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BACKGROUND: The prevalence of coexisting chronic conditions (multimorbidity) is rising. Disease labels, however, give little information about impact on subjective health and personal illness experience. We aim to examine the strength of association of single and multimorbid physical chronic diseases with self-rated health in a middle-aged and older population in England, and to determine whether any association is mediated by depression and other psychosocial factors. METHODS: 25 268 individuals aged 39 to 79 years recruited from general practice registers in the European Prospective Investigation of Cancer (EPIC-Norfolk) study, completed a survey including self-rated health, psychosocial function and presence of common physical chronic conditions (cancer, stroke, heart attack, diabetes, asthma/bronchitis and arthritis). Logistic regression models determined odds of "moderate/poor" compared to "good/excellent" health by condition and number of conditions adjusting for psychosocial measures. RESULTS: One-third (8252) reported one, around 7.5% (1899) two, and around 1% (194) three or more conditions. Odds of "moderate/poor" self-rated health worsened with increasing number of conditions (one (OR = 1.3(1.2-1.4)) versus three or more (OR = 3.4(2.3-5.1)), and were highest where there was comorbidity with stroke (OR = 8.7(4.6-16.7)) or heart attack (OR = 8.5(5.3-13.6)). Psychosocial measures did not explain the association between chronic diseases and multimorbidity with self-rated health.The relationship of multimorbidity with self-rated health was particularly strong in men compared to women (three or more conditions: men (OR = 5.2(3.0-8.9)), women OR = 2.1(1.1-3.9)). CONCLUSIONS: Self-rated health provides a simple, integrative patient-centred assessment for evaluation of illness in the context of multiple chronic disease diagnoses. Those registering in general practice in particular men with three or more diseases or those with cardiovascular comorbidities and with poorer self-rated health may warrant further assessment and intervention to improve their physical and subjective health. ; EPIC-Norfolk is supported by programme grants from Medical Research Council UK (G9502233, G0300128) and Cancer Research UK (C865/A2883), with additional support from the European Union, Stroke Association, Research into Ageing, British Heart Foundation, Department of Health and Wellcome Trust. ; This is the final version. It was first published by BioMed Central at http://www.biomedcentral.com/1471-2296/15/185

The purpose of this study was to ascertain multimorbidity patterns using a non-hierarchical cluster analysis in adult primary patients with multimorbidity attended in primary care centers in Catalonia. Methods Cross-sectional study using electronic health records from 523,656 patients, aged 45–64 years in 274 primary health care teams in 2010 in Catalonia, Spain. Data were provided by the Information System for the Development of Research in Primary Care (SIDIAP), a population database. Diagnoses were extracted using 241 blocks of diseases (International Classification of Diseases, version 10). Multimorbidity patterns were identified using two steps: 1) multiple correspondence analysis and 2) k-means clustering. Analysis was stratified by sex. Results The 408,994 patients who met multimorbidity criteria were included in the analysis (mean age, 54.2 years [Standard deviation, SD: 5.8], 53.3% women). Six multimorbidity patterns were obtained for each sex; the three most prevalent included 68% of the women and 66% of the men, respectively. The top cluster included coincident diseases in both men and women: Metabolic disorders, Hypertensive diseases, Mental and behavioural disorders due to psychoactive substance use, Other dorsopathies, and Other soft tissue disorders. Conclusion Non-hierarchical cluster analysis identified multimorbidity patterns consistent with clinical practice, identifying phenotypic subgroups of patients ; The project has been funded by the Instituto de Salud Carlos III of the Ministry of Economy and Competitiveness (Spain) through the Network for Prevention and Health Promotion in Primary Health Care (redIAPP, RD12/0005), by a grant for research projects on health from ISCiii (PI12/00427) and co-financed with European Union ERDF funds). Jose M. Valderas was supported by the National Institute for Health Research Clinician Scientist Award NIHR/CS/010/024

Abstract Background Health surveys (HS) are a well-established methodology for measuring the health status of a population. The relative merit of using information based on HS versus electronic health records (EHR) to measure multimorbidity has not been established. Our study had two objectives: 1) to measure and compare the prevalence and distribution of multimorbidity in HS and EHR data, and 2) to test specific hypotheses about potential differences between HS and EHR reporting of diseases with a symptoms-based diagnosis and those requiring diagnostic testing. Methods Cross-sectional study using data from a periodic HS conducted by the Catalan government and from EHR covering 80% of the Catalan population aged 15 years and older. We determined the prevalence of 27 selected health conditions in both data sources, calculated the prevalence and distribution of multimorbidity (defined as the presence of ≥2 of the selected conditions), and determined multimorbidity patterns. We tested two hypotheses: a) health conditions requiring diagnostic tests for their diagnosis and management would be more prevalent in the EHR; and b) symptoms-based health problems would be more prevalent in the HS data. Results We analysed 15,926 HS interviews and 1,597,258 EHRs. The profile of the EHR sample was 52% women, average age 47 years (standard deviation: 18.8), and 68% having at least one of the selected health conditions, the 3 most prevalent being hypertension (20%), depression or anxiety (16%) and mental disorders (15%). Multimorbidity was higher in HS than in EHR data (60% vs. 43%, respectively, for ages 15-75+, P <0.001, and 91% vs. 83% in participants aged ≥65 years, P <0.001). The most prevalent multimorbidity cluster was cardiovascular. Circulation disorders (other than varicose veins), chronic allergies, neck pain, haemorrhoids, migraine or frequent headaches and chronic constipation were more prevalent in the HS. Most symptomatic conditions (71%) had a higher prevalence in the HS, while less than a third of conditions requiring diagnostic tests were more prevalent in EHR. Conclusions Prevalence of multimorbidity varies depending on age and the source of information. The prevalence of self-reported multimorbidity was significantly higher in HS data among younger patients; prevalence was similar in both data sources for elderly patients. Self-report appears to be more sensitive to identifying symptoms-based conditions. A comprehensive .