Shared correlates of maternal and childhood overweight in Cameroon: a cross-sectional analysis of demographic and health survey data
Bibliographic record
Abstract
BACKGROUND: Overweight parents are likelier to bear overweight babies, who are likelier to grow into overweight adults. Understanding the shared risks of being overweight between the mother-child dyad is essential for targeted life course interventions. In this study, we aimed to identify such risk factors in Cameroon. METHODS: We conducted secondary data analysis using Cameroon's 2018 Demographic and Health Surveys. We used weighted multilevel binary logistic regressions to examine individual, household, and community correlates of maternal (15-49 years) and child (under five years) overweight. RESULTS: We retained 4511 complete records for childhood and 4644 for maternal analysis. We found that 37% [95%CI:36-38%] of mothers and 12% [95%CI:11-13%] of children were overweight or obese. Many environmental and sociodemographic factors were positively associated with maternal overweight, namely urban residence, wealthier households, higher education, parity and being a Christian. Childhood overweight was positively associated with a child being older and a mother being overweight, a worker, or a Christian. Therefore, only religion affected both mothers overweight (aOR: 0.71[95%CI:0.56-0.91]) and childhood overweight (aOR 0.67[95%CI: 0.5-0.91]). Most of the potentially shared factors only indirectly affected childhood overweight through maternal overweight. CONCLUSION: Besides religion, which affects both mothers and childhood overweight (with the Muslim faith being protective), much of childhood overweight is not directly explained by many of the observed determinants of maternal overweight. These determinants are likely to influence childhood overweight indirectly through maternal overweight. Extending this analysis to include unobserved correlates such as physical activity, dietary, and genetic characteristics would produce a more comprehensive picture of shared mother-child overweight correlates.
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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 | 0.002 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".