Mortality of type 2 diabetes in Germany: additional insights from Gompertz models.

AIMS: The Gompertz law of mortality proclaims that human mortality rates in middle to old ages grow log-linearly with age and this law has been confirmed at multiple instances. We investigated if diabetes mortality in Germany also obeys to the Gompertz law and how this information helps to communicate diabetes mortality more intuitively. METHODS: We analyzed all statutory health-insured persons in Germany in 2013 that were aged 30 years or older. Deaths in 2014 were recorded and given in 5-year age groups. We fitted weighted linear regression models (separately for females and males and for people with and without diabetes) and additionally computed the probability that a person with diabetes dies before a person of the same age and sex without diabetes, and the "diabetes age", that is, the additional years of mortality risk added to an individual's chronological age due to diabetes-related excess mortality. RESULTS: We included N = 47,365,120 individuals, 6,541,181 of them with diabetes. In 2014, 763,228 deaths were recorded, among them 288,515 with diabetes. Diabetes mortality followed nearly perfectly Gompertz distributions. The probability that a person with diabetes dies before a person without diabetes was 61.9% for females and 63.3% for males. CONCLUSIONS: Diabetes mortality for females and males aged 30 years or older in Germany in 2014 followed the Gompertz law of mortality. The survival information of the population with diabetes during a large part of the lifespan can thus be reduced to the two parameters of the Gompertz distribution.

Mediation Analysis in Medical Research.

BACKGROUND: Mediation analysis addresses the question of the mechanisms by which an exposure causes an outcome. This article is intended to convey basic knowledge of statistical mediation analysis. METHODS: Selected articles and examples are used to explain the principle of mediation analysis. RESULTS: The goal of mediation analysis is to express an overall exposure effect as a combination of an indirect and a direct effect. For example, it might be of interest whether the increased risk of diabetes (outcome) due to obesity (exposure) is mediated by insulin resistance (indirect effect), and, if so, how much of a direct effect remains. In this example, insulin resistance is a potential mediator of the effect of obesity on the risk of diabetes. In general, for a mediation analysis to be valid, more confounders must be taken into account than in the estimation of the overall effect size. A regression-based approach can be used to ensure the consideration of all relevant confounders in a mediation analysis. CONCLUSION: By decomposing the overall exposure effect into indirect and direct components, a mediation analysis can reveal not just whether an exposure causes an outcome, but also how. For a mediation analysis to be valid, however, multiple assumptions must be satisfied that cannot easily be checked, potentially compromising such analyses as compared to the estimation of an overall effect.

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

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.

Age-specific incidence of need for long-term care for men and women in Germany 2015: Cross-sectional study comprising 82 million people.

Background: With the growing number of older people, the number of people in need of long-term care is increasing, too. Official statistics only report on the age-specific prevalence of long-term care. Therefore, there is no data on the age- and sex-specific incidence of the need for care at the population level for Germany available. Methods: Analytical relationships between age-specific prevalence, incidence rate, remission rate, all-cause mortality, and mortality rate ratio are used to estimate the age-specific incidence of long-term care among men and women in 2015. The data is based on the official prevalence data from the nursing care statistics for the years 2011 to 2019 and official mortality rates from the Federal Statistical Office. For Germany, there is no data on the mortality rate ratio of people with and without a need for care, which is why we use two extreme scenarios that were obtained in a systematic literature search to estimate the incidence. Results: The age-specific incidence is about 1 per 1000 person-years (PY) in men and women at the age of 50 and increases exponentially up to the age of 90. Up to about the age of 60, men have a higher incidence rate than women. Thereafter, women have a higher incidence. At the age of 90, women and men have an incidence rate of 145 to 200 and 94 to 153 per 1000 PY, respectively, depending on the scenario. Conclusion: We estimated the age-specific incidence of the need for long-term care for women and men in Germany for the first time. We observed a strong increase, leading to a huge number of people in need of long-term care in higher age groups. It is to be expected that this will result in an increased economic burden and a further increased need for nursing and medical staff.

Estimating incidence of type 1 and type 2 diabetes using prevalence data: the SEARCH for Diabetes in Youth study.

