Features of Child Food Insecurity after the 2010 Haiti Earthquake: Results from Longitudinal Random Survey of Households
Bibliographic record
Abstract
BACKGROUND: Recent commentary on the health consequences of natural disasters has suggested a dearth of research on understanding the antecedents prior to the disaster that are associated with health consequences after the disaster. Utilizing data from a two-wave panel survey of Port-au-Prince, Haiti, conducted just prior to and six weeks after the January 2010 earthquake, we test factors prior to the quake hypothesized to be associated with food insecurity after the quake. METHODS: Using random Global Positioning System (GPS) sampling, we re-interviewed 93.1% (N = 1732) of the original 1,800 households interviewed in 2009. Respondents were queried with regard to mortalities, injuries, food security, housing, and other factors after the quake. FINDINGS: Child food insecurity was found to be common on all three indices of food security (17.2%-22.6%). Additionally, only 36.5% of school-aged children were attending school prior to the quake. Findings suggest that prior schooling was associated with a substantial reduction on food insecurity indices (OR 0.62-0.75). Findings further suggest that several household characteristics were associated with food insecurity for children. Prior chronic/acute illnesses, poor living conditions, remittances from abroad, primary respondent mental health, and histories of criminal and other human rights violations committed against family members prior to the quake were associated with food insecurity after the earthquake. Earned household income after the quake was only associated with one of the measures of food insecurity. INTERPRETATION: Food insecurity for children was common after the quake. Those households vulnerable on multiple dimensions prior to the quake were also vulnerable to food insecurity after the quake. Remittances from abroad were leading protective factors for food security. Because Haiti is well known for the potentiality of both hurricanes and earthquakes, reconstruction and redevelopment should focus on ameliorating potential vulnerabilities to poor outcomes in these natural disasters.
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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 | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".