Association between dietary patterns and risk of breast cancer in Chinese female population: a latent class analysis

2020 ◽  
pp. 1-24
Author(s):  
Shang Cao ◽  
Shurong Lu ◽  
Jinyi Zhou ◽  
Zheng Zhu ◽  
Wei Li ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Latent Class Analysis ◽  
Dietary Patterns ◽  
Latent Class ◽  
Chinese Women ◽  
Premenopausal Women ◽  
Positive Association ◽  
Class Analysis ◽  
Female Population ◽  
Soy Foods

ABSTRACT Objective: To determine if specific dietary patterns are associated with breast cancer 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 were 0.30/0.32/0.16/0.23 and 0.29/0.26/0.11/0.33, respectively. Women in Picky class were characterized by higher extreme probabilities of non-consumption on specific foods, the highest probabilities of consumption of pickled foods, and the lowest probabilities of consumption of cereals, soy 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 premenopausal women. The Western class characterized by high-protein, -fat, and -sugar foods, the Chinese traditional class characterized by typical consumption of soy foods and white meat over red meat, both of them showed no difference in BC risk compared with Prudent class did. Conclusions: LCA capture the heterogeneity of individuals embedded in the population, 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 breast cancer.

Body composition patterns and breast cancer risk in Chinese women with breast diseases: A latent class analysis

2019 ◽  
Vol 75 (11) ◽  
pp. 2638-2646
Author(s):  
Jinyu Zhang ◽  
Jichuan Wang ◽  
Jie Zhou ◽  
Qiong Fang ◽  
Nan Zhang ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Body Composition ◽  
Breast Cancer Risk ◽  
Cancer Risk ◽  
Latent Class Analysis ◽  
Latent Class ◽  
Chinese Women ◽  
Breast Diseases ◽  
Class Analysis

scholarly journals Association Between Dietary Patterns and Plasma Lipid Biomarker and Female Breast Cancer Risk: Comparison of Latent Class Analysis (LCA) and Factor Analysis (FA)

2021 ◽  
Vol 8 ◽  
Author(s):  
Shang Cao ◽  
Linchen Liu ◽  
Qianrang Zhu ◽  
Zheng Zhu ◽  
Jinyi Zhou ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Factor Analysis ◽  
Breast Cancer Risk ◽  
Cancer Risk ◽  
Latent Class Analysis ◽  
Dietary Patterns ◽  
Latent Class ◽  
Plasma Lipid ◽  
Apolipoprotein A1 ◽  
Class Analysis

Background: Diet research focuses on the characteristics of “dietary patterns” regardless of the statistical methods used to derive them. However, the solutions to these methods are both conceptually and statistically different.Methods: We compared factor analysis (FA) and latent class analysis (LCA) methods to identify the dietary patterns of participants in the Chinese Wuxi Exposure and Breast Cancer Study, a population-based case-control study that included 818 patients and 935 healthy controls. We examined the association between dietary patterns and plasma lipid markers and the breast cancer risk.Results: Factor analysis grouped correlated food items into five factors, while LCA classified the subjects into four mutually exclusive classes. For FA, we found that the Prudent-factor was associated with a lower risk of breast cancer [4th vs. 1st quartile: odds ratio (OR) for 0.70, 95% CI = 0.52, 0.95], whereas the Picky-factor was associated with a higher risk (4th vs. 1st quartile: OR for 1.35, 95% CI = 1.00, 1.81). For LCA, using the Prudent-class as the reference, the Picky-class has a positive association with the risk of breast cancer (OR for 1.42, 95% CI = 1.06, 1.90). The multivariate-adjusted model containing all of the factors was better than that containing all of the classes in predicting HDL cholesterol (p = 0.04), triacylglycerols (p = 0.03), blood glucose (p = 0.04), apolipoprotein A1 (p = 0.02), and high-sensitivity C-reactive protein (p = 0.02), but was weaker than that in predicting the breast cancer risk (p = 0.03).Conclusion: Factor analysis is useful for understanding which foods are consumed in combination and for studying the associations with biomarkers, while LCA is useful for classifying individuals into mutually exclusive subgroups and compares the disease risk between the groups.

scholarly journals Latent Class Analysis Is Useful to Classify Pregnant Women into Dietary Patterns

2010 ◽  
Vol 140 (12) ◽  
pp. 2253-2259 ◽  
Author(s):  
Daniela Sotres-Alvarez ◽  
Amy H. Herring ◽  
Anna Maria Siega-Riz
Keyword(s):  
Latent Class Analysis ◽  
Pregnant Women ◽  
Dietary Patterns ◽  
Latent Class ◽  
Class Analysis

Schizotypal traits in adolescents: Links to family history of psychosis and psychological distress

2012 ◽  
Vol 28 (4) ◽  
pp. 247-253 ◽  
Author(s):  
M. Cella ◽  
M. Serra ◽  
A. Lai ◽  
O.J. Mason ◽  
D. Sisti ◽  
...  
Keyword(s):  
Psychological Distress ◽  
Family History ◽  
Latent Class Analysis ◽  
Latent Class ◽  
General Health Questionnaire ◽  
Positive Association ◽  
Total Sample ◽  
Class Analysis ◽  
Item Endorsement ◽  
History Of

AbstractObjectiveStudies in the general population report that unusual subjective experiences are relatively common. Such experiences have been conceptualized either as extreme personality traits or as vulnerability markers for psychosis, and often grouped under the expression “schizotypal experiences”. This study investigates the heterogeneity of schizotypal traits using factor and latent class analysis.MethodsOne thousand and thirty-two adolescents were recruited for this study. Schizotypal experiences were assessed with the Oxford-Liverpool Inventory of Feelings and Experiences (O-LIFE); psychological distress was assessed with the General Health Questionnaire (GHQ). Confirmatory Factorial Analysis (CFA) and Latent Class Analysis (LCA) were performed on the O-LIFE and on the association with the GHQ and demographic variables.ResultsCFA replicated the original 4-factor structure of the O-LIFE. Three latent classes (LC) of schizotypal features were identified: participants in LC1 (26% of the total sample) showed minimal level of item endorsement; LC2 accounted for 52% of the sample and showed overall higher item endorsement compared to LC1, especially for disorganization and positive signs of schizotypy, but not for negative affective items. LC3 (22%) showed an overall higher level of item endorsement across schizotypal dimensions, and positive association with psychological distress and family history of psychosis.DiscussionDifferent latent class of schizotypal features can be empirically defined in adolescent community samples. The most extreme class is defined not only by a profile of higher positive replies to the items, but also by anhedonia, high psychological distress, and family history of psychosis. These findings can inform prevention research in schizophrenia.

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