BACKGROUND: Incidence is one of the most important epidemiologic indices in surveillance. However, determining incidence is complex and requires time-consuming cohort studies or registries with date of diagnosis. Estimating incidence from prevalence using mathematical relationships may facilitate surveillance efforts. The aim of this study was to examine whether a partial differential equation (PDE) can be used to estimate diabetes incidence from prevalence in youth. METHODS: We used age-, sex-, and race/ethnicity-specific estimates of prevalence in 2001 and 2009 as reported in the SEARCH for Diabetes in Youth study. Using these data, a PDE was applied to estimate the average incidence rates of type 1 and type 2 diabetes for the period between 2001 and 2009. Estimates were compared to annual incidence rates observed in SEARCH. Precision of the estimates was evaluated using 95% bootstrap confidence intervals. RESULTS: Despite the long period between prevalence measures, the estimated average incidence rates mirror the average of the observed annual incidence rates. Absolute values of the age-standardized sex- and type-specific mean relative errors are below 8%. CONCLUSIONS: Incidence of diabetes can be accurately estimated from prevalence. Since only cross-sectional prevalence data is required, employing this methodology in future studies may result in considerable cost savings.

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

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.

Projections of Type 1 and Type 2 Diabetes Burden in the U.S. Population Aged <20 Years Through 2060: The SEARCH for Diabetes in Youth Study.

OBJECTIVE: To project the prevalence and number of youths with diabetes and trends in racial and ethnic disparities in the U.S. through 2060. RESEARCH DESIGN AND METHODS: Based on a mathematical model and data from the SEARCH for Diabetes in Youth study for calendar years 2002-2017, we projected the future prevalence of type 1 and type 2 diabetes among youth aged <20 years while considering different scenarios of future trends in incidence. RESULTS: The number of youths with diabetes will increase from 213,000 (95% CI 209,000; 218,000) (type 1 diabetes 185,000, type 2 diabetes 28,000) in 2017 to 239,000 (95% CI 209,000; 282,000) (type 1 diabetes 191,000, type 2 diabetes 48,000) in 2060 if the incidence remains constant as observed in 2017. Corresponding relative increases were 3% (95% CI -9%; 21%) for type 1 diabetes and 69% (95% CI 43%; 109%) for type 2 diabetes. Assuming that increasing trends in incidence observed between 2002 and 2017 continue, the projected number of youths with diabetes will be 526,000 (95% CI 335,000; 893,000) (type 1 diabetes 306,000, type 2 diabetes 220,000). Corresponding relative increases would be 65% (95% CI 12%; 158%) for type 1 diabetes and 673% (95% CI 362%; 1,341%) for type 2 diabetes. In both scenarios, substantial widening of racial and ethnic disparities in type 2 diabetes prevalence are expected, with the highest prevalence among non-Hispanic Black youth. CONCLUSIONS: The number of youths with diabetes in the U.S. is likely to substantially increase in future decades, which emphasizes the need for prevention to attenuate this trend.

Projected incidence trends of need for long-term care in German men and women from 2011 to 2021.

Background: The German Federal Statistical Office routinely collects and reports aggregated numbers of people in need of long-term care (NLTC) stratified by age and sex. Age- and sex-specific prevalence of NLTC from 2011 to 2021 is reported as well. One estimation of the incidence rate of NLTC based on the age- and sex-specific prevalence exists that did not explore possible trends in incidence [based on MRR (mortality rate ratio)], which is important for an adequate projection of the future number of people with NLTC. Objective: We aim to explore possible trends in age-specific incidence of NLTC in German men and women from 2011 to 2021 based on different scenarios about excess mortality (in terms of MRR). Methods: The incidence of NLTC was calculated based on an illness-death model and a related partial differential equation based on data from the Federal Statistical Office. Estimation of annual percent change (APC) of the incidence rate was conducted in eight scenarios. Results: There are consistent indications for trends in incidence for men and women aged 50-79 years with APC in incidence rate of more than +9% per year (up to nearly 19%). For ages 80+ the APC is between +0.4% and +12.5%. In all scenarios, women had higher age-specific APCs than men. Conclusion: We performed the first analysis of APC in the age- and sex-specific incidence rate of NLTC in Germany and revealed an increasing trend in the incidences. With these findings, a future prevalence of NLTC can be estimated which may exceed current prognoses.

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

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).

Collider Bias in Observational Studies.

BACKGROUND: The findings of observational studies can be distorted by a number of factors. So-called confounders are well known, but distortion by collider bias (CB) has received little attention in medical research to date. The goal of this article is to present the principle of CB, and measures that can be taken to avoid it, by way of a few illustrative examples. METHODS: The findings of a selective review of the literature on CB are explained with illustrative examples. RESULTS: The simplest case of a collider variable is one that is caused by at least two other variables. An example of CB is the observation that, among persons with diabetes, obesity is associated with lower mortality, even though it is associated with higher mortality in the general population. The false protective association between obesity and mortality arises from the restriction of the study population to persons with diabetes. CONCLUSION: CB is a distortion that arises through restriction on or stratification by a collider variable, or through statistical adjustment for a collider variable in a regression model. CB can arise in many ways. The graphic representation of causal structures helps to identify potential sources of CB. It is important to distinguish confounders from colliders, as methods that serve to correct for confounding can themselves cause bias when applied to colliders. There is no generally applicable method for correcting CB.

