The primary objective of this study was to identify the existence of chronic disease multimorbidity patterns in the primary care population, describing their clinical components and analysing how these patterns change and evolve over time both in women and men. The secondary objective of this study was to generate evidence regarding the pathophysiological processes underlying multimorbidity and to understand the interactions and synergies among the various diseases. This observational, retrospective, multicentre study utilised information from the electronic medical records of 19 primary care centres from 2008. To identify multimorbidity patterns, an exploratory factor analysis was carried out based on the tetra-choric correlations between the diagnostic information of 275,682 patients who were over 14 years of age. The analysis was stratified by age group and sex. Multimorbidity was found in all age groups, and its prevalence ranged from 13% in the 15 to 44 year age group to 67% in those 65 years of age or older. Goodness-of-fit indicators revealed sample values between 0.50 and 0.71. We identified five patterns of multimorbidity: cardio-metabolic, psychiatric-substance abuse, mechanical-obesity-thyroidal, psychogeriatric and depressive. Some of these patterns were found to evolve with age, and there were differences between men and women. Non-random associations between chronic diseases result in clinically consistent multimorbidity patterns affecting a significant proportion of the population. Underlying pathophysiological phenomena were observed upon which action can be taken both from a clinical, individual-level perspective and from a public health or population-level perspective.

The coexistence of several chronic diseases in one same individual, known as multimorbidity, is an important challenge facing health care systems in developed countries. Recent studies have revealed the existence of multimorbidity patterns clustering systematically associated distinct clinical entities. We sought to describe age and gender differences in the prevalence and patterns of multimorbidity in men and women over 65 years.

Background: The epidemiologic study of comorbidities of an index health problem represents a methodological challenge. This study cross-sectionally describes and analyzes the comorbidities associated with dementia in older patients and reviews the existing similarities and differences between identified comorbid diseases using the statistical methods most frequently applied in current research. Methods: Cross-sectional study of 72,815 patients over 64 seen in 19 Spanish primary care centers during 2008. Chronic diseases were extracted from electronic health records and grouped into Expanded Diagnostic Clusters®. Three different statistical methods were applied (i.e., analysis of prevalence data, multiple regression and factor analysis), stratifying by sex. Results: The two most frequent comorbidities both for men and women with dementia were hypertension and diabetes. Yet, logistic regression and factor analysis demonstrated that the comorbidities significantly associated with dementia were Parkinson’s disease, congestive heart failure, cerebrovascular disease, anemia, cardiac arrhythmia, chronic skin ulcers, osteoporosis, thyroid disease, retinal disorders, prostatic hypertrophy, insomnia and anxiety and neurosis. Conclusions: The analysis of the comorbidities associated with an index disease (e.g., dementia) must not be exclusively based on prevalence rates, but rather on methodologies that allow the discovery of non-random associations between diseases. A deep and reliable knowledge about how different diseases are grouped and associated around an index disease such as dementia may orient future longitudinal studies aimed at unraveling causal associations.

The consequences of multimorbidity include polypharmacy and repeated referrals for specialised care, which may increase the risk of adverse drug events (ADEs). The objective of this study was to analyse the influence of multimorbidity, polypharmacy, and multiple referrals on the frequency of ADEs, as an indicator of therapeutic safety, in the context of a national healthcare system. This was a multicentre, retrospective, observational study of 79 089 adult patients treated during 2008 in primary care centres. The explanatory patient variables sex, age, level of multimorbidity, polypharmacy, number of primary care physician visits, and number of different specialties attended were analysed. The response variable was the occurrence of ADEs. Logistic regression models were used to identify associations among the analysed variables. The prevalence of individuals with at least one ADE was 0.88%. Multivariate analysis identified the following variables as risk factors for the occurrence of ADE in descending order of effect size: multimorbidity level (odds ratio [OR]Veryhigh/Low = 45.26; ORHigh/Low = 17.58; ORModerate/Low = 4.25), polypharmacy (OR = 1.34), female sex (OR = 1.31), number of different specialties (OR = 1.20), and number of primary care physician visits (OR = 1.01). Age, however, did not show statistical significance (OR = 1.00; 95% confidence interval = 0.996 to 1.005). The results of this study demonstrate that multimorbidity is strongly related to the occurrence of ADEs, insofar as it requires the intervention of multiple specialties and the prescription of multiple medications. Further research should shed light on the causal pathway between multimorbidity and increased risk of adverse events.

Aging is an important risk factor for most chronic diseases. Patients with COPD develop more comorbidities than non-COPD subjects. We hypothesized that the development of comorbidities characteristically affecting the elderly occur at an earlier age in subjects with the diagnosis of COPD. We included all subjects carrying the diagnosis of COPD (n = 27,617), and a similar number of age and sex matched individuals without the diagnosis, extracted from the 727,241 records of individuals 40 years and older included in the EpiChron Cohort (Aragon, Spain). We compared the cumulative number of comorbidities, their prevalence and the mortality risk between both groups. Using network analysis, we explored the connectivity between comorbidities and the most influential comorbidities in both groups. We divided the groups into 5 incremental age categories and compared their comorbidity networks. We then selected those comorbidities known to affect primarily the elderly and compared their prevalence across the 5 age groups. In addition, we replicated the analysis in the smokers’ subgroup to correct for the confounding effect of cigarette smoking. Subjects with COPD had more comorbidities and died at a younger age compared to controls. Comparison of both cohorts across 5 incremental age groups showed that the number of comorbidities, the prevalence of diseases characteristic of aging and network’s density for the COPD group aged 56–65 were similar to those of non-COPD 15 to 20 years older. The findings persisted after adjusting for smoking. Multimorbidity increases with age but in patients carrying the diagnosis of COPD, these comorbidities are seen at an earlier age.