The epidemic of obesity in South Africa: a study in a disadvantaged community.
Bibliographic record
Abstract
OBJECTIVE: The objective of this study was: 1) to determine the anthropometric profile of adults in Mamre, a small town in South Africa, which has a population of mixed ancestry ("colored" people of Afro-Euro-Malay-Khoisan ancestry); and 2) to determine the change in this profile between 1989 and 1996. DESIGN: Cross-sectional surveys conducted in random samples of adults in 1989 and 1996. PARTICIPANTS: The subjects were 684 women and 529 men in 1989, and 546 women and 430 men in 1996, aged 15 and older. MAIN OUTCOME MEASURES: The following measurements were recorded: height, weight, and circumference of waist, hips, and mid-upper arm. RESULTS: Based on data from the 1996 survey, 32% of women are obese (body mass index [BMI] > or = 30) at ages 25-44 years, rising to 49% at ages 45-64 years. A much lower prevalence of obesity is seen in men: 14% at ages 35-64 years. Obesity levels significantly increased in women between the two surveys (P=.015): up from 44% in 1989 to 49% in 1996 at ages 45-64 years. There was an increase in the prevalence of overweight (BMI 25-29.9) in men, though not in obesity. Mean BMI increased by about 3% in women and 2% in men between 1989 and 1996. CONCLUSIONS: This study conducted among people of mixed ancestry living in a disadvantaged community in South Africa shows that half of middle-aged women are obese. A rising trend in BMI was seen in adults of both sexes between 1989 and 1996. This trend may be explained by factors associated with rural-urban transition, including electrification, reduced physical activity, and increasing availability of energy-dense food.
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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 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".