Integrating accelerometry, GPS, GIS and molecular data to investigate mechanistic pathways of the urban environmental exposome and cognitive outcomes in older adults: a longitudinal study protocol
Bibliographic record
Abstract
INTRODUCTION: Maintaining cognitive health in later life is a global priority. Encouraging individuals to make health behaviour changes, such as regular physical activity, and providing supportive urban environments can help maintain cognitive health, thereby preventing or delaying the progress of dementia and cognitive decline. However, the mechanistic pathways by which the urban environmental exposome influences cognitive health outcomes are poorly understood. The aim of this study is to use granular measures of the urban environment exposome (encompassing the built, natural and social environment) and physical activity to explore how these interact with a person's biology to ultimately influence cognitive health outcomes. METHODS AND ANALYSIS: This ongoing study uses a cohort design, recruiting participants from the Northern Ireland Cohort for the Longitudinal study of Ageing and the Harmonised Cognitive Assessment Protocol study. Participants (n=400 at each wave) will be aged ≥65 years and have the capacity to provide written informed consent. Measures include device-measured physical activity (Actigraph wGT3XP-BT), environmental location data (Global Positioning System, Qstarz BT-Q1000XT), linked to a battery of neuropsychological tests, including the Mini Mental State Examination and the Centre for Epidemiological Studies Depression Scale. Blood-derived biochemical, genetic and epigenetic data will be included in multimodal analyses. These data will be integrated with urban environment Geographic Information System data and analysed using causal inference and mediation methods to investigate plausible mechanistic pathways. ETHICS AND DISSEMINATION: This study has been approved by the Queen's University Belfast, Faculty of Medicine, Health and Life Sciences Research Ethics Committee (MHLS 21_72). Alongside peer-reviewed publications in high-ranking international journals, dissemination activities include conference presentations, project videos, working papers, policy briefing papers, newsletters, summaries and case study stories.
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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 | 0.001 | 0.000 |
| 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 | 0.001 |
| Open science | 0.001 | 0.006 |
| 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".