Chris Sampson’s journal round-up for 24th April 2017

Every Monday our authors provide a round-up of some of the most recently published peer reviewed articles from the field. We don’t cover everything, or even what’s most important – just a few papers that have interested the author. Visit our Resources page for links to more journals or follow the HealthEconBot. If you’d like to write one of our weekly journal round-ups, get in touch.

The association between socioeconomic status and adult fast-food consumption in the U.S. Economics & Human Biology Published 19th April 2017

It’s an old stereotype, that people of lower socioeconomic status eat a lot of fast food, and that this contributes to poorer nutritional intake and therefore poorer health. As somebody with a deep affection for Gregg’s pasties and Pot Noodles, I’ve never really bought into the idea. Mainly because a lot of fast food isn’t particularly cheap. And anyway, what about all those cheesy paninis that the middle classes are chowing down on in Starbuck’s? Plus, wouldn’t the more well-off folk have a higher opportunity cost of time that would make fast food more attractive? Happily for me, this paper provides some evidence to support these notions. The study uses 3 recent waves of data from the National Longitudinal Survey of Youth, with 8136 participants born between 1957 and 1964. The authors test for an income gradient in adult fast food consumption, as well as any relationship to wealth. I think that makes it extra interesting because wealth is likely to be more indicative of social class (which is probably what people really think about when it comes to the stereotype). The investigation of wealth also sets it apart from previous studies, which report mixed findings for the income gradient. The number of times people consumed fast food in the preceding 7 days is modelled as a function of price, time requirement, preferences and monetary resources (income and wealth). The models included estimators for these predictors and a number of health behaviour indicators and demographic variables. Logistic models distinguish fast food eaters and OLS and negative binomial models estimate how often fast food is eaten. 79% ate fast food at least once, and 23% were frequent fast food eaters. In short, there isn’t much variation by income and wealth. What there is suggests an inverted U-shape pattern, which is more pronounced when looking at income than wealth. The regression results show that there isn’t much of a relationship between wealth and the number of times a respondent ate fast food. Income is positively related to the number of fast food meals eaten. But other variables were far more important. Living in a central city and being employed were associated with greater fast food consumption, while a tendency to check ingredients was associated with a lower probability of eating fast food. The study has some important policy implications, particularly as our preconceptions may mean that interventions are targeting the wrong groups of people.

Views of the UK general public on important aspects of health not captured by EQ-5D. The Patient [PubMed] Published 13th April 2017

The notion that the EQ-5D might not reflect important aspects of health-related quality of life is a familiar one for those of us working on trial-based analyses. Some of the claims we hear might just be special pleading, but it’s hard to deny at least some truth. What really matters – if we’re trying to elicit societal values – is what the public thinks. This study tries to find out. Face-to-face interviews were conducted in which people completed time trade-off and discrete choice experiment tasks for EQ-5D-5L states. These were followed by a set of questions about the value of alternative upper anchors (e.g. ‘full health’, ‘11111’) and whether respondents believed that relevant health or quality of life domains were missing from the EQ-5D questionnaire. This paper focuses on the aspects of health that people identified as being missing, using a content analysis framework. There were 436 respondents, about half of whom reported being in a 11111 EQ-5D state. 41% of participants considered the EQ-5D questionnaire to be missing some important aspect of health. The authors identified 22 (!) different themes and attached people’s responses to these themes. Sensory deprivation and mental health were the two biggies, with many more responses than other themes. 50 people referred to vision, hearing or other sensory loss. 29 referred to mental health generally while 28 referred to specific mental health problems. This study constitutes a guide for future research and for the development of the EQ-5D and other classification systems. Obviously, the objective of the EQ-5D is not to reflect all domains. And it may be that the public’s suggestions – verbatim, at least – aren’t sensible. 10 people stated ‘cancer’, for example. But the importance of mental health and sensory deprivation in describing the evaluative space does warrant further investigation.

