Measuring Human Rights (16): The Right to Healthcare

(There’s a more theoretical post here about the reasons why we should call health care a human right. But even if you think those are bad reasons, you may find the following useful).

The right to health care is one of the most difficult rights to measure. You can either try to measure people’s health directly and assume that good health means good health care, or you can measure the provision of health care and assume that there will be good health with a good health care system. Doing the latter means, for example:

  • measuring the number of health workers per capita for countries
  • measuring the quality of hospitals
  • measuring health care spending by governments
  • measuring the availability and affordability of health care
  • measuring the availability and affordability of health insurance
  • etc.

Doing the former means:

  • measuring life expectancy
  • measuring infant mortality
  • measuring maternal mortality
  • measuring calorie intake
  • measuring the incidence of certain diseases
  • measuring the survival rates for certain diseases
  • etc.

Needless to say that every single one of these measurements is fraught with problems, although some more so than others. Even if you’re able to have a pretty good measurement for a single indicator for a single country, it may be difficult to compare the measurement across countries. For example, health insurance is organized in so many different ways that it may be impossible to compare the level of insurance across different countries.

But let’s focus on another measure. Life expectancy is often used as a proxy for health. And indeed, when people live longer, on average, we can reasonably assume that they are healthier and that their health care system is better. It’s also something that is relatively easy to measure, compared to other indicators, since even developing countries usually have reasonably good data based on birth and death certificates. And yet, I say “relatively” because there are some conceptual and definitional problems:

  • Exceptional events such as a natural disasters or a war can drag down life expectancy numbers, but those events need not influence health in general or the quality of health care.
  • Wealthy countries may have more deaths from car accidents than poorer countries, simply because they have more cars. This will pull their relative life expectancy down somewhat, given that younger people are more likely to die in car accidents. And if you use life expectancy to measure health you’ll get a smaller health gap compared to poorer countries than is the case in reality (at least if life expectancy is not corrected for this and if it’s not supplemented with other health indicators).
  • How are miscarriages counted? If they are counted as child mortality, they drag down life expectancy rates compared to countries where they are not counted.
  • What about countries that have more homicides? Or suicides? Although the latter should arguably count since suicides are often caused by bad mental health. If a country’s life expectancy rate is pulled down by high suicide rates, life expectancy rates are still a good indicator of health and of the quality of health care, assuming that health care can reduce suicide rates and remove, to some extent, the underlying health causes of suicide. However, homicides are different: a country with a very good health care system, a very high level of health and a high murder rate can have its health rating pulled down artificially when only life expectancy is used to measure health.
  • Differences in diet and other types of risky behavior should also be excluded when comparing health and life expectancy across countries. It’s wellknown, for instance, that obesity is more of a problem in the U.S. than in many countries that are otherwise comparable to it. Obesity drags down life expectancy and reduces the average level of health, so life expectancy rates which are not corrected for obesity rates are still a good measure for health, but they are not a good measure for the quality of the U.S. health care system. If you want to use life expectancy rates to compare the quality of health care systems you’ll have to correct for obesity rates and perhaps for other types of risky behavior such as smoking or the absence of exercise. Maybe the U.S. health care system, even though it “produces” somewhat lower life expectancy rates than in comparable countries, is actually better than in other countries, yet still not good enough to offset the detrimental effects of high average obesity.

Hence, uncorrected life expectancy rates may not be such a good indicator of national health and of the quality of a national health care system. If we return to the case of the U.S., some of this may explain the strange fact that this country spends a lot more on health and yet has somewhat lower life expectancy rates than comparable countries.

Or maybe this discrepancy is caused by a combination of some misuse and waste at the spending side – more spending on health doesn’t necessarily result in better health – and some problems or peculiarities with the measurement of life expectancy. Let’s focus on the latter. As stated above, some cultural elements of American society, such as obesity, pull down life expectancy and worsen health outcomes. But there are other peculiarities that also pull down life expectancy, and that have nothing to do with health. I’m thinking of course of the relatively high levels of violence in the U.S. Death by assault is 5 to 10 times higher in the U.S. than in comparable countries (although those numbers tend to go down with the passing of time). This affects younger people more than older people, and when more young people die, life expectancy rates drop sharper than when more old people die.

