Limits...
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.


Distribution of FI34 scores of individuals in the Louisiana Healthy Aging Study (LHAS) and the Healthy Aging Family Study (HAFS). The FI34 scores were compiled for subjects in LHAS [76] and HAFS [35], according to the methods described [35]. Shown are all the age groups (A), 459 young individuals (20–60 years old) (B); 348 middle-aged (60–90 years old) (C), and 382 old (90–104 years old) (D).
© Copyright Policy - open-access
Related In: Results  -  Collection

License
getmorefigures.php?uid=PMC4440677&req=5

Figure 1: Distribution of FI34 scores of individuals in the Louisiana Healthy Aging Study (LHAS) and the Healthy Aging Family Study (HAFS). The FI34 scores were compiled for subjects in LHAS [76] and HAFS [35], according to the methods described [35]. Shown are all the age groups (A), 459 young individuals (20–60 years old) (B); 348 middle-aged (60–90 years old) (C), and 382 old (90–104 years old) (D).

Mentions: The distribution of FI scores is usually positively skewed (Figure 1A), which is best fit by the gamma density function where two parameters determining shape and scale are involved [16]. Demographically, the distribution of FI scores changes depending on the age groups considered (Figure 1B–D). Since the FI is highly correlated with age, the skewed distribution reflects the presence of healthy groups (gamma distribution) and unhealthy frail groups (normal distribution). Longitudinally, the two-parameter distribution might represent two-stage changes, where the first stage corresponds to individuals’ resilience to the deleterious changes, and the second stage to the deteriorating stage of declining function with age [16].


Quantitative measures of healthy aging and biological age.

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

Distribution of FI34 scores of individuals in the Louisiana Healthy Aging Study (LHAS) and the Healthy Aging Family Study (HAFS). The FI34 scores were compiled for subjects in LHAS [76] and HAFS [35], according to the methods described [35]. Shown are all the age groups (A), 459 young individuals (20–60 years old) (B); 348 middle-aged (60–90 years old) (C), and 382 old (90–104 years old) (D).
© Copyright Policy - open-access
Related In: Results  -  Collection

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

Figure 1: Distribution of FI34 scores of individuals in the Louisiana Healthy Aging Study (LHAS) and the Healthy Aging Family Study (HAFS). The FI34 scores were compiled for subjects in LHAS [76] and HAFS [35], according to the methods described [35]. Shown are all the age groups (A), 459 young individuals (20–60 years old) (B); 348 middle-aged (60–90 years old) (C), and 382 old (90–104 years old) (D).
Mentions: The distribution of FI scores is usually positively skewed (Figure 1A), which is best fit by the gamma density function where two parameters determining shape and scale are involved [16]. Demographically, the distribution of FI scores changes depending on the age groups considered (Figure 1B–D). Since the FI is highly correlated with age, the skewed distribution reflects the presence of healthy groups (gamma distribution) and unhealthy frail groups (normal distribution). Longitudinally, the two-parameter distribution might represent two-stage changes, where the first stage corresponds to individuals’ resilience to the deleterious changes, and the second stage to the deteriorating stage of declining function with age [16].

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.