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Background: Following the active ageing model based on the Health, Lifelong Learning, Participation and Security pillars, this research has a twofold objective: i) to classify older adults according to active ageing profiles, taking into account the four pillars, and ii) to ascertain the relationship between the profiles and personal and contextual factors, as well as well-being and quality of life in old age. Methods: A study sample of 5,566 Spanish older adults who participated in wave 6 of the Survey of Health, Ageing and Retirement in Europe (SHARE) was included. Data were analysed in different steps applying several statistical analyses (Principal Component, Cluster, Discriminant, Multiple Correspondence and bivariate analysis with Pearson chi-square and ANOVA). Results: Five older adult profiles were obtained (I: with moderate activity; II: quasi-dependents; III: with active ageing-limiting conditions; IV: with diverse and balanced activity; V: with excellent active ageing conditions). The first three profiles were characterised by subjects with a high average age, low educational level, who were retired or housewives, and who perceived a moderate level of loneliness, satisfaction with the social network and quality of life, as well as having a larger family network, but living in small households or alone. In contrast, the latter two profiles showed better personal and contextual conditions, well-being and quality of life. Discussion and conclusions: The multidimensional approach to active ageing followed in this article has revealed the presence of several older adult profiles, which are confined to groups with better or worse active ageing conditions. In this context, if ageing is a process that reflects the previous way of life, intervention priorities will have to consider actions that promote better conditions during the life cycle. [ABSTRACT FROM AUTHOR]

The objective of this study was to assess how disease burden caused by chronic conditions is related to mortality (predictive validity) and other health outcomes (convergent validity). This was studied in 625 community-dwelling adults living in Spain aged 65 years and older. Disease burden was measured with the Disease Burden Morbidity Assessment (DBMA). The association with 5-year mortality was assessed using a Cox model and Kaplan–Meier curves. For convergent validity, mean age, sex ratio, patient-centered outcomes and healthcare utilization were compared for high and low DBMA scores (< 10 vs. ≥ 10). Also, a multivariable linear regression model was used to evaluate the DBMA as a function of these variables. Mean DBMA score in our sample was 7.5. After 5 years, 35 participants had died (5.5%). The Cox model displayed a hazard ratio of 1.07, and the Kaplan–Meier curves showed lower survival for high DBMA scores. Among participants with high DBMA scores, low self-perceived health, disability and female sex were more frequent, and this group showed lower mean scores for quality of life (Personal Wellbeing Index), affect balance (Scale of Positive and Negative Experience) and physical activity (Yale Physical Activity Survey), higher mean age and higher healthcare utilization than persons with low DBMA scores. In the multivariable regression, all variables but age were significantly associated with the DBMA. In conclusion, the DBMA showed satisfactory predictive and convergent validity. In our aging society, it can be applied to better understand and improve care for older persons with multiple chronic conditions. [ABSTRACT FROM AUTHOR]

Aim: To carry out an analysis of the psychometric properties of the Disease Burden Morbidity Assessment (DBMA) according to the assumptions of the Classical Test Theory. Methods: A sample of 707 community-dwelling adults aged 65 years and older, living in Spain, completed the DBMA. Psychometric properties of the scale (feasibility, acceptability, scaling assumptions, reliability and construct validity) were analyzed. Results: The mean DBMA score was 6.8. Feasibility and acceptability were satisfactory, except for large floor effects (>50%), as well as a skewed distribution (1.8). Item-total corrected correlation ranged 0.10–0.49, item homogeneity index was 0.09 and Cronbach's alpha was 0.72. Disease burden correlated strongly with physical functioning (r = –0.56) and perceived health (r = –0.56), and moderately with depression (r = 0.41) and the Personal Wellbeing Index (r = –0.41). Exploratory factor analysis extracted five factors, explaining 44% of the variance. Conclusions: The DBMA is an acceptable and valid instrument for measuring disease burden in older adults. Future studies should include Rasch analysis to further assess dimensionality and explore other measurement properties. [ABSTRACT FROM AUTHOR]