Re-thinking ‘The different perspectives that can be used when eliciting preferences in health’. Health Economics [PubMed] Published 21st March 2017

Pedantry is a virtue when it comes to valuing health states, which is why you’ll often find me banging on about the need for clarity. And why I like this paper. The authors look at a 2003 article by Dolan and co that outlined the different perspectives that health preference researchers ought to be using (though notably aren’t) when presenting elicitation questions to respondents. Dolan and co defined 6 perspectives along two dimensions: preferences (personal, social and socially-inclusive personal) and context (ex ante and ex post). This paper presents the argument that Dolan and co’s framework is incomplete. The authors throw new questions into the mix regarding who the user of treatment is, who the payer is and who is assessing the value, as well as introducing consideration of the timing of illness and the nature of risk. This gives rise to a total of 23 different perspectives along the dimensions of preferences (personal, social, socially-inclusive personal, non-use and proxy) and context (4 ex ante and 1 ex post). This new classification makes important distinctions between different perspectives, and health preference researchers really ought to heed its advice. However, I still think it’s limited. As I described in a recent blog post and discussed at a recent HESG meeting, I think the way we talk about ex ante and ex post in this context is very confused. In fact, this paper demonstrates the problem nicely. The authors first discuss the ex post context, the focus being on the value of ‘treatment’ (an event). Then the paper moves on to the ex ante context, and the discussion relates to ‘illness’ (a state). The problem is that health state valuation exercises aren’t (explicitly) about valuing treatments – or illnesses – but about valuing health states in relation to other health states. ‘Ex ante’ means making judgements about something before an event, and ‘ex post’ means to do so after it. But we’re trying to conduct health state valuation, not health event valuation. May the pedantry continue.

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Thesis Thursday: Sara Machado

On the third Thursday of every month, we speak to a recent graduate about their thesis and their studies. This month’s guest is Dr Sara Machado who graduated with a PhD from Boston University. If you would like to suggest a candidate for an upcoming Thesis Thursday, get in touch.

Title
Essays on the economics of blood donations
Supervisors
Daniele Paserman, Johannes Schmieder, Albert Ma
Repository link
https://open.bu.edu/pdfpreview/bitstream/handle/2144/19216/Machado_bu_0017E_12059.pdf

What makes blood donation an interesting context for economic research?

I’m generally interested in markets in which there is no price mechanism to help supply and demand meet. There are several examples of such markets in the health field, such as organ, bone marrow, and blood donations. In general, all altruistic markets share this feature. I define altruistic markets as markets with a volunteer supply and no market price, therefore mainly driven by social preferences.

In a way, the absence of a price leads to a very traditional coordination problem. However, it requires not-so-traditional solutions, such as market design, registries, and different types of incentives, due to many historical, political, and ethical constraints (which leads us to the concept of repugnant markets, by Roth (2007)). The specific constraints for blood donations are outlined in Slonim et al’s The Market for Blood, which also outlines the main experimental findings regarding the effects of incentives on blood donations. The blood donations market is the perfect setup to study altruistic markets, not only because of its volunteer supply but also due to the fact that it is a potentially repeated behaviour. Moreover, the donation is not to a specific patient, but to the supply of blood in general. Social preferences, as well as risk and time preferences, play a key role in minimizing market imbalances.

How did you come to identify the specific research questions for your PhD?

I was quite fortunate, due to an unfortunate situation… There was a notorious blood shortage, in Portugal, when I started thinking about possible topics for my dissertation. It got a lot of media coverage, possibly due to political factors, since the shortage happened shortly after a change in the incentives for blood donors. My first question, which eventually became the main chapter of my dissertation, was whether there was a causal relationship.

The second chapter is the outcome of spending many hours cleaning the data, to tell you the truth. I started to realize that there are many other factors determining blood donation behaviour. All non-monetary aspects of the donation process are very relevant in determining future donation behaviour (also highlighted by Slonim et al (2014) and Lacetera et al (2010)). I show that time can be a far more important currency than other forms of incentives.

Finally, I realized how important it would be for me to be able to measure social preferences to continue my research on altruistic markets and joined a team lead by Matteo Galizzi, who is working on measuring preferences of a representative sample of the UK population. My third chapter is the first installment of our work in this domain.

Your research looked at people’s behaviour. How does it relate to the growing recognition that people make ‘irrational’ choices?

