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Record W4413669183 · doi:10.1016/j.advnut.2025.100503

Adolescent Dietary Intake and Breast Cancer in Adulthood: A Systematic Review and Meta-analysis

2025· review· en· W4413669183 on OpenAlexaboutno aff
Gladys Huiyun Lim, Ying Tan, Ethan Lee, Christine Kim Yan Loo, Nivetha Kumar, Mary Foong‐Fong Chong, Airu Chia

Bibliographic record

VenueAdvances in Nutrition · 2025
Typereview
Languageen
FieldMedicine
TopicCancer Risks and Factors
Canadian institutionsnot available
FundersNational University of Singapore
KeywordsMeta-analysisBreast cancerMedicineOncologyMEDLINECancerInternal medicinePhysiologyBiology

Abstract

fetched live from OpenAlex

: Adolescence represents a key opportunity for breast cancer prevention, as the rapid proliferation of breast tissue during puberty creates a critical window of vulnerability for the development of cancerous cells. With increasing research on adolescent dietary factors and breast cancer risk, we conducted a systematic review and meta-analysis to summarize the associations between adolescent diet and risk of breast cancer in adulthood, as well as benign breast disease (BBD) and high mammographic breast density, which are markers for breast cancer. We searched Web of Science, Ovid MEDLINE, Cochrane CENTRAL and Embase for epidemiological studies assessing dietary intakes in adolescent girls (aged 10-18 years), published through 16 October 2024, with no language or time restrictions. Study quality was assessed using the Newcastle-Ottawa Scale and results were pooled using random-effects models. The review included 51 studies, mostly from the USA, with the majority relying on adult recall of adolescent diet, and only 20 studies assessed as high quality. Higher adolescent intakes of fruits and vegetables (RR: 0.90; 95% CI: 0.82, 0.99; n=3 studies), soy (RR: 0.67; 95% CI: 0.55, 0.82; n=3), dietary fiber (RR: 0.78; 95% CI: 0.67, 0.92; n=3), and vegetable fat (RR: 0.76; 95% CI: 0.66, 0.88; n=2) were associated with lower risks of breast cancer in adulthood. No significant associations were observed for meat and poultry, fish, processed meat/fish, eggs, dairy, milk, grains, alcohol, total fat, animal fat, and isoflavone. Additionally, greater consumption of dietary fiber (RR: 0.64; 95% CI: 0.50, 0.82; n=2) and vitamin D (RR: 0.77; 95% CI: 0.62, 0.95; n=2) during adolescence was associated with lower risks of BBD, while no dietary associations were observed for mammographic breast density. Our findings underscore the importance of both diet and timing in breast cancer prevention. Future well-designed prospective life course studies are needed to strengthen this evidence base. Registry This systematic review and meta-analysis was registered with PROSPERO (CRD42024532597). Statement of significance To our knowledge, this is the first comprehensive review to review and quantify the association between adolescent intake of various dietary components and breast cancer risk in adulthood. Current dietary strategies for breast cancer prevention are largely informed by epidemiological evidence from studies involving adult populations. Our findings offer preliminary insights into potential pathways linking dietary exposures during adolescence to breast cancer development. We also identify critical gaps in adolescent research, emphasizing the need for continued high-quality research targeting the formative years to inform future prevention efforts.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.010
metaresearch head score (Gemma)0.029
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Meta-analysis · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.016
Threshold uncertainty score0.053

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0100.029
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0160.032
Bibliometrics0.0060.007
Science and technology studies0.0010.001
Scholarly communication0.0030.002
Open science0.0020.002
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0040.000

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.

Opus teacher head0.042
GPT teacher head0.391
Teacher spread0.349 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designMeta-analysis
Domainnot available
GenreReview

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".

Quick stats

Citations2
Published2025
Admission routes1
Has abstractyes

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