Showing posts with label le. Show all posts
Showing posts with label le. Show all posts

Jun 7, 2009

Happy Life Expectancy

As we know, Life Expectation can be measured in many ways. The three most common methods are:
  • LE = Life Expectation (standard), the average number of years that a newborn can expect to live.
  • HALE = Health Adjusted Life Expectation, the average number of years that a newborn can expect to live in "full health"
  • HLE = Healthy Life Expectation, the average number of years that a newborn can expect to live in "full perceived health"

As comparisons between LE an HALE show, 'living longer' doesn't necessarily mean 'living longer in good health'. However, it has become clear that a strong Healthy Working Life Expectancy at age 50 or higher is the best guarantee that people will be able to work longer as they live longer.

One step further. Living in "good (perceived) health" doesn't automatically mean that people are living a happy life.

Happiness is one of the most important lifestyle statistics. Optimizing the number of 'happy years' in our life is therefore an important issue.

Happy Life Expectancy
Here is where Prof.dr. Ruut Veenhoven (Publications), comes in.

Veenhoven defines a different HLE as:

In formula:

HLE = LE x Happiness-score/10

The Happiness-score (H) is the average happiness as expressed on a 0-10 scale.

Let's compare the HALE an HLE (Happy Life Expectancy) scores with each other for different (top-30 ranked) countries:

A full list and data is available at the World Database of Happiness.

It's clear that in most top-30 countries we spend about 90% of our life in healthy conditions and only about 70-80% in happy conditions. There room for improvement here! I'll leave the other conclusions up to yourself....

Let's conclude with two other correlated interesting findings:

1. Happy Life Expectancy Determination
What public policies are most conducive to happiness? This requires a view on the determinants of happiness in nations:

It turns out that six societal qualities (wealth, security, freedom, inequality, brotherhood and justice) explain 83% of the differences in Average happiness, 71% of the differences in Inequality of happiness and no less than 87% of the differences in Happy Life Years.
Enough for an interesting discussion between actuaries and politicians, I would say....

2. Wealth and happiness correlation
As expected wealth (expressed in GDP per capita) and happiness (e.g. highly satisfaction) are strongly correlated in clear distinguished regions.
Also the 'mean life satisfaction' turns out to be correlated to different age-groups and countries:

These graphics are food for thought on the relationship between mortality and wealth. More about that soon......