Identifying Cofactors Contributing to Food Insecurity in Elderly Maine Residents Living at Home
Bibliographic record
Abstract
The purpose of this study was to identify cofactors that contribute to food insecurity in Maine's older adults living at home, examine how the COVID-19 pandemic affected access to nutritious food, and make recommendations for program expansion and development. This study was a cross-sectional survey design of older adults aged 65 years and older participating in the Meals on Wheels program in Maine (n = 58) in early 2021. Research participants were compensated with grocery store gift cards. The DETERMINE Nutrition Checklist total nutrition scores and USDA Six-Item Food Security scores were compared to self-reported access to food to see how accurately older adults view their nutritional status. Chi-squared analysis was used to examine associations among food insecurity and demographic traits. A probability of p ≤ 0.05 was chosen for significance. Region of residence and food security score were significantly associated; 55.2% (n = 32) of participants had scores (0–1) indicating they were food secure. One-quarter of participants had low food security, and 11 persons had very low food security. DETERMINE scores were not statistically significant for either age range or region, suggesting that risk of malnutrition functioned independently from region and age range. However, 75.9% (n = 44) of participants received scores indicating that they were at high risk of malnutrition. Only 20 persons regularly used SNAP benefits, and few people took advantage of other food programs such as the Senior Farmers Market Nutrition Program and food pantries. Food security among Maine seniors is not necessarily related to finances, especially during the COVID-19 pandemic. The most common cofactors influencing access to food were physical access and ability, and fear or guilt of asking for help. Future work should seek to survey older adults, especially those in the most rural and impoverished counties, who are not currently using food support services such as Meals on Wheels to better evaluate food insecurity among older Maine residents. Maine Top Scholar Award and NIFA Hatch funds were used in this study.
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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 | 0.002 |
| 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 | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".