Obesity burden by socioeconomic measures between 2000 and 2018 among women in sub‐Saharan Africa: A cross‐sectional analysis of demographic and health surveys
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Background: The increasing global burden of obesity especially in low-and-middle-income countries (LMICs) accentuates the need for critical action. In the absence of evidence-based approaches to mitigate recent obesity trends, the likelihood of reaching global obesity targets will be almost zero. Objective: This study examined the obesity prevalence in Sub-Sahara Africa and observed transitions on the burden of obesity prevalence over time. Methods: Data from the Demographic and Health Survey which is based on cross sessional design was used. Most recent surveys carried out in 16 sub-Saharan Africa (SSA) between 2000 and 2018 were included in the analysis. Equiplot by the International Centre for Equity was used to display the inequities by the following socioeconomic measures: wealth index, education, and place of residence. Age-standardized prevalence was measured across these socioeconomic measures using the WHO standard population age distribution, examined changing trends and finally assessed transition in obesity prevalence by percentage point difference of highest and lowest prevalence within each of the three socioeconomic measures. Results: A total of 496,482 women were included in the analysis. Obesity prevalence among women varied substantially, from 2% in Chad to 27% in Lesotho. Variation in obesity prevalence was observed across countries and by socioeconomic status measures. Among women in all the countries except Comoros, the burden was concentrated among the wealthiest. Out of the 16 countries included, the prevalence of obesity was concentrated among women with no education in eight countries (Benin, Burundi, Chad, Cote d'Ivoire, Guinea, Mali, Niger, Comoros) while it was concentrated in those with primary education in Congo and Lesotho and among those with secondary school education in DR Congo, Gabon, Namibia, Nigeria, and Zimbabwe. The burden of obesity was more concentrated in the urban across the 16 countries except in Comoros and Lesotho where they were higher in the rural (8.9 [7.2, 11.1] and 15.1 [13.0, 17.5] respectively) than in urban (6.6 [5.0, 8.8] and 6.8 [5.2, 8.8] respectively). Finally, the trend analysis with five countries indicated that the prevalence and gap in obesity among women increased between previous and most recent surveys except in Zimbabwe where it reduces across the three socioeconomic measures between 2011 and 2018. Conclusions: This study examined transition in obesity prevalence among women across three socioeconomic measures in selected sub-Saharan African countries. Increasing prevalence of obesity was found in SSA but transition to women in lower socioeconomic status is already taking place in some countries.
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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 | 0.016 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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 it