The association between different types of exercise and energy expenditure in young nonoverweight and overweight adults
Bibliographic record
Abstract
With decades of trends for decreasing activity during work and travel, exercise becomes an important contributor to total physical activity (PA) and energy expenditure. The purpose of this study was to examine the contribution of different types of exercise to the variability in energy expenditure and time spent at different PA intensities in young adults. Four hundred and seventeen adults (49.9% male; 46.2 overweight/obese) between 21 and 36 years of age provided valid objective PA and energy expenditure data, assessed via the SenseWear Armband (BodyMedia Inc.). Frequency and duration of participation in various exercise types was self-reported. Weight status was based on body mass index (BMI) (kg/m(2)) with body weight and height being measured according to standard procedures. Eighty-four percent of the participants reported regular exercise engagement with no difference in participation rate by sex or BMI category. Exercise time along with sex and ethnicity explained roughly 60% of the variability in total daily energy expenditure (TDEE) while the association between exercise and time spent in moderate to vigorous PA or being sedentary was low or nonsignificant. Engagement in endurance exercise and sports contributed predominantly to the variability in energy expenditure and PA in nonoverweight participants. In overweight/obese participants engagement in resistance exercise and swimming contributed significantly to variability in TDEE. Current exercise recommendations focus primarily on aerobic exercise, but results of the present study suggest that nonweight-bearing exercises, such as resistance exercise and swimming, contribute significantly to the variability in TDEE in overweight/obese adults, which would make these types of activities viable options for exercise interventions.
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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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 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".