Association of Household Food Insecurity with the Mental and Physical Health of Low-Income Urban Ecuadorian Women with Children
Bibliographic record
Abstract
Chronic physical and mental health conditions account for a rising proportion of morbidity, mortality, and disability in the Americas region. Household food insecurity (HFI) has been linked to chronic disease in US and Canadian women but it is uncertain if the same is true for low- and middle-income Latin American countries in epidemiologic transition. We conducted a survey to investigate the association of HFI with the physical and mental health of 794 women with children living in low-income Quito, Ecuador, neighborhoods. Data were collected on HFI and health indicators including self-reported health (SF-1), mental health (MHI-5), blood pressure, and self-reported mental and physical health complaints. Fasting blood glucose and lipids were measured in a subsample. The multivariate analyses revealed that HFI was associated with poorer self-rated health, low MHI-5 scores, and mental health complaints including stress, depression, and ethnospecific illnesses. It was also associated with chest tightness/discomfort/pain, dental disease, and gastrointestinal illness but not other conditions. The findings suggest that improving food security in low-income households may help reduce the burden of mental distress in women with children. The hypothesized link with diabetes and hypertension may become more apparent as Ecuador moves further along in the epidemiologic transition.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".