Powdered Baby Formula Sold in North America: Assessing the Environmental Impact
Bibliographic record
Abstract
Background: According to the Intergovernmental Panel on Climate Change, Greenhouse Gas emissions must decline by around 45% by 2030 and reach net zero in 2050. Biofuels, solar, and wind energy are obvious choices for reduction of the 75% of emissions from the energy sector (including transportation), but making reductions in the remaining 25%, the food sector, is more of a challenge. One way is to change our diets to increase low-carbon food alternatives. Objective: We chose to examine the impact of powdered baby formula products. The aim of this study is to compute a minimal estimate of green house gas (GHG) emissions for powdered baby formula products sold in North America comprising Canada, Mexico, and the United States. Results: We found that in 2016, the North America Greenhouse Gas emissions (in tons of CO 2 eq.) attributable to sales of powdered formula for Canada was 70,256, for Mexico, 435,820, and for the United States, 655,956. The North American per capita emissions based on infants and toddlers from birth to 36 months of age in 2016 was, at a minimum, 59.06 kg of CO 2 eq. Conclusion: The environmental and Greenhouse Gas impact of powdered baby formula, and related hazards arising from climate change, can be a relevant factor for health care providers in their advice to families on infant feeding. This study makes an innovative and potentially useful addition to the emerging evidence on this issue and should be considered when developing and funding infant and young child feeding policies and supportive programs.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".