De-standardising ageing? Shifting regimes of age measurement

Departing from the proposition that, in the sociological debate about whether there has been a shift towards a de-standardised lifecourse in advanced economies, little attention has been devoted to the infrastructural arrangements that would support such a transition, this paper explores the changing role of standards in the governance of ageing societies. In it, I outline a sociological theory of age standard substitution which suggests that contradictory rationalities used in the implementation of chronological age fuelled the emergence of a critique of chronological age within the diverse strands of gerontological knowledge during the 20th century. The paper analyses how these critiques were linked to a proliferation of substitute, ‘personalised’ age standards that aimed to conjoin individuals’ unique capacities or needs to roles or services. The paper suggests that this configuration of age standards’ production, characterised by uncertainty and an opening of moral and epistemic possibilities, has been shrouded by another, more recent formation where institutional responses to decentred processes of standardisation moved research and political investment towards an emphasis on biological age measurement.

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".

A Note on Age-Related Biomarkers

Forty-eight randomly selected age-related human biological functions were analyzed in order to establish whether or not their (linear) regressions were modified by age-related standard errors. Possible reasons for this are advanced. Statistically significant multiple regressions were obtained in 25%, and 21% of the functions yielded statistically significant changes in the correlations between data and age when partial correlation coefficients were calculated. The conclusion is that age-related data need to be subjected to the above tests in order to minimize confounding factors.

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.

Human biological decline and mortality rates

Intercepts on the x (age)-axis of 107 normalized declining human biological functions were determined and assembled in 3 histograms, being placed in increasing order within each decade (10 year period). The histograms were classed accordingly as they contained properties associated with dividing cells, sensory properties and non-dividing cells respectively. Their cumulants were determined, multiple regressions calculated and compared with current death-rates for women and men respectively, for 10 amongst the longest living populations in the World. An alternative verification based on risk theory led to an estimate of an optimal life expectancy of 96 years. The survival curve turns out to be of the form (See text: Formula) where the inner integral represents the cumulant dimension (t') and the outer one age (t"). The premises underlying this study are compatible with the notion of a probable life-span, rather than a fixed one.

Why does the human visual system age in the way it does?

The tentative observation that the decrease of lenticular glutathione in man and in cattle may be under genetic control is extended to other biological functions which show a systematic reduction with age. Ocular and visual parameters are shown to decline consistently with the view that the human eye has evolved in keeping with other biological functions sustaining a life-span of approximately 120 years. Analysis of the data suggests that presbyopia represents an outlier in the distribution of ocular attributes, and should not be used as a biomarker for ageing.

Human sensory functions and longevity

Age-related variations of human sensory properties have been expressed in a manner which permits them to be validly compared with other biological functions presented on a similar basis. They are found to be representative of much larger data-base, and it is tentatively suggested that they may have evolved in support of a life-span of approximately 120 years. Some theoretical arguments are advanced to explain this.