Assessment of Obesity Among Pregnant Women in the Volta Region of Ghana
Bibliographic record
Abstract
Background: Obesity remains a rising challenge in both developed and developing countries, and maternal obesity has become one of the most occurring risk factors, which can lead to gestational diabetes, pre-eclampsia and prematurity in obstetric practice for both the mother and the child. Pregnancy is a timeline where obesity cannot be effectively worked on as the mother is more likely to live unhealthy lifestyle such as unhealthy diet, binge eating and less physical activity, which would most likely affect foetal health. This is an issue as most pregnant women in Volta Region are either overweight or obese. This research assessed the prevalence of obesity among pregnant women in the Volta Region of Ghana. Material and Method: A full structured questionnaire was administered to 220 participants based on their knowledge of obesity and its effect on pregnancy, food choices, mealtimes and portion sizes, as well as physical activity during pregnancy. Body weight and height were measured using standardized procedures and body mass index (BMI) was calculated. Overweight and obesity were defined based on WHO criteria. Data analysis was performed using SPSS version 20.0. Results: Based on excessive gestational weight gain, prevalence of obesity among the pregnant women was 54% (119). Majority of respondents had poor knowledge of obesity and its effect on the mother and the foetus, which represented a significant correlation (p< 0.0001) between their caloric intake and high gestational weight gain. Physical activity showed no significant effect (p = 0.2) on gestational weight gain. However, pre-pregnancy BMI of the expectant mothers was directly linked to high gestational weight gain with age being the significant risk factor (p<0.02) for obesity before pregnancy. Conclusion: This research found limited awareness of excessive gestational weight gain and its health consequences among pregnant women and the unborn baby. Therefore, monitoring gestational weight gain using diverse approaches to integrate and manage the condition in routine antenatal care needs consideration.
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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 | 0.000 | 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".