Association between Geriatric Nutrition Risk Index and low muscle mass in Chinese elderly people

Eur J Clin Nutr. 2019 Jun;73(6):917-923. doi: 10.1038/s41430-018-0330-8. Epub 2018 Oct 4.

Abstract

Background/objectives: The aim of the study was to evaluate the relationship between Geriatric Nutrition Risk Index (GNRI) and low muscle mass (LMM) in elderly people.

Subjects/methods: A cross-sectional study was carried out in Chinese PLA General Hospital with 3240 participants who underwent a health check-up examination between February 2016 and February 2017. Linear regression and logistic regression were used to examine the relationship between GNRI and LMM.

Results: The mean age of the participants in the study was 64.6 years. The mean appendicular skeletal muscle mass index (ASMI) was 8.92 ± 0.93 kg/m2 in men and 7.62 ± 0.73 kg/m2 in women. The incidences of LMM were 7.9% in men and 3.7% in women. Linear regression demonstrated that GNRIs were positively correlated with ASMIs in both men and women (β = 0.055 for men and 0.039 for women, all P < 0.001). The cut-off point of the GNRI in elderly people for LMM was 104.0 in men and 107.0 in women and were identified by Classification and Regression Trees (CART). Logistic regression showed that both men and women with decreased GNRIs had higher ratios of LMM [odds ratio (OR) = 3.904 for men and 4.486 for women, P < 0.001 and P = 0.001, respectively].

Conclusions: Elderly people with a low GNRI had a higher incidence of LMM, which suggested that GNRI had a close relationship with LMM and that it could be a good indicator in identifying senior people who need further nutritional support and physical activity.

MeSH terms

  • Aged
  • Aged, 80 and over
  • Asian People
  • China / epidemiology
  • Cross-Sectional Studies
  • Female
  • Frail Elderly*
  • Geriatric Assessment*
  • Health Services for the Aged
  • Humans
  • Incidence
  • Male
  • Malnutrition / complications
  • Malnutrition / physiopathology*
  • Middle Aged
  • Muscle, Skeletal / diagnostic imaging
  • Regression Analysis
  • Risk
  • Sarcopenia / epidemiology*
  • Sarcopenia / physiopathology