Comparison of the dietary intake of the urban black population in Cape Town in 1990 with 2009
Bibliographic record
Abstract
Background: In 1990 the BRISK was undertaken in the black population in five townships in Cape Town, Langa, Gugulethu, Khayalitsha, Nyanga, and Crossroads.The prevalence of noncommunicable diseases (diabetes and heart disease) and their risk factors, including dietary intake were investigated.Aim: To determine the dietary intake of the urban black population (25-64 years) of Cape Town in 2009 and compare these findings with a similar sample examined in the same townships in 1990. Study design and sample:A cross-sectional survey including a representative sample of 392 males and 707 females (n=1099) was drawn from the same townships as in 1990.Methods: Socio-demographic data were collected by trained field workers.Weight, height, and waist and hip circumference were measured.Body mass index (BMI), and waist-hip ratio (WHR) were calculated.Dietary intake data (macro-and micronutrients, mean adequacy ratio (MAR), food groups and portion sizes) were calculated using the MRC FoodFinder program and compared with the dietary reference intakes.The MAR was calculated for each participant.Data analyses: Anthropometric and dietary data are presented as means and standard deviations by age, level education, type of housing, degree of urbanisation and asset index (proxy for socioeconomic status).Associations of dietary data with anthropometric and biochemistry data (TC, HDL-C, LDL-C, and glucose), blood pressure, asset index, and degree of urbanisation were assessed.A linear regression model was computed using MAR as the dependent variable and adding age, gender, urbanisation, asset index and other variables to the model.Correlations between the asset index and urbanisation duration were done with energy and nutrient intakes using Pearson's correlations.Regressions were done to test the significance of various variables.Results: Most of the adults had an education of at least 8-12 years, though 60% of the males and 58.3% of females were unemployed, and 13.8% were pensioners.Twenty-one per cent lived in formal houses, 35.4% in council houses or hostels, and 43.6% in shacks.Only 12.1% of adults had spent less than 20% of their life in an urban area.Thirty three per cent were classified as falling within the poorest tertile of the asset index.The percentage of adults with a BMI greater than 30 kg/m 2 was 63.3% in females and 12% in males.Males had a WC and WHR of 85.7 cm and 0.89 and females 97.5 cm and 0.85, respectively.Analysis of the 24-hour dietary recall data showed very low mean energy intakes [M 6516 (2929); F 5760 (2446) kJ].These results did not support the high prevalence of obesity, particularly in females, and also in four other studies among urban black populations.Hence the Goldberg equation was used to remove under-reporters.The remaining sample comprised 544 (214 males and 330 females) participants residing in Khayelitsha (42.4%),Langa (31.4%),Gugulethu (15.3%), and less than 10% in Crossroads and Nyanga.
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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 | 0.001 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 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".