oalib
Search Results: 1 - 10 of 100 matches for " "
All listed articles are free for downloading (OA Articles)
Page 1 /100
Display every page Item
Multimorbidity and health-related quality of life in the older population: results from the German KORA-Age study
Matthias Hunger, Barbara Thorand, Michaela Schunk, Angela D?ring, Petra Menn, Annette Peters, Rolf Holle
Health and Quality of Life Outcomes , 2011, DOI: 10.1186/1477-7525-9-53
Abstract: The EQ-5D was administered in the population-based KORA-Age study of 4,565 Germans aged 65 years or older. A generalised additive regression model was used to assess the effects of chronic conditions on HRQL and to account for the nonlinear associations with age and body mass index (BMI). Disease interactions were identified by a forward variable selection method.The conditions with the greatest negative impact on the EQ-5D index were the history of a stroke (regression coefficient -11.3, p < 0.0001) and chronic bronchitis (regression coefficient -8.1, p < 0.0001). Patients with both diabetes and coronary disorders showed more impaired HRQL than could be expected from their separate effects (coefficient of interaction term -8.1, p < 0.0001). A synergistic effect on HRQL was also found for the combination of coronary disorders and stroke. The effect of BMI on the mean EQ-5D index was inverse U-shaped with a maximum at around 24.8 kg/m2.There are important interactions between coronary problems, diabetes mellitus, and the history of a stroke that negatively affect HRQL in the older German population. Not only high but also low BMI is associated with impairments in health status.Multimorbidity, defined as the coexistence of two or more chronic conditions, is a common phenomenon among the older population worldwide: two recent population-based studies indicated that the prevalence of multimorbidity ranges between 40% and 56% in the general population aged 65 years and older [1,2]. Multimorbidity is known to negatively affect health outcomes including mortality, hospitalisation, and readmission [3].Health-related quality of life (HRQL) is a health outcome measure which is increasingly used to assess the medical effectiveness of interventions and to support allocation decisions in the health care sector. Generic HRQL instruments like the EQ-5D are appropriate for non-disease-specific analyses and allow comparisons between patient groups with different medical conditions [
Multimorbidity Patterns in a National Representative Sample of the Spanish Adult Population  [PDF]
Noe Garin, Beatriz Olaya, Jaime Perales, Maria Victoria Moneta, Marta Miret, Jose Luis Ayuso-Mateos, Josep Maria Haro
PLOS ONE , 2014, DOI: 10.1371/journal.pone.0084794
Abstract: Background In the context of population aging, multimorbidity has emerged as a growing concern in public health. However, little is known about multimorbidity patterns and other issues surrounding chronic diseases. The aim of our study was to examine multimorbidity patterns, the relationship between physical and mental conditions and the distribution of multimorbidity in the Spanish adult population. Methods Data from this cross-sectional study was collected from the COURAGE study. A total of 4,583 participants from Spain were included, 3,625 aged over 50. An exploratory factor analysis was conducted to detect multimorbidity patterns in the population over 50 years of age. Crude and adjusted binary logistic regressions were performed to identify individual associations between physical and mental conditions. Results Three multimorbidity patterns rose: ‘cardio-respiratory’ (angina, asthma, chronic lung disease), ‘mental-arthritis’ (arthritis, depression, anxiety) and the ‘aggregated pattern’ (angina, hypertension, stroke, diabetes, cataracts, edentulism, arthritis). After adjusting for covariates, asthma, chronic lung disease, arthritis and the number of physical conditions were associated with depression. Angina and the number of physical conditions were associated with a higher risk of anxiety. With regard to multimorbidity distribution, women over 65 years suffered from the highest rate of multimorbidity (67.3%). Conclusion Multimorbidity prevalence occurs in a high percentage of the Spanish population, especially in the elderly. There are specific multimorbidity patterns and individual associations between physical and mental conditions, which bring new insights into the complexity of chronic patients. There is need to implement patient-centered care which involves these interactions rather than merely paying attention to individual diseases.
