Dynapaenic obesity and its association with health outcomes in older adult populations: protocol for a systematic review
Bibliographic record
Abstract
INTRODUCTION: Two major global health challenges are the rapidly ageing population and the high prevalence of obesity in all age groups. Older adults are also susceptible to age-related loss of muscle strength, termed dynapaenia. The co-occurrence of both obesity and dynapaenia, termed dynapaenic obesity (DO), has been associated with poorer health outcomes and increased healthcare usage compared with either state alone. The purpose of this systematic review is to quantify the prevalence and incidence of DO in older adult populations, and to explore the association between DO and health outcomes, specifically chronic disease and multimorbidity, functional disability and healthcare usage. METHODS AND ANALYSIS: Using the Meta-analyses Of Observational Studies in Epidemiology guidelines, we will conduct a systematic review of cross-sectional and longitudinal observational studies of older adults, which include measures of DO and specified outcomes. Detailed literature searches of will be conducted using six electronic databases: Excerpta Medica dataBASE (EMBASE), PubMed, MEDLINE, SCOPUS, ScienceDirect and Cumulative Index of Nursing and Allied Health Complete (CINAHL), including articles published from database inception until Febuary 2019. The reference lists of included articles will also be searched. Two independent reviewers will undertake a three-step screening and review process using the Population, Risk Factor, Outcome framework to define eligibility. The Newcastle Ottawa Scale for non-randomised studies will be used to assess risk of bias and to rate study quality. The findings will be synthesised in a narrative summary, and a meta-analysis will be conducted where appropriate. ETHICS AND DISSEMINATION: Ethical approval is not required for this systematic review. Findings from this research will be submitted for peer-reviewed publication in academic journals, and presented at relevant academic conferences. PROSPERO REGISTRATION NUMBER: CRD42018112471.
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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 | 0.064 | 0.075 |
| Meta-epidemiology (narrow) | 0.006 | 0.005 |
| Meta-epidemiology (broad) | 0.018 | 0.019 |
| Bibliometrics | 0.014 | 0.013 |
| Science and technology studies | 0.004 | 0.004 |
| Scholarly communication | 0.008 | 0.009 |
| Open science | 0.005 | 0.006 |
| Research integrity | 0.007 | 0.006 |
| Insufficient payload (model declined to judge) | 0.059 | 0.007 |
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".