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Association of physical activity intensity with cardiovascular disease and mortality in high-income, middle-income and low-income countries: the PURE study

2023· article· en· W4388915454 on OpenAlexafffund
Scott A. Lear, Shun Li, Sumathy Rangarajan, Salim Yusuf

Bibliographic record

VenueEuropean Heart Journal · 2023
Typearticle
Languageen
FieldMedicine
TopicPhysical Activity and Health
Canadian institutionsPopulation Health Research InstituteSimon Fraser University
FundersHamilton Health Sciences
KeywordsMedicineDemographyRural areaMyocardial infarctionHousehold incomeStroke (engine)RecreationDiseaseEnvironmental healthGerontologyInternal medicine

Abstract

fetched live from OpenAlex

Abstract Background The WHO recommends adults get 150-300 minutes of moderate physical activity (MPA) and/or 75-150 minutes of vigorous physical activity (VPA) per week. Few studies have investigated the independent benefits of PA intensity. Those that have, have found VPA to be protective, while others found excessive VPA to be harmful. These studies have primarily been conducted in high-income countries using recreational PA as the exposure of interest. Purpose To evaluate the effects of activity intensity (walking, MPA and VPA) with all-cause mortality, and cardiovascular disease (CVD) in countries at different economic levels. Methods Participants (35-70 years) were recruited from 21 countries at various stages of economic development. Within each country, urban and rural areas in and around selected cities and towns were identified to reflect the geographical diversity. Physical activity (total, walking, MPA, VPA, as well as recreational vs. non-recreational PA) was assessed using the International Physical Activity Questionnaire. Primary outcomes were mortality plus major CVD (CVD mortality, myocardial infarction, stroke, or heart failure), either as a composite or separately. After excluding those with baseline CVD, cancer and HIV, a total of 136,766 participants who had complete data were analyzed. Models were adjusted for age, sex, urban or rural residency, country income level, education, household wealth index, smoking, baseline chronic diseases, physical impairments and center as a random effect. All models were mutually adjusted for PA intensity. Results During the median follow-up of 11.5 (8.6-12.4) years, there were 9846 deaths and 7900 major cardiovascular events. The mean min/wk for walking, MPA and VPA were 339±539, 640±825 and 103±390, respectively. Increasing walking time had a U-shaped relationship with the composite outcome, such that walking between 300-1200 min/wk had the lowest risk, whereas walking at this amount and ≥1200 min/wk was associated with the lowest risk for mortality (p<0.001 for trend). Both MPA and VPA were linearly associated with the composite outcome and mortality even at levels below the recommended guidelines and up to ≥1800 min/wk (p<0.001 for trend). At each PA category, the hazard ratio for VPA was lower than MPA, such that at ≥1800 min/wk it was 0.64 (0.50,0.81) and 0.70 (0.57,0.85), for VPA and MPA, respectively, for the composite outcome. When VPA was stratified into either recreational or non-recreational VPA, recreational VPA displayed a U-shape relationship, whereas increasing non-recreational VPA continued to confer reduced risk even ≥3000 min/wk (Figure). Conclusion For both MPA and VPA, the benefits began at very low levels of PA and continued to increase with increasing PA. At each amount of PA, the lowest risk was in those participating in VPA. We did not observe any harmful effects of VPA, even at extremely high levels. However, at higher recreational VPA, the benefits began to diminish.

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 machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.003
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.005
Threshold uncertainty score0.011

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.003
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.002
Science and technology studies0.0010.000
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.038
GPT teacher head0.301
Teacher spread0.263 · 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 source (direct Gemma or distilled Codex), 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".

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Citations0
Published2023
Admission routes2
Has abstractyes

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