Low calf circumference can predict nutritional risk and mortality in adults with metabolic syndrome aged over 80 years

BMC Endocr Disord. 2022 Feb 23;22(1):47. doi: 10.1186/s12902-022-00964-1.

Abstract

Background: Metabolic disorders and malnutrition are a double burden worldwide. The aim was to determine whether low calf circumference (CC) could predict nutritional risk and the cut-off values of CC for predicting nutritional risk in metabolic syndrome (MetS) patients aged over 80 years. We aimed to evaluate the risk factors for predicting mortality in MetS.

Methods: A total of 514 patients aged over 80 years with MetS were enrolled and followed for 2.5 years. On admission, demographic data, CC, and laboratory parameters were obtained. Patients with a Nutritional Risk Screening 2002 (NRS 2002) total score ≥ 3 were considered to have nutritional risk.

Results: The CC level was significantly lower in the nutritional risk group than in the non-nutritional risk with MetS group (27.1 ± 4.0 cm vs. 30.8 ± 3.9 cm). Logistic regression analysis of nutritional risk revealed that increasing CC (adjusted OR, 0.81; 95% CI, 0.74-0.88) was an independent protective factor against nutrition risk. The best CC cut-off value for predicting nutritional risk according to the NRS 2002 was 28.8 cm. Cox regression multivariate models showed nutritional risk (HR, 2.48; 95% CI, 1.22-5.04) and decreased CC (HR, 2.78; 95% CI, 1.27-5.98) remained independent risk factors for mortality.

Conclusion: Decreased CC could predict not only nutritional risk but also mortality in MetS patients aged over 80 years. The elderly who had MetS with nutritional risk should be discovered early, early intervention and early treatment. CC may be a valuable index to screen out this population.

Keywords: Calf circumference; Metabolic syndrome; Mortality; NRS 2002; Nutritional risk.

MeSH terms

  • Aged, 80 and over
  • Anthropometry
  • Humans
  • Leg / pathology*
  • Malnutrition / complications
  • Malnutrition / diagnosis
  • Mass Screening
  • Metabolic Syndrome / mortality*
  • Metabolic Syndrome / pathology*
  • Nutritional Status*
  • Odds Ratio
  • Proportional Hazards Models
  • Risk Factors