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Quantitative measures of healthy aging and biological age.

Kim S, Jazwinski SM - Healthy Aging Res (2015)

Bottom Line: To facilitate the study of these factors, various descriptors of biological aging, including 'successful aging' and 'frailty', have been put forth as integrative functional measures of aging.Using FI34, we found elevated levels of resting metabolic rate linked to declining health in nonagenarians.Using FI34 as a quantitative phenotype, we have also found a genomic region on chromosome 12 that is associated with healthy aging and longevity.

View Article: PubMed Central - PubMed

Affiliation: Tulane Center for Aging and Department of Medicine, Tulane University Health Sciences Center, New Orleans, LA, USA.

ABSTRACT

Numerous genetic and non-genetic factors contribute to aging. To facilitate the study of these factors, various descriptors of biological aging, including 'successful aging' and 'frailty', have been put forth as integrative functional measures of aging. A separate but related quantitative approach is the 'frailty index', which has been operationalized and frequently used. Various frailty indices have been constructed. Although based on different numbers and types of health variables, frailty indices possess several common properties that make them useful across different studies. We have been using a frailty index termed FI34 based on 34 health variables. Like other frailty indices, FI34 increases non-linearly with advancing age and is a better indicator of biological aging than chronological age. FI34 has a substantial genetic basis. Using FI34, we found elevated levels of resting metabolic rate linked to declining health in nonagenarians. Using FI34 as a quantitative phenotype, we have also found a genomic region on chromosome 12 that is associated with healthy aging and longevity.

No MeSH data available.


Age trajectories of FI34 scores of individuals in the Healthy Aging Family Study [35]. FI34 scores can decline individually as noted previously [38], but the population or group statistic of FI34 increases over time. The plots (arrows) are from two data sets collected over a three- to four-year interval from 25 HAFS participants who were 50 to 75 years old at the time of collection of the initial data set. The blue line is the average FI34 for this group of subjects.
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Figure 3: Age trajectories of FI34 scores of individuals in the Healthy Aging Family Study [35]. FI34 scores can decline individually as noted previously [38], but the population or group statistic of FI34 increases over time. The plots (arrows) are from two data sets collected over a three- to four-year interval from 25 HAFS participants who were 50 to 75 years old at the time of collection of the initial data set. The blue line is the average FI34 for this group of subjects.

Mentions: FI is highly correlated with age and increases nonlinearly with increasing age. The non-linear relationship is best fit either by an exponential function or by a quadratic equation [16, 36]. Interestingly the rates of accumulation of deficits with age calculated from different numbers of health variables (e.g., from 20 to 92) are all close to ~2–3% per year. With FI34, the instantaneous rate of deficit accumulation falls within this range (Figure 2). The seemingly narrow range of rates may reflect insensitivity of the FI to the choice of particular items. This robustness may also come from the redundancy of variables, which may further reflect interrelationships of different body systems. Thus, redundancy is a statistical phenomenon, but it may well be based on functional relatedness between variables. It is important to remember that this continuous increase in FI34 is a population phenomenon. We have found that FI34 can increase, decrease, or remain unchanged over a period of three to five years (Figure 3).


Quantitative measures of healthy aging and biological age.

Kim S, Jazwinski SM - Healthy Aging Res (2015)

Age trajectories of FI34 scores of individuals in the Healthy Aging Family Study [35]. FI34 scores can decline individually as noted previously [38], but the population or group statistic of FI34 increases over time. The plots (arrows) are from two data sets collected over a three- to four-year interval from 25 HAFS participants who were 50 to 75 years old at the time of collection of the initial data set. The blue line is the average FI34 for this group of subjects.
© Copyright Policy - open-access
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC4440677&req=5

Figure 3: Age trajectories of FI34 scores of individuals in the Healthy Aging Family Study [35]. FI34 scores can decline individually as noted previously [38], but the population or group statistic of FI34 increases over time. The plots (arrows) are from two data sets collected over a three- to four-year interval from 25 HAFS participants who were 50 to 75 years old at the time of collection of the initial data set. The blue line is the average FI34 for this group of subjects.
Mentions: FI is highly correlated with age and increases nonlinearly with increasing age. The non-linear relationship is best fit either by an exponential function or by a quadratic equation [16, 36]. Interestingly the rates of accumulation of deficits with age calculated from different numbers of health variables (e.g., from 20 to 92) are all close to ~2–3% per year. With FI34, the instantaneous rate of deficit accumulation falls within this range (Figure 2). The seemingly narrow range of rates may reflect insensitivity of the FI to the choice of particular items. This robustness may also come from the redundancy of variables, which may further reflect interrelationships of different body systems. Thus, redundancy is a statistical phenomenon, but it may well be based on functional relatedness between variables. It is important to remember that this continuous increase in FI34 is a population phenomenon. We have found that FI34 can increase, decrease, or remain unchanged over a period of three to five years (Figure 3).

Bottom Line: To facilitate the study of these factors, various descriptors of biological aging, including 'successful aging' and 'frailty', have been put forth as integrative functional measures of aging.Using FI34, we found elevated levels of resting metabolic rate linked to declining health in nonagenarians.Using FI34 as a quantitative phenotype, we have also found a genomic region on chromosome 12 that is associated with healthy aging and longevity.

View Article: PubMed Central - PubMed

Affiliation: Tulane Center for Aging and Department of Medicine, Tulane University Health Sciences Center, New Orleans, LA, USA.

ABSTRACT

Numerous genetic and non-genetic factors contribute to aging. To facilitate the study of these factors, various descriptors of biological aging, including 'successful aging' and 'frailty', have been put forth as integrative functional measures of aging. A separate but related quantitative approach is the 'frailty index', which has been operationalized and frequently used. Various frailty indices have been constructed. Although based on different numbers and types of health variables, frailty indices possess several common properties that make them useful across different studies. We have been using a frailty index termed FI34 based on 34 health variables. Like other frailty indices, FI34 increases non-linearly with advancing age and is a better indicator of biological aging than chronological age. FI34 has a substantial genetic basis. Using FI34, we found elevated levels of resting metabolic rate linked to declining health in nonagenarians. Using FI34 as a quantitative phenotype, we have also found a genomic region on chromosome 12 that is associated with healthy aging and longevity.

No MeSH data available.