Genetic, Socioecological, and Health Determinants of Extreme Longevity in Semi-Supercentenarians and Supercentenarians: Protocol for a Scoping Review
Bibliographic record
Abstract
BACKGROUND: The study of supercentenarians (individuals aged 110 years or older) offers valuable insights into aging, longevity, and the factors contributing to exceptional lifespans. These individuals often exhibit extraordinary cognitive and physical performance, which can inform strategies to improve the health of the general population. Research on centenarians (individuals aged 100 years or older), semi-supercentenarians (individuals aged 105-109 years), and supercentenarians covers themes like genetic factors, microbiome, inflammation, diet, lifestyle, and psychological aspects. These studies often focus on various aspects of extreme longevity, using varied objectives and methodologies, highlighting the need for a comprehensive synthesis to map the breadth of research and identify gaps in understanding this demographic. OBJECTIVE: This scoping review aims to map and synthesize existing evidence on the determinants of extreme longevity, focusing on individuals living beyond 105 years. This review seeks to categorize genetic factors associated with semi-supercentenarians and supercentenarians; explore the range of socioecological factors contributing to their longevity; and identify common themes such as health, functional capacity, cognition, mental health, behaviors, social support, quality of life, personality traits, environmental factors, and religiosity. Additionally, it aims to examine and describe the methodologies and assessment tools used in studies on extreme longevity and provide an overview of global demographic trends and patterns among supercentenarians, including geographic distribution, gender prevalence, and socioeconomic characteristics. METHODS: This scoping review follows the PRISMA-P (Preferred Reporting Items for Systematic Review and Meta-Analysis Protocols) 2015 guidelines and the Population, Exposure, and Outcome framework. It includes observational and interventional, quantitative and qualitative studies on supercentenarians and semi-supercentenarians. Data will be sourced from databases like Scopus, PubMed, ProQuest, PsycINFO, and The Cochrane Library. The selection process involves abstract and full-text screening by two independent reviewers, with data extraction focusing on study characteristics, participant demographics, interventions or exposures, and key findings. A thematic analysis will identify patterns across various themes. RESULTS: As of October 2, 2024, five databases were searched, yielding 844 studies. After removing duplicates, 706 studies remained. Following the first and second screening stages, 135 studies were found to be eligible. The study is expected to be completed by the end of February 2025. CONCLUSIONS: By synthesizing evidence, this study will understand the global scope of supercentenarians, describe the main themes of research interest, and identify gaps. The findings are expected to contribute significantly to the body of knowledge on longevity, informing future research and public health policies. This scoping review aims to enhance the understanding of factors promoting healthy aging and extreme longevity, benefiting broader public health initiatives. TRIAL REGISTRATION: PROSPERO CRD42024512298; https://tinyurl.com/4cmux7h4.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.062 | 0.072 |
| Meta-epidemiology (narrow) | 0.004 | 0.004 |
| Meta-epidemiology (broad) | 0.013 | 0.015 |
| Bibliometrics | 0.014 | 0.012 |
| Science and technology studies | 0.005 | 0.004 |
| Scholarly communication | 0.007 | 0.007 |
| Open science | 0.004 | 0.006 |
| Research integrity | 0.008 | 0.006 |
| Insufficient payload (model declined to judge) | 0.071 | 0.011 |
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 source (direct Gemma or distilled Codex), 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".