Older men from global settings more vulnerable to clinical changes associated with food insecurity
Bibliographic record
Abstract
Abstract Background Studies of the food security status of older adults are rare outside of the United States, especially in low- and middle-income settings. Food insecurity may contribute to disease and disability. Using a diverse sample of older adults, we examine the association of food insecurity with clinical and self-reported measures that are related to disease and impairment. Methods Cross sectional analysis of 1482 older adults from Kingston and St. Hyacinthe (Canada), Tirana (Albania), Manizales (Colombia), and Natal (Brazil). Outcome measures were Body Mass Index (BMI), waist circumference, and self-reported unintentional weight loss. Food insecurity was assessed with the 9-item Latin American and Caribbean Household Food Security Scale. Covariates were age, sex, study site, and education. Statistical analyses included Student's T-test, Chi-square test, and linear regression. Results 83% of participants were food secure; 12% experienced mild food insecurity and 5%, moderate/severe food insecurity. Among men, BMI and waist circumference varied significantly by food security status (p < 0.05). Mean BMI among men with moderate/severe food insecurity was 25.5 compared to 27.0 for mild and 27.5 for no food insecurity. The pattern for waist circumference was similar (93.9cm for moderate/severe, 96.7cm for mild, and 98.9cm for no food insecurity). More food insecure men reported unintentional weight loss (13%) than food secure men (10%). This pattern was not observed among women. Statistical adjustment for study site, education, and age did not change the findings. Conclusions Significant differences in clinical indicators of disease were observed by food security status in men. At the extreme, low BMI and waist circumference are linked to increased risk of malnutrition, compromised immune function, and respiratory and digestive diseases. Differences in these measures by food security status emphasize the need for gender and age specific food security interventions. Key messages Food insecure men experience clinical indicators of disease significantly more than food insecure women. Successful food security interventions may require sex specific focus across global settings. Little research has been done on food insecurity in elderly outside of North America and study findings contribute to significant gap in sex specific research in this population across global settings.
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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 | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".