Some comparisons of France and the US are fairly obvious, like their different languages and geography, but there are certain observations of the two countries that lie beneath the surface and necessitate further research and analysis. One such comparison is average mortality. In 2019, Magali Barbieri, a researcher in the department of demography at UC Berkeley and the French Institute for Demographic Studies (INED), and Hippolyte d’Albis, a professor at the Paris School of Economics and Senior Researcher at CNRS, received an FBF grant to compare the length of life in France and the US. A particular focus of the project was to not only compare the countries at the national level, but to also use statistical methods that could analyze data at local levels, namely counties in the US and départements in France. Much of this research was and continues to be conducted by Florian Bonnet, then a PhD student and now a full time researcher at INED.
Their research revealed some fascinating information regarding the two countries. In both France and the US, inequalities between local levels decreased until 1980, a year that “seems to be a turning point,” according to Bonnet. After 1980, inequalities among counties increased in the US, while inequalities among départements in France did not increase, but instead leveled off. Overall, the average length of life in the US lags behind France; in 2016, the average American lived 3.5 years fewer than the average French person. Additionally, this difference in lifespan cannot solely be attributed to internal inequalities in the US. “Even the most affluent Americans, the Americans in those areas that are doing the best, are still not doing much better than the average French or the average European,” explains Barbieri, which implies that there are “some structural problems in the US that create a resistance to progress in survival, and we hope that by conducting these comparative analyses we’ll be able to understand better what’s driving this pattern.”
Once the team completes their data analysis on the local and national level for both France and the US, they plan to add cause of death to their analysis in order to understand what exactly is causing the various patterns. Though the data Barbieri, Bonnet, and d’Albis have been analyzing during this project is limited to France and the US, there is great research potential beyond these two countries. The research methods that they have used can be applied to other countries, “in particular other countries in the European Union,” says d’Albis, and “it could be a global project as well”.
The project was not without its challenges. Due to COVID-19 lockdowns, access to certain research facilities containing critical data was restricted until very recently. Also, the group was unable to continue collaborating in person as they had planned. Beyond the effect the pandemic had on their collaboration, it also will impact the data the team collects in years to come. For example, there is already a gap in life expectancy in the US compared to France, and this gap is likely to widen due to the pandemic, with the US falling even further behind. There are also indirect impacts to consider; even if one survives the virus, they might be more vulnerable to other illnesses. This is especially true for “people who have preconditions, things like diabetes, or obesity, or hypertension” who will be “more susceptible to the severe form of the disease” explains Barbieri, and as there are more people with these conditions in the US than in France, her prediction is that “we’ll see more fallout from the disease in the US than in France.”
Additionally, since the crisis has economic and social impacts as well, people will likely be better supported in France due to the bigger social net that exists there as compared to the US. Within each country, it’s important to note that “not all regions are impacted the same way,” says d’Albis. Some regions may be hit harder depending on their economy, such as areas that rely heavily on tourism. Even if “two regions are hit the same way from an epidemiological perspective,” says Barbieri, “one region...might be more resilient than another because of its socio-economic characteristics.” For these reasons, the pandemic, combined with the resulting economic crisis “could increase differences across regions both in the US and in France”, says d’Albis.
While the pandemic has revealed weaknesses, it has also shown the possibility of resilience and unity in many different parts of life, including research. Due to the circumstances, “a lot of people realized that we can still do a lot of things remotely,” says Barbieri, “but we also realized that we still need in person interactions...and that’s why I look forward to when the pandemic will be done so Florian can visit or I can spend more time in France and we can sit together with Hippolyte.” She adds that “never before has the international research community come together in this way to make progress against an important public health threat...there have been a lot of connections that weren’t so straightforward before that we created through the pandemic”.
In terms of their work with the FBF, Barbieri describes the grant as a “great way to start the process of collaboration” and a way to “plant the seeds and start thinking of what could be done.” D’Albis adds that for those considering applying, that “it’s quite easy to try” and the grant is “quite flexible.” The FBF has already facilitated valuable work, which will be made available to the scientific community at large online. The French data is already available online at the French Human Mortality Database, and the US state-level data is available on the United States Mortality Database, with the US county-level data to arrive soon.
Images: In the figures above, each dot is a US state (black) or a French département (red). The x-axis indicates the level of life expectancy at birth in 1980 in years and the y-axis, how many years of life were added between 1980 and 2015. There is one figure for each sex (men on the left, women on the right). The figures show that, though the level of life expectancy at birth in 1980 was not significantly different in the US states and in the French departments, progress in survival was much faster in France than in the US (i.e., the cloud of red dots is clearly above the cloud of black dots on both plots though the pattern is particularly pronounced for women). Furthermore, the range of values in life expectancy at birth in 1980 is larger for the US than for France, even though French departments are much smaller in size (demographically) than US states (so everything else equal, the spread should have been larger in France). This result indicates larger inequalities in mortality across the US than across France though most of the spread in the US is determined by two extreme values in 1980 (Washington D.C. for the lowest life expectancy at birth and Hawaii for the highest).