Central obesity and diet quality in rural farming women of Ngamiland, Botswana.
Bibliographic record
Abstract
Rapid economic growth in Botswana like in other countries has led to the emergence of nutrition transition . Overweight/obesity , central adiposity and associated co - morbidities are on the rise, especially amongst women. Urban women have been shown to be more prone to overweight/obesity compared to men . However , the situation in rural women has not been studied. Therefore, this paper assesses the prevalence of central obesity in rural female farmers (N=113) of Ngamiland, Botswana over two years. Estimation of central obesity was made through assessment of waist circumference (WC) and waist hip ratios (WHR) . The WHO Indicator cut - off points ( WC: l ow risk = <80 cm ; increased = 80 - 87.9 cm ; and substantially increased = >88 cm and WHR: low risk = ≤0.85 and high risk = 0.85+ ) for risk of metabolic complication were used to categorize women according to body fat ness levels . A non - quantified dietary diversity questionnaire was also administered to individual s with responsibility over food , to assess the participant ’ s dietary diversity. Women were assigned dietary diversity score s (DDS) ranging from 0 to 8, depending on the number of food groups represented in their diet in the past 24 hours. The higher the number t he more diversified the diet . These measurements were collected in August 2010 and September 2011. Between 2010 and 2011 the mean WC increased from 87±11.8 to 90.2±14.5 while the WHRs in 2010 increased from 0.83±0.1 to 0.86±0.1 respectively . Diets comprised mostly of starchy foods, milk and miscellaneous foods such as fats/oils, sugars, and condiments. Mean DDS for both periods was 3 showing poo r quality diet and little change over the two years. Central adiposity was observed amongst the women as shown by a significant increase in WC between 2010 and 2011 (t=2.818, df=112, p=0.006) . Contrary to expectations that rural female farmers in Ngamiland Botswana would be healthy compared to their non - farming counterparts, there seems to be an observable similar trend of overweight. Furthermore, quality of traditional diets seems to be deteriorating with less consumption of healthy protective and nutrient dense foods , which are likely to influence a rise in metabolic complications. The authors therefore recommend strategies that will facilitate reduction of waist size s to 80.0 cm such as farming and consumption of healthier foods such as fruits and vegetables along with the commonly produced ones in the fields . F arming communities should also value and include traditional and wild foods in their diets to increase dietary diversity and reduce the risk of development of chronic diseases.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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 | 0.000 |
| 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) | 0.000 | 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 teacher head, 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".