Michaela Schunk

Regional differences in the prevalence of known Type 2 diabetes mellitus in 45–74 years old individuals: Results from six population‐based studies in Germany (DIAB‐CORE Consortium)

Diabet. Med. 29, e88–e95 (2012)

Multimorbidity and health-related quality of life in the older population: results from the German KORA-Age study

BackgroundMultimorbidity in the older population is well acknowledged to negatively affect health-related quality of life (HRQL). Several studies have examined the independent effects of single diseases; however, little research has focused on interaction between diseases. The purpose of this study was to assess the impact of six self-reported major conditions and their combinations on HRQL measured by the EQ-5D.MethodsThe EQ-5D was administered in the population-based KORA-Age study of 4,565 Germans aged 65 years or older. A generalised additive regression model was used to assess the effects of chronic conditions on HRQL and to account for the nonlinear associations with age and body mass index (BMI). Disease interactions were identified by a forward variable selection method.ResultsThe conditions with the greatest negative impact on the EQ-5D index were the history of a stroke (regression coefficient -11.3, p < 0.0001) and chronic bronchitis (regression coefficient -8.1, p < 0.0001). Patients with both diabetes and coronary disorders showed more impaired HRQL than could be expected from their separate effects (coefficient of interaction term -8.1, p < 0.0001). A synergistic effect on HRQL was also found for the combination of coronary disorders and stroke. The effect of BMI on the mean EQ-5D index was inverse U-shaped with a maximum at around 24.8 kg/m2.ConclusionsThere are important interactions between coronary problems, diabetes mellitus, and the history of a stroke that negatively affect HRQL in the older German population. Not only high but also low BMI is associated with impairments in health status.

Health-related quality of life in subjects with and without Type 2 diabetes: pooled analysis of five population-based surveys in Germany.

Diabet. Med. 29, 646–653 (2012)

Medical care of type 2 diabetes in German Disease Management Programmes: a population‐based evaluation

Type 2 diabetes disease management programmes (DDMPs) are offered by German social health insurance to promote healthcare consistent with evidence‐based medical guidelines. The aim of this study was to compare healthcare quality and medical endpoints between diabetes management programme participants and patients receiving usual care designated as controls.

Blood pressure and lipid management fall far short in persons with type 2 diabetes: results from the DIAB-CORE Consortium including six German population-based studies

BackgroundAlthough 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.MethodsThe 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.ResultsThe 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.ConclusionsBlood 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.

Regional differences in the incidence of self-reported type 2 diabetes in Germany: results from five population-based studies in Germany (DIAB-CORE Consortium)

Background Population-based data are paramount to investigate the long-term course of diabetes, for planning in healthcare and to evaluate the cost-effectiveness of primary prevention. We analysed regional differences in the incidence of self-reported type 2 diabetes mellitus in Germany. Methods Data of participants (baseline age 45–74 years) from five regional population-based studies conducted between 1997 and 2010 were included (mean follow-up 2.2–7.1 years). The incidence of self-reported type 2 diabetes mellitus at follow-up was compared. The incidence rates per 1000 person-years (95% CI) and the cumulative incidence (95% CI) from regional studies were directly standardised to the German population (31 December 2007) and weighted by inverse probability weights for losses to follow-up. Results Of 8787 participants, 521 (5.9%) developed type 2 diabetes mellitus corresponding to an incidence rate of 11.8/1000 person-years (95% CI 10.8 to 12.9). The regional incidence was highest in the East and lowest in the South of Germany with 16.9 (95% CI 13.3 to 21.8) vs 9.3 (95% CI 7.4 to 11.1)/1000 person-years, respectively. The incidence increased with age and was higher in men than in women. Conclusions The incidence of self-reported type 2 diabetes mellitus shows regional differences within Germany. Prevention measures need to consider sex-specific differences and probably can be more efficiently introduced toward those regions in need.

Anthropometric markers and their association with incident type 2 diabetes mellitus: which marker is best for prediction? Pooled analysis of four German population-based cohort studies and comparison with a nationwide cohort study

Objective To compare the association between different anthropometric measurements and incident type 2 diabetes mellitus (T2DM) and to assess their predictive ability in different regions of Germany. Methods Data of 10 258 participants from 4 prospective population-based cohorts were pooled to assess the association of body weight, body mass index (BMI), waist circumference (WC), waist-to-hip-ratio (WHR) and waist-to-height-ratio (WHtR) with incident T2DM by calculating HRs of the crude, adjusted and standardised markers, as well as providing receiver operator characteristic (ROC) curves. Differences between HRs and ROCs for the different anthropometric markers were calculated to compare their predictive ability. In addition, data of 3105 participants from the nationwide survey were analysed separately using the same methods to provide a nationally representative comparison. Results Strong associations were found for each anthropometric marker and incidence of T2DM. Among the standardised anthropometric measures, we found the strongest effect on incident T2DM for WC and WHtR in the pooled sample (HR for 1 SD difference in WC 1.97, 95% CI 1.75 to 2.22, HR for WHtR 1.93, 95% CI 1.71 to 2.17 in women) and in female DEGS participants (HR for WC 2.24, 95% CI 1.91 to 2.63, HR for WHtR 2.10, 95% CI 1.81 to 2.44), whereas the strongest association in men was found for WHR among DEGS participants (HR 2.29, 95% CI 1.89 to 2.78). ROC analysis showed WHtR to be the strongest predictor for incident T2DM. Differences in HR and ROCs between the different markers confirmed WC and WHtR to be the best predictors of incident T2DM. Findings were consistent across study regions and age groups (<65 vs ≥65 years). Conclusions We found stronger associations between anthropometric markers that reflect abdominal obesity (ie, WC and WHtR) and incident T2DM than for BMI and weight. The use of these measurements in risk prediction should be encouraged.

