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Alastair Canaway’s journal round-up for 12th September 2016

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.

Question order sensitivity of subjective well-being measures: focus on life satisfaction, self-rated health, and subjective life expectancy in survey instruments. Quality of Life Research [PubMed] Published 30th April 2016

It’s interesting to see an ‘old’ and well known issue rearing its head within the health economics literature. In this case, the focus is on ordering bias within wellbeing questionnaires. It is established within the psychometric and psychological literature that the location of a question within a survey can influence how respondents interpret the meaning of the question, and therefore their answers. This study sought to empirically examine how ordering in subjective well-being measures (life satisfaction, self-rated health, and subjective life expectancy) affected answers. Given ordering bias is an established concept, it wasn’t too surprising to find notable ordering bias depending on how the questionnaire was ordered. For example, as hypothesised by the authors, placing self-rated health immediately before life satisfaction within the survey led to different values compared to when placed apart. For well-being research, the paper has important implications, particularly in how to best order questionnaires to reduce the impact of prior questions on answers, e.g. keeping self-rated health and life satisfaction questions apart to encourage respondents to independently evaluate each question. Ordering bias is one of those issues that most researchers are aware of, but tend to forget about. As much as anything I feel this is for pragmatic reasons, for example, in terms of ease of producing case report forms and also for facilitating data entry within trials. Ideally, we probably should be randomising the order of questionnaires, whether we can persuade wider trial teams that this is necessary remains to be seen.

You sneeze, you lose: The impact of pollen exposure on cognitive performance during high-stakes high school exams. Journal of Health Economics [PubMed] [RePEcPublished September 2016

As a ‘summer sneezer’ and someone with poor exam results in year 9, it was of great interest to read this article. It is known that health and productivity are intrinsically linked, indeed productivity costs related to health are commonly discussed within health economics circles. Elsewhere there are studies that have identified pollution levels as having significant effects on labour productivity and supply. As any fellow hay fever (seasonal allergic rhinitis) sufferers will attest, hay fever has a direct negative impact on wellbeing. Hay fever is relatively prevalent with over one in five people being reported to suffer (in the Norwegian setting at least). This study combined a large administrative dataset from the Norwegian high school system with daily pollen counts from measurement stations across Norway. Student exam data were matched with location of exams and the pollen count for the area in which the exam took place. Fixed effect panel data methods were used to analyse the data. The primary result found that one standard deviation increase in pollen levels led to a decrease in a student’s exam score by about 2.5% of a standard deviation, the implication of this is that for allergic students, this negative effect is approximately 10% of a standard deviation. This is a notable margin. The paper has an interesting discussion on the potential long term impact of hay fever on allergic students, and their future prospects e.g. impact on university enrolment. To avoid such impacts the paper emphasises the need to diagnose early and optimise treatment for hay fever in children. One final point (and word of caution) would be that the methods don’t prove causality, however as a hay fever sufferer, it was very interesting nonetheless to consider how the condition may have impacted upon my own performance at school.

The fatter are happier in Indonesia. Quality of Life Research [PubMed] Published 31st August 2016

An eye-catching title. In developed countries, being overweight and obese typically has negative connotations, and studies repeatedly suggest this is the case: those who are overweight are less happy. In developing countries however, this is not necessarily true. The paper offers the following reason for this: wealth and obesity are positively correlated in such countries, and likewise, happiness and wealth are positively related. Those who are poor in developing countries literally cannot afford to be obese. In contrast, in developed countries, even lower socioeconomic classes can afford to be obese (and obesity is indeed more prevalent in these classes). With this in mind, this study sought to determine how obesity and happiness were related in Indonesia. The study used a large long term survey of over 22,000 participants over a long time period. As hypothesised, the study found there to be a positive association between obesity and self-reported happiness within Indonesia. The paper in a roundabout way suggests that a different approach to evaluating obesity prevention is required in the developing world. I’m not sure this is necessarily the case, in my experience it is rare to assess obesity prevention interventions with respect to ‘happiness’. It takes me back to a previous journal round-up discussing the maximand within economic evaluation. Obesity, if not immediately, eventually is associated with poor health, therefore there is nothing to suggest that an evaluative framework that seeks to maximise health over happiness will not be sufficient. There are many issues related to the long term evaluation of obesity prevention interventions, particularly those focussed in children (as outlined here), however I think the case stated in this paper is a bit of red herring.

Photo credit: Antony Theobald (CC BY-NC-ND 2.0)

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Terry Flynn (@tflynnhealth)
7 years ago

Regarding the first paper. *Sigh*. I counted to ten before typing this. However, this is an old issue and I wish people would put it to bed. Of course people think of whatever you’ve just asked them about when answering a general life satisfaction question. But if you ask it before the specific questions (as we and others did) then you have absolutely no control over what they’re thinking about when they answer it.

Even the experienced utility bigwigs have talked more about domain specific life satisfaction scores, which of course then begs the question “how do you combine them in a theoretically satisfactory way?” Short answer, you can’t, when the properties of the scales are not even intervally scaled.

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