This study uses an approach of cumulative deficits (Kulminski et al., 2006
; Mitnitski et al., 2001
) to evaluate the rate of aging characterized by DIs constructed using overlapping and non-overlapping sets of deficits associated with wide spectrum of health dimensions in successful population of long-living families. We show that these DIs robustly characterize accelerated rates of aging of about the same magnitude irrespective of specific of deficits. Similar accelerated patterns were observed in different populations worldwide suggesting law-like behavior (Mitnitski et al., 2005
; Rockwood and Mitnitski, 2006
) which can be related to the fundamental processes of intrinsic biological aging in an organism. When the entire LLFS sample is characterized by deficits covering a wide spectrum of health dimensions these rates are robustly approximated by quadratic law. Exponential increase is more characteristic of more severe health dimensions (e.g., morbidity and disability).
Our results suggest that the aging rates approximated by the rates of changes in respective DIs are not altered by gender. At first glance this is surprising because it is widely believed that females have worse health than males although they live longer than males (Nathanson, 1975
; Oksuzyan et al., 2008
; Verbrugge, 1982
). Consequently, females should accumulate more deficits than males over age. Various studies suggest, however, that gender differences may vary by health dimensions (see e.g., (Gorman and Read, 2006
) and references therein). Furthermore, studies of age patterns of health deficits in the Framingham Heart Study population suggest presence of female and male specific health dimensions associated with cumulative effect of minor-effect traits (Kulminski et al., 2008a
). As a result, females are found to accumulate more deficits than males when female-specific health dimensions are considered and vice-versa. Given the wide spectrum of health dimensions such opposite trends for males and females can result in no gender differences (Kulminski et al., 2008a
Our results show that healthy individuals (i.e., those who contracted neither one of 21 major diseases listed in ) can accumulate deficits in about the same () or even in more accelerated () fashion compared to unhealthy individuals. In each case, however, the shape of the age patterns was the same, i.e., quadratic for DI58 and exponential for DI27. Of importance is that faster aging rates for healthier individuals were also documented in other studies (Kulminski et al., 2006
; Mitnitski et al., 2005
). The differences in age dynamics between more and less healthy samples in those studies were, however, considerably more pronounced.
Disability status appears to be crucial for characterization of the aging rates. The age patterns for non-disabled individuals are likely the result of a convolution of different age-specific dynamics. This can be better understood when more severe health dimensions are considered (DI27). For instance, exponential pattern for disabled individuals in (and ) is likely the result of: (i) exponential increase of disease-related deficits at younger ages (, non-disabled), (ii) diminishing their role at older ages (, non-disabled), (iii) non-essential role of disability-related deficits early in life (, healthy), and (iv) exponential increase of disability-related deficits at older ages (, healthy).
An interesting result is diminishing role of severe deficits in for non-disabled individuals at advanced ages. Given that DI27 for non-disabled individuals characterizes co-morbidity, this pattern can decelerate because: (i) individuals at older ages are less fitted and, thus, they can be tolerant to smaller number of concurrent diseases than at younger ages or/and (ii) incidence of geriatric diseases can decline at advanced ages (see, e.g., (Kamangar et al., 2006
; Lerner and Kannel, 1986
; Schoenberg et al., 1987
The members of the LLFS study residing in Denmark, Boston, New York, and Pittsburg exhibit similar patterns of health deterioration. The oldest-old Danes aged 90 to 94 years can have, however, higher levels of disability and morbidity (characterized by DI27) compared to New York residents of the same age. Importantly, overall health status of centenarians residing in New York appears to be better compared to Boston residents.
At a first glance, lack of difference in the aging rates as characterized by the DI’s age patterns for individuals selected for exceptional longevity and for their spouses, who should represent a general (control) population, is surprising. Indeed, it would be natural to expect differences in the aging rates for genetically unrelated individuals in the LLFS because DIs are good predictors of longevity (Kulminski et al., 2008b
) whereas longevity shows modest heritability, i.e., about 25-35% (Cournil et al., 2000
; Gudmundsson et al., 2000
; Herskind et al., 1996
; Ljungquist et al., 1998
; Skytthe et al., 2003
). Furthermore, prior studies show that numerous health traits tend to be inherited in the LLFS (Matteini et al., 2010
) and in other studies. For instance, offspring from the long-lived families in the Leiden Longevity Study had more favorable lipid profile, glucose tolerance, and hypertensive status (Rozing et al., 2010
; Vaarhorst et al., 2010
; Westendorp et al., 2009
)). Ashkenazi Jewish probands with exceptional longevity and their offspring also show better lipid profile compared to controls (Barzilai et al., 2003
). Typically, centenarians have also little history of major aging-related diseases as, for instance, cardiovascular diseases and cancer (Barzilai et al., 2003
; Willcox et al., 2008
). Nevertheless, the same Leiden Longevity Study found no differences in some other health dimensions in long-living individuals, as, for instance, in hematopoietic capacity (Willems et al., 2008
). Not all centenarians escaped major aging-related diseases (Engberg et al., 2009
; Evert et al., 2003
These findings suggest that offspring of long living individuals should not necessarily have better health in all possible health dimensions. This is actually in line with quite modest trend on better health (as characterized by the most comprehensive deficit index) of children of probands compared to controls, i.e., beta=0.45, in the age-aggregated sample. Although this trend was highly significant (p=2.2×10-5), the effect size might be not sufficient to result in well pronounced differences in aging rates.
Furthermore, we should keep in mind at least three important considerations. First, inadequate sample size and lack of data at old ages (75+ years) prevents more detail comparison of the DIs age patterns at that age range. It might well be that aging rates for offspring and their spouses can diverge at more advanced ages. This would be an important observation which eventually implicates compression of morbidity. Second, in general, intrinsic (basal) aging rate for both long- and normal-living individuals can be the same even at advanced ages. Then, difference in lifespan of the normal- and long-living individuals can be due to weaker vulnerability of long-livers, i.e., due to their higher capacity coping with environmental stresses. Third, environmental changes occurring during lifespan of the same and different generations can greatly modulate the aging rates both directly and through interactions with genes resulting in so-called cohort effects and secular trends. Unfortunately, currently available data does not allow for testing the first two hypotheses. Third hypothesis looks interesting but it deserves separate analyses which are currently in progress.
Thus, we show that participants of the LLFS exhibit accelerated rates of aging following primarily quadratic pattern. These patterns are the same for males and females. Individuals contracted major diseases and those who were free of them exhibited the same aging rates as characterized by the DIs constructed using mild (no major diseases and disability) deficits. Unlike health, disability status can qualitatively change aging patterns. There are systemic differences in health among centenarians residing in New York and Boston.