For Publishers
DiscoveryMetadataPeer reviewHostingPublishing
For Researchers
JoinPublishReviewCollect
Register
Blog
About
Search
Advanced search
My ScienceOpen
Search
For Publishers
For Researchers
Blog
About
14
views
26
references
 Top references
cited by
40
    
0 reviews
 Review
0
comments
 Comment
0
recommends
+1 Recommend
0 collections
    0
    shares
      135
      similar
       All similar
      • Record: found
      • Abstract: found
      • Article: found
      Is Open Access

      The impact of comorbid chronic conditions on quality of life in type 2 diabetes patients

      research-article

      Read this article at

      ScienceOpenPublisherPMC
      Bookmark
          There is no author summary for this article yet. Authors can add summaries to their articles on ScienceOpen to make them more accessible to a non-specialist audience.

          Abstract

          Objective

          To study the prevalence, impact and dose–response relationship of comorbid chronic conditions on quality of life of type 2 diabetes patients.

          Research design and methods

          Cross-sectional data of 1676 type 2 diabetes patients, aged 31–96 years, and treated in primary care, were analyzed. Quality of life (QoL) was measured using the mental component summary (MCS) and the physical component summary (PCS) scores of the Short Form-12. Diagnosis of type 2 diabetes was obtained from medical records and comorbidities from self-reports.

          Results

          Only 361 (21.5 %) of the patients reported no comorbidities. Diabetes patients with comorbidities showed significantly lower mean difference in PCS [−8.5; 95 % confidence interval (CI) −9.8 to −7.3] and MCS scores (−1.9; 95 % CI −3.0 to −0.9), compared to diabetes patients without. Additional adjustments did not substantially change these associations. Both MCS and PCS scores decrease significantly with the number of comorbid conditions, yet most pronounced regarding physical QoL. Comorbidities that reduced physical QoL most significantly were retinopathy, heart diseases, atherosclerosis in abdomen or legs, lung diseases, incontinence, back, neck and shoulder disorder, osteoarthritis and chronic rheumatoid arthritis, using the backwards stepwise regression procedure.

          Conclusion

          Comorbidities are highly prevalent among type 2 diabetes patients and have a negative impact on the patient’s QoL. A strong dose–response relationship between comorbidities and physical QoL was found. Reduced physical QoL is mainly determined by musculoskeletal and cardiovascular disorders.

          Related collections

          Most cited references26

          • Record: found
          • Abstract: found
          • Article: found
          Is Open Access

          Health-related quality of life in diabetes: The associations of complications with EQ-5D scores

          Oddvar Solli, Knut Stavem, IS Kristiansen (2010)
          Background The aim of this study was to describe how diabetes complications influence the health-related quality of life of individuals with diabetes using the individual EQ-5D dimensions and the EQ-5D index. Methods We mailed a questionnaire to 1,000 individuals with diabetes type 1 and 2 in Norway. The questionnaire had questions about socio-demographic characteristics, use of health care, diabetes complications and finally the EQ-5D descriptive system. Logistic regressions were used to explore determinants of responses in the EQ-5D dimensions, and robust linear regression was used to explore determinants of the EQ-5D index. Results In multivariate analyses the strongest determinants of reduced MOBILITY were neuropathy and ischemic heart disease. In the ANXIETY/DEPRESSION dimension of the EQ-5D, "fear of hypoglycaemia" was a strong determinant. For those without complications, the EQ-5D index was 0.90 (type 1 diabetes) and 0.85 (type 2 diabetes). For those with complications, the EQ-5D index was 0.68 (type 1 diabetes) and 0.73 (type 2 diabetes). In the linear regression the factors with the greatest negative impact on the EQ-5D index were ischemic heart disease (type 1 diabetes), stroke (both diabetes types), neuropathy (both diabetes types), and fear of hypoglycaemia (type 2 diabetes). Conclusions The EQ-5D dimensions and the EQ-5D seem capable of capturing the consequences of diabetes-related complications, and such complications may have substantial impact on several dimensions of health-related quality of life (HRQoL). The strongest determinants of reduced HRQoL in people with diabetes were ischemic heart disease, stroke and neuropathy.
          Article 0 comments Cited 140 times – based on 0 reviews     Review now
            Bookmark
            • Record: found
            • Abstract: found
            • Article: found
            Is Open Access

            Subjective assessments of comorbidity correlate with quality of life health outcomes: Initial validation of a comorbidity assessment instrument

