Association between risk-related lifestyle factors, screening adherence and breast cancer incidence: a decomposition analysis.

Md Sohel Rana, M Luke Marinovich, Nehmat Houssami, Dominic Cavenagh, Julie E Byles, Xue Qin Yu, Md Mijanur Rahman

Abstract read

In one paragraph

Article in Scientific reports, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it

0cells of the map it votes in

0citing papers in PubMed

–field-weighted citation impact

1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

7 authors.

Md Sohel RanaThe Daffodil Centre, The University of Sydney and Cancer Council NSW, Sydney, Australia. mran9130@uni.sydney.edu.au.ORCID 0000-0003-3749-6807

M Luke MarinovichThe Daffodil Centre, The University of Sydney and Cancer Council NSW, Sydney, Australia.

Nehmat HoussamiThe Daffodil Centre, The University of Sydney and Cancer Council NSW, Sydney, Australia.

Dominic CavenaghCentre for Women's Health Research, University of Newcastle, Newcastle, Australia.

Julie E BylesHunter Medical Research Institute, New Lambton Heights, Australia.

Xue Qin Yu *The Daffodil Centre, The University of Sydney and Cancer Council NSW, Sydney, Australia.

Md Mijanur Rahman *The Daffodil Centre, The University of Sydney and Cancer Council NSW, Sydney, Australia.

Funding

National Breast Cancer Foundation 2023/IIRS0028National Breast Cancer Foundation EC-21-001National Health and Medical Research Council 1194410

6 · The paper itself

Abstract

Adherence to breast cancer (BC) screening may have mediated the association between lifestyle-related risk factors and BC incidence, but evidence on this hypothesis remains limited. This study aimed to decompose the overall effects of lifestyle factors on BC incidence, considering the mediating effect of screening adherence. In this longitudinal cohort study with follow-up from 2001 (cohort age: 50-55) to 2019 (cohort age: 68-73), we used a four-way decomposition approach to break down the overall effect of lifestyle factors on BC incidence into direct effects and mediated effects through screening adherence to quantify their total excess risk ratios (TERRs). Of the 10,579 women included in the study, 5.40% (n = 571) were diagnosed with BC during follow-up, with a higher proportion among those who adhered to BC screening (5.83%, n = 474) than non-adherers (3.96%, n = 97). The overall increased risk of BC was observed for higher body mass index (BMI) (TERR = 1.30), alcohol consumption (TERR = 1.55), and hormone replacement therapy (HRT) use (TERR = 1.57) (all P < 0.0001). The direct effects remained significant for BMI (excess relative risk [ERR] = 0.37, p = 0.001), alcohol consumption (ERR = 0.44, p = 0.003), and oral contraceptive use (ERR = - 0.69, p < 0.001) after adjusting for the mediation effect of screening. Significant indirect effects were also observed for alcohol consumption (3.32%, p = 0.001) and HRT use (5.08%, p < 0.001). These findings underscore the complex nature of BC risk and highlight the importance of considering both lifestyle factors and screening in cancer prevention strategies.

Indexed as

Breast NeoplasmsEarly Detection of CancerLife StylePatient ComplianceAgedAlcohol DrinkingBody Mass IndexFemaleHumansIncidenceLongitudinal StudiesMiddle AgedRisk FactorsBreast cancerFour-way decompositionLifestyle factorsScreening adherence

Identifiers

PMID42332007

DOI10.1038/s41598-026-58989-8

PMCPMC13572556

What Socratic holds

Textmetadata

Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the Socratic graph.