Maternal smoking during pregnancy and newborn telomere length (TL): a systematic review and meta-analysis of observational studies
Bibliographic record
Abstract
BACKGROUND: Telomeres indicate cellular aging. Shortened telomeres are linked to various diseases and mortality, influenced by factors like inflammation, genetics, and environmental exposures, including smoking. Assessing newborn telomere length (TL) and maternal smoking association remains unexplored. A systematic review aims to fill this gap, potentially advancing clinical understanding and guiding future research. METHODS: This systematic review involved searching six English electronic databases—PubMed, Scopus, PsycINFO, Web of Science, Embase, and CINAHL Complete—for records from their inception until February 2024. The review focused solely on observational studies. Included studies assessed the impact of maternal smoking during pregnancy on the TL of newborns. The quality of these studies was evaluated using the Newcastle–Ottawa quality assessment scale. A random-effect model was employed, and the statistical analysis was conducted with Stata software version 17. RESULTS: Eight of 485 initial studies were included for systematic and five for meta-analysis. Eight studies involving 2,797 participants investigated prenatal smoking’s impact on infant telomere length, predominantly using qPCR and umbilical cord blood cells for measurement of TL. Five studies with 1,822 participants assessed the effect of maternal smoking during pregnancy on newborn TL, revealing a significant negative correlation (-0.19 [-0.32, -0.09]). Despite high heterogeneity (I2: 85.57%), no publication bias was found. Sensitivity analysis, excluding one study, showed a stronger correlation (-0.27 [-0.36, -0.17]) and reduced heterogeneity (I2: 53.21%). Subgroup analysis by nationality indicated a slightly stronger correlation in North American studies (-0.21 [-0.30, -0.12]) compared to Asian studies (-0.17 [-0.52, 0.17]). No significant differences were observed (p = 0.85). CONCLUSION: A meta-analysis found maternal smoking in pregnancy correlates negatively with neonatal telomere length, impacting aging. Urgent awareness and further research are needed for preventive measures.
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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 | 0.021 | 0.059 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.016 | 0.035 |
| Bibliometrics | 0.009 | 0.011 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| 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".