However, even if you correct U.S. life expectancy rates for this, the rates don’t move up a lot (see here). The reason is that the numbers of deaths caused by homicide pale in comparison to other causes. Obesity levels, for instance, are a more important cause. But correcting life expectancy rates for obesity levels doesn’t seem appropriate, because we want to measure health. If you leave out all reasons for bad health from life expectancy statistics, your life expectancy rates go up, but your average health doesn’t. Obesity isn’t the same as homicide. Correcting life expectancy statistics for non-health related deaths such as homicide makes them a better indicator of health. Removing deaths from obesity doesn’t. If you have life expectancy rates without obesity, they may be a fairer judgment of the health care system but not a fairer judgment of health: a health care system in a country with a lot of obesity may be equally good as the one in another country and yet result in lower life expectancy. The former country does not necessarily have lower life expectancy because of its underperforming health care system – we assumed it’s of the same quality as elsewhere – but because of its culture of obesity.

However, if you really want to judge health care systems, you could argue that countries plagued by obesity should have a better quality system than other countries. They need a better quality system to fight the consequences of obesity and achieve similar life expectancy rates as other countries that don’t need to spend so much to fight obesity. So, life expectancy is then reinstituted as a good measure of health.

Lies, Damned Lies, and Statistics (33): The Omitted Variable Bias, Ctd.

I discussed the so-called Omitted Variable Bias before on this blog (here and here). So I suppose I can mention this other example: guess what is the correlation, on a country level, between per capita smoking rates and life expectancy rates? High smoking rates equal low life expectancy rates, right? And vice versa?

Actually, and surprisingly, the correlation goes the other way: the higher smoking rates – the more people smoke in a certain country – the longer the citizens of that country live, on average.

Why is that the case? Smoking is unhealthy and should therefore make life shorter, on average. However, people in rich countries smoke more; in poor countries they can’t afford it. And people in rich countries live longer. But they obviously don’t live longer because they smoke more but because of the simple fact they have the good luck to live in a rich country, which tends to be a country with better healthcare and the lot. If they would smoke less they would live even longer.

Why is this important? Not because I’m particularly interested in smoking rates. It’s important because it shows how easily we are fooled by simple correlations, how we imagine what correlations should be like, and how we can’t see beyond the two elements of a correlation when we’re confronted with one that goes against our intuitions. We usually assume that, in a correlation, one element should cause the other. And apart from the common mistake of switching the direction of the causation, we often forget that there can be a third element causing the two elements in the correlation (in this example, the prosperity of a country causing both high smoking rates and high life expectancy), rather than one element in the correlation causing the other.

More posts in this series are here.

Measuring Poverty (4): The Problem of the Definition of Poverty

Before you can start to measure poverty, you first have to decide what you actually want to measure. What is poverty? That’s not just a philosophical problem because depending on the definition of poverty you use, your measurements will be radically different (even with an identical definition, measurements will be different because of different measurement methods).

Among people who measure poverty, roughly 6 different definitions of poverty are used:

  • insufficient income
  • insufficient consumption spending
  • insufficient calorie intake
  • food consumption spending above a certain share of total spending
  • certain health indicators such as stunting, malnutrition, infant mortality rates or life expectancy
  • certain education indicators such as illiteracy.

None of these definitions is ideal, although the first and second on the list are the most widely used. A few words about the advantages and disadvantages of each.

Income

Advantages:

In developed countries, income is a common definition because it’s easy to measure. Most people in developed countries earn a salary or get their income from sources that are easy to estimate (interest payments, the value of houses, stock market returns etc.). They don’t depend for their income on the climate, crop yields etc. Moreover, developed countries have good tax data which can be used to calculate incomes.

Disadvantages:

In developing countries, however, income data tend to be underestimated because it’s difficult to value the income of farmers and shepherds. Farmers’ incomes fluctuate heavily with climate conditions, crop yields etc. If you ask them one day what their income is, there’s no guarantee that this is a good estimate of their yearly income.

Another disadvantage is that people are generally reluctant to disclose their full income. Some income may have been hidden from the tax administration or may have been earned from illegal activity such as corruption, smuggling, drug trade, prostitution, theft etc. For this reason, using income to estimate poverty means overestimating it.

And, finally, some income may be difficult to calculate (e.g. rising value of livestock).

Consumption

Advantages:

The main advantage of using consumption rather than income to measure poverty is that consumption is much more stable over the year and over a lifetime (see above). Hence, if you ask people about the level of their consumption, they can just tell you about their current situation, without having to go back in time or to predict the future – which they would have to do if you asked them about income. Their current consumption is likely to be representative of their long term consumption, which isn’t the case for income. This is even more true in the case of farmers who depend on the weather for their income and hence have a more volatile income. If you know that farmers are often relatively poor, then this issue is all the more salient for poverty measurement.

