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Record W2171664751 · doi:10.1186/s12916-014-0161-y

The effects of antenatal dietary and lifestyle advice for women who are overweight or obese on maternal diet and physical activity: the LIMIT randomised trial

2014· article· en· W2171664751 on OpenAlexfundno aff
Jodie M Dodd, Courtney Cramp, Zhixian Sui, Lisa N Yelland, Andrea R. Deussen, Rosalie M Grivell, Lisa Moran, Caroline A Crowther, Deborah Turnbull, Andrew J McPhee, Gary Wittert, Julie A. Owens, Jeffrey S. Robinson

Bibliographic record

VenueBMC Medicine · 2014
Typearticle
Languageen
FieldMedicine
TopicGestational Diabetes Research and Management
Canadian institutionsnot available
FundersNational Health and Medical Research CouncilNational Heart, Lung, and Blood InstituteUniversity of AdelaideSouth Australian Health and Medical Research InstituteNational Heart Foundation of AustraliaChildren's Health Research InstituteHarvard University
KeywordsMedicineOverweightObesityRandomized controlled trialPhysical activityPregnancyObstetricsPhysical therapyInternal medicine

Abstract

fetched live from OpenAlex

BACKGROUND: Overweight and obesity is a significant health concern during pregnancy. Our aim was to investigate the effect of providing antenatal dietary and lifestyle advice to women who are overweight or obese on components of maternal diet and physical activity. METHODS: We conducted a randomised controlled trial, in which pregnant women with a body mass index≥25 kg/m2, and singleton gestation between 10(+0) to 20(+0) weeks were recruited and randomised to Lifestyle Advice (involving a comprehensive dietary and lifestyle intervention over their pregnancy) or Standard Care. Within the intervention group, we conducted a nested randomised trial in which a subgroup of women were further randomised to receive access to supervised group walking sessions in addition to the standard information presented during the intervention contacts (the Walking group) or standard information only. The outcome measures were maternal dietary intake, (including food groups, macronutrient and micronutrient intake, diet quality (using the Healthy Eating Index; HEI), dietary glycaemic load, and glycaemic index) and maternal physical activity. Women completed the Harvard Semi-Structured Food Frequency Questionnaire, and the Short Questionnaire to Assess Health-enhancing Physical Activity (SQUASH), at trial entry, 28 and 36 weeks' gestational age, and 4 months postpartum. Analyses were performed on an intention-to-treat basis, using linear mixed effects models with adjustment for the stratification variables. RESULTS: Women randomised to Lifestyle Advice demonstrated a statistically significant increase in the number of servings of fruit and vegetables consumed per day, as well as increased consumption of fibre, and reduced percentage energy intake from saturated fats (P<0.05 for all). Maternal HEI was significantly improved at both 28 (73.35±6.62 versus 71.86±7.01; adjusted difference in means 1.58; 95% CI 0.89 to 2.27; P<0.0001) and 36 (72.95±6.82 versus 71.17±7.69; adjusted difference in means 1.77; 95% CI 1.01 to 2.53; P<0.0001) weeks. There were no differences in dietary glycaemic index or glycaemic load. Women randomised to Lifestyle Advice also demonstrated greater total physical activity (adjusted difference in means 359.76 metabolic equivalent task units (MET) minutes/week; 95% CI 74.87 to 644.65; P=0.01) compared with women receiving Standard Care. The supervised walking group was poorly utilised. CONCLUSIONS: For women who are overweight or obese, antenatal lifestyle advice improves maternal diet and physical activity during pregnancy. Please see related articles: http://www.biomedcentral.com/1741-7015/12/163 and http://www.biomedcentral.com/1741-7015/12/201. TRIAL REGISTRATION: Australian and New Zealand Clinical Trials Registry ( ACTRN12607000161426).

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)0.003
metaresearch head score (Gemma)0.007
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Randomized trial · Consensus signal: Randomized trial
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.008
Threshold uncertainty score0.025

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.007
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0040.002
Bibliometrics0.0010.000
Science and technology studies0.0000.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0020.003
Insufficient payload (model declined to judge)0.0080.001

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.

Opus teacher head0.017
GPT teacher head0.298
Teacher spread0.281 · 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 designRandomized trial
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

Citations173
Published2014
Admission routes1
Has abstractyes

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