Londondare
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The gap
This gap between the average male and female life expectancy of given population group is alternately labeled as Life Expectancy Gender Gap (LEGG) or Gender Gap in Life Expectancy (GGLE). Going forward I will be using the LEGG acronym.
The expectancy
There are basically two types of life expectancy. In historical context, we usually refer to the Cohort Life Expectancy. We track a group of people born in a particular year, many decades ago, and observe the exact date in which each one of them died. Then we can calculate this cohort’s life expectancy by simply calculating the average of the ages of all members when they died.
It is of course not possible to know this metric before all members of the cohort have died. That is why when talking about the present and the future we use Period Life Expectancy. This is an estimate of the average length of life for a hypothetical cohort assumed to be exposed, from birth through death, to the mortality rates observed at one particular period – commonly the previous year. Estimates of life expectancy of the current generation, which are also used in the calculations of indexes like the Human Development Index or Gender Development Index, are of this Period Life Expectancy type.
There is a corollary: because we are judging the existing generation based on mortality rates of the previous year only, whatever happened to that generation before that year is not taken into account. So let's say. if there was a recent deadly pandemic that affected one gender disproportionally, and this pandemic ended and is not affecting the mortality rates of the previous year, there will be little evidence of said gender disproportionally in the current life expectancy estimates.
The lost years
The first important thing to know about the LEGG is that its impact is, without an exaggeration, enormous. Let's take for example the US, with a LEGG of 5.8 years at the average predicted age for men and women 73.5 and 79.3 years respectively. Do you see the enormity? You don't, do you.
Ok, let's put things into perspective - how do you measure an impact of early death? With Years of Potential Life Lost (YPLL). This is an estimate of the average years a person would have lived if they had not died "prematurely". It is usually reported in years per 100,000 people and the reference, "mature" age should correspond roughly to the life expectancy of the population and is now usually given as 75 years.
Now, men and women in the US lose some 8,265 and 4,862 potential years per of life per 100,000. Given the population as 332 millions, men lose some 5,648,980 more years of potential life than women. Do you see the enormity now? Not yet?
During the roughly 3.5 years of WW2 the US lost 407,300 military and 12,100 civilian lives. With an average life expectancy back then 68 years, and a guestimated age at the time of death 21 years, every killed American lost some 47 years and the US as a whole lost some 5,640,000 potential years of life every year of the war. Do you see the enormity of the LEGG now? I think you do.
The causes
The second important think to know about the LEGG is that nobody seem to care. Biologists, statisticians, politicians, Wikipedians - not even men's rights activists - nobody seems to be franticly looking for the causes or proposing policies to stop this haemorrhage of men's lives. Let me paraphrase what Wikipedia has to says about it:
It is the life style, men drink more and smoke more and eat crap. And it is also the biology, men lack the double X chromosome, we see this across all mammalian species, plus male babies and boys dies of diseases much more than girls.
Speaking of Wikipedia, it has dedicated pages for many things, including the Orgasm gender gap, but it does not have a dedicated page for the LEGG.
To my surprise I have not been able to find any further information, neither on biology forums, nor on Google Scholar. Studies usually focus on one cause or divide the mechanisms into social and biological but there our knowledge seem to end.
At this point I was so intrigued that I decided to do some "research" myself. My first observation was that there is a great variance between developed countries with similar GDP and life expectancy, suggesting that a large part of the gap is not biological. Example:
- 2021 Norway - LE: 83.16 years, LEGG: 3,0 years
- 2021 France - LE: 82.32 years, LEGG: 6,2 years
Next, I knew where to find Eurostat data on causes of death - unfortunately only from 2010 - and I filtered out everything mechanical: suicides, assaults, accidents and drug and alcohol overdoses. The LEGG shrunk significantly:
- 2010 Norway - all LEGG: 4.54 | non-mechanical LEGG: 3,51, decrease by 29.5%
- 2010 France - all LEGG: 7.14 | non-mechanical LEGG: 6.19, decrease by 15.3%
Then I was curious how much of the LEGG is caused by mortality differences of infants and children so I calculated non-mechanical LEGG at 20 years, as opposed to LEGG at birth. The difference is negligible:
- 2010 Norway - non-mechanical LEGG at birth: 3,51, non-mechanical LEGG at 20: 3.37, difference: 3.8%
- 2010 France - non-mechanical LEGG at birth: 6.19, non-mechanical LEGG at 20: 6.07, difference: 1.7%
Next, I did one more napkin calculation. Assuming that smoking reduces the life expectancy on average by 10 yers and smoking rate among French men and women are 0.349 and 0.319 and smoking rate among Norwegian men and women are 0.17 and 0.154, I reduced the LEGG further:
- 2010 Norway - all LEGG: 4.54 | non-mechanical, non-smoking LEGG: 3,35, decrease by 35.7%
- 2010 France - all LEGG: 7.14 | non-mechanical, non-smoking LEGG: 5.89, decrease by 21.2%
Of course this does not mean the reminder is caused by biological factors. There are drugs and alcohol, there is a meat consumption and overall life style. Man also do more paid work so there is work related stress and exposure. It should not be a rocket science to isolate these factors, actually, it would amount to a very cool paper with plenty of citations. So where is this paper?