Another advantage of using consumption is that people aren’t as reticent to talk about it as they are about certain parts of their income. It’s also appears that people tend to remember their spending better than their income.

Disadvantages:

If you want to measure how much people consume, you have to include durable goods and housing. And consumption of those goods is difficult to measure because it’s difficult to value them. For example, if a household owns a house, you have to estimate what it would cost to rent that particular house and add this to the total consumption of that household, at least if you want to compare their consumption to the consumption of the household next door who has to rent its house. And you can’t make poverty statistics if you don’t make such comparisons. Then you have to do the same for cars etc.

Another difficulty in measuring consumption, is that in developing countries households consume a lot of what they themselves produce on the family farm. This as well is often difficult to value correctly.

And finally, different people have different consumption needs, depending of their age, health, work etc. It’s not clear to me how these different needs are taken into account when consumption is measured and used as an indicator of poverty.

Other definitions

Calorie intake: the problem with this is that different people need different amounts of calories (depending on their type of work, their age, health etc.), and that it isn’t very easy to measure how many calories people actually consume.

Food spending as a fraction of total spending: if you say people who spend more than x % of their total spending on food are considered poor, you still have to factor in relative food prices.

Stunting as an indicator of malnutrition and hence of poverty: stunting (height for age) is a notoriously difficult thing to measure.

Other issues

Some aspects of life tend to be excluded from poverty measurement, even though they have a huge impact on people’s wellbeing. The amount of leisure time people have is perhaps a good indicator of poverty, in certain circumstances (excluding CEOs and US Presidents), but it’s hardly ever counted in poverty measurements.

Another thing: people may have comparable incomes or even consumption patterns, but they may face very different social or environmental conditions: an annual income of $500 may be adequate for people living in a rural environment with a temperate climate where housing is cheap, heating isn’t necessary and subsistence farming is relatively easy. But the same income can mean deep poverty for a family living in a crowded city on the edge of a desert. The presence or absence of public goods such as quality schools, roads, running water and electricity also makes a lot of difference, but poverty measurement usually doesn’t take these goods into account.

Lies, Damned Lies, and Statistics (12): Generalization

An example from Greg Mankiw’s blog:

Should we [the U.S.] envy European healthcare? Gary Becker says the answer is no:

“A recent excellent unpublished study by Samuel Preston and Jessica Ho of the University of Pennsylvania compare mortality rates for breast and prostate cancer. These are two of the most common and deadly forms of cancer – in the United States prostate cancer is the second leading cause of male cancer deaths, and breast cancer is the leading cause of female cancer deaths. These forms of cancer also appear to be less sensitive to known attributes of diet and other kinds of non-medical behavior than are lung cancer and many other cancers. [Health effects of diet and behavior should be excluded when comparing the quality of healthcare across countries. FS]

These authors show that the fraction of men receiving a PSA test, which is a test developed about 25 years ago to detect the presence of prostate cancer, is far higher in the US than in Sweden, France, and other countries that are usually said to have better health delivery systems. Similarly, the fraction of women receiving a mammogram, a test developed about 30 years ago to detect breast cancer, is also much higher in the US. The US also more aggressively treats both these (and other) cancers with surgery, radiation, and chemotherapy than do other countries.

Preston and Hu show that this more aggressive detection and treatment were apparently effective in producing a better bottom line since death rates from breast and prostate cancer declined during the past 20 [years] by much more in the US than in 15 comparison countries of Europe and Japan.” (source)

Even if all this is true, how on earth can you assume that a healthcare system is better because it is more successful in treating two (2!) diseases?

Another example: the website of the National Alert Registry for sexual offenders used to post a few “quick facts”. One of them said:

“The chance that your child will become a victim of a sexual offender is 1 in 3 for girls… Source: The National Center for Victims of Crime“.

Someone took the trouble of actually checking this source, and found that it said:

Twenty-nine percent [i.e. approx. 1 in 3] of female rape victims in America were younger than eleven when they were raped.

One in three rape victims is a young girl, but you can’t generalize from that by saying that one in three young girls will be the victim of rape. Perhaps they will be, but you can’t know that from these data. Like you can’t conclude from the way the U.S. deals with two diseases that it “shouldn’t envy European healthcare”. Perhaps it shouldn’t, but more general data on life expectancy says it should.

These are two examples of induction or inductive reasoning, sometimes called inductive logic, a reasoning which formulates laws based on limited observations of recurring phenomenal patterns. Induction is employed, for example, in using specific propositions such as:

This door is made of wood.

to infer general propositions such as:

All doors are made of wood. (source)

More posts in this series.