The more I look into this, the more I think that we have to be careful about a generalization of irrationality. There is nothing “irrational” in blood donors’ behaviour, for the most part. So far, I have only resorted to very neoclassical models to explain donors’ behaviour – and it worked just fine.

The way I see it, there are two separate aspects to take into account. First, the market response. It is worrisome if we find market responses that are only possible if the majority of agents are making “irrational choices”. Those markets need tailored interventions to inform the decision-making process.

The second aspect zooms in into individual decision-making. In this case, it is important to determine whether there are psychological biases leading to suboptimal, or irrational, choices.

One might argue that a blood donation due to an emotional response to some stimuli is “irrational”. I strongly disagree with that categorization. For example, there is nothing suboptimal in donating blood as a sign of gratitude to previous blood donors.

The main message is that it is important to identify behavioural biases that lead to inefficient market outcomes, but “irrational choices” is too wide an umbrella term and should be used with caution.

Are any of your key findings generalisable to settings other than blood donation?

I think two key findings are quite general. The first one is the fact that it is possible to design incentive schemes that bypass the question of the crowding out of intrinsic motivation. This is a fairly general issue, that ranges from motivating employees at the workplace in general to the design of incentive schemes for physicians, to the elicitation of charitable giving, just to name a few examples. As long as it is a repeated behaviour, the result holds. This highlights a different aspect, the importance of placing lab and isolated field experimental evidence into perspective when informing policy making. There is extensive experimental literature on the crowding out of intrinsic motivation, but very little has been done at the market level and with a longitudinal component. This has limited the ability to take into account the advantages of focusing on repeated blood donation, on the one hand, and of incorporating demand side responses, on the other hand (namely by increasing the number of blood drives).

The second key aspect is the advantage of using time as the main opportunity cost faced by a volunteer supply, in the context of prosocial behaviour.

Based on your research, what might an optimal blood donation policy look like?

I believe there are two key ingredients in the design of the optimal blood donation policy: 1) promoting blood donation as a repeated behaviour; and 2) increasing the responsiveness of blood donation services in order to minimize demand and supply imbalances.

The first aspect can be addressed by designing incentive schemes targeted at repeated donors, with no rewards for non-regular behaviour. The second would greatly benefit from the existence of a blood donor registry, similar to the one already in place for bone marrow donation. This registry would allow for regular blood donors to be called to donate when their blood is needed, minimizing waste in the system. The organization of blood drives would also be more efficient if such a system was in place.

These two components contribute to the development of the blood donor identity, which guarantees a steady supply of blood, whenever necessary.

Paul Mitchell’s journal round-up for 17th April 2017

Every Monday our authors provide a round-up of some of the most recently published peer reviewed articles from the field. We don’t cover everything, or even what’s most important – just a few papers that have interested the author. Visit our Resources page for links to more journals or follow the HealthEconBot. If you’d like to write one of our weekly journal round-ups, get in touch.

Is foreign direct investment good for health in low and middle income countries? An instrumental variable approach. Social Science & Medicine [PubMed] Published 28th March 2017

Foreign direct investment (FDI) is considered a key benefit of globalisation in the economic development of countries with developing economies. The effect FDI has on the population health of countries is less well understood. In this paper, the authors draw from a large panel of data, primarily World Bank and UN sources, for 85 low and middle income countries between 1974 and 2012 to assess the relationship between FDI and population health, proxied by life expectancy at birth, as well as child and adult mortality data. They explain clearly the problem of using basic regression analysis in trying to explain this relationship, given the problem of endogeneity between FDI and health outcomes. By introducing two instrumental variables, using grossed fixed capital formation and volatility of exchange rates in FDI origin countries, as well as controlling for GDP per capita, education, quality of institutions and urban population, the study shows that FDI is weakly statistically associated with life expectancy, estimated to amount to 4.15 year increase in life expectancy during the study period. FDI also appears to have an effect on reducing adult mortality, but a negligible effect on child mortality. They also produce some evidence that FDI linked to manufacturing could lead to reductions in life expectancy, although these findings are not as robust as the other findings using instrumental variables, so they recommend this relationship between FDI type and population health to be explored further. The paper also clearly shows the benefit of robust analysis using instrumental variables, as the results without the introduction of these variables to the regression would have led to misleading inferences, where no relationship between life expectancy and FDI would have been found if the analysis did not adjust for the underlying endogeneity bias.

