Ethical issues in the development and implementation of nutrition-related public health policies and interventions: A scoping review
Bibliographic record
Abstract
BACKGROUND: The limited integration of ethics in nutrition-related public health policies and interventions is one major concern for those who have the task of implementing them. Ethical challenges that are overlooked during the development of such interventions could raise serious ethical issues during their implementation and even after. As a result, these decision makers need technical support and ethical guidance for adaptation of interventions to local (cultural, social, economic, etc.) contexts. AIM: The goal of this scoping review is to delineate and "map" the range of ethical issues in nutrition-related public health interventions, as well as the range of the various fields in which they may arise. METHODS: A scoping review of empirical research and conceptual literature was conducted following the framework of Arksey and O'Malley. Searches using PubMed with Medical Subject Headings (MeSH) categories and Advanced Search Builder as well as in the Global Health Library were performed. The final sample consists of 169 publications. RESULTS: The ethics of public health prevention or treatment of obesity and non-communicable diseases is the most explicitly and frequently discussed subject. In comparison, ethical issues raised by public health interventions in the fields of undernutrition, breastfeeding, vitamin/mineral supplementation and food fortification, food security, food sustainability and food safety are addressed in a lower proportion of the sample. The results illustrate the various natures, types, and scopes of existing public health nutrition-related interventions, and the various ethical issues that may be raised by these interventions, in addition to the numerous and different contexts in which they may be implemented. DISCUSSION: The ethical issues faced in the development and implementation of nutrition-related public health interventions are varied and cannot be equated with, nor generalized about, when dealing with specific activities in this field. More importantly, these ethical issues cannot be managed without a careful consideration for the complexity of contexts in which nutrition-related interventions are expected to be implemented. These interventions engage a variety of actors with diverse perspectives and interests. We discuss these challenges and also comment on the importance of considering ethical impacts in the monitoring and evaluation of such interventions. CONCLUSION: General ethical frameworks or recommendations-although useful-cannot be expected to provide policy makers, implementators and other public health personnel with sufficient practical ethical guidance as they cannot consider and anticipate the particularities of all specific nutrition-related public health interventions and the complexity of the contexts in which they are implemented. Further research is needed in order to develop more targeted ethical frameworks.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.249 | 0.497 |
| Meta-epidemiology (narrow) | 0.002 | 0.002 |
| Meta-epidemiology (broad) | 0.004 | 0.004 |
| Bibliometrics | 0.019 | 0.020 |
| Science and technology studies | 0.005 | 0.014 |
| Scholarly communication | 0.014 | 0.015 |
| Open science | 0.004 | 0.010 |
| Research integrity | 0.010 | 0.007 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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.
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 source (direct Gemma or distilled Codex), 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".