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The use of data from Food Frequency Questionnaire (FFQ) for network analysis on cancer survivorship and food intake

Principal Investigator
Name
Linghan Qian
Degrees
M.S.
Institution
Tufts University
Position Title
Master candidate
Email
About this CDAS Project
Study
PLCO (Learn more about this study)
Project ID
PLCO-405
Initial CDAS Request Approval
Oct 15, 2018
Title
The use of data from Food Frequency Questionnaire (FFQ) for network analysis on cancer survivorship and food intake
Summary
This study aims to analyze the network relations between the prostate, lung, colorectal and ovarian cancer incidence/mortality and the dietary food intake among the U.S. population. Dietary and Dietary History data, Incidence data and Mortality data from PLCO dataset will be used for the network analysis. DQX and DHQ data will be merge via inner join. To deal with missing data, multiple imputation packages in SAS (Proc MI and Proc MIANALYZE) will be used. The health outcomes will be the incidence and mortality of PLCO cancer. The environmental exposure will be the dietary food intake. The predictors are the cross-section correlations between the prostate, lung, colorectal and ovarian cancer incidence/mortality and each food group (whole grain, refined grain, meat, fruits, vegetables, etc.). The results will be adjusted by age, gender, and total energy intake.

Network theory: Network theory is the study of complex relationships between discrete objects using node-edge weighted network as a representation. Network analysis is widely applied to analyze complex relational data in different disciplines, including physics, computer science, biology and etc. In health field, network theory
Aims

- To study the overall relationship between survivorship of different cancers and food categories
- To apply the weighed correlation network analysis on cancer survivorship and food intake

Collaborators

Elena N. Naumova Tufts University