Association Of Physical Activity During Pregnancy With Intelligence In Childhood: The Gestafitos Project
Bibliographic record
Abstract
PURPOSE: To assess the influence of maternal sedentary time and physical activity during pregnancy on children’s intelligence at 4 years of age. METHODS: Data from 73 pregnant individuals and their children were collected between 2015 and 2021. To objectively measure their sedentary time and physical activity levels (light, moderate, moderate-to-vigorous and total physical activity), participants wore Actigraph GT3X+ Triaxial accelerometers for 9 consecutive days during their 16th gestational week. Children’s verbal, non-verbal and composite intelligence were assessed, at 4 years of age, with the Kaufman Brief Intelligence test. RESULTS: Moderate maternal physical activity in the 16th gestational week was associated with better non-verbal intelligence (model 1, β = 0.297, R2 = 0.464, p = 0.020; model 2, β = 0.335, R2 = 0.582, p = 0.014) and composite intelligence (model 1, β = 0.305, R2 = 0.274, p = 0.039; model 2, β = 0.344, R2 = 0.328, p = 0.044) in their children at 4 years of age. Moderate-to-vigorous physical activity was associated with better non-verbal intelligence (model 1, β = 0.286, R2 = 0.456, p = 0.030; model 2, β = 0.319, R2 = 0.570, p = 0.024) and composite intelligence (model 1, β = 0.306, R2 = 0.270, p = 0.045; model 2, β = 0.336, R2 = 0.320, p = 0.056). The remaining associations were not significant (all p > 0.05). CONCLUSION: Moderate and moderate-to-vigorous physical activity during pregnancy were associated with greater intelligence in children at 4 years of age. Table 1. - Influence of maternal sedentary time and physical activity at 16th gestational week on Kaufman Brief Intelligence test score Model Independent sample Dependent sample B SEE β R 2 P 1 Sedentary time (min/week) Verbal intelligence 0.000 4.577 -0.042 0.398 0.729 2 0.000 5.118 -0.061 0.379 0.677 1 Non-verbal intelligence 0.000 3.999 -0.033 0.401 0.788 2 0.000 3.706 -0.018 0.500 0.893 1 Composite intelligence -0.001 23.880 -0.036 0.207 0.800 2 -0.001 24.688 -0.040 0.243 0.803 1 Light physical activity (min/week) Verbal intelligence 0.000 4.575 0.049 0.398 0.687 2 0.001 5.107 0.082 0.382 0.574 1 Non-verbal intelligence 0.000 3.999 -0.034 0.401 0.781 2 -0.001 3.689 -0.073 0.505 0.575 1 Composite intelligence 0.000 23.896 -0.004 0.206 0.979 2 0.000 24.709 -0.012 0.242 0.943 1 Moderate physical activity (min/week) Verbal intelligence 0.007 4.504 0.168 0.417 0.197 2 0.008 5.007 0.202 0.406 0.199 1 Non-verbal intelligence 0.010 3.782 0.297 0.464 0.020 2 0.011 3.389 0.335 0.582 0.014 1 Composite intelligence 0.056 22.850 0.305 0.274 0.039 2 0.058 23.257 0.344 0.328 0.044 1 Moderate-to-vigorous physical activity (min/week) Verbal intelligence 0.007 4.505 0.172 0.417 0.201 2 0.008 5.017 0.199 0.403 0.219 1 Non-verbal intelligence 0.010 3.809 0.286 0.456 0.030 2 0.010 3.436 0.319 0.570 0.024 1 Composite intelligence 0.555 22.908 0.306 0.270 0.045 2 0.056 23.404 0.336 0.320 0.056 1 Total physical activity (min/week) Verbal intelligence 0.001 4.563 0.076 0.402 0.522 2 0.001 5.083 0.113 0.387 0.426 1 Non-verbal intelligence 0.000 4.001 0.017 0.400 0.885 2 -8.446-5 3.706 -0.012 0.500 0.928 1 Composite intelligence 0.002 23.864 0.049 0.208 0.719 2 0.002 24.674 0.050 0.244 0.752 *Model 1 is adjusted for age and sex of the child, maternal age, educational status and adherence to Mediterranean diet in the 16th gestational week; model 2 is adjusted for age and sex of the child, maternal age, educational status, adherence to Mediterranean diet in the 16th gestational week and physical activity and adherence to Mediterranean diet of the child. Andalusian FEDER operational program; 7th Framework Program of the European Community, Marie Skłodowska-Curie Actions; Ministry of Economy, Innovation, Science and Employment of the Board from Andalusia; National Plan for Scientific and Technical Research and Innovation 2017-2020 (FPU20 02938)
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.002 |
| 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".