Is Energy Expenditure or Physical Activity Considered When Energy Intake Is Measured? A Scoping Review 1975–2015
Bibliographic record
Abstract
The health-transitions humans have delivered during the 20th Century associated with the nutrition is that from undernutrition to obesity, which perseveres in the current years of the 21st Century. Energy intake (EI) is a contributing factor and therefore a fascination in nutritional sciences. However, energy expenditure (EE) has not been usually considered as a conjoint factor. Thus, this study aimed to review if studies on adults consider data on dietary intake, specifically EI, and included data on EE and physical activity (PA). A search of MEDLINE from 1975 to December 2015 was managed. Our scoping review consisted of keywords related to EI, dietary allowances, and nutritional requirements. From 2229 acknowledged articles, 698 articles were finally taken fulfilling inclusion and quality criteria. A total of 2,081,824 adults (53.7% females) were involved, and most studies had been conducted in EEUU (241), Canada (42), Australia (30), Japan (32), and Brazil (14). In Europe, apart from UK (64), the Netherlands (31) and France (26) led the classification, followed by Sweden (18), Denmark (17), and France (26). Mediterranean countries are represented with 27 studies. A total of 76.4% did not include EE and 93.1% did not include PA. Only 23.6% of the studies contained both EI and EE. A large methodological diversity was perceived, with more than 14 different methods regarding EI, and more than 10 for EE. PA was only analyzed in scarce articles, and scarcely considered for interpretation of data and conclusions. Moreover, PA was often measured by subjective questionnaires. Dietary surveys show a large diversity regarding methodology, which makes comparability of studies difficult. EE and PA are missing in around 80% of studies or are not included in the interpretation of results. Conclusions regarding EI or diet adequacy in adults should not be taken without analyzing EE and PA.
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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 | 0.008 | 0.043 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.005 | 0.005 |
| Bibliometrics | 0.028 | 0.030 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.004 | 0.005 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.006 | 0.001 |
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".