A assessment of the effects of parental age on the development of autism in children: a systematic review and a meta-analysis
Bibliographic record
Abstract
OBJECTIVE: There has been conflicting evidence in earlier research on the association between parental age and autism risk. To clarify this association, we conducted a comprehensive meta-analysis of observational studies. The primary objective of this study was to determine the association between parents' age and the risk of autism in the offspring. METHODS: PubMed, EMBASE and Web of Science were searched for reports published up to November 2023. Results from relevant studies were pooled using random effects models. Subgroup analyses and meta-regression were performed to examine heterogeneity between the studies. Studies were included in this meta-analysis that focused on children with autism and examined the relationship between parents' age (mother or father) and the risk of autism.The quality of studies was assessed using the Newcastle-Ottawa Scale (NOS). RESULTS: This meta-analysis included 41 articles. The low age of mother (OR = 0.96, (95% CIs: 0.88-1.05) and father (OR = 1.11, (95% CIs: 0.98-1.24) was not significantly associated with lower risk of autism in children. Conversely, greater paternal and maternal ages were associated with an increased risk of autism in their children. The adjusted odds ratios for mothers' and fathers' ages were 1.47 (95% CIs: 1.33-1.62) and 1.51 (95% CIs: 1.40-1.62), respectively. CONCLUSION: Increased risk of autism in children is significantly associated with greater parents' ages. Further research is needed to gain further insight into the mechanisms responsible for the effects of parents' ages on the risk of autism in children. The findings of previous studies on the association between parents' ages and their children's autism risk have been mixed. Therefore, by carefully examining a number of previous investigations, in this study we aimed to determine the exact relationship between parental age and autism risk. According to the study's findings, parents who are older have a higher chance of their child getting autism. In other words, children of older parents are more likely to develop autism. The exact causes of this relationship, however, are still unclear. This study shows that higher age of parents can be one of the risk factors for autism in their childs.
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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 | 0.023 | 0.046 |
| Meta-epidemiology (narrow) | 0.004 | 0.002 |
| Meta-epidemiology (broad) | 0.025 | 0.062 |
| Bibliometrics | 0.011 | 0.010 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".