Distribution and determinants of functioning and disability in aged adults - results from the German KORA-Age study
Ralf Strobl, Martin Müller, Rebecca Emeny, Annette Peters, Eva Grill
BMC Public Health , 2013, DOI: 10.1186/1471-2458-13-137
Abstract: The objective of our study is to examine the frequency, distribution and determinants of functioning and disability in aged persons and to assess the contribution of diseases to the prevalence of disability.Data originate from the MONICA/KORA study, a population-based epidemiological cohort. Survivors of the original cohorts who were 65 and older were examined by telephone interview in 2009. Disability was assessed with the Health Assessment Questionnaire Disability Index (HAQ-DI). Minimal disability was defined as HAQ-DI > 0. Logistic regression was used to adjust for potential confounders and additive regression to estimate the contribution of diseases to disability prevalence.We analyzed a total of 4117 persons (51.2% female) with a mean age of 73.6 years (SD = 6.1). Minimal disability was present in 44.7% of all participants. Adjusted for age and diseases, disability was positively associated with female sex, BMI, low income, marital status, physical inactivity and poor nutritional status, but not with smoking and education. Problems with joint functions and eye diseases contributed most to disability prevalence in all age groups.In conclusion, this study could show that there are vulnerable subgroups of aged adults who should receive increased attention, specifically women, those with low income, those over 80, and persons with joint or eye diseases. Physical activity, obesity and malnutrition were identified as modifiable factors for future targeted interventions.
Patterns of multimorbidity in working Australians
Libby Holden, Paul A Scuffham, Michael F Hilton, Alexander Muspratt, Shu-Kay Ng, Harvey A Whiteford
Population Health Metrics , 2011, DOI: 10.1186/1478-7954-9-15
Abstract: The Australian Work Outcomes Research Cost-benefit (WORC) study cross-sectional screening dataset (approximately 78,000 working Australians) was used to explore patterns of multimorbidity. Exploratory factor analysis was used to identify nonrandomly occurring clusters of multimorbid health conditions.Six clinically-meaningful groups of multimorbid health conditions were identified. These were: factor 1: arthritis, osteoporosis, other chronic pain, bladder problems, and irritable bowel; factor 2: asthma, chronic obstructive pulmonary disease, and allergies; factor 3: back/neck pain, migraine, other chronic pain, and arthritis; factor 4: high blood pressure, high cholesterol, obesity, diabetes, and fatigue; factor 5: cardiovascular disease, diabetes, fatigue, high blood pressure, high cholesterol, and arthritis; and factor 6: irritable bowel, ulcer, heartburn, and other chronic pain. These clusters do not fall neatly into organ or body systems, and some conditions appear in more than one cluster.Considerably more research is needed with large population-based datasets and a comprehensive set of reliable health diagnoses to better understand the complex nature and composition of multimorbid health conditions.The term 'comorbidity' was first used in 1970 by Feinstein (as cited by Kessler et al, 2001 [1]) and by van den Akker et al [2,3] to refer to situations where an individual has two or more physical and/or mental health conditions. More recently, the term multimorbidity was introduced [2-4]. Although comorbidity and multimorbidity are both used to describe two or more health conditions, a distinction is made between these two terms. Comorbidity is used when an index condition of interest is being discussed, and multimorbidity is used when no reference condition is considered [4]. Although these distinctions often are not clearly applied, and both terms are used interchangeably in the literature, we will use this definition of these terms in this paper. Sometimes hea
The influence of age, gender and socio-economic status on multimorbidity patterns in primary care. first results from the multicare cohort study
Ingmar Sch?fer, Heike Hansen, Gerhard Sch?n, Susanne H?fels, Attila Altiner, Anne Dahlhaus, Jochen Gensichen, Steffi Riedel-Heller, Siegfried Weyerer, Wolfgang A Blank, Hans-Helmut K?nig, Olaf von dem Knesebeck, Karl Wegscheider, Martin Scherer, Hendrik van den Bussche, Birgitt Wiese
BMC Health Services Research , 2012, DOI: 10.1186/1472-6963-12-89
