Affiliation:
1. Department of Oncology, The First Affiliated Hospital of Nanjing Medical University, 300 Guangzhou Road, Nanjing 210029, China
2. Geriatric Institute, Jiangsu Province Geriatric Hospital, Nanjing Medical University Affiliated Geriatric Hospital, Nanjing 210029, China
Abstract
Aims. This paper aims to investigate the relationship of waist circumference (WC) with digestive tract cancer morbidity and mortality. Methods. Based on the data from a nationally representative US population survey, we summarized the prevalence of digestive tract cancer and all-cause mortality of cancer patients across WC quartiles. Adjusted logistic regression and restricted spline curve were used to analyze WC and the prevalence of digestive tract cancer. Moreover, Cox regression and the Kaplan-Meier curve were applied to investigate the association of WC with all-cause mortality. We also attempted to make a model to predict cancer happening. Results. This paper included a total of 34,041 participants, with digestive tract cancer observed in 265 (0.7%) individuals. WC was positively associated with digestive tract cancer morbidity after full adjustment of covariates (OR: 1.72 and 95% CI: 1.41-2.10). Also, individuals in the highest WC group had a higher risk of digestive tract cancer (Q4, OR: 2.71 and 95% CI: 1.48-5.00). Moreover, no significant association was observed in upper digestive cancer, and WC was associated with a longer survival time once diagnosed (hazard ratio (HR): 0.50 and 95% CI: 0.28-0.92). Finally, the model we made proved to be effective. Conclusion. High WC is a risk factor for digestive tract cancer with or without adjusting for body mass index, especially those located in the lower digestive tract. However, once digestive tract cancer has been diagnosed, patients with higher WC showed better survival outcomes. Moreover, machine learning methods can be used to predict digestive tract cancer risk in the future.
Funder
National Basic Research Program of China
Subject
Applied Mathematics,General Immunology and Microbiology,General Biochemistry, Genetics and Molecular Biology,Modeling and Simulation,General Medicine