Health-related quality of life in women and men with type 2 diabetes: a comparison across treatment groups

AIM This study compares health-related quality of life (HRQL) in patients with type 2 diabetes (T2DM) across treatment groups and explores gender differences. METHODS Four regional surveys (KORA, CARLA, SHIP, DHS) and a national survey (GNHIES98) were pooled at individual level. HRQL was assessed with the SF-12/-36v1. Linear regression models were used to assess the effect of T2DM by treatment type (no medication; oral; oral/insulin combination; insulin) on the physical (PCS-12) and mental summary score (MCS-12) and the SF-6D, controlling for age, sex, study and covariates. We also performed an explanatory analysis of single items. RESULTS PCS-12 scores and treatment type were associated (P-value 0.006), with lowest values for insulin treatment (-4.44 vs. oral; -4.41 vs. combination). MCS-12 scores were associated with treatment type and gender (P-value <0.012), with lower scores for women undergoing oral (-4.25 vs. men) and combination treatment (-6.99 vs. men). Similar results were observed for SF-6D utilities and single items, related to mental health, social functioning, vitality and role limitation (emotional). Comorbidities were predictors of lower PCS-12 and SF-6D scores. CONCLUSIONS T2DM treatment impacts differently on physical and mental HRQL and on women and men. Further studies of gender-specific perceptions of T2DM treatment regimens are needed.

Regional Differences of Undiagnosed Type 2 Diabetes and Prediabetes Prevalence Are Not Explained by Known Risk Factors

Background We have previously found regional differences in the prevalence of known type 2 diabetes between northeastern and southern Germany. We aim to also provide prevalence estimates for prediabetes (isolated impaired fasting glucose (i-IFG), isolated glucose intolerance (i-IGT), combined IFG and IGT) and unknown type 2 diabetes for both regions. Methods Prevalence (95%CI) of prediabetes (i-IFG: fasting glucose 5.6–6.9 mmol/l; i-IGT: 2 h postchallenge gluose 7.8–11.0 mmol/l, oral glucose tolerance test (OGTT), ≥8 h overnight fasting) and unknown diabetes were analyzed in two regional population-based surveys (age group 35–79 years): SHIP-TREND (Study of Health in Pomerania (northeast), 2008–2012) and KORA F4 (Cooperative Health Research in the region of Augsburg (south), 2006–2008). Both studies used similar methods, questionnaires, and identical protocols for OGTT. Overall, 1,980 participants from SHIP-TREND and 2,617 participants from KORA F4 were included. Results Age-sex-standardized prevalence estimates (95%CI) of prediabetes and unknown diabetes were considerably higher in the northeast (SHIP-TREND: 43.1%; 40.9–45.3% and 7.1%; 5.9–8.2%) than in the south of Germany (KORA F4: 30.1%; 28.4–31.7% and 3.9%; 3.2–4.6%), respectively. In particular, i-IFG (26.4%; 24.5–28.3% vs. 17.2%; 15.7–18.6%) and IFG+IGT (11.2%; 9.8–12.6% vs. 6.6%; 5.7–7.5%) were more frequent in SHIP-TREND than in KORA. In comparison to normal glucose tolerance, the odds of having unknown diabetes (OR, 95%CI: 2.59; 1.84–3.65) or prediabetes (1.98; 1.70–2.31) was higher in the northeast than in the south after adjustment for known risk factors (obesity, lifestyle). Conclusions The regional differences of prediabetes and unknown diabetes are in line with the geographical pattern of known diabetes in Germany. The higher prevalences in the northeast were not explained by traditional risk factors.

The Association Between Patient-Reported Self-Management Behavior, Intermediate Clinical Outcomes, and Mortality in Patients With Type 2 Diabetes: Results From the KORA-A Study

OBJECTIVE Little is known about the impact of diabetes self-management behavior (SMB) on long-term outcomes. We aimed to examine the association among patient-reported SMB, intermediate clinical outcomes, and mortality in patients with type 2 diabetes. RESEARCH DESIGN AND METHODS Data were collected from 340 patients with type 2 diabetes of the KORA-A study (1997/1998) who were recruited from two previous population-based surveys (n = 161) and a myocardial infarction registry (n = 179) in southern Germany. Based on previous methodological work, a high level of SMB was defined as being compliant with at least four of six different self-care dimensions, comprising physical exercise, foot care, blood glucose self-monitoring, weight monitoring, having a diet plan, and keeping a diabetes diary. The vital status of the participants was observed until 2009. Multivariable linear, logistic, and Cox regression models were applied to assess the association with intermediate clinical outcomes at baseline and to predict mortality over the follow-up period, adjusted for sociodemographic, behavioral, and disease-related factors. RESULTS In the cross-sectional perspective, a high level of SMB was weakly associated with a lower glycated hemoglobin A1c level (−0.44% [−4.8 mmol/mol] [95% CI −0.88 to 0.00]), but not with low-density lipoprotein cholesterol, systolic blood pressure, or the presence of microalbuminuria, peripheral arterial disease, or polyneuropathy. During a mean follow-up time of 11.6 years, 189 patients died. SMB was a preventive factor for all-cause (hazard ratio 0.61 [95% CI 0.40–0.91]) and cardiovascular mortality (0.65 [95% CI 0.41–1.03]). CONCLUSIONS Although measuring SMB is difficult and the used operationalization might be limited, our results give some indication that a high level of SMB is associated with prolonged life expectancy in patients with type 2 diabetes and highlight the potential impact of the patients’ active contribution on the long-term trajectory of the disease. We assume that the used proxy for SMB is associated with unmeasured, but important, dimensions of health behavior.