In my last blog (http://www.genre.com/knowledge/blog/how-biological-age-beats-counting-birthdays-for-predicting-life-expectancy-en.html),

I looked at how knowledge about the age of our cells may help determine biological age. Statistics can also help, but the data shows that life expectancy isn’t the same for everyone.

Only a statistical, as opposed to a deterministic, relationship can be established between life expectancy and the circumstances that can influence it.

For example, statistics show that smokers die earlier than nonsmokers, and that Japanese people live longer than Nigerian people. Despite this, some smokers outlive nonsmokers while some Japanese die young. This is because statistics work with grouped values.

The averages summarize the actual life spans of distinct individuals of the same chronological age into a homogenous single number. In practice people will deviate from the average to a lesser or greater extent.

Role of biological age

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An individual’s biological age may be estimated by reference to remaining life expectancy and by how much the age of their cells is lower than, equal to or higher than their chronological age.

We may assume that a 50-year-old person in poor health has below-average life expectancy, and it follows that their biological age is therefore higher than their chronological age. The opposite would apply to a person in excellent health.

However, there is a risk that the person in excellent health could die prematurely in an accident, even though this is less likely.

Nevertheless, they may still not outlive the standard remaining life expectancy of their physical age.
Statistics allow the calculation of life expectancy of large subgroups of the population. We can add or subtract years of life from an individual’s life expectancy, depending on the subgroup to which he or she belongs.

This provides a better estimate of this person’s life span than the general life expectancy.

For example, a group of males aged 50 will include subgroups of individuals in varying states of health and socioeconomic groups, smokers, nonsmokers and so on. Such subgroups have higher or lower life expectancy than the group average.

As a result, we can say that if an individual belongs to a subgroup, his or her biological age would be calculated on the basis of chronological age with the difference (plus or minus) that reflects the variation between the average life expectancies of the main group and the subgroup.

Crude estimate

Standard remaining life expectancy is based on nothing more than current chronological age (and perhaps gender). This is only a very crude estimate as we know that factors including nutrition, lifestyle and disease history influence mortality and, in turn, an individual’s life span.

We can divide the people of a given age into many subgroups using further information. The remaining life expectancy for those subgroups can then be used as a proxy for the biological age defined in the first blog of the series.

Several applications and websites that offer to calculate an individual’s "Bio Age" use this statistical approach with varying degrees of rigor. Many also offer site visitors advice on health and nutrition, with the promise of reducing their biological age.

© Published with the permission of General Reinsurance AG 2016, http://www.genre.com/knowledge/blog/how-biological-age-may-affect-life-expectancy-calculation-en.html

Francisco Garcia is the General Manager of Gen Re’s Madrid office