Translating the Developmental Origins of Health and Disease concept to improve the nutritional environment for our next generations: a call for a reflexive, positive, multi-level approach
Bibliographic record
Abstract
Evidence supporting the Developmental Origins of Health and Disease (DOHaD) hypothesis indicates that improving early life environments can reduce non-communicable disease risks and improve health over the lifecourse. A widespread understanding of this evidence may help to reshape structures, guidelines and individual behaviors to better the developmental conditions for the next generations. Yet, few efforts have yet been made to translate the DOHaD concept beyond the research community. To understand why, and to identify priorities for DOHaD Knowledge Translation (KT) programs, we review here a portion of published descriptions of DOHaD KT efforts and critiques thereof. We focus on KT targeting people equipped to apply DOHaD knowledge to their everyday home or work lives. We identified 17 reports of direct-to-public DOHaD KT that met our inclusion criteria. Relevant KT programs have been or are being initiated in nine countries, most focusing on secondary school students or care-workers-in-training; few target parents-to-be. Early indicators suggest that such programs can empower participants. Main critiques of DOHaD KT suggest it may overburden mothers with responsibility for children's health and health environments, minimizing the roles of other people and institutions. Simultaneously, though, many mothers-to-be seek reliable guidance on prenatal health and nutrition, and would likely benefit from engagement with DOHaD KT. We thus recommend emphasizing solidarity, and bringing together people likely to one day become parents (youth), people planning pregnancies, expecting couples, care workers and policymakers into empowering conversation about DOHaD and about the importance and complexity of early life environments.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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.
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 teacher head, 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".