Leader: Rossella Miglio (UNIBO); Other collaborator(s): Enrico Roma
Frailty indicators can bestrong predictor of healthy aging and the onset of disability. They can be relevant to understand timing, size, territorial, gender, and age differences and determinants of adverse health outcomes. Moreover they can be used to stratify adult and old population in order to predict specific onset of disability by group with a preventive perspective. Using longitudinal data, our aim is to study trajectories of these indicators in order to identify the predictors of their level and rate of change from adulthood to later life, with an evaluation of life expectancy and life expectancy in good health. Moreover, special attention will be paid to the occurrence and impact on the disability of COVID-19 in later life.
Brief description of the activities and of the intermediate results
Current activities are aimed at understanding factors influencing healthy aging and quality of life in older adults, particularly focusing on frailty, disability, and multimorbidity patterns. Disability Trends in Europe: The study uses SHARE data to analyse disability trends in European countries, with a specific focus on Italy. Variables such as the global index of activity limitation (gali), instrumental activities of daily living (iadl), and non-instrumental activities of daily living (adl) were examined. Logistic age-period-cohort models were employed to estimate prevalence across gender and different wealth quintiles within individual countries.
Frailty and Social Components: We further explore the relationship between frailty and social component like activity participation and the size of social network, its proximity and its composition and closeness using SHARE data. We included a wide range of variables, describing anthropometric and demographic characteristics, health status, risk behaviours, use of time, participation in activity, size of the individual social network and physical frailty. Each domain was represented by multiple variables. To infer the causal structure between these constructs, we are studying a causal discovery analysis algorithm.
Multimorbidity Patterns and Frailty Indicator: this study constitutes one of the steps of frailty indicator construction. The study emphasizes the importance of considering multimorbidity patterns beyond simple counts or individual chronic diseases in assessing health frailty. Using longitudinal administrative health data and survey data, we adopted an approach that combine probabilistic estimates from graphical model and intuitive visualization from network analysis that is emerging quickly as powerful tool in recent years to not only efficiently explore the richness of administrative health data, but also to provide an analysis framework whom predictability can be assessed.
Main policy, industrial and scientific implications
Frailty, disability, and multimorbidity are interconnected phenomena that often coexist and mutually influence each other, understanding the relationship among them is important for their influence on aging and for chronic disease management and for developing comprehensive and personalized care strategies aimed at promoting healthy aging and improving the quality of life for older adults with complex health needs, moreover understanding the evolution of disability with age and during time is critical for policy makers and researchers to develop effective interventions and allocate resources efficiently.
Data analysis: Data analysis of SHARE data and administrative data has either been completed or is proceeding. Further surveys are being considered to extend the analysis of disability trends in Italy and to assess patterns of multimorbidity for the elderly.
Scientific publications: The writing of scientific articles is either completed or advancing.
Policy Brief in collaboration with other WP4 tasks: A policy brief on biological and social aspects of aging is currently in progress.
Dissemination activities: Dissemination activities have already started and will continue.
Brief description of the activities and of the intermediate results:
An age-period-cohort analysis of perceived disability in Italy was completed using the research datasets from the ISTAT survey “Aspects of Daily Life.” This study complements a previously initiated project based on SHARE data, which provided spatial resolution at the European and national levels. The new model enables inference at the regional level, distinguishing between males and females, as well as different age groups and historical periods. The findings have been compiled into a scientific manuscript, which has been submitted to a scientific journal and it is currently under review.
Work on multimorbidity, frailty, and social participation has continued with the implementation of graphical models (maximal ancestral graphs) that allow for a causal interpretation of relationships between variables. The dataset used was derived from the Survey of Health, Ageing and Retirement in Europe. The application of this model was presented at the 32nd International Biometric Conference, held from December 8–13, 2024, in Atlanta, USA. Efforts are currently underway to formalize this work into a scientific manuscript.
Different scientific contributions provide a comprehensive analysis of multimorbidity patterns, highlighting the complex interrelationships between chronic conditions and their impact on patient outcomes across diverse populations. One paper is under review about SHARE data while a second one based on administrative data is in progress.
Main policy, industrial and scientific implications
The first project provides a model for predicting perceived disability while accounting for the evolution of the population's demographic pyramid and the effect of being born in a specific historical period.
