scholarly journals Dietary patterns and oral and pharyngeal cancer using latent class analysis

2019 ◽  
Vol 147 (3) ◽  
pp. 719-727 ◽  
Author(s):  
Michela Dalmartello ◽  
Adriano Decarli ◽  
Monica Ferraroni ◽  
Francesca Bravi ◽  
Diego Serraino ◽  
...  
2020 ◽  
pp. 1-24
Author(s):  
Shang Cao ◽  
Shurong Lu ◽  
Jinyi Zhou ◽  
Zheng Zhu ◽  
Wei Li ◽  
...  

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.


2010 ◽  
Vol 140 (12) ◽  
pp. 2253-2259 ◽  
Author(s):  
Daniela Sotres-Alvarez ◽  
Amy H. Herring ◽  
Anna Maria Siega-Riz

2021 ◽  
Vol 8 ◽  
Author(s):  
Shang Cao ◽  
Linchen Liu ◽  
Qianrang Zhu ◽  
Zheng Zhu ◽  
Jinyi Zhou ◽  
...  

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.


2018 ◽  
Vol 21 (16) ◽  
pp. 2929-2940 ◽  
Author(s):  
Ilana Nogueira Bezerra ◽  
Nila Mara Smith Galvão Bahamonde ◽  
Dirce Maria Lobo Marchioni ◽  
Dóra Chor ◽  
Letícia de Oliveira Cardoso ◽  
...  

AbstractObjectiveTo identify generational differences in the dietary patterns of Brazilian adults born between 1934 and 1975.DesignA cross-sectional study from the baseline of the multicentre Brazilian Longitudinal Study of Adult Health (ELSA-Brasil) cohort. Year of birth was categorized into three birth generations: Traditionalists (born between 1934 and 1945); Baby Boomers (born between 1946 and 1964); and Generation X (born between 1965 and 1975). Food consumption was investigated using an FFQ. Latent class analysis (LCA) was used to identify data-driven dietary patterns.SettingBrazil.SubjectsIndividuals (n 15 069) aged 35–74 years.ResultsA three-class model was generated from the LCA for each birth generation. Generation X presented higher energy intakes (kJ/kcal) from soft drinks (377·4/90·2) and sweets (1262·3/301·7) and lower energy intakes from fruit (1502·5/359·1) and vegetables (311·3/74·4) than Baby Boomers (283·7/67·8, 1047·7/250·4, 1756·0/419·7 and 365·3/87·3, respectively) and Traditionalists (186·2/44·5, 518·8/124·0, 1947·7/465·5 and 404·6/96·7, respectively). For Baby Boomers and Generation X, we found food patterns with similar structures: mixed pattern (22·7 and 29·7 %, respectively), prudent pattern (43·5 and 34·9 %, respectively) and processed pattern (33·8 and 35·4 %, respectively). Among Traditionalists, we could also identify mixed (30·9 %) and prudent (21·8 %) patterns, and a third pattern, named restricted dietary pattern (47·3 %).ConclusionsThe younger generation presented higher frequencies of consuming a pattern characterized by a low nutritional diet, compared with other generations, indicating that they may age with a greater burden of chronic diseases. It is important to develop public health interventions promoting healthy foods, focusing on the youngest generations.


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