Income Inequality (9): Absolute and Relative Poverty

The problem of poverty and related problems such as income inequality have received a lot of attention on this blog, because I consider poverty to be one of the most urgent human rights problems. Now and again, I’ve also mentioned the possibility of distinguishing between different types of poverty, and one such possibility in particular, namely the difference between absolute and relative poverty. Absolute poverty meaning the lack of basic resources, and relative poverty meaning income inequality.

I’ve taken the view that absolute poverty is a more urgent priority than relative poverty, and that therefore measurements of income inequality – such as the Gini coefficient – are less relevant than measurements of absolute poverty – such as the $1 a day measure. It’s the absolute income of people that matters, not the fact that other people are richer than you are and can afford more luxuries, at least from a human rights point of view (the absence of a certain minimum amount of basic resources is a human rights violation in itself and renders many other human rights meaningless).

Inequality of wealth or income is less urgent than the fight against absolute poverty, and a lot of opposition to income inequality can be easily categorized as the politics of envy. If inequality really matters it is the inequality of opportunity and other types of inequality not related to wealth (<discrimination for example).

But this is perhaps putting it too strongly. There are negative effects of high levels of income inequality, for example on the adequate functioning of democracy. There is also a correlation between relative poverty and absolute poverty: countries with relatively unequal income distribution don’t score well on absolute poverty measures either.

Richard Wilkinson has pointed out, some time ago already, that relative poverty matters. Once economic growth has pushed up absolute (albeit average per capita) income levels and done away with penury, people tend to be more healthy and live longer if levels of income inequality are relatively low. Countries with lower per capita income levels but also lower income inequality, can do better in terms of public health than high income countries with higher levels of income inequality. Poorer countries with a more equal wealth distribution are healthier and happier than richer, more unequal ones. There’s also a link between inequality (measured not by Gini but by way of the concentration of wealth in the 10% richest people) and both life expectancy and child mortality.

Some of the reasons for this are the stress of living at the bottom of the pecking order, the stress of disrespect and the lack of esteem and respect (including self-respect).

The Ethics of Human Rights (11): Organ Trade

The shortage of organs for transplantation is a universal problem. The supply of organs is way below the demand. And demand is increasing due to progress in medical science and increasing average age. The demand comes mainly from developed countries. The reason is that life expectancy is higher in these countries, and therefore also the demand for organs. Also, the health care system is more developed and hence more likely to engage in transplants.

There are two ways to harvest organs: deceased organ donation, and live organ donation.

Deceased organ donation

In some countries, deceased organ donation is hampered by social, cultural, religious, legal and other factors. In some cases, donors have to state their intent while living. They have to opt in. In other cases, they have to opt out and hence they are donors by default, which tends to produce higher rates of donation.
In other cases still, family members of the deceased have to consent, which brings down rates.

Live organ donation

The use of live donors for non-vital organs such as kidneys and parts of liver, for example, is also practiced, but the purchase and sale of transplant organs from live donors are prohibited in many countries.

Transplant tourism and international organ trade

The shortage of a local supply of organs – due to some of the reasons given above, or a combination – has led to the development of transplant tourism and international organ trade. Poor people in developing countries are often forced to donate a non-vital organ; forced by poverty or forced by outright violence. People are kidnapped and operated under duress, and often don’t even get paid. Sometimes they simply get killed because this bypasses the requirement of consent. Corpses are also harvested, not rarely without the consent of the deceased or his or her relatives. The legality of live organ donations in some countries encourages poor people to sell some of their non-vital organs such as kidneys. However, the circumstances in which they are operated can turn a non-vital organ donation into a fatal one.

Rich people travel to countries where these different kinds of harvesting are possible, legally or illegally, and where hospitals are willing to cooperate in such a scheme and are relatively capable so as not to scare away patients. China is a well-known destination because there’s the enormous supply of thousands of people executed every year.

Although those who can afford to buy organs are obviously exploiting those who are desperate enough to sell their organs, the recipients may also suffer from the trade. They may receive substandard or even sick organs.

Some contend that the poor should be allowed to sell their organs, because we merely contribute to their poverty. Exploitation may be morally preferable to death, but given the risk of forced donation and of complications during surgery, this is a slippery slope.

Someone has aptly called the whole business New Cannibalism.

