The annual feasibility and affordability of a healthy diet for families with children in Israel by income quintile and geographic area of residency
Bibliographic record
Abstract
BACKGROUND: Dietary guidelines for families with children are designed to meet 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 age distribution and the number of children per household by income quintile and geographic area in Israel in 2018 were obtained from the Central Bureau of Statistics. Food cost information was purchased from the commercial company Stornext. The cost of the recommended food items in the healthy diet for adults and children (by age group) was calculated using standard food portions and meal frequency and expressed as a percentage of the households net income. The proportion of households for which food expenditures exceeded 15% of the net income was calculated, followed by changes in food prices during 2018. RESULTS: The average daily cost of a healthy diet for an average Israeli family was 35.5 ± 7.7 New Israeli shekels (equivalent to $9.7 ± $2.11). For households with children, the median monthly cost of the recommended diet, as a percentage of net household income was 20%. There was an inverse association with socioeconomic status, as the median monthly food expenses for the first (lowest) quintile were 55% of the household's net income and only 9.3% of the 5th (highest) income quintile. By geographic residential area, the median percentage of the net income from monthly dietary costs was 23%. The highest costs were in Judea, Samaria, and Jerusalem. Lunch made up 47% of food expenditures, if theoretically omitted, diet expenditures for households with children would decrease by an average of 15%. 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%). CONCLUSION: This theoretical calculation shows that two-thirds of the households with children in Israel could not purchase the recommended diet in 2018, with significant disparities according to socioeconomic status. Policymakers should consider steps to decrease health inequality in food affordability, targeting the three middle-lower income quintiles. Our findings suggest the need to expand the provision of school lunches. Further research is required to examine how changes in household food costs influence consumers' food choices and the potential health implications of the high expenses identified in this study.
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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 | 0.008 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".