            Elizabeth Bayliss, Jennifer Ellis, John Steiner (2005)
            Background Interventions to improve care for persons with chronic medical conditions often use quality of life (QOL) outcomes. These outcomes may be affected by coexisting (comorbid) chronic conditions as well as the index condition of interest. A subjective measure of comorbidity that incorporates an assessment of disease severity may be particularly useful for assessing comorbidity for these investigations. Methods A survey including a list of 25 common chronic conditions was administered to a population of HMO members age 65 or older. Disease burden (comorbidity) was defined as the number of self-identified comorbid conditions weighted by the degree (from 1 to 5) to which each interfered with their daily activities. We calculated sensitivities and specificities relative to chart review for each condition. We correlated self-reported disease burden, relative to two other well-known comorbidity measures (the Charlson Comorbidity Index and the RxRisk score) and chart review, with our primary and secondary QOL outcomes of interest: general health status, physical functioning, depression screen and self-efficacy. Results 156 respondents reported an average of 5.9 chronic conditions. Median sensitivity and specificity relative to chart review were 75% and 92% respectively. QOL outcomes correlated most strongly with disease burden, followed by number of conditions by chart review, the Charlson Comorbidity Index and the RxRisk score. Conclusion Self-report appears to provide a reasonable estimate of comorbidity. For certain QOL assessments, self-reported disease burden may provide a more accurate estimate of comorbidity than existing measures that use different methodologies, and that were originally validated against other outcomes. Investigators adjusting for comorbidity in studies using QOL outcomes may wish to consider using subjective comorbidity measures that incorporate disease severity.
            Article 0 comments Cited 85 times – based on 0 reviews     Review now
              Bookmark
              • Record: found
              • Abstract: found
              • Article: not found

              Monitoring health inequalities through general practice: the Second Dutch National Survey of General Practice.

              F. Schellevis, J Dalén, J Bensing … (2005)
              For the second time a plan to monitor public health and health inequalities in the Netherlands through general practice was put into action: the Second National Survey of General Practice (DNSGP-2, 2001). The first aim of this paper is to describe the general design of DNSGP-2. Secondly, to describe self assessed health inequalities in the Netherlands. Thirdly, to present differences in prevalence of chronic conditions by educational attainment using both self-assessed health and medical records of GPs. Finally, inequalities in 1987 (DNSGP-1) and 2001 will be compared. Data were collected from 96 (1987) and 104 (2001) general practices. The data include background information on patients collected via a census, approximately 12,000 health interview surveys per time point and more than one million recorded contacts of patients with their GPs in both years. The method of statistical analysis is logistic regression. The analyses shows that the lower educated have significantly higher odds of feeling unhealthy and having chronic conditions in 2001. Diabetes and myocardial infarction (GP data) showed the largest difference in prevalence between educational groups (OR 2.5 and 2.4, self-reported data). The way the data is collected (self-assessment versus GP registration) hardly affects the magnitude of the educational differences in the prevalence of chronic conditions. The pattern of health inequalities across chronic conditions in 1987 and 2001 hardly differs. Diabetes doubled in prevalence and health inequalities were not significant in 1987, but compared to the other conditions were largest in 2001 (OR 1.1 versus 2.5). Health inequalities were shown to be substantial in 2001 and persistent over time. Socio-economic differences were shown to be similar using self-assessed health data and GP data. Hence, a person's educational attainment did not appear to play a part in presenting health problems to the GP.
              Article 0 comments Cited 74 times – based on 0 reviews     Review now
                Bookmark
                All references

                Author and article information

                Contributors
                Marcel C. Adriaanse: +31 20 59 89946 , marcel.adriaanse@falw.vu.nl , marcel.adriaanse@vu.nl
                Journal
                Journal ID (nlm-ta): Qual Life Res
                Journal ID (iso-abbrev): Qual Life Res
                Title: Quality of Life Research
                Publisher: Springer International Publishing (Cham )
                ISSN (Print): 0962-9343
                ISSN (Electronic): 1573-2649
                Publication date (Electronic): 13 August 2015
                Publication date PMC-release: 13 August 2015
                Publication date (Print): 2016
                Volume: 25
                Pages: 175-182
                Affiliations
                [ ]Department of Health Sciences and EMGO Institute for Health and Care Research, VU University Amsterdam, De Boelelaan 1085, 1081 HV Amsterdam, The Netherlands
                [ ]Centre for Nutrition, Prevention and Health Services, National Institute for Public Health and the Environment, Bilthoven, The Netherlands
                Article
                Publisher ID: 1061
                DOI: 10.1007/s11136-015-1061-0
                PMC ID: 4706581
                PubMed ID: 26267523
                SO-VID: 44945d8d-bdce-4357-ac7d-663400453724
                Copyright © © The Author(s) 2015
                License:

                Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License ( http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made.

                History
                Date accepted : 1 July 2015
                Categories
                Subject: Article
                Custom metadata
                issue-copyright-statement © Springer International Publishing Switzerland 2016

                ScienceOpen disciplines: Public health
                Keywords: type 2 diabetes,comorbidities,quality of life,primary care
                Data availability:
                ScienceOpen disciplines: Public health
                Keywords: type 2 diabetes, comorbidities, quality of life, primary care

                Comments

                Comment on this article

                scite_

                Similar content135

                See all similar

                Cited by40

                See all cited by

                Most referenced authors600

                See all reference authors