Abstract: The MultiCare Cohort Study is a multicentre, prospective, observational cohort study of 3.189 multimorbid patients aged 65+ randomly selected from 158 GP practices. Data were collected in GP interviews and comprehensive patient interviews. Missing values have been imputed by hot deck imputation based on Gower distance in morbidity and other variables. The association of patient characteristics with the number of chronic conditions is analysed by multilevel mixed-effects linear regression analyses.Multimorbidity in general is associated with age (+0.07 chronic conditions per year), gender (-0.27 conditions for female), education (-0.26 conditions for medium and -0.29 conditions for high level vs. low level) and income (-0.27 conditions per logarithmic unit). The pattern of cardiovascular and metabolic disorders shows comparable associations with a higher coefficient for gender (-1.29 conditions for female), while multimorbidity within the pattern of ADS and pain correlates with gender (+0.79 conditions for female), but not with age or socioeconomic status.Our study confirms that the morbidity load of multimorbid patients is associated with age, gender and the socioeconomic status of the patients, but there were no effects of living arrangements and marital status. We could also show that the influence of patient characteristics is dependent on the multimorbidity pattern concerned, i.e. there seem to be at least two types of elderly multimorbid patients. First, there are patients with mainly cardiovascular and metabolic disorders, who are more often male, have an older age and a lower socio-economic status. Second, there are patients mainly with ADS and pain-related morbidity, who are more often female and equally distributed across age and socio-economic groups.ISRCTN89818205Over the last decade, a noticeable deal of epidemiological research has concentrated on multimorbidity in the elderly. In most studies multimorbidity means the presence of several chronic disease
Which chronic diseases and disease combinations are specific to multimorbidity in the elderly? Results of a claims data based cross-sectional study in Germany
Hendrik van den Bussche, Daniela Koller, Tina Kolonko, Heike Hansen, Karl Wegscheider, Gerd Glaeske, Eike-Christin von Leitner, Ingmar Sch?fer, Gerhard Sch?n
BMC Public Health , 2011, DOI: 10.1186/1471-2458-11-101
Abstract: 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.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.The above list of dominating chronic conditions and their combinations could present a pragmatic start for the development of needed guidelines related to multimorbidity.Driven by increasing longevity and the rise of healthcare costs, a growing interest in multimorbidity is observable in industrialized countries [1]. Still, there is a far smaller number of studies on multimorbidity than on individual chronic diseases [2]. Pioneering work on multimorbidity has been done in a few countries, in particular Australia [3,4], Canada [5,6], The Netherlands [7,8], and Sweden [9,10]. Al
Multimorbidity Patterns in the Elderly: A New Approach of Disease Clustering Identifies Complex Interrelations between Chronic Conditions  [PDF]
Ingmar Sch?fer,Eike-Christin von Leitner,Gerhard Sch?n,Daniela Koller,Heike Hansen,Tina Kolonko,Hanna Kaduszkiewicz,Karl Wegscheider,Gerd Glaeske,Hendrik van den Bussche
PLOS ONE , 2012, DOI: 10.1371/journal.pone.0015941
Abstract: Multimorbidity is a common problem in the elderly that is significantly associated with higher mortality, increased disability and functional decline. Information about interactions of chronic diseases can help to facilitate diagnosis, amend prevention and enhance the patients' quality of life. The aim of this study was to increase the knowledge of specific processes of multimorbidity in an unselected elderly population by identifying patterns of statistically significantly associated comorbidity.
Multimorbidity Patterns in Primary Care: Interactions among Chronic Diseases Using Factor Analysis  [PDF]
Alexandra Prados-Torres, Beatriz Poblador-Plou, Amaia Calderón-Larra?aga, Luis Andrés Gimeno-Feliu, Francisca González-Rubio, Antonio Poncel-Falcó, Antoni Sicras-Mainar, José Tomás Alcalá-Nalvaiz
PLOS ONE , 2012, DOI: 10.1371/journal.pone.0032190
Abstract: Objectives 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. Methods 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. Results 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. Conclusions 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.
