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      Multimorbidity and comorbidity in the Dutch population – data from general practices

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          Abstract

          Background

          Multimorbidity is increasingly recognized as a major public health challenge of modern societies. However, knowledge about the size of the population suffering from multimorbidity and the type of multimorbidity is scarce. The objective of this study was to present an overview of the prevalence of multimorbidity and comorbidity of chronic diseases in the Dutch population and to explore disease clustering and common comorbidities.

          Methods

          We used 7 years data (2002–2008) of a large Dutch representative network of general practices (212,902 patients). Multimorbidity was defined as having two or more out of 29 chronic diseases. The prevalence of multimorbidity was calculated for the total population and by sex and age group. For 10 prevalent diseases among patients of 55 years and older (N = 52,014) logistic regressions analyses were used to study disease clustering and descriptive analyses to explore common comorbid diseases.

          Results

          Multimorbidity of chronic diseases was found among 13% of the Dutch population and in 37% of those older than 55 years. Among patients over 55 years with a specific chronic disease more than two-thirds also had one or more other chronic diseases. Most disease pairs occurred more frequently than would be expected if diseases had been independent. Comorbidity was not limited to specific combinations of diseases; about 70% of those with a disease had one or more extra chronic diseases recorded which were not included in the top five of most common diseases.

          Conclusion

          Multimorbidity is common at all ages though increasing with age, with over two-thirds of those with chronic diseases and aged 55 years and older being recorded with multimorbidity. Comorbidity encompassed many different combinations of chronic diseases. Given the ageing population, multimorbidity and its consequences should be taken into account in the organization of care in order to avoid fragmented care, in medical research and healthcare policy.

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          Most cited references18

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          Causes and consequences of comorbidity: a review.

          A literature search was carried out to identify and summarize the existing information on causes and consequences of comorbidity of chronic somatic diseases. A selection of 82 articles met our inclusion criteria. Very little work has been done on the causes of comorbidity. On the other hand, much work has been done on consequences of comorbidity, although comorbidity is seldom the main subject of study. We found comorbidity in general to be associated with mortality, quality of life, and health care. The consequences of specific disease combinations, however, depended on many factors. We recommend more etiological studies on shared risk factors, especially for those comorbidities that occur at a higher rate than expected. New insights in this field can lead to better prevention strategies. Health care workers need to take comorbid diseases into account in monitoring and treating patients. Future studies on consequences of comorbidity should investigate specific disease combinations.
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            Patterns of chronic multimorbidity in the elderly population.

            To describe patterns of comorbidity and multimorbidity in elderly people. A community-based survey. Data were gathered from the Kungsholmen Project, a urban, community-based prospective cohort in Sweden. Adults aged 77 and older living in the community and in institutions of the geographically defined Kungsholmen area of Stockholm (N=1,099). Diagnoses based on physicians' examinations and supported by hospital records, drug use, and blood samples. Patterns of comorbidity and multimorbidity were evaluated using four analytical approaches: prevalence figures, conditional count, logistic regression models, and cluster analysis. Visual impairments and heart failure were the diseases with the highest comorbidity (mean 2.9 and 2.6 co-occurring conditions, respectively), whereas dementia had the lowest (mean 1.4 comorbidities). Heart failure occurred rarely without any comorbidity (0.4%). The observed prevalence of comorbid pairs of conditions exceeded the expected prevalence for several circulatory diseases and for dementia and depression. Logistic regression analyses detected similar comorbid pairs. The cluster analysis revealed five clusters. Two clusters included vascular conditions (circulatory and cardiopulmonary clusters), and another included mental diseases along with musculoskeletal disorders. The last two clusters included only one major disease each (diabetes mellitus and malignancy) together with their most common consequences (visual impairment and anemia, respectively). In persons with multimorbidity, there exists co-occurrence of diseases beyond chance, which clinicians need to take into account in their daily practice. Some pathological mechanisms behind the identified clusters are well known; others need further clarification to identify possible preventative strategies.
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              Which chronic diseases and disease combinations are specific to multimorbidity in the elderly? Results of a claims data based cross-sectional study in Germany

              Background Growing interest in multimorbidity is observable in industrialized countries. For Germany, the increasing attention still goes still hand in hand with a small number of studies on multimorbidity. The authors report the first results of a cross-sectional study on a large sample of policy holders (n = 123,224) of a statutory health insurance company operating nationwide. This is the first comprehensive study addressing multimorbidity on the basis of German claims data. The main research question was to find out which chronic diseases and disease combinations are specific to multimorbidity in the elderly. Methods The study is based on the claims data of all insured policy holders aged 65 and older (n = 123,224). Adjustment for age and gender was performed for the German population in 2004. A person was defined as multimorbid if she/he had at least 3 diagnoses out of a list of 46 chronic conditions in three or more quarters within the one-year observation period. Prevalences and risk-ratios were calculated for the multimorbid and non-multimorbid samples in order to identify diagnoses more specific to multimorbidity and to detect excess prevalences of multimorbidity patterns. Results 62% of the sample was multimorbid. Women in general and patients receiving statutory nursing care due to disability are overrepresented in the multimorbid sample. Out of the possible 15,180 combinations of three chronic conditions, 15,024 (99%) were found in the database. Regardless of this wide variety of combinations, the most prevalent individual chronic conditions do also dominate the combinations: Triads of the six most prevalent individual chronic conditions (hypertension, lipid metabolism disorders, chronic low back pain, diabetes mellitus, osteoarthritis and chronic ischemic heart disease) span the disease spectrum of 42% of the multimorbid sample. Gender differences were minor. Observed-to-expected ratios were highest when purine/pyrimidine metabolism disorders/gout and osteoarthritis were part of the multimorbidity patterns. Conclusions The above list of dominating chronic conditions and their combinations could present a pragmatic start for the development of needed guidelines related to multimorbidity.
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                Author and article information

                Journal
                BMC Public Health
                BMC Public Health
                BMC Public Health
                BioMed Central
                1471-2458
                2012
                30 August 2012
                : 12
                : 715
                Affiliations
                [1 ]Centre for Prevention and Health Services Research, National Institute for Public Health and the Environment, P.O. Box 1, Bilthoven 3720 BA, the Netherlands
                [2 ]Centre for Public Health Forecasting, National Institute for Public Health and the Environment, P.O. Box 1, Bilthoven, 3720 BA, the Netherlands
                [3 ]Department of General Practice, Netherlands Institute for Health Services Research, P.O. Box 1568, Utrecht, 3500 BN, the Netherlands
                [4 ]Department of General Practice/EMGO Institute, VU University Medical Centre, Amsterdam, the Netherlands
                Article
                1471-2458-12-715
                10.1186/1471-2458-12-715
                3490727
                22935268
                9271c769-dc9d-4efc-a869-494c7dff9131
                Copyright ©2012 van Oostrom et al.; licensee BioMed Central Ltd.

                This is an Open Access article distributed under the terms of the Creative Commons Attribution License ( http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

                History
                : 5 March 2012
                : 10 August 2012
                Categories
                Research Article

                Public health
                comorbidity,prevalence,multimorbidity,epidemiology,chronic disease
                Public health
                comorbidity, prevalence, multimorbidity, epidemiology, chronic disease

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