Do prenatal factors shape the risk for dementia?: A systematic review of the epidemiological evidence for the prenatal origins of dementia
Bibliographic record
Abstract
PURPOSE: Prenatal factors such as maternal stress, infection and nutrition affect fetal brain development and may also influence later risk for dementia. The purpose of this systematic review was to provide an overview of all studies which investigated the association between prenatal factors and later risk for dementia. METHODS: We systematically searched MEDLINE and Embase for original human studies reporting on associations between prenatal factors and dementia from inception to 23 November 2022. Prenatal factors could be any factor assessed during pregnancy, at birth or postnatally, provided they were indicative of a prenatal exposure. Risk of bias was assessed using the Newcastle Ottawa Scale. We followed PRISMA guidelines for reporting. RESULTS: A total of 68 studies met eligibility criteria (including millions of individuals), assessing maternal age (N = 30), paternal age (N = 22), birth order (N = 15), season of birth (N = 16), place of birth (N = 13), prenatal influenza pandemic (N = 1) or Chinese famine exposure (N = 1), birth characteristics (N = 3) and prenatal hormone exposure (N = 4). We observed consistent results for birth in a generally less optimal environment (e.g. high infant mortality area) being associated with higher dementia risk. Lower and higher birth weight and prenatal famine exposure were associated with higher dementia risk. The studies on season of birth, digit ratio, prenatal influenza pandemic exposure, parental age and birth order showed inconsistent results and were hampered by relatively high risk of bias. CONCLUSION: Our findings suggest that some prenatal factors, especially those related to a suboptimal prenatal environment, are associated with an increased dementia risk. As these associations may be confounded by factors such as parental socioeconomic status, more research is needed to examine the potential causal role of the prenatal environment in dementia.
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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 | 0.008 | 0.046 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.008 | 0.010 |
| Bibliometrics | 0.010 | 0.013 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".