Evidence map›Paper›PMID 26629347›Full record

ArticleBMJ open diabetes research & care2015

Changes in diabetes care indicators: findings from German National Health Interview and Examination Surveys 1997-1999 and 2008-2011.

Yong Du, Christin Heidemann, Angelika Schaffrath Rosario, Amanda Buttery, Rebecca Paprott, Hannelore Neuhauser, Thea Riedel, Andrea Icks, Christa Scheidt-Nave

Abstract read
In one paragraph

Article in BMJ open diabetes research & care, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 34 papers.

0numbers the graph read from it
0cells of the map it votes in
34citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

34 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
  4. Article
  5. [Development and Internal Validation of Case Definitions for Prevalence Estimation of Microvascular Complications of Diabetes in Routine Data].Gesundheitswesen (Bundesverband der Arzte des Offentlichen Gesundheitsdienstes (Germany)) · 2024
    Article
  6. Article
  7. Article
  8. Article
  9. [Effectiveness and Ethical Evaluation of Nudging to Promote the Self-Management in Diabetes Mellitus Type 2].Gesundheitswesen (Bundesverband der Arzte des Offentlichen Gesundheitsdienstes (Germany)) · 2022
    Review
  10. Review
  11. Article
  12. Article
  13. Article
  14. Article
  15. Observational
  16. Article
  17. Article
  18. Observational
  19. Article
  20. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

9 authors.

Yong DuDepartment of Epidemiology and Health Monitoring , Robert Koch Institute , Berlin , Germany.
Christin HeidemannDepartment of Epidemiology and Health Monitoring , Robert Koch Institute , Berlin , Germany.
Angelika Schaffrath RosarioDepartment of Epidemiology and Health Monitoring , Robert Koch Institute , Berlin , Germany.
Amanda ButteryKing's College London , Faculty of Life Sciences and Medicine , London , UK.
Rebecca PaprottDepartment of Epidemiology and Health Monitoring , Robert Koch Institute , Berlin , Germany.
Hannelore NeuhauserDepartment of Epidemiology and Health Monitoring , Robert Koch Institute , Berlin , Germany.
Thea RiedelDepartment of Epidemiology and Health Monitoring , Robert Koch Institute , Berlin , Germany.
Andrea IcksJean Philippe Assal Group for Health Services Research and Health Economics , German Diabetes Center , Düsseldorf , Germany ; Public Health Unit, Faculty of Medicine , Heinrich-Heine University , Düsseldorf , Germany ; German Centre for Diabetes Research (DZD) , Munich , Germany.
Christa Scheidt-NaveDepartment of Epidemiology and Health Monitoring , Robert Koch Institute , Berlin , Germany.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

objectivesTo investigate changes in type 2 diabetes care indicators over time in Germany.

methodsAdults aged 45-79 years with type 2 diabetes were identified from two national health examination surveys conducted in 1997-1999 (GNHIES98, n=333) and in 2008-2011 (DEGS1, n=526). We examined diabetes care indicators including treatment and preventive targets (glycemic control, blood pressure (BP), total cholesterol (TC), smoking, weight reduction, sports activity), self-management and care process measures (glucose self-monitoring, holding a diabetes passport, annual foot and eye examination; statin use), and the presence of diabetes-specific complications (diabetic nephropathy, retinopathy, neuropathy, diabetic foot, amputations) and comorbid cardiovascular disease (CVD) or chronic kidney disease (CKD). We calculated proportions of persons meeting these care indicators by survey and examined unadjusted and adjusted changes between surveys.

resultsSignificant improvement (GNHIES98 vs DEGS1) over time was observed for glycated hemoglobin (HbA1c) <7.0% (53 mmol/mol) (32.4% vs 65.4%), BP <130/80 mm Hg (32.0% vs 47.2%), TC <190 mg/dL (13.5% vs 41.9%), statin use (11.7% vs 35.9%), eye (51.1% vs 78.4%) and foot (48.0% vs 61.4%) examination within the past 12 months, diabetes-specific complications (29.7% vs 21.8%), and CVD (44.5% vs 37.1%). Blood glucose self-monitoring significantly increased (37.4% vs 62.8%), while holding a diabetes passport did not change. Current smoking did not change and obesity rose, although sports activity significantly increased over time. Proportions of adults achieving combination goals of HbA1c, BP, TC, and smoking cessation were low in both surveys in spite of significant improvement.

conclusionsIn Germany, the quality of diabetes care improved over time. There is much room for improvement, in particular regarding preventive goals and diabetes self-management.

Indexed as

ChangeNational Health SurveysQuality of CareType 2 Diabetes

Identifiers

PMID26629347
PMCPMC4653864

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.