Identification of determinants of healthy ageing in Italy: results from the national survey IDAGIT
Bibliographic record
Abstract
Abstract Healthy ageing is a public health problem globally. In Europe, the dependency ratio of the elderly is expected to increase by 21.6 per cent to 51.2 per cent in 2070. The World Health Organization (WHO) study on healthy ageing started in 2002 as a concept whereby all people of all ages should be able to live in a healthy, safe and socially inclusive way. The aim of this study is to present preliminary results of the project Identification of Determinants of Healthy Ageing in Italy (IDAGIT) that aimed to collect data on the active and healthy ageing of the Italian population aged over 18 using the conceptual framework of the WHO's ageing model. To link the determinants of the IDAGIT studies to those of the WHO model, we performed a confirmatory factor analysis which reported these variables as significant (in order of factor loading): smoking, cognition score, comorbidity, outdoor built environment, participation, working expertise and income. Considering comorbidity, 83.8 per cent of the sample declared not having any chronic diseases or to have only one, and regarding neurological diseases, only nine people had received a diagnosis of stroke. Regarding gender, the personal determinants and physical and social environments did not result in statistically significant differences, whereas we found statistical differences between the aged groups in all variables analysed. These results provide a first bio-psycho-social perspective on ageing in the Italian population.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".