Food behavior, social aspects and nutritional status in Romania
Bibliographic record
Abstract
Introduction. Health status is directly linked with nutritional status, life style and food behaviour. There are 4 Health Indicators: Health Conscience, Health Information Orientation, Health-Oriented Beliefs, and Healthy Activities. People who are health conscious have a positive attitude towards preventive measures such as healthy eating. Health information refers to the extent to which an individual is willing to seek health information. At the cognitive level, health orientation is manifested in the field of health beliefs, which refers to the specific cognitions held by individuals about health behaviors. Also, health-oriented individuals are more likely to engage in healthy activities than other people in the population. The four aspects of the health orientation mentioned suggest the differences between individuals in the context of their sources of information in the health field. Our aim was to evaluate connections between social characteristics, nutritional status data and food behaviour, in a Romanian population sample. Material and methods. We followed a qualitative cross-sectional study based on screening of 751 Romanian adults from different regions of our country, which was carried out in 2018. We used a validated questionnaire from an international project, based on 26 specific questions, filled in online, regarding their nutritional and social data completed by their attitudes and information towards food behaviour. In our group, 68.7% were women, one quarter had over 50 years old, 82.3% were from urban areas and almost 2/3rds were higly educated. Results. We obtained a positive correlation between demographic parameters and the BMI, also healthy food behaviors were more frequent at women versus man. On the opposite, the confidence of men upon the information about healthy eating from the internet was higher than that of women. The number of hours/day spent watching TV or in front of the computer was positively correlated with age and also with their BMI. A high education level was significantly positively associated with healthier choices regarding nutrition practices. Health status in relation with nutritional status showed us that the most concerned group for their diet was those who suffered from different pathologies especially cardiovascular disorders. We obtained no significant associations among BMI, environment, current professional activity, responsibility for eating, and physical activity. Conclusions. Nutritionists, specialists in medicine, and food stakeholders should promote healthy diets through adequate sources of information aimed at target groups. Multidisciplinary teams should develop a more efficient strategy to motivate people to make healthy eating choices and improve population food behavior.
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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 | 0.001 |
| 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 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".