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Record W2802739011 · doi:10.2196/mhealth.8320

Relationship Between Weekly Patterns of Caloric Intake and Reported Weight Loss Outcomes: Retrospective Cohort Study

2018· article· en· W2802739011 on OpenAlexvenueno aff
Christine Hill, Brian W. Weir, Laura W Fuentes, Alicia García-Álvarez, Danya P Anouti, Lawrence J. Cheskin

Bibliographic record

VenueJMIR mhealth and uhealth · 2018
Typearticle
Languageen
FieldHealth Professions
TopicMobile Health and mHealth Applications
Canadian institutionsnot available
FundersJohns Hopkins Bloomberg School of Public HealthSchool of Medicine, Vanderbilt UniversityJohns Hopkins UniversityVanderbilt University
KeywordsCaloric theoryWeight lossRetrospective cohort studyMedicineCaloric intakeCohortCohort studyDemographyGerontologyEnvironmental healthBody weightObesityInternal medicine

Abstract

fetched live from OpenAlex

BACKGROUND: Although millions of overweight and obese adults use mobile phone apps for weight loss, little is known about the predictors of success. OBJECTIVE: The objective of this study was to understand the relationship between weight loss outcomes and weekly patterns of caloric intake among overweight and obese adults using a mobile phone app for weight loss. METHODS: We examined the relationship between weekly patterns of caloric intake and weight loss outcomes among adults who began using a weight loss app in January 2016 and continued consistent use for at least 5 months (N=7007). Unadjusted and adjusted linear regression analyses were used to evaluate the predictors of percentage of bodyweight lost for women and men separately, including age, body mass index category, weight loss plan, and difference in daily calories consumed on weekend days (Saturday and Sunday) versus Monday. RESULTS: In adjusted linear regression, percentage of bodyweight lost was significantly associated with age (for women), body mass index (for men), weight loss plan, and differences in daily caloric intake on Mondays versus weekend days. Compared with women consuming at least 500 calories more on weekend days than on Mondays, those who consumed 50 to 250 calories more on weekend days or those with balanced consumption (±50 calories) lost 1.64% more and 1.82% more bodyweight, respectively. Women consuming 250 to 500 calories or more than 500 calories more on Mondays than on weekend days lost 1.35% more and 3.58% more bodyweight, respectively. Compared with men consuming at least 500 calories more on weekend days than on Mondays, those consuming 250 to 500 calories or more than 500 calories more on Mondays than on weekend days lost 2.27% and 3.42% less bodyweight, respectively. CONCLUSIONS: Consistent caloric intake on weekend days and Mondays or consuming slightly fewer calories per day on Mondays versus weekend days was associated with more successful weight loss. TRIAL REGISTRATION: ClinicalTrials.gov NCT03136692; https://clinicaltrials.gov/ct2/show/NCT03136692 (Archived by WebCite at http://www.webcitation.org/6y9JvHya4).

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)0.001
metaresearch head score (Gemma)0.002
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 score0.013
Threshold uncertainty score0.026

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.001
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.111
GPT teacher head0.468
Teacher spread0.357 · 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".

Quick stats

Citations12
Published2018
Admission routes1
Has abstractyes

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