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

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.

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 ([Formula: see text]) 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 [Formula: see text] 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 [Formula: see text] 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.

Impact of diagnostic accuracy on the estimation of excess mortality from incidence and prevalence: simulation study and application to diabetes in German men.

Aggregated data about the prevalence and incidence of chronic conditions is becoming more and more available. We recently proposed a method to estimate the age-specific excess mortality in chronic conditions from aggregated age-specific prevalence and incidence data. Previous works showed that in age groups below 50 years, estimates from this method were unstable or implausible. In this article, we examine how limited diagnostic accuracy in terms of sensitivity and specificity affects the estimates. We use a simulation study with two settings, a low and a high prevalence setting, and assess the relative importance of sensitivity and specificity. It turns out that in both settings, specificity, especially in the younger age groups, dominates the quality of the estimated excess mortality. The findings are applied to aggregated claims data comprising the diagnoses of diabetes from about 35 million men in the German Statutory Health Insurance. Key finding is that specificity in the lower age groups (<50 years) can be derived without knowing the sensitivity. The false-positive ratio in the claims data increases linearly from 0.5 per mil at age 25 to 2 per mil at age 50. As a conclusion, our findings stress the importance of considering diagnostic accuracy when estimating excess mortality from aggregated data using the method to estimate excess mortality. Especially the specificity in the younger age-groups should be carefully taken into account.

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.

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.

Relative and absolute socioeconomic inequality in smoking: time trends in Germany from 1995 to 2013.

PURPOSE: This study aimed to investigate time trends in relative and absolute socioeconomic inequality in smoking prevalence in Germany using several indicators for socioeconomic position. METHODS: We conducted a repeated cross-sectional study using representative samples of the German population aged between 25 and 64 years in 1995, 1999, 2005, 2009, and 2013 (n = 857,264). Socioeconomic position was measured by indicators for income, education, and occupation. Relative and absolute socioeconomic inequalities were estimated with the regression-based relative index of inequality and the slope index of inequality, respectively. Trends in inequalities were estimated with interaction terms for time and relative index of inequality/slope index of inequality. RESULTS: Highest and increasing smoking prevalence was observed among long-term unemployed and people with less than 60% of the median household income. Between 1995 and 2013, relative increases in inequalities in smoking prevalence ranged from 31% (95% confidence interval, 26%-36%; men, occupation) to 94% (95% confidence interval, 84%-104%; women, education). Absolute increases ranged from 6.2 (95% confidence interval, 4.7-7.6) percentage points (men, occupation) to 20.3 (95% confidence interval, 18.9-21.7) percentage points (women, education). CONCLUSIONS: Relative and absolute socioeconomic inequalities in smoking prevalence increased in Germany between 1995 and 2013, with regard to income, education, and occupation, particularly among women.

Assessing two methods for estimating excess mortality of chronic diseases from aggregated data.

OBJECTIVE: To assess the numerical properties of two recently published estimation techniques for excess mortality based on aggregated data about diabetes in Germany. RESULTS: Application of the new methods to the claims data yields implausible findings for the excess mortality of type 2 diabetes in ages below 50 years of age.

Estimating prevalence of type I and type II diabetes using incidence rates: the SEARCH for diabetes in youth study.

PURPOSE: Most surveillance efforts in childhood diabetes have focused on incidence, whereas prevalence is rarely reported. This study aimed to assess whether a mathematical illness-death model accurately estimated future prevalence from baseline prevalence and incidence rates in children. METHODS: SEARCH for Diabetes in Youth is an ongoing population-based surveillance study of prevalence and incidence of diabetes and its complications among youth in the United States. We used age-, sex-, and race/ethnicity-specific SEARCH estimates of the prevalence of type I and type II diabetes in 2001 and incidence from 2002 to 2008. These data were used in a partial differential equation to estimate prevalence in 2009 with 95% bootstrap confidence intervals. Model-based prevalence was compared with the observed prevalence in 2009. RESULTS: Most confidence intervals for the difference between estimated and observed prevalence included zero, indicating no evidence for a difference between the two methods. The width of confidence intervals indicated high precision for the estimated prevalence when considering all races/ethnicities. In strata with few cases, precision was reduced. CONCLUSIONS: Future prevalence of type I and type II diabetes in youth may be accurately estimated from baseline prevalence and incidence. Diabetes surveillance could benefit from potential cost savings of this method.