Significant inequalities in the cost of food for households with children in Israel in 2018
Bibliographic record
Abstract
Abstract Background Dietary guidelines for families with children are designed to reach the Dietary Recommended Intake. However, the cost of a healthy diet and the extent to which families can afford it in Israel is unclear. Methods The distribution of ages and the number of children per household in Israel in 2018 was obtained from the Central Bureau of Statistics. Food prices were purchased from the commercial company Stornext. The cost of the recommended food items in the healthy diet for adults and children was calculated using standard food portions and meal frequency as well as a percentage of the household's net income. The proportion of households for which food expenditures exceed 15% of the net income was calculated by income quintiles, followed by changes in food prices during 2018. Results The average daily cost of a healthy diet was 35.51±7.7 new Israeli shekels (NIS). The older the individual, the more food costs increase. The ratio between the average cost of breakfast, lunch, dinner, and two intermediate meals was 1.5:3.4:1.2:1, respectively. The median monthly dietary cost for households with children as a percentage of net income was 20%. There was an inverse association with socioeconomic status (SES) as the median monthly food expenses for the first (lowest) quintile was 55% of the household's income and only 9.3% of the 5th (highest) income quintile. The food group that composed the highest component of the food budget was the vegetable group, with an average cost of 29% monthly, followed by the meat and meat substitutes group (19%). Discussions Policymakers should consider steps to decrease health inequality in food affordability targeting the three middle-lower income quintiles. The cost of a healthy diet compared with food expenditure in high-income countries was 1.8 higher in Israel. Our findings indicate that expanding the program to provide school lunches five days a week to more students would reduce household food expenditures by 15%. Key messages • Households with children in Israel would need to spend 20% of their net income to meet dietary guidelines. • Significant gaps by income quintile, number of children, and food group were identified.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.004 | 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 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".