Observational studyInternational journal of epidemiology2026
Adiposity and risk of breast cancer in 280 000 Chinese women: a prospective cohort study.
Christiana Kartsonaki, Neil Wright, Iona Millwood, Yuanjie Pang, Dianjianyi Sun, Pei Pei, Dan Schmidt, Rebecca Stevens, Yuan Cao, Huaidong Du and 8 more
Abstract readObservational Study
In one paragraphObservational study in International journal of epidemiology, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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0citing papers in PubMed
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1 · What the graph read from itWhat 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 registryThe 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 literatureWho cites it
0 citing papers in PubMed.
No citing paper in PubMed yet.
4 · The recordCorrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
5 · Who and what moneyAuthors and funding
18 authors.
Christiana KartsonakiClinical Trial Service Unit & Epidemiological Studies Unit (CTSU), Nuffield Department of Population Health, Big Data Institute Building, University of Oxford, Oxford, United Kingdom.ORCID 0000-0002-3981-3418 Neil WrightClinical Trial Service Unit & Epidemiological Studies Unit (CTSU), Nuffield Department of Population Health, Big Data Institute Building, University of Oxford, Oxford, United Kingdom.
Iona MillwoodClinical Trial Service Unit & Epidemiological Studies Unit (CTSU), Nuffield Department of Population Health, Big Data Institute Building, University of Oxford, Oxford, United Kingdom.
Yuanjie PangDepartment of Epidemiology and Biostatistics, School of Public Health, Peking University Health Science Center, Beijing, China.ORCID 0000-0002-4826-8861 Dianjianyi SunDepartment of Epidemiology and Biostatistics, School of Public Health, Peking University Health Science Center, Beijing, China.ORCID 0000-0003-3651-6693 Pei PeiPeking University Center for Public Health and Epidemic Preparedness & Response, Beijing, China.ORCID 0000-0002-5741-6563 Dan SchmidtClinical Trial Service Unit & Epidemiological Studies Unit (CTSU), Nuffield Department of Population Health, Big Data Institute Building, University of Oxford, Oxford, United Kingdom.
Rebecca StevensClinical Trial Service Unit & Epidemiological Studies Unit (CTSU), Nuffield Department of Population Health, Big Data Institute Building, University of Oxford, Oxford, United Kingdom.
Yuan CaoTongxiang CDC, Tongxiang, Zhejiang, China.
Huaidong DuClinical Trial Service Unit & Epidemiological Studies Unit (CTSU), Nuffield Department of Population Health, Big Data Institute Building, University of Oxford, Oxford, United Kingdom.ORCID 0000-0002-9814-0049 Jun LvDepartment of Epidemiology and Biostatistics, School of Public Health, Peking University Health Science Center, Beijing, China.ORCID 0000-0001-7916-3870 Yiping ChenClinical Trial Service Unit & Epidemiological Studies Unit (CTSU), Nuffield Department of Population Health, Big Data Institute Building, University of Oxford, Oxford, United Kingdom.ORCID 0000-0002-4973-0296 Canqing YuDepartment of Epidemiology and Biostatistics, School of Public Health, Peking University Health Science Center, Beijing, China.ORCID 0000-0002-0019-0014 Junshi ChenChina National Center for Food Safety Risk Assessment, Beijing, P. R. China.
Derrick BennettClinical Trial Service Unit & Epidemiological Studies Unit (CTSU), Nuffield Department of Population Health, Big Data Institute Building, University of Oxford, Oxford, United Kingdom.ORCID 0000-0002-9170-8447 Liming LiDepartment of Epidemiology and Biostatistics, School of Public Health, Peking University Health Science Center, Beijing, China.
Ling YangClinical Trial Service Unit & Epidemiological Studies Unit (CTSU), Nuffield Department of Population Health, Big Data Institute Building, University of Oxford, Oxford, United Kingdom.ORCID 0000-0001-5750-6588 Zhengming ChenClinical Trial Service Unit & Epidemiological Studies Unit (CTSU), Nuffield Department of Population Health, Big Data Institute Building, University of Oxford, Oxford, United Kingdom.ORCID 0000-0001-6423-105X Funding
Kadoorie Charitable Foundation in Hong Kong 104085/Z/14/ZKadoorie Charitable Foundation in Hong Kong 202922/Z/16/ZKadoorie Charitable Foundation in Hong Kong 212946/Z/18/Z
6 · The paper itselfAbstract
backgroundAdiposity is associated with increased risk of breast cancer in post-menopausal women, while the association appears to be the inverse among premenopausal women in Western populations, but is unclear for Chinese women.
methodsUsing data on 284 538 women with no history of cancer, hysterectomy, oophorectomy, or breast surgery at baseline in 2004-8 from the China Kadoorie Biobank (a prospective cohort study), Cox regression was used to estimate adjusted hazard ratios (HRs) for breast cancer and its subtypes by measured body mass index (BMI) and other adiposity measures (waist circumference, fat percentage, waist-hip ratio, fat mass) and by self-reported BMI at age 25 years.
resultsMean BMI was 23.8 (3.5 SD) kg/m2 at baseline (mean age 51.4 years) and 21.9 (2.7 SD) kg/m2 at age 25 years. During 10 years of follow-up, there were 2379 incident breast cancer cases. Higher BMI was associated with a higher risk of breast cancer in women who were post-menopausal [HR = 1.35, 95% confidence interval (CI) 1.24-1.47] and premenopausal (HR = 1.13, 95% CI 1.03-1.24) at baseline, but not when censoring at age 50 years to capture mainly premenopausal cancers. Among post-menopausal women, BMI was associated with oestrogen-receptor positive (ER ) (HR = 1.47, 95% CI 1.24-1.74), but not with oestrogen-receptor negative (ER-) breast cancer (HR = 1.02, 95% CI 0.75-1.37). Waist circumference and fat percentage were associated with a higher risk of breast cancer.
conclusionIn this cohort of Chinese women, higher levels of general and central adiposity were associated with a higher risk of breast cancer, in both women who were premenopausal and women who were post-menopausal at baseline. Among post-menopausal women, adiposity was associated with ER but not ER - breast cancer.
Indexed as
AdiposityBreast NeoplasmsObesityAdultBody Mass IndexChinaFemaleHumansIncidenceMiddle AgedPostmenopauseProportional Hazards ModelsProspective StudiesRisk FactorsWaist CircumferenceWaist-Hip Ratioadipositybreast cancerChina
Identifiers
PMID42618884
PMCPMC13489709
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