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Record W4322770514 · doi:10.1016/s2214-109x(23)00098-0

An intergenerational life-course approach to address early childhood obesity and adiposity: the Healthy Life Trajectories Initiative (HeLTI)

2023· article· en· W4322770514 on OpenAlexafffundabout
Kalyanaraman Kumaran, Catherine S. Birken, Jean‐Patrice Baillargeon, Cindy‐Lee Dennis, William D. Fraser, Hefeng Huang, Jianxia Fan, Stephen J. Lye, Stephen G. Matthews, Shane A. Norris

Bibliographic record

VenueThe Lancet Global Health · 2023
Typearticle
Languageen
FieldMedicine
TopicBirth, Development, and Health
Canadian institutionsLunenfeld-Tanenbaum Research InstituteCentre Hospitalier Universitaire de SherbrookeSt. Michael's HospitalUniversité de SherbrookeSickKids FoundationUniversity of Toronto
FundersCanadian Institutes of Health Research
KeywordsOverweightLife course approachMedicineChildhood obesityObesityGerontologyMalnutritionEnvironmental healthBody mass indexPsychological interventionEarly childhoodPediatricsPsychologyDevelopmental psychologyPsychiatry

Abstract

fetched live from OpenAlex

BACKGROUND: Interactions between genes and early-life exposures during conception, fetal life, infancy, and early childhood have been shown to affect an individual's health later in life. Maternal undernutrition and obesity, gestational diabetes, and impaired growth in utero and in early life are associated with adiposity and overweight and obesity in childhood, which are risk factors for poor health trajectories and non-communicable diseases. In Canada, China, India, and South Africa, 10-30% of children aged 5-16 years are overweight or obese. METHODS: The application of developmental origins of health and disease principles offers a novel approach to prevention of overweight and obesity and reduction of adiposity by delivering integrated interventions across the life course, starting before conception and continuing through early childhood. The Healthy Life Trajectories Initiative (HeLTI) was established in 2017 through a unique collaboration between national funding agencies in Canada, China, India, South Africa, and WHO. The aim of HeLTI is to evaluate the effect of an integrated four-phase intervention starting preconceptionally and continuing through pregnancy, infancy, and early childhood on reducing childhood adiposity (fat mass index) and overweight and obesity, and optimising early child development, nutrition, and other healthy behaviours. FINDINGS: Approximately 22 000 women are being recruited in Shanghai (China), Mysore (India), Soweto (South Africa), and across various provinces of Canada. Women who conceive (an expected 10 000) and their children will be followed up until the child reaches the age of 5 years. INTERPRETATION: HeLTI has harmonised the intervention, measures, tools, biospecimen collection, and analysis plans for the trial to be run across four countries. HeLTI will help establish whether an intervention aimed at addressing maternal health behaviours, nutrition, and weight; providing psychosocial support to reduce maternal stress and prevent mental illness; optimising infant nutrition, physical activity, and sleep; and promoting parenting skills can reduce the intergenerational risk of excess childhood adiposity and overweight and obesity across diverse settings. FUNDING: Canadian Institutes of Health Research; National Science Foundation of China; Department of Biotechnology, India; and South African Medical Research Council.

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)0.002
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation 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 score0.565
Threshold uncertainty score0.720

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.059
GPT teacher head0.356
Teacher spread0.297 · 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 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

Citations8
Published2023
Admission routes3
Has abstractyes

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