Age- and gender-related prevalence of multimorbidity in primary care: the swiss fire project  [cached]
Rizza Alessandro,Kaplan Vladimir,Senn Oliver,Rosemann Thomas
BMC Family Practice , 2012, DOI: 10.1186/1471-2296-13-113
Abstract: Background General practitioners often care for patients with several concurrent chronic medical conditions (multimorbidity). Recent data suggest that multimorbidity might be observed more often than isolated diseases in primary care. We explored the age- and gender-related prevalence of multimorbidity and compared these estimates to the prevalence estimates of other common specific diseases found in Swiss primary care. Methods We analyzed data from the Swiss FIRE (Family Medicine ICPC Research using Electronic Medical Record) project database, representing a total of 509,656 primary care encounters in 98,152 adult patients between January 1, 2009 and July 31, 2011. For each encounter, medical problems were encoded using the second version of the International Classification of primary Care (ICPC-2). We defined chronic health conditions using 147 pre-specified ICPC-2 codes and defined multimorbidity as 1) two or more chronic health conditions from different ICPC-2 rubrics, 2) two or more chronic health conditions from different ICPC-2 chapters, and 3) two or more medical specialties involved in patient care. We compared the prevalence estimates of multimorbidity defined by the three methodologies with the prevalence estimates of common diseases encountered in primary care. Results Overall, the prevalence estimates of multimorbidity were similar for the three different definitions (15% [95%CI 11-18%], 13% [95%CI 10-16%], and 14% [95%CI 11-17%], respectively), and were higher than the prevalence estimates of any specific chronic health condition (hypertension, uncomplicated 9% [95%CI 7-11%], back syndrome with and without radiating pain 6% [95%CI 5-7%], non-insulin dependent diabetes mellitus 3% [95%CI 3-4%]), and degenerative joint disease 3% [95%CI 2%-4%]). The prevalence estimates of multimorbidity rose more than 20-fold with age, from 2% (95%CI 1-2%) in those aged 20–29 years, to 38% (95%CI 31-44%) in those aged 80 or more years. The prevalence estimates of multimorbidity were similar for men and women (15% vs. 14%, p=0.288). Conclusions In primary care, prevalence estimates of multimorbidity are higher than those of isolated diseases. Among the elderly, more than one out of three patients suffer from multimorbidity. Management of multimorbidity is a principal concern in this vulnerable patient population.
Similar Multimorbidity Patterns in Primary Care Patients from Two European Regions: Results of a Factor Analysis  [PDF]
Beatriz Poblador-Plou, Marjan van den Akker, Rein Vos, Amaia Calderón-Larra?aga, Job Metsemakers, Alexandra Prados-Torres
PLOS ONE , 2014, DOI: 10.1371/journal.pone.0100375
Abstract: Objective To compare the similarities among the multimorbidity patterns identified in primary care patients from two European regions (Spain and the Netherlands) with similar organisational features of their primary care systems, using validated methodologies. Methodology This observational, retrospective, multicentre study analysed information from primary care electronic medical records. Multimorbidity patterns were assessed using exploratory factor analysis of the diagnostic information of patients over 14 years of age. The analysis was stratified by age groups and sex. Results The analysis of Dutch data revealed a higher prevalence of multimorbidity which corresponds with the clustering of a higher number of diseases in each of the patterns. Relevant clinical similarities were found between both countries for three multimorbidity patterns that were previously identified in the original Spanish study: cardiometabolic, mechanical and psychiatric-substance abuse. In addition, the clinical evolution towards complexity of the cardiometabolic pattern with advancing age -already demonstrated in the original study- was corroborated in the Dutch context. A clear association between mechanical and psychosocial disorders was unique to the Dutch population, as well as the recurrent presentation of the psychiatric-substance abuse pattern in all age and sex groups. Conclusions The similarities found for the cardiometabolic, mechanical and psychiatric-substance abuse patterns in primary care patients from two different European countries could offer initial clues for the elaboration of clinical practice guidelines, if further evidenced in other contexts. This study also endorses the use of primary care electronic medical records for the epidemiologic characterization of multimorbidity.
Page 1 /100
Display every page Item


Home
Copyright © 2008-2017 Open Access Library. All rights reserved.