Global projections of heat exposure of older adults

The global population is aging at the same time as heat exposures are increasing due to climate change. Age structure, and its biological and socio-economic drivers, determine populations’ vulnerability to high temperatures. Here we combine age-stratified demographic projections with downscaled temperature projections to mid-century and find that chronic exposure to heat doubles across all warming scenarios. Moreover, >23% of the global population aged 69+ will inhabit climates whose 95th percentile of daily maximum temperature exceeds the critical threshold of 37.5 °C, compared with 14% today, exposing an additional 177–246 million older adults to dangerous acute heat. Effects are most severe in Asia and Africa, which also have the lowest adaptive capacity. Our results facilitate regional heat risk assessments and inform public health decision-making.


Figure SI- 1 .
Figure SI-1.Comparison of the age-stratified population projections against values estimated in Striessing et al. 77 .

Figure SI- 2 .
Figure SI-2.Comparison of the age-stratified population projections against values estimated in Striessing et al. 77 .

Figure SI- 3 .
Figure SI-3.Comparison of the age-stratified population projections against values estimated in Hauer 79 .

Figure SI- 4 .
Figure SI-4.Comparison of the age-stratified population projections against values estimated in Hauer 79 .

Figure SI- 5 .
Figure SI-5.Comparison of the age-stratified population projections against values estimated in Eurostat 78 .

Figure SI- 6 .
Figure SI-6.Comparison of the age-stratified population projections against values estimated in Eurostat 78 .

Figure SI- 7 .
Figure SI-7.Comparison of the age-stratified population projections against values estimated in Chen et al. 82 .

Figure SI- 8 .
Figure SI-8.Comparison of the age-stratified population projections against values estimated in Chen et al. 82 .

Figure SI- 9 .
Figure SI-9.Comparison of the age-stratified population projections against values estimated in Nash 81 .

Figure SI- 10 .
Figure SI-10.Comparison of the age-stratified population projections against values estimated in Nash 81 .

Figure SI- 11 .
Figure SI-11.Comparison of the age-stratified population projections against values estimated in KC et al. 80 .

Figure SI- 12 .
Figure SI-12.Comparison of the age-stratified population projections against values estimated in KC et al. 80 .
Figure SI-15.Global intersection of aging and heat exposure in the current climate (left column) and circa 2050, SSP3(70) (right column).Proportion of population aged 69+ exposed to annual Cooling Degree Days (A, B), annual temperatures corresponding to the 95th percentile of local extreme heat exposure (C,D), and annual days with T Max > 37.5 • C (E,F).

Figure SI- 19 .
Figure SI-19.Regional and age-group specific trends in the cumulative and intensity of acute exposure of population groups: 2020-2050.(A) GCM uncertainty range for the count of individuals exposed to a given CDD exposure level, age stratification, faceted by region, difference between SSP5(85) and current population.(B) GCM uncertainty range for the count of individuals exposed to a given number of annual days with T Max > 37.5 • C, age stratification, faceted by region, , difference between SSP5(85) and current population.(C) GCM uncertainty range for the count of individuals exposed to a given 95 th percentile maximum temperature exposure level, age stratification, faceted by region, , difference between SSP5(85) and current population.

Figure SI- 20 .
Figure SI-20.Regional and age-group specific trends in the cumulative and intensity of acute exposure of population groups: 2020-2050.(A) GCM uncertainty range for the count of individuals exposed to a given CDD exposure level, age stratification, faceted by region, difference between SSP1(26) and current population.(B) GCM uncertainty range for the count of individuals exposed to a given number of annual days with T Max > 37.5 • C, age stratification, faceted by region, , difference between SSP1(26) and current population.(C) GCM uncertainty range for the count of individuals exposed to a given 95 th percentile maximum temperature exposure level, age stratification, faceted by region, , difference between SSP1(26) and current population.

Figure SI- 21 .
Figure SI-21.Regional and age-group specific trends in the cumulative and intensity of acute exposure of population groups: 2020-2050.(A) GCM uncertainty range for the count of individuals exposed to a given CDD exposure level, age stratification, faceted by region, difference between SSP3(70) and current population.(B) GCM uncertainty range for the count of individuals exposed to a given number of annual days with T Max > 37.5 • C, age stratification, faceted by region, , difference between SSP3(70) and current population.(C) GCM uncertainty range for the count of individuals exposed to a given 95 th percentile maximum temperature exposure level, age stratification, faceted by region, , difference between SSP3(70) and current population.

Figure SI- 23 .
Figure SI-23.Country-level decomposition of determinants of exposure E r projections, by region and scenario.

Figure SI- 24 .
Figure SI-24.Country-level decomposition of determinants of exposure E r projections, by region and scenario.

Figure SI- 25 .
Figure SI-25.Country-level decomposition of determinants of exposure E r projections, by region and scenario.

Figure SI- 26 .
Figure SI-26.Country-level decomposition of determinants of exposure E r projections, by region and scenario.

Figure SI- 27 .
Figure SI-27.Country-level decomposition of determinants of exposure E r projections, by region and scenario.

Figure SI- 28 .
Figure SI-28.Country-level decomposition of determinants of T MAX th 95 exposure E r projections, by region and scenario.

Figure SI- 29 .
Figure SI-29.Country-level decomposition of determinants of T MAX th 95 exposure E r projections, by region and scenario.

Figure SI- 30 .
Figure SI-30.Country-level decomposition of determinants of T MAX th 95 exposure E r projections, by region and scenario.

Figure SI- 31 .
Figure SI-31.Country-level decomposition of determinants of T MAX th 95 exposure E r projections, by region and scenario.

Figure SI- 32 .
Figure SI-32.Country-level decomposition of determinants of T MAX th95 exposure E r projections, by region and scenario.

Figure SI- 33 .
Figure SI-33.Country-level decomposition of determinants of #hotdays exposure E r projections, by region and scenario.

Figure SI- 34 .
Figure SI-34.Country-level decomposition of determinants of #hotdays exposure E r projections, by region and scenario.

Figure SI- 35 .
Figure SI-35.Country-level decomposition of determinants of #hotdays exposure E r projections, by region and scenario.

Figure SI- 36 .
Figure SI-36.Country-level decomposition of determinants of #hotdays exposure E r projections, by region and scenario.

Figure SI- 37 .
Figure SI-37.Country-level decomposition of determinants of #hotdays exposure E r projections, by region and scenario.

Table SI -
2. Population-weighted t-test of difference in means between age groups CDD exposure, by region and scenario Figure SI-22.Cumulative share of regional population exposed to a given amount of CDDs, age stratification, historical climate.