Evidence map›Paper›PMID 37058154›Full record

ReviewInnere Medizin (Heidelberg, Germany)2023

[Prevalence of metabolic syndrome : Analysis based on routine statutory health insurance data].

Sabrina Schütte, Sveja Eberhard, Birte Burger, Melissa Hemmerling, Siegbert Rossol, Jona T Stahmeyer

Abstract readEnglish AbstractReview
PubMed Publisher
In one paragraph

Review in Innere Medizin (Heidelberg, Germany), 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

  1. Article
  2. 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

6 authors.

Sabrina SchütteStabsbereich Versorgungsforschung, AOK Niedersachsen. Die Gesundheitskasse, Hildesheimer Str. 273, 30519, Hannover, Deutschland. sabrina.schuette@nds.aok.de.
Sveja EberhardStabsbereich Versorgungsforschung, AOK Niedersachsen. Die Gesundheitskasse, Hildesheimer Str. 273, 30519, Hannover, Deutschland.
Birte BurgerStabsbereich Versorgungsforschung, AOK Niedersachsen. Die Gesundheitskasse, Hildesheimer Str. 273, 30519, Hannover, Deutschland.
Melissa HemmerlingStabsbereich Versorgungsforschung, AOK Niedersachsen. Die Gesundheitskasse, Hildesheimer Str. 273, 30519, Hannover, Deutschland.
Siegbert RossolMedizinische Klinik, Krankenhaus Nordwest, Steinbacher Hohl 2-26, 60488, Frankfurt, Deutschland.
Jona T StahmeyerStabsbereich Versorgungsforschung, AOK Niedersachsen. Die Gesundheitskasse, Hildesheimer Str. 273, 30519, Hannover, Deutschland.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundThe metabolic syndrome is a decisive risk factor for the manifestation of cardiovascular and metabolic diseases. Metabolic syndrome is the term used to describe the joint presence of specific diseases (obesity, hypertension, type 2 diabetes mellitus, disorders of fat metabolism). A classification is made more difficult by inconsistent definition criteria and a missing International Statistical Classification of Diseases and Related Health Problems (ICD) code. There are no known prevalence studies for Germany based on routine data of the statutory health insurance (GKV).

objectiveThe main aim of the present study was to classify the metabolic syndrome based on routine data of the GKV and to estimate the frequency of diagnosis. In addition, the influence of social factors (school and educational qualifications) was examined for the subgroup of employees with social insurance. MATERIAL AND

methodsA retrospective routine data analysis was carried out based on routine administrative data from the AOK Lower Saxony (AOKN). In contrast to the established definitions, which use medical parameters, the risk factors are taken into account via four coded diagnoses according to the ICD-10 classification: 1) obesity (E66.0, E66.8, E66.9), 2) type 2 diabetes mellitus (E11), 3) hypertension (I10) and 4) metabolic disorders (E78). A metabolic syndrome is present if at least two of the four diagnoses are present.

resultsThe prevalence of metabolic syndrome in the population of the AOKN in 2019 was 25.7%. The standardized comparison according to the census population of 2011 showed an increase in the frequency of diagnosis (2009: 21.5% and 2019: 24%). The frequency of diagnosis differed according to school and educational qualifications.

conclusionA classification and analysis of the frequency of the metabolic syndrome based on routine data of the GKV is possible. Between 2009 and 2019 there was a clear increase in the frequency of diagnoses.

Indexed as

Diabetes Mellitus, Type 2HypertensionMetabolic SyndromeHumansInsurance, HealthObesityPrevalenceRetrospective StudiesEducational status, professionalEducational status, schoolMetabolic syndrome/epidemiologyMetabolic syndrome/frequency of diagnosisSocial factors

Identifiers

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Registered trials

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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.