Other issues

One can also see a trend to declare a person dead at an earlier stage than in the past, for example some seconds after cessation of brain activity or heart activity, rather than minutes. Some organs become useless after a certain waiting period. This means shifting the definition of life and death, and perhaps less reanimation enthusiasm. Another, and opposite form of abuse is keeping brain-dead people artificially “alive” as an “organ warehouse” for future donations.

Also, the use of cloning and designer babies for the purpose of organ production is controversial, as is the use of animal organs.

Economic Human Rights (14): Health

Health is a human rights issue in two respects. First, people have a right to health care and health insurance. Article 25 of the Universal Declaration states that

Everyone has the right to a standard of living adequate for the health and well-being of himself and of his family, including food, clothing, housing and medical care and necessary social services, and the right to security in the event of unemployment, sickness, disability, widowhood, old age or other lack of livelihood in circumstances beyond his control.

The International Covenant on Economic, Social and Cultural Rights is more specific. Article 7 guarantees the rights to safe and healthy working conditions. Article 10 deals with child labor:

The employment of children in work harmful to their morals or health or dangerous to life or likely to hamper their normal development should be punishable by law.

Article 12 states:

1. The States Parties to the present Covenant recognize the right of everyone to the enjoyment of the highest attainable standard of physical and mental health. 2. The steps to be taken by the States Parties to the present Covenant to achieve the full realization of this right shall include those necessary for: (a) The provision for the reduction of the stillbirth-rate and of infant mortality and for the healthy development of the child; (b) The improvement of all aspects of environmental and industrial hygiene; (c) The prevention, treatment and control of epidemic, endemic, occupational and other diseases; (d) The creation of conditions which would assure to all medical service and medical attention in the event of sickness.

The second way in which health is a human rights issue is the fact that good health is a precondition for the enjoyment of all human rights. In this way, bad health is similar to poverty. You have to be healthy and without pain in order to be able to use freedom rights and political rights. A sick, suffering or toiling person is thrown back upon himself and unable to relate to the outside world, just as a person who concentrates exclusively on his or her body for pleasurable reasons. Intense bodily sensations of any kind – positive and negative – shut us off from the world, because they make it impossible to perceive anything except our own body. In other words, they make the use of our classical rights impossible or undesirable.

Economic Human Rights (12): Life Expectancy

Life expectancy, or the average length of life in a given population (mostly a country), is of importance to the issue of human rights. A low life expectancy means shorter life spans. Now, it’s not because a life is relatively short that is has to be less fulfilling, less happy or less meaningful. However, it is obvious that a longer life will allow for more activity, self-development and freedom, and hence for more enjoyment of human rights, than a shorter life.

Moreover, longer life expectancies are often an indicator of better health and healthcare, and good health is a prerequisite for human rights. Bad average health or healthcare and low life expectancy, on the contrary, are indicators of poverty, and poverty is in itself a violation of certain human rights and makes other human rights impossible.

Life expectancy in Western countries today is almost double what it was in the pre-modern era. This is the consequence of highly reduced infant mortality rates, modern medicine (e.g. before modern medicine, one in four women died in childbirth), improvements in sanitation (sewers) and nutrition, etc. Especially in the last century did we see enormous progress. In the US for example, life expectancy at the beginning of the 1900s was 50 years. At the end of the same century it was 77 (with differences of course between male and female and between social classes; poverty, in particular, has a substantial effect on life expectancy).

Of course, as in most cases, the developing countries haven’t achieved the same levels as the West. They have improved their numbers but there are still large and shocking inequalities in life expectancy, with Africa again bearing the heaviest burden. Sub-Saharan Africa (partly because of HIV) has even seen a decrease in life expectancy during the last decades. The former USSR also saw a decrease.

 

 

 

A person’s life in one of the poorest countries will on average be half as long as the life of a person fortunate enough to be born in a rich country.

(High infant mortality rates in a particular country can bring down rates of life expectancy at birth drastically. In these cases, another measure such as life expectancy at age 5 can be used to exclude the effects of infant mortality to reveal the effects of causes of death other than early childhood causes. However, that’s somehow “cooking the books” since infant mortality does reduce the life expectancy of the infants in question. On the other extreme are some people who want to include aborted fetuses in life expectancy rates).

Economic Human Rights (8): Poverty

Poverty is a violation of human rights. Article 25 of the Universal Declaration states:

“Everyone has the right to a standard of living adequate for the health and well-being of himself and of his family, including food, clothing, housing and medical care and necessary social services, and the right to security in the event of unemployment, sickness, disability, widowhood, old age or other lack of livelihood in circumstances beyond his control.”

And we all know the devastating effects of poverty on other human rights.