Evidence map›Paper›PMID 25342083›Full record

ArticleHealth and quality of life outcomes2014

Health-related quality of life for pre-diabetic states and type 2 diabetes mellitus: a cross-sectional study in Västerbotten Sweden.

Anne Neumann, Olaf Schoffer, Fredrik Norström, Margareta Norberg, Stefanie J Klug, Lars Lindholm

Abstract read
In one paragraph

Article in Health and quality of life outcomes, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 24 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
24citing papers in PubMed, 2 pooled it
–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

24 citing papers in PubMed, 2 syntheses or guidelines pooled it.

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  8. Glycemic status and health-related quality of life (HRQOL) in populations at risk of diabetes in two Latin American cities.Quality of life research : an international journal of quality of life aspects of treatment, care and rehabilitation · 2023
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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.

Anne NeumannEpidemiology and Global Health, Department of Public Health and Clinical Medicine, Umeå University, SE-901 87, Umeå, Sweden. anne.neumann@uniklinikum-dresden.de.
Olaf SchofferCancer Epidemiology, University Cancer Center, University Hospital, Technische Universität Dresden, Fetscherstr. 74, 01307, Dresden, Germany. olaf.schoffer@uniklinikum-dresden.de.
Fredrik NorströmEpidemiology and Global Health, Department of Public Health and Clinical Medicine, Umeå University, SE-901 87, Umeå, Sweden. fredrik.norstrom@epiph.umu.se.
Margareta NorbergEpidemiology and Global Health, Department of Public Health and Clinical Medicine, Umeå University, SE-901 87, Umeå, Sweden. margareta.norberg@epiph.umu.se.
Stefanie J KlugCancer Epidemiology, University Cancer Center, University Hospital, Technische Universität Dresden, Fetscherstr. 74, 01307, Dresden, Germany. stefanie.klug@uniklinikum-dresden.de.
Lars LindholmEpidemiology and Global Health, Department of Public Health and Clinical Medicine, Umeå University, SE-901 87, Umeå, Sweden. lars.lindholm@epiph.umu.se.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundType 2 diabetes (T2D) decreases health-related quality of life, but there is a lack of information about the health status of people in pre-diabetic states. However, information on health utility weights (HUWs) for pre-diabetic states and T2D are essential to estimate the effect of prevention initiatives. We estimated and compared HUWs for healthy individuals, those with pre-diabetes and those with T2D in a Swedish population and evaluated the influence of age, sex, education and body mass index on HUWs.

methodsParticipants of the Västerbotten Intervention Program, Sweden, between 2002 and 2012, who underwent an oral glucose tolerance test or indicated they had T2D and who filled in the Short Form-36 questionnaire (SF-36) were included. Individuals were categorized as healthy, being in any of three different pre-diabetic states, or as T2D. The pre-diabetic states are impaired fasting glucose (IFG), impaired glucose tolerance (IGT) or a combination of both (IFG&IGT). The SF-6D index was used to convert SF-36 responses to HUWs. HUWs were stratified by age, sex, education and body mass index. Beta regression analyses were conducted to estimate the effect of multiple risk factors on the HUWs.

resultsIn total, 55 882 individuals were included in the analysis. The overall mean HUW was 0.764. The mean HUW of healthy individuals was 0.768, 0.759 for those with IFG, 0.746 for those with IGT, 0.745 for those with IFG&IGT, and 0.738 for those with T2D. In the overall model, all variables except underweight vs. normal weight were significantly associated with HUW. Younger age, male sex, and higher education were associated with increased HUW. Normal weight, or being overweight was associated with elevated HUW, while obesity was associated with lower HUW.

conclusionsHealthy individuals had higher HUWs than participants with T2D, while individuals with IFG, IGT or IFG&IGT had HUWs that ranged between those for NGT and T2D. Therefore, preventing the development of pre-diabetic states would improve health-related quality of life in addition to lowering the risk of developing T2D.

Indexed as

Health StatusQuality of LifeAdultBlood GlucoseCross-Sectional StudiesDiabetes Mellitus, Type 2HumansMaleMiddle AgedPrediabetic StateSurveys and QuestionnairesSwedenBlood Glucose

Identifiers

PMID25342083
PMCPMC4212131

What OpenQuestion holds

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LicenceCC BY
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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.