Socioeconomic inequalities in intergenerational overweight and obesity transmission from mothers to offsprings in South Africa
Bibliographic record
Abstract
This study assesses socioeconomic inequality in the intergenerational transmission of overweight and obesity from mothers to offsprings in South Africa, including the factors contributing to inequality. Data were drawn from the 2017 National Income Dynamic Study, which collected anthropometric and socioeconomic information. Non-pregnant mothers aged 15-49 years and their offsprings 0-14 years were included in the analysis. The dependent variables used in the study were the intergenerational transmission of overweight and obesity. Socioeconomic inequality was assessed using the concentration index. A positive index means that intergenerational overweight and obesity is more likely among the wealthier populations, while a negative index signifies the opposite. The concentration index was decomposed to understand the factors that explain inequalities in the transmission of overweight and obesity from mothers to offsprings. Concentration indices for the intergenerational transmission of overweight and obesity were positive for boys (0.17) and girls (0.23). Thus the intergenerational transmission of overweight and obesity occurs more among wealthier mothers. Although factors explaining socioeconomic inequality in the intergenerational transmission of overweight and obesity differed by offspring sex, mother's marital status (+38%) and socioeconomic status (around +8%) were central determinants of socioeconomic inequalities in intergenerational overweight, while mother's smoking (around +25%), education (about +13%) and employment status (around +12%) contributed to intergenerational obesity inequality. Policies to reduce overweight and obesity burdens and the intergenerational transmission of overweight and obesity in South Africa should target women who bear a significant burden of overweight and obesity and could transmit them to their offsprings. The policies should also recognise the key factors explaining these socioeconomic inequalities. This approach will reduce the future burden of diseases associated with overweight and obesity in South Africa and improve the country's overall health outcomes.
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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 | 0.001 | 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 | 0.001 | 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 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".