Uncovering waste in US healthcare: evidence from ambulance referral patterns. Journal of Health Economics [PubMed] Published 22nd March 2017

This study looks to unpick some of the reasons behind the estimated waste in US healthcare spending, by focusing on mortality rates across the country following an emergency admission to hospital through ambulances. The authors argue that patients admitted to hospital for emergency care using ambulances act as a good instrument to assess hospital quality given the nature of emergency admissions limiting the selection bias of what type of patients end up in different hospitals. Using linear regressions, the study primarily measures the relationship between patients assigned to certain hospitals and the 90-day spending on these patients compared to mortality. They also consider one-year mortality and the downstream payments post-acute care (excluding pharmaceuticals outside the hospital setting) has on this outcome. Through a lengthy data cleaning process, the study looks at over 1.5 million admissions between 2002-2011, with a high average age of patients of 82 who are predominantly female and white. Approximately $27,500 per patient was spent in the first 90 days post-admission, with inpatient spending accounting for the majority of this amount (≈$16,000). The authors argue initially that the higher 90-day spending in some hospitals only produces modestly lower mortality rates. Spending over 1 year is estimated to cost more than $300,000 per life year, which the authors use to argue that current spending levels do not lead to improved outcomes. But when the authors dig deeper, it seems clear there is an association between hospitals who have higher spending on inpatient care and reduced mortality, approximately 10% lower. This leads to the authors turning their attention to post-acute care as their main target of reducing waste and they find an association between mortality and patients receiving specialised nursing care. However, this target seems somewhat strange to me, as post-acute care is not controlled for in the same way as their initial, insightful approach to randomising based on ambulatory care. I imagine those in such care are likely to be a different mix from those receiving other types of care post 90 days after the initial event. I feel there really is not enough to go on to make recommendations about specialist nursing care being the key waste driver from their analysis as it says nothing, beyond mortality, about the quality of care these elderly patients are receiving in the specialist nurse facilities. After reading this paper, one way I would suggest in reducing inefficiency related to their primary analysis could be to send patients to the most appropriate hospital for what the patient needs in the first place, which seems difficult given the complexity of the private and hospital provided mix of ambulatory care offered in the US currently.

Population health and the economy: mortality and the Great Recession in Europe. Health Economics [PubMed] Published 27th March 2017

Understanding how economic recessions affect population health is of great research interest given the recent global financial crisis that led to the worst downturn in economic performance in the West since the 1930s. This study uses data from 27 European countries between 2004 and 2010 collected by WHO and the World Bank to study the relationship between economic performance and population health by comparing national unemployment and mortality rates before and after 2007. Regression analyses appropriate for time-series data are applied with a number of different specifications applied. The authors find that the more severe the economic downturn, the greater the increase in life expectancy at birth. Additional specific health mortality rates follow a similar trend in their analysis, with largest improvements observed in countries where the severity of the recession was the highest. The only exception the authors note is data on suicide, where they argue the relationship is less clear, but points towards higher rates of suicide with greater unemployment. The message the authors were trying to get across in this study was not very clear throughout most of the paper and some lay readers of the abstract alone could easily be misled in thinking recessions themselves were responsible for better population health. Mortality rates fell across all six years, but at a faster rate in the recession years. Although the results appeared consistent across all models, question marks remain for me in terms of their initial variable selection. Although the discussion mentions evidence that suggests health care may not have a short-term effect on mortality, they did not consider any potential lagged effect record investment in healthcare as a proportion of GDP up until 2007 may have had on the initial recession years. The authors rule out earlier comparisons with countries in the post-Soviet era but do not consider the effect of recent EU accession for many of the countries and more regulated national policies as a consequence. Another issue is the potential of countries’ mortality rates to improve, where countries with existing lower life expectancy have more room for moving in the right direction. However, one interesting discussion point raised by the authors in trying to explain their findings is the potential impact of economic activity on pollution levels and knock-on health impacts from this (and to a lesser extent occupational health levels), that may have some plausibility in better mortality rates linked to physical health during recessions.

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