Actually, I found one piece of information: Causes of Male Excess Mortality: Insights from Cloistered Populations, the abstract talks about 11,000 Bavarian monks and nuns living in "very nearly identical behavioral and environmental conditions" with nuns having only a "slight advantage" in life expectancy - whatever that means, I can't access the paper itself. This of course only applies to men and women who already survived into their teens or twenties, but as we saw above the contribution of different child mortality to LEGG is negligible.
The bad and the ugly
FYI, about 80% of suicide victims are men and suicide is the second leading cause of death in middle aged men only after car accidents. Also, 90% of workplace accidents are men - constructions, mining, trucking, heavy industry, you know - and even though the total numbers are too small to meaningfully influence the LEGG it does not cover exposure to chemicals, hard labour or health impact of night shifts.
Some social and biological mechanisms out there are causing men to lose life equivalent to WW2 every year. We should be creating policies to reduce this loss but we don't. Why? We know that men are far less likely than women to visit a doctor. Where are the public health campaigns and safe driving campaign targeted at men specifically?
Could it be the case of "you grow what you measure"? UN's Gender Development Index that measures gender disparity in achievements between men and women very quietly removes 5 years from the LEGG in it's calculations, arguing that men living 5 years shorter is necessary biology. The Global Gender Gap Report published annually by the World Economic Forum does something similar, arguing that if women live at least 6% longer than men, parity is assumed - but if it is less than 6% it counts as a gender gap.
As a corollary, women is Norway living only 3 years longer than men is interpreted as oppression.
I think that UN manipulating it's own index is not culture wars even if the index is related to gender. Let me know if I am wrong.
Human development
The Gender Development Index (GDI), along with its more famous sibling Human Development Index (HDI) is a an index published annually by UN's agency, the United Nations Development Programme (UNDP). Whether an index is manipulated or not can be judged only against a precise definition of what the index claims to be measuring. So how do you measure human development? Whatever you do, you will never capture all nuances of the real world - you will have to simplify. The UNDP puts it this way:
The Human Development Index (HDI) was created to emphasize that people and their capabilities should be the ultimate criteria for assessing the development of a country, not economic growth alone.
So the UNDP defines the Human Development Index as a geometric mean of three dimensions represented by four indices:
| Dimension | Index |
|---|---|
| Long and healthy life | Life expectancy at birth (years) |
| Knowledge | Expected years of schooling (years) |
| Mean years of schooling (years) | |
| Decent standard of living | Gross National Income (GNI) per capita (2017 PPP$) |
Source: https://hdr.undp.org/data-center/human-development-index#/indicies/HDI
Gender Development
So far so good. Next, on it's website the Gender Development Index (GDI) is defined like this:
GDI measures gender inequalities in achievement in three basic dimensions of human development: health, measured by female and male life expectancy at birth; education, measured by female and male expected years of schooling for children and female and male mean years of schooling for adults ages 25 years and older; and command over economic resources, measured by female and male estimated earned income.
Source: https://hdr.undp.org/gender-development-index#/indicies/GDI
While in the actual report HDI it is simply defined as a ratio of female to male HDI values:
Definitions - Gender Development Index: Ratio of female to male HDI values.
