Consumption of Ultra-Processed Foods and Anthropometric Status of Adults in Ikwuano Local Government Area, Abia State Nigeria
Bibliographic record
Abstract
Background: Ultra-processed foods are industrially formulated food products manufactured largely by food companies packaged in such a way to make them intensely palatable, have long shelf stability and eliminate the need for culinary preparations. Objective: This study assessed the consumption of ultra-processed foods and anthropometric status of adults aged (20-49 years) in Ikwuano Local Government Area Abia State, Nigeria. Methods: The study was a cross sectional survey of 440 adults randomly selected for the study. A well-structured and validated questionnaire was used to collect information on the socio-economic and demographic characteristics, the consumption of ultra-processed foods, the dietary pattern and anthropometric status of the respondents. The questionnaires were coded and entered into computer using the statistical package for social sciences (SPSS) version 23.0. The data were analyzed using descriptive statistics. Chi-square analysis was used to assess the relationship between the consumption of ultra-processed foods and anthropometric status of the respondents. Results: More than half of the respondents (67.0%) were males while 33.0% were females. Majority of the adults (62.3%) were between the ages of 26 and 32 years. Majority of the respondents (80.0%) were Christian, about 18.0% were traditionalist, and more than half of the respondents (82.2%) were Igbo. More than half of the respondents (63.6%) had tertiary education. About a quarter of the respondents (48.0%) were traders/business persons, 27.7% were civil/public servant, 8.2% were farmers and 2.5% were unemployed. About a quarter of the respondents (46.8%) earned less than ₦30,000 a month. only a few of the respondents (3.4%) earned above ₦91,000 per month. One third of the respondents consumed sweets, candies, soft drinks, pizza, burger, pasta, canned vegetables and sweetened breakfast cereals daily. About half of the respondents (53.0%) who were overweight consumed soft drinks daily. A total of 36.3% of the respondents were overweight, while 20% were obese. The chi-square analysis showed there was a significant association (p<0.000) between consumption of cake, pizza, burger and BMI of the respondents. Obesity was higher amongst male adults than female adults. Conclusion: One third of the respondents were overweight, while about 20% were obese. There is need to focus on educating the community on the need to consume home-made dishes from fresh indigenous foods.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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) | 0.002 | 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".