BACKGROUND: it has been observed that a frailty index (FI) is limited by the value of 0.7. Whether this holds in countries with higher mortality rates is not known. OBJECTIVES: to test for and quantify a limit in very old Chinese adults and to relate mortality risk to the FI. DESIGN: secondary analysis of four waves (1998, 2000, 2002 and 2005) of the Chinese Longitudinal Health and Longevity Study (CLHLS). SUBJECTS: a total of 6,300 people from 22 of 31 provinces in China, aged 80-99 years at baseline and followed up to 7 years. METHODS: an FI was calculated as the ratio of actual to 38 possible health deficits. Frequency distributions were used to evaluate the limit to the FI. Logistic regression and survival analysis were used to evaluate the relationship between the FI and mortality. RESULTS: at each wave, a 99% submaximal limit to frailty was observed at FI = 0.7, despite consecutive losses to death. The death rate for those who were healthiest at baseline (i.e. those in whom the baseline FI = 0) increased from 0.18 at the 2-year follow-up to 0.69 by 7 years. At each wave, 100% mortality at 2 years was observed at FI close to 0.67. A baseline FI >0.45 was associated with 100% 7-year mortality. CONCLUSIONS: a limit to frailty occurred with FI = 0.7 which was not exceeded at any age or in any wave. There appears to be a demonstrable limit to the number of health problems that people can tolerate.
BACKGROUND: it has been observed that a frailty index (FI) is limited by the value of 0.7. Whether this holds in countries with higher mortality rates is not known. OBJECTIVES: to test for and quantify a limit in very old Chinese adults and to relate mortality risk to the FI. DESIGN: secondary analysis of four waves (1998, 2000, 2002 and 2005) of the Chinese Longitudinal Health and Longevity Study (CLHLS). SUBJECTS: a total of 6,300 people from 22 of 31 provinces in China, aged 80-99 years at baseline and followed up to 7 years. METHODS: an FI was calculated as the ratio of actual to 38 possible health deficits. Frequency distributions were used to evaluate the limit to the FI. Logistic regression and survival analysis were used to evaluate the relationship between the FI and mortality. RESULTS: at each wave, a 99% submaximal limit to frailty was observed at FI = 0.7, despite consecutive losses to death. The death rate for those who were healthiest at baseline (i.e. those in whom the baseline FI = 0) increased from 0.18 at the 2-year follow-up to 0.69 by 7 years. At each wave, 100% mortality at 2 years was observed at FI close to 0.67. A baseline FI >0.45 was associated with 100% 7-year mortality. CONCLUSIONS: a limit to frailty occurred with FI = 0.7 which was not exceeded at any age or in any wave. There appears to be a demonstrable limit to the number of health problems that people can tolerate.
Authors: Jeremy Walston; Thomas N Robinson; Susan Zieman; Frances McFarland; Christopher R Carpenter; Keri N Althoff; Melissa K Andrew; Caroline S Blaum; Patrick J Brown; Brian Buta; E Wesley Ely; Luigi Ferrucci; Kevin P High; Stephen B Kritchevsky; Kenneth Rockwood; Kenneth E Schmader; Felipe Sierra; Kaycee M Sink; Ravi Varadhan; Arti Hurria Journal: J Am Geriatr Soc Date: 2017-04-19 Impact factor: 5.562
Authors: Ariela R Orkaby; Lisa Nussbaum; Yuk-Lam Ho; David Gagnon; Lien Quach; Rachel Ward; Rachel Quaden; Enzo Yaksic; Kelly Harrington; Julie M Paik; Dae H Kim; Peter W Wilson; J Michael Gaziano; Luc Djousse; Kelly Cho; Jane A Driver Journal: J Gerontol A Biol Sci Med Sci Date: 2019-07-12 Impact factor: 6.053
Authors: Ruth E Hubbard; Nancye M Peel; Mayukh Samanta; Leonard C Gray; Brant E Fries; Arnold Mitnitski; Kenneth Rockwood Journal: BMC Geriatr Date: 2015-03-18 Impact factor: 3.921
Authors: Joanne Ryan; Sara Espinoza; Michael E Ernst; A R M Saifuddin Ekram; Rory Wolfe; Anne M Murray; Raj C Shah; Suzanne G Orchard; Sharyn Fitzgerald; Lawrence J Beilin; Stephanie A Ward; Jeff D Williamson; Anne B Newman; John J McNeil; Robyn L Woods Journal: J Gerontol A Biol Sci Med Sci Date: 2022-01-07 Impact factor: 6.591