Type 2 Diabetes in Health Insurance Claims Data of 70 Million Germans. Frontiers in Epidemiology. 2022;2: 887335.Large data sets comprising diagnoses of chronic conditions are becoming increasingly available for research purposes. In Germany, it is planned that aggregated claims data – including medical diagnoses from the statutory health insurance – with roughly 70 million insurants will be published regularly. The validity of the diagnoses in such big datasets can hardly be assessed. In case the dataset comprises prevalence, incidence, and mortality, it is possible to estimate the proportion of false-positive diagnoses using mathematical relations from the illness-death model. We apply the method to age-specific aggregated claims data from 70 million Germans about type 2 diabetes in Germany stratified by sex and report the findings in terms of the age-specific ratio of false-positive diagnoses of type 2 diabetes (FPR) in the dataset. The FPR for men and women changes with age. In men, the FPR increases linearly from 1 to 3 per 1,000 in the age group of 30–50 years. For age between 50 and 80 years, FPR remains below 4 per 1,000. After 80 years of age, we have an increase to approximately 5 per 1,000. In women, we find a steep increase from age 30 to 60 years, the peak FPR is reached at approximately 12 per 1,000 between 60 and 70 years of age. After age 70 years, the FPR of women drops tremendously. In all age groups, the FPR is higher in women than in men. In terms of absolute numbers, we find that there are 217,000 people with a false-positive diagnosis in the dataset (95% confidence interval, CI: 204–229), the vast majority being women (172,000, 95% CI: 162–180). Our work indicates that possible false-positive (and negative) diagnoses should appropriately be dealt with in claims data, for example, by the inclusion of age- and sex-specific error terms in statistical models, to avoid potentially biased or wrong conclusions

Comment on Nanditha et al. Secular TRends in DiabEtes in India (STRiDE–I): Change in Prevalence in 10 Years Among Urban and Rural Populations in Tamil Nadu. Diabetes Care 2019;42:476–485

Tönnies T, Hoyer A, Brinks R. Comment on Nanditha et al. Secular TRends in DiabEtes in India (STRiDE–I): Change in Prevalence in 10 Years Among Urban and Rural Populations in Tamil Nadu. Diabetes Care 2019;42:476–485. Diabetes Care. 2019;42(8):e138-e138

Future prevalence of type 2 diabetes—A comparative analysis of chronic disease projection methods

Voeltz D, Tönnies T, Brinks R, Hoyer A. Future prevalence of type 2 diabetes—A comparative analysis of chronic disease projection methods. PLOS ONE. 2022;17(3): e0264739.**Background** Accurate projections of the future number of people with chronic diseases are necessary for effective resource allocation and health care planning in response to changes in disease burden. **Aim** To introduce and compare different projection methods to estimate the number of people with diagnosed type 2 diabetes (T2D) in Germany in 2040. **Methods** We compare three methods to project the number of males with T2D in Germany in 2040. Method 1) simply combines the sex- and age-specific prevalence of T2D in 2010 with future population distributions projected by the German Federal Statistical Office (FSO). Methods 2) and 3) additionally account for the incidence of T2D and mortality rates using partial differential equations (PDEs). Method 2) models the prevalence of T2D employing a scalar PDE which incorporates incidence and mortality rates. Subsequently, the estimated prevalence is applied to the population projection of the FSO. Method 3) uses a two-dimensional system of PDEs and estimates future case numbers directly while future mortality of people with and without T2D is modelled independently from the projection of the FSO. **Results** Method 1) projects 3.6 million male people with diagnosed T2D in Germany in 2040. Compared to 2.8 million males in 2010, this equals an increase by 29%. Methods 2) and 3) project 5.9 million (+104% compared to 2010) and 6.0 million (+116%) male T2D patients, respectively. **Conclusions** The results of the three methods differ substantially. It appears that ignoring temporal trends in incidence and mortality may result in misleading projections of the future number of people with chronic diseases. Hence, it is essential to include these rates as is done by method 2) and 3)

Future number of people with diagnosed type 1 diabetes in Germany until 2040: an analysis based on claims data

Voeltz D, Brinks R, Tönnies T, Hoyer A. Future number of people with diagnosed type 1 diabetes in Germany until 2040: an analysis based on claims data. BMJ Open Diabetes Research & Care. 2023;11(2): e003156.**Introduction** We aim to project the number of people with diagnosed type 1 diabetes in Germany between 2010 and 2040. **Research design and methods** We first estimate the age-specific and sex-specific incidence and prevalence of type 1 diabetes in Germany in 2010 using data from 65 million insurees of the German statutory health insurance. Then, we use the illness-death model to project the prevalence of type 1 diabetes until 2040. We alter the incidence and mortality underlying the illness-death model in several scenarios to explore the impact of possible temporal trends on the number of people with type 1 diabetes. **Results** Applying the prevalence from 2010 to the official population projections of Germany’s Federal Statistical Office yields a total number of 252 000 people with type 1 diabetes in Germany in 2040 (+1% compared with 2010). Incorporating different annual trends of the incidence and mortality in the projection model results in a future number of people with type 1 diabetes between 292 000 (+18%) and 327 000 (+32%). **Conclusions** For the first time in Germany, we provide estimates for the incidence, prevalence, and number of people with diagnosed type 1 diabetes for the whole German population between 2010 and 2040. The relative increase of the people with type 1 diabetes ranges from 1% to 32% in 2040 compared with 2010. The projected results are mainly influenced by temporal trends in the incidence. Ignoring these trends, that is, applying a constant prevalence to population projections, probably underestimates future chronic disease numbers

Spatio-Temporal Trends in the Incidence of Type 2 Diabetes in Germany

Tönnies T, Hoyer A, Brinks R, Kuss O, Hering R, Schulz M. Spatio-Temporal Trends in the Incidence of Type 2 Diabetes in Germany. Deutsches Ärzteblatt international . 2023;120(11):173-179.BACKGROUND: There are no data on recent trends in the incidence rate of type 2 diabetes (T2D) in Germany. The aim of this study was to determine the sex-, age-, and region-specific trends in the T2D incidence rate between 2014 and 2019.; METHODS: Based on nationwide data from statutorily insured persons in Germany, negative binomial regression models were used to analyze age- and sex-specific trends in the T2D incidence rate. Age- and sex-adjusted trends were calculated for 401 administrative districts using a Bayesian spatio-temporal regression model.; RESULTS: During the period concerned, approximately 450 000 new cases of T2D were observed each year among some 63 million persons. Taking all age groups together, the incidence rate decreased in both women and men, from 6.9 (95% confidence interval [6.7; 7.0]) and 8.4 [8.2; 8.6] respectively per 1000 persons in 2014 to 6.1 [5.9; 6.3] and 7.7 [7.5; 8.0] per 1000 persons in 2019. This corresponds to an annual reduction of 2.4% [1.5; 3.2] for women and 1.7% [0.8; 2.5] for men. The incidence rate increased in the age group 20-39 years. The age- and sex-adjusted incidence rate decreased in almost all districts, although regional differences persisted.; CONCLUSION: The T2D incidence rate should be closely monitored to see whether the decreasing trend continues. One must not forget that the prevalence can rise despite decreasing incidence. For this reason, the findings do not necessarily mean a decrease in the disease burden of T2D and the associated demand on healthcare resources