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Performing Data Mining And Integrative Analysis Of Biomarker in Breast Cancer Using Multiple Publicly Accessible Databases
Published on: May 17, 2019
Association between dietary patterns and risk of breast cancer in Chinese female population: a latent class analysis
Shang Cao1, Shurong Lu2, Jinyi Zhou2
1Department of Epidemiology and Health Statistics, Southeast University, Dingjiaqiao Road 87, Nanjing210009, Jiangsu, China.
Objective:
To determine if specific dietary patterns are associated with breast cancer (BC) risk in Chinese women.
Design:
Latent class analysis (LCA) was performed to identify generic dietary patterns based on daily food-frequency data.
Setting:
The Chinese Wuxi Exposure and Breast Cancer Study (2013-2014).
Participants:
A population-based case-control study (695 cases, 804 controls).
Results:
Four dietary patterns were identified, Prudent, Chinese traditional, Western and Picky; the proportion in the controls and cases was 0·30/0·32/0·16/0·23 and 0·29/0·26/0·11/0·33, respectively. Women in Picky class were characterised by higher extreme probabilities of non-consumption of specific foods, the highest probabilities of consumption of pickled foods and the lowest probabilities of consumption of cereals, soya foods and nuts. Compared with Prudent class, Picky class was associated with a higher risk (OR = 1·42, 95 % CI 1·06, 1·90), while the relevant association was only in post- (OR = 1·44, 95 % CI 1·01, 2·05) but not in premenopausal women. The Western class characterised by high-protein, high-fat and high-sugar foods, and the Chinese traditional class characterised by typical consumption of soya foods and white meat over red meat, both of them showed no difference in BC risk compared with Prudent class did.
Conclusions:
LCA captures the heterogeneity of individuals embedded in the population and could be a useful approach in the study of dietary pattern and disease. Our results indicated that the Picky class might have a positive association with the risk of BC.
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