It is worth weighting for better health measures

By Sonja Spitzer, research assistant in the IIASA World Population Program

Sonja Spitzer discusses how survey data often fails to capture all socioeconomic groups and explains how to ensure health information used by policymakers is based on accurate statistics.

© Victor Freitas | Unsplash

Life expectancy continues to increase in Europe. We live longer, but do we live healthier? One way of tackling this question is by analysing health expectancy: a widely used indicator that counts the number of years an average person can expect to live in good health. To create this indicator researchers usually combine information about mortality with health data from surveys – and this is where many problems begin.

Survey participation is shaped by socioeconomic differences

Surveys do not always correctly represent the countries they seek to describe. A common deviation is that highly educated individuals are more likely to participate in surveys than less-educated individuals This is problematic for health research in particular, because highly educated people tend to be healthier than those who are less educated. Overrepresenting healthy and better educated individuals in surveys makes countries appear to have healthier populations than is the actual case. A recent study I conducted, that focused on European countries, showed that health expectancy measures are frequently upward biased, because less-educated people are underrepresented in the underlying data. The results of this study reflect the outcomes of other research; for example, estimates of rates of diabetes and asthma in Belgium are too low because individuals with a high level of education are overrepresented in the core data. In the Netherlands, the underrepresentation of those with lower levels of education has led to underestimating smoking prevalence, alcohol intake, and low levels of physical activity.

Make everyone count with statistical weights

Are you now wondering if you can ever trust health measures again? Do not despair! Surveys can still be a very useful source for answering health-related questions if the appropriate statistical tools are used. It is possible to account for the misrepresentation of participants with lower levels of education in surveys. The only thing needed is accurate information about the education structure of the population, that is: How many highly educated versus less-educated individuals live in a given country? In Europe, this information is readily available via censuses. Using information from censuses makes it possible to calculate statistical weights for surveys. If the less educated are underrepresented in surveys, each observation of a less educated individual is weighted relatively more than those with a higher level of education to account for the misrepresentation. This weighting enables surveys to resemble the population in the real world and the health measures that are based on them to no longer be biased by educational differences in survey participation.

Why do the less educated not participate in surveys?

Using survey methods such as statistical weights might become even more necessary in the future – it appears that the gap in survey participation between the higher and the less-educated is increasing year upon year. Those with low levels of education are frequently more difficult to engage, for example, less educated people can have less stable life paths and thus more often change their address. They may be less likely to provide requested information in surveys because they are too sick to participate or are less aware of the details of their health and financial situation. Finally, survey participation is usually voluntary and those with lower levels of education are more likely to refuse participation. One could speculate that this refusal to participate is because we, as researchers fail to engage with, or reach out to, less-educated individuals and the “value” of participating in surveys is therefore not well-communicated. This concern seems particularly important in the age of ‘fake news’. If less-educated individuals were better represented in surveys, this would make official statistics more reliable and might also lead to a better appreciation of statistics and how they can be more profound indicators than, for example, an opinion posed by someone on TV.

References:

[1] Demarest, S., Van Der Heyden, J., Charafeddine, R., Tafforeau, J., Van Oyen, H., Van Hal, G.: Socio economic differences in participation of households in a Belgian national health survey. European Journal of Public Health. 23, 981–985 (2013). DOI:10.1093/eurpub/cks158

[2] Korkeila, K., Suominen, S., Ahvenainen, J., Ojanlatva, A., Helenius, H.: Non-response and related factors in a nation-wide health survey. European Journal of Epidemiology 17, 991–999 (2001)

[3] Reinikainen, J., Tolonen, H., Borodulin, K., Härkänen, T., Jousilahti, P., Karvanen, J., Koskinen, S., Kuulasmaa, K., Männistö, S., Rissanen, H., Vartiainen, E.: Participation rates by educational levels have diverged during 25 years in Finnish health examination surveys. European Journal of Public Health. 28, 237–243 (2018). DOI:10.1093/eurpub/ckx151

[4] Spitzer, S., Biases in health expectancies due to educational differences in survey participation of older Europeans: It’s worth weighting for. The European Journal of Health Economics. (2020) IIASA doi:10.1007/s10198-019-01152-0. http://pure.iiasa.ac.at/id/eprint/16281/ 

Note: This article gives the views of the author, and not the position of the Nexus blog, nor of the International Institute for Applied Systems Analysis.

