MétaCan
Menu
Back to cohort
Record W4405450172 · doi:10.1017/s0029665124005494

Meal patterns and risk of childhood obesity and metabolically unhealthy obesity: a systematic review of the evidence, methodological issues and research gaps

2024· review· en· W4405450172 on OpenAlexaboutno aff
Georgios Saltaouras, Athanasia Kyrkili, Eirini Bathrellou, Michael Georgoulis, Mary Yannakoulia, Vassiliki Bountziouka, Meropi Kontogianni

Bibliographic record

VenueProceedings of The Nutrition Society · 2024
Typereview
Languageen
FieldMedicine
TopicObesity, Physical Activity, Diet
Canadian institutionsnot available
FundersEuropean Commission
KeywordsMealOverweightObesityContext (archaeology)Childhood obesityMedicineEnvironmental healthEveningSupperGerontologyInternal medicineBiology

Abstract

fetched live from OpenAlex

Childhood overweight/obesity (Ov/Ob) is a major public health problem, of greater concern when accompanied with comorbidities such as hypertension, insulin resistance leading to metabolically unhealthy obesity (MUO). Current evidence suggests a linkage between meal frequency, diet quality and nutritional status (1–3) in children and adolescents, however data regarding associations between meal patterns, Ov/Ob risk and MUO are limited. The aim was to explore associations between meal patterns and the risk of childhood Ov/Ob and MUO. The PRISMA methodology was used to retrieve prospective studies and randomized controlled trials conducted in children/adolescents 2-19 years old in Europe, USA, Canada or Oceania, from 01/2013 to 06/2023. Exposures that were considered under the umbrella “meal patterns” included consumption of a meal, meal skipping, timing, format and context. The quality of the studies was assessed with the ROBINS-E and RoB-2 tools. Of the 3,020 studies initially retrieved, 27 were included. All studies reported on Ov/Ob risk, whilst no studies on MUO were identified. All but one study had a longitudinal study design. Twenty-two studies (81%) had a high/very high risk of bias, mainly due to the methods measures of exposure were assessed. Consumption of/skipping breakfast was the most common exposure, followed by consumption of lunch (n = 5), dinner (n = 5), meal frequency/eating occasion (EO; n = 5) and consumption of fast foods (n = 4). Some studies reported on meal context (eating while watching TV; n = 4). In most studies, frequent breakfast and evening family dinners (i.e. 7 days/week vs <7days/week) were associated with lower odds of childhood Ov/Ob, BMI and %body fat at followup (FU). Four studies also showed that skipping breakfast was associated with increased obesity markers, while three studies showed no associations. There was limited evidence of a positive association between eating while watching TV and weight trajectories (n = 2). No associations were reported in relation to frequency of lunch and fast food intake. Results regarding meal frequency/EO and Ov/Ob at FU are conflicting, with differences attributed to the definition of an EO. Evidence supports that frequent consumption of breakfast and family dinners may be associated with lower Ov/Ob risk in children and adolescents, while eating in front of TV with increasing weight trajectories. No studies were identified in relation to MUO, highlighting a significant research gap. Nevertheless, clear definition on EOs and improved methodological approach in the assessment of meal patterns emerged as a need, according to current review findings.

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)0.008
metaresearch head score (Gemma)0.005
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Systematic review · Consensus signal: Systematic review
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.040
Threshold uncertainty score0.827

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0080.005
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0040.001
Bibliometrics0.0000.001
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.001
Research integrity0.0000.002
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 head0.151
GPT teacher head0.438
Teacher spread0.287 · 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 designSystematic review
Domainnot available
GenreReview

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
Published2024
Admission routes1
Has abstractyes

Explore more

Same venueProceedings of The Nutrition SocietySame topicObesity, Physical Activity, DietFrench-language works237,207