Association between dietary intake networks identified through a Gaussian graphical model and the risk of cancer: a prospective cohort study.
Purpose: In this study, we aimed to investigate the association between dietary communities identified by a Gaussian graphical model (GGM) and cancer risk. Methods: We performed GGM to identify the dietary communities in a Korean population. GGM-derived communities were then scored and investigated...
| Publicado en: | European Journal of Nutrition Vol. 61; no. 8; pp. 3943 - 3961 |
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| Autores principales: | , , , |
| Formato: | equations & formulas research tables/charts Journal Article |
| Publicado: |
Springer Nature
Dec2022
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| Acceso en línea: | Ver este registro en EBSCOhost |
| fields | @attributes: recordID: 1 pdfLink: plink: https://search.ebscohost.com/login.aspx?direct=true&db=ccm&AN=159838921&site=ehost-live header: @attributes: shortDbName: ccm uiTerm: 159838921 longDbName: CINAHL Complete uiTag: AN controlInfo: bkinfo: dissinfo: jinfo: jid: 14366207 CR0 jtl: European Journal of Nutrition issn: 14366207 maglogo: N pubinfo: dt: Dec2022 vid: 61 iid: 8 pid: 237 pub: Springer Nature place: New York, New York artinfo: ui: 159838921 157682397 159838921 159838921 10.1007/s00394-022-02938-4 159838921 ppf: 3943 ppct: 18 formats: fmt: – @attributes: type: T – @attributes: type: P tig: atl: Association between dietary intake networks identified through a Gaussian graphical model and the risk of cancer: a prospective cohort study. aug: au: Gunathilake, Madhawa Hoang, Tung Lee, Jeonghee Kim, Jeongseon affil: Department of Cancer Biomedical Science, National Cancer Center Graduate School of Cancer Science and Policy, 323 Ilsan-ro, Ilsandong-gu, 10408, Goyang, Gyeonggi-do, Republic of Korea sug: subj: Diet Neoplasms Risk Factors Risk Assessment South Korea Human Female Male Prospective Studies Cox Proportional Hazards Model Factor Analysis Regression Descriptive Statistics Confidence Intervals Dairy Products Bread Female Male ab: Purpose: In this study, we aimed to investigate the association between dietary communities identified by a Gaussian graphical model (GGM) and cancer risk. Methods: We performed GGM to identify the dietary communities in a Korean population. GGM-derived communities were then scored and investigated for their association with cancer incidence in the entire population as well as in the 1:1 age- and sex-matched subgroup using a Cox proportional hazards model. In the sensitivity analysis, GGM-derived communities were compared to dietary patterns (DPs) that were identified by principal component analysis (PCA) and reduced rank regression (RRR). Results: During a median time to follow-up of 6.6 years, 397 cancer cases were newly diagnosed. The GGM identified 17 and 16 dietary communities for the total and matched populations, respectively. For each one-unit increase in the standard deviation of the community-specific score of the community that was composed of dairy products and bread, there was a reduced risk of cancer according to the fully adjusted model (HR: 0.80, 95% CI: 0.66–0.96). In the matched population, the third tertile of the community-specific score of the community composed of poultry, seafood, bread, cakes and sweets, and meat by-products showed a significantly reduced risk of cancer compared to that of the lowest tertile in the fully adjusted model (HR: 0.66, 95% CI: 0.50–0.86, p-trend = 0.002). Conclusion: We found that the GGM-identified community composed of dairy products and bread showed a reduced risk of cancer. Further population-based prospective studies should be conducted to examine possible associations of dietary intake and specific cancer types. pubtype: Academic Journal doctype: equations & formulas research tables/charts Journal Article ougenre: Article language: English refInfo: holdings: @attributes: islocal: N |
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