The Population Bullet
by Jason S. Brinkley, PhD, MA, MS
On the Brink addresses topics related to data, analytics, and visualizations on personal health and public health research. This column explores current practices in the health arena and how both the data and mathematical sciences have an impact. (The opinions and views represented here are the author’s own and do not reflect any group for which the author has an association.)
Between 1950 and 2017, the United States population has more than doubled from about 158 million people to nearly 327 million. While growth has come from a combination of changes in birth rates, average life spans, and immigration, the simple fact is that these changes have impacted many of our public health systems and health policy at both the national and local level. Being able to look back at how our population has changed can provide evidence of how best to forecast what lies ahead and provide a deeper understanding of the challenges to come. I recently found a terrific online tool that can help us do just that.
Population Pyramid is a website devoted to taking UN population estimates and providing a distinct and compelling set of visualizations that shows the distribution of the population of areas of the world grouped by gender and by age. Consider the population pyramid for the United States for 2017: the blue side represents the male population and the red the female population. As you look from bottom to top, you see the distribution of the US by age. So today the US is about 3% of each age/gender combination from 0-60 in five-year blocks across each gender. Then we see declines as people age and die, starting in the 65-69-year-old age group, and the rate continues to decline until around age 100. So simply put, the US has about the same number of men and women in each age block across the “typical” lifespan. Has this always been the case? Certainly not.
In playing with the website, one can look across a wide array of time points. Listed below are the US population pyramids in 10-year blocks from 1950 to 2000. While the 1950 and 2017 visuals look very different, the most interesting phenomenon demonstrated here is the “hump” that moves through the “baby boom,” that generation of US residents born after World War II. The boomer bubble here is distinct and provides insight as to how demographics have shifted over the past 67 years, which is almost certainly associated with the shifts in our national health policy and health systems. It seems clear that a system designed for a 1950 population would not perform as well with the population of 2017.
Population Pyramid goes further and provides visuals based on forecast projections from the United Nations. These projections predict the US to have added another 125 million residents by the year 2100, and the shape of the population looks something akin to a bullet with age/gender groups continuing to even out and life expectancy continuing to rise. These models make several assumptions to obtain these forecasts and are never perfect. For example, they assume births to be constant and that another baby boom will not occur this century. This kind of forecast is essential in determining what changes to our health and policy systems are necessary to satisfy the US in 2100, but the real question is whether this forecast is very accurate, given the dramatic difference in the visuals from 1950 to 2017. Will the population really continue to bullet or shift into something else entirely?
The website can provide hours of distracted fun. I suggest that you take some time to look at a couple of different countries and regions of the world and see just how different they are from the US. Population Pyramid well documents gender by age disparities in places like Saudi Arabia, Qatar, and Hong Kong. Likewise, we see several countries whose populations are already bulleting just like the United States (for example Canada, France, Norway, Iceland, and Sweden) which provides some indirect evidence that the UN forecasts could be accurate.
While many countries have a similar look to the US, many in the developing world do not. Consider the population pyramid for Africa, which still looks more like a pyramid than a bullet. As we work to improve our health systems worldwide, all estimates point to continued population growth here as well as a lengthening of the lifespan. Indeed, Africa is poised to potentially see a bubble over the next 50 years in the way that the US did during the baby boom. All of this begs the question of whether global health systems are ready for such a shift in demographics. UN estimates for 2100 have Africa at a population of 4 billion and certainly with a more bullet-like shape. Given what we know about the need for changes in our systems to accommodate the shift in US demographics, it is very likely that the current systems are not designed to handle the population of Africa in 2100.
The population bullet doesn’t have to be a deadly prospect; indeed, it can be a driver for innovation and a place for discussion of how we manage populations that continue to shift and age. What these graphs don’t convey is the real growth of the overall population. If the population pyramids were resized to correspond to the total population, then the 2017 graph would be twice the size of the 1950 graph. Those changes in net population have also impacted health systems and policy, and there is no known limit as to how large a population the planet can sustain.
Of course, maybe we have it all wrong and the Earth is really flat and the excess population will just fall off the edge. That could certainly be a discussion point at the 2017 Flat Earth International Conference, which is being held in November in Raleigh, North Carolina. Sorry to say that registration for the conference is full and all the tickets have been sold out.
If that doesn’t strike you as a little bit funny, I can’t help you.
Jason S. Brinkley, PhD, MS, MA is a Senior Researcher and Biostatistician at Abt Associates Inc. where he works on a wide variety of data for health services, policy, and disparities research. He maintains a research affiliation with the North Carolina Agromedicine Institute and serves on the executive committee for the NC Chapter of the American Statistical Association and the Southeast SAS Users Group. Follow him on Twitter. [Full Bio]
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