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Record W6962683260 · doi:10.17863/cam.83264

The descriptive and aetiological epidemiology of physical activity: composition, volume, and intensity.

2022· dissertation· en· W6962683260 on OpenAlexaboutno aff

Bibliographic record

VenueApollo (University of Cambridge) · 2022
Typedissertation
Languageen
FieldMedicine
TopicPhysical Activity and Health
Canadian institutionsnot available
FundersMedical Research Council
KeywordsPhysical activityObesityEpidemiologyPopulationEtiologyPublic healthEnergy expenditureBody mass index

Abstract

fetched live from OpenAlex

Physical activity is known to play a role in the prevention of obesity and related cardiometabolic conditions. However, in order to develop targeted public health interventions, it is first necessary to understand how levels of physical activity vary in different populations, along with the determinants of physical activity and its association with intermediate disease traits. This thesis presents the results of descriptive studies of physical activity in three population cohorts: the UK-based National Diet and Nutrition Survey, the Cambridgeshire-based Fenland Study, and the Russian-based Know Your Heart Study, along with an ecological analysis of 35 population estimates of physical activity energy expenditure from populations as diverse as Arctic Inuit to the Maasai of Kenya. In summary, the analysis shows that physical varies by age, sex, BMI and location. The thesis additionally presents the results of two aetiological studies, one examining the associations between energy intake and macronutrient composition as the exposure, and physical activity energy expenditure as the outcome, and the other examining the joint associations of physical activity volume and intensity as the exposure with body-fatness as the outcome. Those analyses show that volume, be it intake or expenditure, is more strongly associated with the outcome than the underlying macronutrient composition or intensity. Overall, the body of work presented in this thesis represents a meaningful addition to the physical activity literature and adds specific additional information about the determinants of, and associations with, physical activity.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.844
Threshold uncertainty score0.552

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.036
GPT teacher head0.293
Teacher spread0.257 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations0
Published2022
Admission routes1
Has abstractyes

Explore more

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