Serum total cholesterol: A mortality predictor in elderly hospitalized patients

Avraham Weiss, Yichayaou Beloosesky, Hemda Schmilovitz-Weiss, Ehud Grossman, Mona Boaz

Research output: Contribution to journalArticlepeer-review

22 Scopus citations


Background & aims: Elevated serum total cholesterol levels are associated with increased risk of cardiovascular mortality among middle aged adults, but not the elderly. We therefore examined whether increased serum total cholesterol reduces mortality risk in the hospitalized elderly. Methods: Of 1852 patients consecutively admitted to an acute geriatric department from 1/1/99-12/31/00, only 298 (49.6% males, mean age 81.36±6.3 years) who had measured serum total cholesterol and albumin levels were included in the study and followed until August 31, 2004. Mortality data were extracted from their death certificates. Results: During follow-up of 3.47±1.87 years, 248 patients died. These patients had significantly lower levels of baseline serum total cholesterol (183.3±45.4 vs. 200.2±37.9, p=0.01) and albumin (3.6±0.5 vs. 3.8±0.3g/l, p=0.002) than the survivors. In the Cox regression analysis, serum total cholesterol emerged as a significant, independent predictor of mortality in this cohort. Specifically, each 1mg/dl increase in serum total cholesterol reduced risk of death by 0.4%. This association persisted even after controlling for serum creatinine, age, body mass index, dementia and congestive heart failure. These factors were also significantly, independently associated with mortality. Conclusion: In very elderly hospitalized subjects, increased levels of serum total cholesterol and albumin may be associated with reduced mortality risk.

Original languageEnglish
Pages (from-to)533-537
Number of pages5
JournalClinical Nutrition
Issue number4
StatePublished - Aug 2013


  • Elderly
  • Hospitalized
  • Mortality
  • Serum total cholesterol


Dive into the research topics of 'Serum total cholesterol: A mortality predictor in elderly hospitalized patients'. Together they form a unique fingerprint.

Cite this