VoxEU Column Health Economics

The rise of obesity in Europe: An economic perspective

Should the government intervene to reduce obesity on the basis of equity or efficiency? This column gives reasons to be sceptical common arguments for such interventions. Unless health insurance provision creates significant moral hazard problems that encourage obesity, there is little reason to attack obesity on the basis of health insurance externalities.

When comparing obesity rates in Europe and the US, two basic facts emerge:

  • continental Europe has much lower rates of obesity than the UK and US (Figure 1)
  • while Europe is heading in the same direction as the US – higher obesity rates – it is doing so at a significantly slower pace, according to OECD data.

Figure 1. Prevalence of obesity in 2004 among adults (aged 18+) by gender

Source: OECD Health Data (2005)

From an economic viewpoint, a relevant policy question is whether public intervention that would reduce obesity can be justified on the basis of equity or efficiency considerations. Consider equity first. Both Baum and Ruhm (2009) and Brunello, Michaud and Sanz-de-Galdeano (2009) provide evidence that individuals’ BMI is generally inversely related to their mothers’ educational attainment in the US and in Europe; BMI is higher among those with less educated mothers. However, establishing whether such correlation purely reflects causality, which would imply that individuals’ BMI is at least partly determined by circumstances beyond their control, is a complex empirical task that remains on the research agenda.

The second rationale for public intervention on economic grounds is efficiency. Cawley (2004) rightly argues that if individuals were perfectly rational and their decisions about food and weight imposed no costs on others in society, if information about the consequences of obesity were accurate and readily available and if markets were perfectly competitive, there would be no market failure and no reason for government intervention. In Brunello, Michaud and Sanz-de-Galdeano (2009), we provide cross-country evidence on the relevance of the inefficiencies related to obesity and we organise them around four categories of market failures:

  • productive inefficiencies,
  • limited information,
  • limited rationality, and
  • health insurance externalities.

In this column, we focus on the health insurance externality. First, obesity, through its associated health problems, can have a substantial impact on healthcare expenditures. Second, health insurance is invoked by many as a “rationale” for public intervention to reduce obesity although, as we will argue, the fact that obese individuals may “cost” more than the non-obese is not a “good” reason for public intervention. As it turns out, there is crucial distinction between an insurance subsidy, which is not necessarily inefficient, and an insurance externality, which takes the form of moral hazard and leads to inefficiency.

The health insurance subsidy

In almost any health insurance system, there is some degree of risk pooling, given that weight is not used to charge differentially for insurance coverage. This is often enforced by law. Under actuarial fairness, the obese would pay higher premiums, because premiums would be set to equal expected health expenditures. Generally, if risks differ in the population but individuals pay the same premium, this will create a positive subsidy for some individuals and a negative subsidy for others. The difference between lifetime expenditures and premium contributions gives the size of the “insurance subsidy”.

We estimate the difference in lifetime expenditures using a micro-simulation approach both in the US and Europe. We find that an obese American at age 55 faces, on average, an additional $22,251 in health expenditures, which represents 10% of a non-obese person’s lifetime health expenditures. Since a 55 year old can expect to live approximately 29 years, the expected loss in income/consumption (using a 3% real interest rate) is close to $1166 per year. In Europe, the difference in lifetime health expenditures is slightly lower, at $13,840 or 11.1% of a non-obese person’s lifetime expenditures, reflecting mostly the differences in average costs across countries but also better baseline health in Europe.

Given that in both the US and Europe obese individuals face larger lifetime health expenditures, the next question is whether a subsidy exists or these additional expenditures are born by individuals themselves. The fraction of individuals covered by a public health scheme is likely to be a good proxy for the degree of risk pooling. This is because public insurance schemes seldom allow for risk rating of premiums for equity reasons but also because expenses are financed either through a flat contribution rate or through taxation. Except for the US, public health schemes are predominant in OECD countries. In the US, about a fourth of the population, mostly the elderly, is covered by public insurance. Only 44% of total health expenditures are financed through the public system and 60% of the population rely solely on private health insurance.

Private health insurance is unique in the US and is mostly provided through the workplace. This allows health providers to do firm-level risk rating but it does not allow them to rate workers directly. Hence, there is still some degree of risk pooling, albeit less than in a public system (because worker’s health tends to correlate). Total outlays by private insurers represents 42% of total cost in the US, while 14% is paid directly by individuals through deductibles and co-payments for health services (so-called out-of-pocket expenditures).

Private insurance is generally less present in European countries. Interestingly, the amount of total expenditures paid for by individuals themselves (out-of-pocket expenditures) varies greatly across European countries, ranging from 7.8% in the Netherlands to 44% in Greece. Therefore, in countries such as Greece, Italy, and Spain, it is unclear how much risk pooling exists. On the one hand, the existence of universal health systems gives an indication of high degree of pooling in Europe, while on the other hand high out-of-pocket expenditures imply less pooling in some countries. Yet since private health insurance is largely underdeveloped in Europe relative to the US, we can conclude that the insurance subsidy is likely to be higher in most European countries, particularly in countries such as France, Germany, UK, Sweden, and the Netherlands.

The health insurance externality

But the existence of a subsidy is not necessarily inefficient. If one thinks of obesity as a trait that individuals inherit, then there is nothing inefficient about risk pooling, i.e. the subsidy is a pure transfer that can be undone, if desired, on equity grounds. It is the change in behaviour induced by the subsidy that may be inefficient. In other words, the subsidy must affect the propensity of individuals to gain more weight. There is little evidence in the literature that this behavioural response is important.

In fact, one can make the conservative assumption that the behavioural response to the subsidy is similar across countries. In that case, despite being small, one would expect the insurance externality to be higher in Northern European countries than in the US The fact that obesity is higher in the US provides a rough indication that the behavioural response ought to be small; i.e. Europeans are not fatter in spite of the fact that they face a larger insurance subsidy. Hence, a conclusion from our study is that the obesity externality, although more likely to be important in Europe than in the US, is unlikely to be a good reason for public intervention.

References

Baum, C.L. and C. Ruhm (2009), “Age, Socioeconomic Status and Obesity Growth”, Journal of Health Economics, 28(3), 635-648.

Brunello, G., Michaud, P.C. and A. Sanz-de-Galdeano (2009), “The rise of obesity in Europe: an economic perspective”, Economic Policy, 57, 553-96

Cawley J. (2004), “An Economic Framework for Understanding Physical Activity and Eating Behaviours”, American Journal of Preventive Medicine, 27, 115-125

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