How can happiness research help to build better lives?

By Anastasia Aldelina Lijadi, research scholar in the IIASA World Population Program

What does happiness mean? The concept of “happiness” has somewhat abstruse meanings in different languages. Some suggest the idea of luck or good fortune (German, Norwegian, French, Korean, Russian, Japanese, Chinese) and others intimate satisfaction of one’s desires or wishes and goals and enjoyable experiences (Italian, Portuguese, Spanish). Anthropologists, economists, linguists, psychologists, sociologists, and other researchers from various disciplines are still struggling to operationalize the concept, and ensure that enhanced quality of life is a realistic and obtainable goal for human kind.

As part of the project Empowered Life Years, at the World Population Program at IIASA, the concept of happiness has been identified as one of the conditions for sustainable human wellbeing, along with health, literacy, and being out of poverty. Being the newest in the team, I was privileged to attend the 15th annual conference of International Society for Quality-of-Life Studies (ISQOLs) to attend lectures and presentations and better comprehend the concept of happiness and how this research-based knowledge can contribute to people’s wellbeing.

Six supports for happiness

The distinguished keynote speaker Prof. John F. Helliwell specified six prerequisites for a human being to be happy, which are material (such as food and shelter), relationships, mental and physical health, freedom from oppression, generosity, and trust. His studies showed that mental and physical health is more effective in increasing happiness than raising income or ending unemployment. Moreover, people are more generous (i.e., show strong altruism or pro-social behavior such as donating blood, or care for environment) when they have a good social relationships within their community.

Keynote lecture at the ISQOLs conference. © Anastasia Aldelina Lijadi | IIASA

Measuring Happiness beyond GDP: How and for whom?

It is hard to tell what does cause (un)happiness in a country when wealth has failed to fully explain it. The Easterlin Paradox claims that a society’s economic development and its average level of happiness are not linked beyond a certain level of income that satisfies basic needs. This is the case in Latin America, as Prof. Mariano Rojas, president of ISQOLs, pointed out in his presentation. Bhutan also fits this theory, said Prof. Shrotyia Vikar Kumar of the University of Delhi, as it has controversially the highest happiness index in the world despite low GDP.

In addressing income inequality, Prof. Richard Wilkinson of the London School of Economics, stressed that the story is the same in unequal societies worldwide: men in poorer households feel low, outcast, and very sensitive to what others think about them, wives loathe their husbands, and children ashamed of their condition. We witness a higher discrepancy in health, crime, infant mortality, and civic participation between rich and poor communities. The rich also rate themselves better than poorer people, and are more likely to search for ‘status goods’ in google!

Prof. Antonella Delle-Fave, University of Milan, urged us to review the construct of happiness before trying to measure it. She also criticized the polarizing and overused concepts of hedonic and eudemonic happiness. Hedonic happiness is based on the experience of pleasure or positive feelings while generally avoiding any painful experiences. Eudemonic happiness is the notion of wellbeing based on the pursuit of personal fulfillment and realizing one’s potential by engaging in meaningful activity. Delle-Fave  found that many researchers use a mix of variables derived from both concepts.

Prof. Richard Layard, author of Happiness: Lessons from a New Science, stated that happiness evolves over the life course. A simple cross-sectional correlation study cannot explain the evolution of happiness throughout life course, and Layard urged future research to employ an interdisciplinary approach to find the determinants of happiness. This will help policymakers to create meaningful, accessible, and age-sensitive opportunities for promoting quality of life throughout a lifetime.

Prof. Delle-Fave added that bottom-up qualitative research is needed to define happiness, eliciting voices directly from the source: “After learning from university, we need to learn from people.” I will use this powerful yet simple advice in my work on Empowered Life Years at IIASA.

Note: This article gives the views of the author and not the position of the Nexus blog, nor of the International Institute for Applied Systems Analysis.