Nutritional Risk Assessment by Scored Patient-Generated Subjective Global Assessment Associated with Demographic Characteristics in 23, 904 Common Malignant Tumors Patients. (2nd January 2019)

• Record Type: Journal Article
• Authors: Song, Chunhua; Cao, Jingjing; Zhang, Feng; Wang, Chang; Guo, Zengqing; Lin, Yuan; Shi, Yingying; Hu, Wen; Ba, Yi; Xu, Hongxia; Li, Wei; Shi, Hanping
• Is Part Of: Nutrition and cancer. Volume 71:Number 1(2019)
• Page Start: 50
• Page End: 60
• Publication Date: 2019-01-02
• Subjects: Cancer -- Periodicals; Nutrition -- Periodicals; Cancer; Nutrition; Periodicals; 616.9940654
• DOI: 10.1080/01635581.2019.1566478
• Languages: English
• ISSNs: 0163-5581

Abstract

Abstract: Malnutrition is a problem affecting tumor patients greatly. This study aims to investigate whether demographic characteristics are related to the malnutrition of cancer patients. Twenty-three thousand nine hundred and four (23, 904) patients with 16 common malignant tumors were enrolled in the study. Patient Generated Subjective Global Assessment (PG-SGA) was used as a screening tool to assess the nutritional risk of patients and analysis of variance was used to compare PG-SGA scores of patients. Correlations between PG-SGA scores and demographic characteristics were evaluated by correlation analysis. We observed that 57.88% tumor patients had some degree of malnutrition (score ≥4) and only 20.61% were well-nourished (score 0–1). Screening scores were higher among older patients for most of the tumors. PG-SGA scores showed the significant difference between females and males in some tumors. In addition, the PG-SGA scores of some tumors were significantly different in various types of medical insurances, education levels, occupations, regions, and nationalities. Correlation analysis indicated the existence of associations between PG-SGA scores and demographic characteristics. Understanding the distribution of nutritional risk of tumor patients and the correlations between the PG-SGA scores and demographic characteristics could help identify subgroups who may benefit from targeted interventions to improve the effect of clinical treatment and the quality of life for oncology patients.