Food Inhibitory Control and Reward Responsiveness in Healthy Aging
Bibliographic record
Abstract
OBJECTIVES: Living in a complex food environment, humans face numerous decisions and choices every day. These decisions necessitate cognitive resources and the ability to balance metabolic needs with gratification. This study sought to examine whether aging enhances responses to food stimuli due to reduced inhibitory control or reduces such responses due to a decline in the motivational system. METHODS: 50 young adults, aged 20-30 years, and 55 older adults, aged 65-91 years, without obesity, were recruited. Participants were asked to rate explicitly liking, wanting, and healthiness of both high- and low-calorie foods on a Likert scale. Additionally, they completed an affective priming task measuring affective reactions toward foods and a food go/no-go task to assess inhibitory control. RESULTS: Older adults exhibit reduced food liking and wanting compared to young adults, but did not show increased impulsivity or implicit preference for high- and/or low-calorie foods. No significant relationship between perceived healthiness and reward responsiveness was observed in the older adult group. DISCUSSION: Our findings suggest that healthy aging is characterized by a diminished response to food due to low reward responsiveness. This is noteworthy, as the hedonic properties of foods are commonly believed to guide dietary choices. Understanding the relationship between age and food-related behavior is crucial for developing targeted dietary interventions for older adults, which could enhance their overall health and quality of life.
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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 | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 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) | 0.001 | 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".