The graphs used in the second project have a causal interpretation, making it possible, under certain assumptions, to calculate the effect that an intervention on one node of the graph may have on other target nodes. This tool is particularly valuable from a policy perspective, as it allows for the assessment of the effectiveness of complex policies that act on multiple nodes simultaneously.
Brief description of the activities and of the intermediate results.
Building on the age-period-cohort analyses, we implemented a continuous-time multistate Markov model to project the evolution of disability prevalence over time under the assumption of a closed population. Due to the lack of Italian longitudinal datasets tracking the same individuals over time, transition rates for the Markov model were approximated using prevalence estimates from the previous model (along with other models) and life tables provided by ISTAT.
We are currently working to expand the multistate model beyond disability, incorporating chronic diseases and frailty where feasible. In parallel, we are comparing our estimates across multiple Italian surveys, including the European Social Survey, SHARE, AVQ, and the ISTAT Health Survey. Our goal is to produce demographic projections of disability through 2050.
Work on multimorbidity patterns is still in progress evaluating the progression over time and using it as component of frailty index, one paper is under review: the analysis is based on administrative data.
Dissemination activities
Roma, E., Miglio, R. “Frailty and social network: a causal discovery analysis using survey data” (Oral). 32nd International Biometric Conference, Session: Big Data Analytics, Atlanta, Georgia, USA, 8-13 December 2024.
Roma, E., Miglio, R. “Causal discovery for a better understanding of frailty and its effects in Europe” (Oral). The Demography of Ageing, Roma, Italy, 3-4 October 2024.
Roma, E., Miglio, R. “Causal discovery for a better understanding of fraitly using survey data” (Oral). Measuring and Interpreting World Changes with Statistics, Data Science and AI, Roma, Italy, 18-20 September 2024.
Roma, E., Miglio, R. “Frailty and social network: a causal discovery analysis using survey data” (Oral). PRIN – SOcial and health Frailty as determinants of Inequality in Aging (SOFIA), Padova, Italy, 9-10 September 2024.
Roma, E., Miglio, R. “Disability trends in Italy and Europe: An Age-Period-Cohort analysis” (Oral). LX Riunione scientifica Societ`a Italiana di Economia Demografia e Statistica, “Salute, ambiente e disuguaglianze: istituzioni, imprese e societ`a”, Milano, Italy, 22-24 May 2024.
Dang, L.H.K., Caranci, N., Rettaroli, R., Giulia, R., Miglio, R. “Trajectories of multimorbidity patterns at older ages using graphical model, network analysis and hidden Markov model”, Applied Statistics Conference (ASA), "Health and Demographic studies”, 18-20/09/2024, Rome, Italy.
Dang, L.H.K., Caranci, N., Rettaroli, R., Giulia, R., Miglio, R., “Multimorbidity patterns at older ages: A study using graphical model and network analysis” - Age-It, session “Frailty and multimorbidity”, 20-22/05, Venice, Italy - European Association for Population Studies (EAPS), session “Wellbeing in older ages”, 12-15/06/2024, Edinburgh, United Kingdom.
Dang, L.H.K., Caranci, N., Rettaroli, R., Giulia, R., Miglio, R., “Multimorbidity patterns at older ages: An application of graphical model and network analysis in the Emilia-Romagna Longitudinal Study”, Congress of Association of Italian Epidemiologists, session “Chronic diseases and tumour”, 16-19/04/2024, Rimini-Riccione, Italy.
Paper under review
Roma, E., Miglio, R. “Disability trends in selected European countries: An Age-Period-Cohort analysis”. Under Review
Roma, E., Miglio, R. “Examining Disability Prevalence in Italy: A Novel Application of Age-Period-Cohort Interaction Model”. Submitted
Caselli, N., Dang, H. K. L., Rettaroli, R., Miglio, R. “Data science approaches to the study of multimorbidity patterns at older ages”. Under Review
Paper recently published
Miglio, R., Puglisi, C., Rettaroli, R., Roli, G., Scalone, F. “Frailty, activity participation, and welfare: An analysis using SHARE data”, «Italian Journal of Applied Statistics», 2023, 35, n. 3 supplement, pp. 305 - 310.