Source: https://hdr.undp.org/system/files/documents/global-report-document/hdr2021-22pdf_1.pdf
Let's look, for instance, at the Gender Development Index of United Kingdom. The value 0.987 means that despite longer life and more education, in UK, females are less developed than males.
| Dimension | Index | Female value | Male value |
|---|---|---|---|
| Long and healthy life | Life expectancy at birth (years) | 82.2 | 78.7 |
| Knowledge | Expected years of schooling (years) | 17.8 | 16.8 |
| Mean years of schooling (years) | 13.4 | 13.4 | |
| Decent standard of living | Gross National Income (GNI) per capita (2017 PPP$) | 37,374 | 53,265 |
Source: https://hdr.undp.org/system/files/documents/global-report-document/hdr2021-22pdf_1.pdf
Wait, what?? What does it mean that females in UK have command over economic resources of post Soviet Estonia (GNI Estonia=38,048) while males in UK have command over economic resources of EU leader Germany (GNI Germany=54,534)?
The manipulation
The UNDP calculates separate command over economic resources for females and males, as a product of the actual Gross National Income (GNI) and two indices: female and male shares of the economically active population (the non-adjusted employment gap) and the ratio of the female to male wage in all sectors (the non-adjusted wage gap).
The UNDP provides this simple example about Mauritania:
Gross National Income per capita of Mauritania (2017 PPP $) = 5,075
| Indicator | Female value | Male value |
|---|---|---|
| Wage ratio (female/male) | 0.8 | 0.8 |
| Share of economically active population | 0.307 | 0.693 |
| Share of population | 0.51016 | 0.48984 |
| Gross national income per capita (2017 PPP $) | 2,604 | 7,650 |
According to this index, males in Mauritania enjoy the command over economic resources of Viet Nam (GNI Viet Nam=7,867) while females in Mauritania suffer the command over economic resources of Haiti (GNI Haiti=2,847).
Let's be honest here: this is total bullshit. There are two reasons why you cannot use raw employment gap and raw wage gap for calculating the command over economic resources:
Argument 1
Bread winners share income with their families. This is a no brainer. All over the world, men are expected to fulfil their gender role as a bread winer. This does not mean that they keep the pay check for themselves while their wives and children starve to death. Imagine this scenario: a poor father from India travels to Qatar where he labours in deadly conditions, so that his family can live a slightly better life. According to UNDP, he just became more developed, while the standard of living his wife is exactly zero.
Argument 2
Governments redistribute wealth. This is a no brainer too. One's command over economic resources and standard of living is not equal to ones pay check. There are social programs, pensions, public infrastructure. Even if you have never earned a pay check yourself, you can take a public transport on a public road to the next public hospital. Judging by the Tax Freedom Day, states around the world redistribute 30% to 50% of all income. And while men pay most of the taxis (obviously, they have higher wages) women receive most of the subsidies (obviously, they have lover wages). But according the UNDP, women in India (female GNI 2,277) suffer in schools and hospitals of the war-torn Rwanda, while men in India (male GNI 10,633) enjoy the infrastructure and social security of the 5-times more prosperous Turkey.
Don't get me wrong, the employment gap and pay gap are not irrelevant for the standard of living and command over economic resources. Pensions and social security schemes mostly do not respect the shared family income and as a result the partner doing less paid work - usually a women - gets lower pension, unemployment benefit etc. What's worse, the non-working partner is severely disadvantaged in case of divorce or break up. But while this has an impact on each gender's standard of living it certainly does not define 100% of that value.
Argument 3
You may argue that the command over economic resources measured by estimated earned income is some kind of proxy for all other disadvantages women face in society. But do you remember what I said in the beginning?
Whether an index is manipulated or not can be judged only against a precise definition of what the index claims to be measuring.
The HDI measures "people and their capabilities" and the GDI is a ratio of these capabilities measured separately for men and women. The economic dimension of the GDI is supposed to be standard of living or command over economic resources - neither of which can be represented by earned income alone.
The taboo
Wikipedia says: "For most countries, the earned-income gap accounts for more than 90% of the gender penalty." (I have not verified this.) This is important, because when we look at the other two dimensions it becomes clear that while men have shorter and less health lives they also increasingly fall behind in mean and expected years of schooling. Without the misrepresentation of the command over economic resources value, the index would show something very uncomfortable: that according to UN's own definition of Human Development men are the less developed gender.
PS: Is there a way to give those tables some borders and padding?