Human biological decline and mortality rates

Modeling biological age and its link with the aging process

Differences in health status at older ages are a result of genetic predispositions and physiological responses to exposure accumulation over the lifespan. These vary across individuals and lead to health status heterogeneity as people age. Chronological age (CA) is a standard indicator that reflects overall risks of morbidity and mortality. However, CA is only a crude proxy for individuals' latent physiological deterioration. An alternative to CA is biological age (BA), an indicator of accumulated age-related biological change reflected in markers of major physiological systems. We propose and validate two BA estimators that improve upon existing ones. These estimators (i) are based on a structural equation model (SEM) that represents the relation between BA and CA, (ii) circumvent the need to impose arbitrary assumptions about the relation between CA and BA, and (iii) provide tools to empirically test the validity of assumptions the researcher may wish to invoke. We use the US National Health and Nutrition Examination Survey 1988-1994 and compare results with three commonly used methods to compute BA (principal components-PCA, multiple regression-MLR, and Klemera-Doubal's method-KD). We show that SEM-based estimates of BA differ significantly from those generated by PCA and MLR and are comparable to, but have better predictive power than KD's. The proposed estimators are flexible, allow testing of assumptions about functional forms relating BA and CA, and admit a rich interpretation as indicators of accelerated aging.

Biomarkers by gender

Regressions were determined for age-related human biological functions containing information for both genders. Their intercept T(0) on the age axis (x) was used as a measure of the aging rate. The peak of the frequency distribution of T(0) was consistent with earlier estimates. The frequency distribution of the ratio R of T(0)(women)/T(0)(men) peaked at unity. However, when the T(0)-values were divided into two groups, namely those relating to functions involving musculature vs. the rest, respectively, the ratio of R for musculature was <1 and that for the latter significantly >1. This suggests that men are the stronger gender when musculature is involved, but, more broadly, women are "biologically stronger".

Biorepair mechanisms and longevity

The purpose of the study was to find out whether a link could be established between hypothetical biological repair mechanisms, their decay, and longevity. Human biological functions (biomarkers) can be classified accordingly as their generally linear age-related decline starts at birth or in adulthood ( approximately 1% per annum), or occurs at a rate of less than approximately 0.5% per annum Sums of exponentially declining functions representing the decline of repair mechanisms are fitted to the averages of each of the above groups. The time constants of the mechanisms are lowest for those ceasing normal function at the age of approximately 35-40 years, i.e., approximately at twice the maximal age at which puberty is reached. An extrapolation of the overall loss of the mechanisms, postulated to account for the declining biomarkers, is, at present, such as to reach zero in the twelfth decade of life.

Biological age--what is it and can it be measured?

Biological age is a concept used loosely and with little objectivity to describe a shortfall between a population cohort average life expectancy and the perceived life expectancy of an individual of the same age. Many biomarkers decline roughly linearly with age with a slope of <1% per annum. The use of a battery of 16 biomarkers is described as a method of calculating an individual biological age. They include: the concentration of prostacyclin in fibroblasts, cell membrane viscosity, the electroretinogram, baroreflex regulation of the heart rate, the concentration of lymphocytes, leucocyte density and velocity, grip strength, cells of the corneal endothelium and the buccal epithelium, neck muscle mobility, and vital capacity. Although not subjected to a prospective validation, the method might provide an objective approach to this widely used concept.

Low vision rehabilitation in patients with age-related macular degeneration at a tertiary eye care centre in southern India

PURPOSE

To evaluate the specific needs and types of low vision devices (LVDs) in patients with age-related macular degeneration (AMD) so as to use the residual vision effectively.

METHODS

One hundred consecutive patients with diagnosis of AMD were evaluated to ascertain the degree of visual disability. Different LVDs were used to suit the specific needs of individual patients. The distribution of LVDs for distance and near and other rehabilitation measures were stratified for vision >or=6/18 and <6/18. Statistical analysis was performed using chi2 test/Fisher's exact test and paired t-test.

RESULTS

The percentage of patients with visual acuity <6/18 reduced from 72.2% (26/36) to 47.2% (17/36) with the use of standard spectacles (P = 0.03). Similarly, the percentage of patients with visual acuity <6/18 reduced from 85.7% (6/7) to 14.3% (1/7) with the use of a telescope (P = 0.029). The optical devices for near tasks included spectacle magnifiers (n = 59), stand magnifiers (n = 19), and hand magnifiers (n = 18). With these LVDs, the near vision improved from 0.13 (decimal notations) to 0.39 (P < 0.001). Eighty-six patients were given at least one of the LVDs and 20% were prescribed more than one near device (bifocals, spectacle magnifiers, hand magnifiers, stand magnifiers). Additionally, patients also needed counselling (n = 89) and training on eccentric viewing (n = 39), coin identification (n = 45), and independent mobility (n = 41).

CONCLUSION

The overall management of a patient with AMD must include counselling, prescription of appropriate LVDs and training to utilize the residual vision to its fullest advantage. This is expected to improve the patient's quality of life.

Why we need reading-glasses before a zimmer-frame

Accommodative loss represents the fastest human biological decrement. Why? To examine this, the shape of the eye-lens during accommodation or its relaxation is analysed with special reference to age-related changes. The capsule is viewed as a force transmitter: the distribution of forces along centripetal capsular arcs and the resulting stresses and strains are calculated. The effect of zonular 'shifts' is considered. Age-related accommodative loss can be modelled successfully if changes in mechanical properties are linked to those in lenticular and capsular shape.

How the United Nations mortality tables hang together

The mortality statistics of 80 member states of the United Nations were used to calculate Gompertz constants. When compared with a model based on the cumulant of failures of 46 human biological functions, they were found to form essentially one set, their slopes spreading out from a constant value like spokes from the axle of a wheel. Data for the longest lived regions agree with a prediction based on the above model, and those for less long lived regions are consistent with such a model having a constant normal cumulant average but increased S.D.s. Several different approaches support the view that the data are based on a probabilistic life-span.

Statistical mechanic prediction of non-Gomperzian ageing in extremely aged populations

Observations of large populations of ageing organisms have suggested that the exponential increase in the rate of age-related mortality (Gompertz rule) declines in extreme old age, and that the mortality of the extremely long-lived is independent of age. I show that this phenomenon is an expected outcome of ageing being the effect of stochastic failure of highly interconnected networks of elements with constant failure rates, and does not require the postulation of a separate 'long-lived' population of individuals.