How populations change over time is a crucial area of concern for both educators and futurists. This week some important new research appeared from The Lancet in their new Global Burden of Disease Study. Teams dove into demographic and health changes over the past 70 years, assembling truly impressive amounts of transnational data.
I’ll summarize some of the key points here, and would love to hear your thoughts.
Human life expectancy has really soared in just a few generations:
Globally, life expectancy at birth has increased from 48·1 years… in 1950 to 70·5 years (70·1–70·8) in 2017 for men and from 52·9 years…in 1950 to 75·6 years… in 2017 for women.
Some of that growth is quite recent, taking place over the past 30 years. “Globally, from 1990 to 2017, life expectancy at birth increased by 7·4 years… from 65·6 years… in 1990 to 73·0 years… in 2017.”
A key driver of this growth is the “remarkable… decline in under-5 mortality since 1950… at the global level.”
Yet there are some local variations, such as America’s “deaths from despair” and “the obesity epidemic, the opioid crisis, or the rise of drug-related violence in some locations.” Researchers offer this useful and sobering caution:
Because of the celebrated progress in many locations, many people have come to expect age-specific death rates to always decline; however, there is nothing inevitable about the trajectory of death rates, particularly in adults.
One side effect of this terrific rise in life expectancy is rising amounts of disability.
If you want to think about what’s most likely to kill you, it isn’t violence or infectious disease. No, the world’s leading killers are, by far, “non-communicable diseases [which] contribut[ed] to 73·4%… of total deaths in 2017.” Similarly, what’s most likely to take a toll on your lifespan? “[N]eonatal disorders, ischaemic heart disease, stroke, lower respiratory infections, and chronic obstructive pulmonary disease.” (Media note: let’s see how that plays on violence and fear-obsessed American tv “news”, hm?)
Human population growth is slowing down, as “global population growth rates have declined from a peak of 2·0% in 1964 to 1·1% in 2017.” In many nations populations have plateaued. In several, population is starting to shrink. Most of the nations experiencing active growth are in Africa:
Overall, we’re still producing net more humans, just at a slower rate.
One major driver for this is a massive drop in how many children women have. “From 1950 to 2017, TFRs [total fertility rates] decreased by 49·4%.”
Again, as I and others keep saying:
In high-income countries, the proportion of the population that is of working age has also decreased in the past 5 years, and this trend is likely to continue for the foreseeable future. This demographic shift toward an older population has a broad range of consequences, from reductions in economic growth, decreasing tax revenue, greater use of social security with fewer contributors, and increasing health-care and other demands prompted by an ageing population.
Meanwhile, the reports offer a glimpse of rising health care issues:
The risks with the highest increases in SEVs [summary exposure value]* globally include high BMI, ambient particulate matter pollution, and high FPG; the risks with the largest decreases in exposure are unsafe sanitation, diet high in trans fatty acids, and household air pollution.
Watch for more public health movements along those lines.
One historical note: thanks to the timeline of these studies (1950 on) the biggest single disaster in that period is one that receives not much attention. Again and again researchers in these articles single out China’s Great Leap Forward as a massive catastrophe, “[t]he most notable fatal discontinuity in the past 68 years.” For example,
The huge impact of the Great Leap Forward in China in 1960 is shown clearly at both the global and regional level. Globally, life expectancy dropped by 5·1 years (3·9–6·2) as a result of the famine.
Equally as astonishing is how China bounced back:
Despite the massive setback around the famine in 1960, China has made steady progress and, in 2017, life expectancy was 74·5 years (95% UI 74·1 to 75·0) for men and 79·9 years (79·4 to 80·4) for women.
Remember, as Branko Milanovic observes, people outside of China often don’t pay enough attention to that great nation.
Where does all of this data take us? The giant pile of research also has a forecasting section. One key futuring conclusion is that lifespans may well keep increasing:
We forecasted global life expectancy to increase by 4·4 years (95% UI 2·2 to 6·4) for men and 4·4 years (2·1 to 6·4) for women by 2040, but based on better and worse health scenarios, trajectories could range from a gain of 7·8 years (5·9 to 9·8) to a non-significant loss of 0·4 years (–2·8 to 2·2) for men, and an increase of 7·2 years (5·3 to 9·1) to essentially no change (0·1 years [–2·7 to 2·5]) for women.
What should educators take away from this? Let me offer some points.
- Once again, most of our populations are aging. This has plenty of ramifications.
- Higher education institutions seeking to boost traditional-age enrollment would do well to recruit from Africa, the Middle East, Pakistan, and parts of Southeast Asia. Perhaps this is a good time to partner up with local secondary education as well. This may well take significant resources.
- Campuses will have to expand disability accommodations, both in person and online. This will be even more needed as we teacher older folks.
- For people who are still worried about humanity growing too large, are you really talking about Africa and parts of Asia? There might be some ugly politics there.
- Changing health issues should help feed increasing demand for academic medical studies and career preparation. (Another datapoint for the Health Care Nation scenario)
- Stresses around population changes, both individual and social, may well spur rising interest in and acceptance of suicide, as I’ve noted previously.
- Please, please, please teach media criticism so that students don’t get distracted by bad reporting of actual, real-world disease, violence, and death.
*SEVs are “a summary measure of exposure… The metric is a risk-weighted prevalence of an exposure, and it offers an easily comparable single-number summary of exposure to each risk. SEVs range from 0% to 100%, where 0% reflects no risk exposure in a population and 100% indicates that an entire population is exposed to the maximum possible level for that risk.”