A slide series from a seminar series I delivered at my university.

1. The Rise and Rise of Chronic Disease:
Effects of Societal Ageing
Presenter
Hamish Robertson, PhD

2. Contents
• Introduction
• Population ageing as a global phenomenon
• Health, ageing and chronic disease
• Chronic disease patterns
• Visualising the possibilities – when and ‘what if’
• Systemic effects and societal implications
• Conclusion

3. Introduction
• As usual I’m coming from a geographic perspective
• Chronic disease is a big topic so apologies for any gross simplifications
• Key focus here is population ageing and chronic disease
• Emphasis on some socio-cultural aspects and spatial engagements
with ageing and chronic disease
• Spatial emphasis about pragmatics – how the ‘problem’ of ageing can
be better managed by adding a geographic perspective
• As always, acknowledge my colleague Nick on the mapping side of the
equation

4. Population
Ageing is an
Increasingly
Global
Phenomenon
• It has a history that is improving all the time –
origins are not some fixed or static process
• Variation has occurred across the globe – no
singular pattern of population ageing – timing,
tempo, cohorts, composition etc.
• Outliers have a long history – centenarian studies
and their exceptional (and contested) scenarios
• The question of replication in other environments
– e.g. healthy cities?
• Growing the scientific understanding of what age
and ageing are - a fully developed science of
ageing…?
• Chronic disease matters less if you live less e.g.
older women

5. Population Ageing is Not Really New
• Three to four centuries of development in the European and North American
context – fairly good historical data and improving over time but a focus of
contestation and debate
• Only two major demographic criteria required – falling fertility and rising life
expectancies
• Source of these changes? Agricultural change? Industrialisation? Growing
production and wealth? Rise of public health and clinical medicine?
McKeown debate? Johansson’s thesis? Outlier effects? etc.
• Western Europe and affiliates already concerned by 1900 – Spengler - Decline
of the West, ‘racial suicide’, eugenics, family planning, population policies,
‘orphan’ migration schemes – numerous consequences still with us today
• Now even faster demographic transitions in East Asia and fastest (to date) in
Iran - 15 years (see BPR, USA)!
• Post-WW2 baby boom was a demographic anomaly – conservative push-
back, Cold War etc.

6. Three Centuries of Demographic Change

7. And Similar for Life Expectancies
- Parish records
- Civil registration systems
- Insurance company
modelling and analysis

8. Data from Max Roser’s Work
Source: https://ourworldindata.org/

10. Ageing in the OECD
Source: https://data.oecd.org/pop/elderly-population.htm

11. 2021 AIHW
Dementia
Report

12. Mortality, Morbidity and Chronic Disease
• In general terms, life expectancies are still rising – with some notable conditionals
e.g. Covid-19 pandemic, neoliberal theory and effects, conventional
racism/sexism/classism persistent effects
• The number of very old is rising fastest – 85+, centenarians, super centenarians etc.
• Emphasis on mortality shifts to morbidity patterns and interventions
• Social and political ecology of age-related disease intensifies – lifestyles, blame, cost
emphasis,
• Issue of chronic disease is foregrounded – complex, lack of cures, treatments
ongoing and costly, numbers rising
• Issue of what health is can be remarked on – not an idealized state of absences but
a dynamic and complex environmental nexus
• Also, representations of ageing and chronic disease matter – affluent, educated,
self-reliant, relatively health y etc. – advertising and ageism
• Idealised ageing is a risk for older people -> older women as the majority of
survivors living with disability, cognitive impairments and chronic conditions framed
as largely medical (upstream versus downstream approaches)

14. The
Australian
Context

15. Living longer…and
its implications
The RC identified
148
recommendations

17. The Longest
Lived Among Us

18. Saul Justin Newman of
the Biological Data
Science Institute at
Australian National
University, 2019
- poor record keeping?
- fraud?

20. Theories of Demographic, Epidemiological and
Health Transition

21. Australian Population Theory

22. Modelling and Visualising the Geography
of Chronic Disease(s): A Pragmatic Approach

23. Spatial health informatics: Dementia in EU28
ID Coloring Country Country Dementia Rate 2015 Popn 60+ Dementia 2015 2020 Popn 60+ Dementia 2020 2030 Popn 60+ Dementia 2030 2040 Popn 60+ Dementia 2040 2050 Popn 60+ Dementia 2050
4153733 2AT Austria 7.1 2180080 155481 2377353 169551 2937094 209471 3176463 226542 3343594 238462
4153779 1BE Belgium 7.2 8331533 601073 8711320 628473 9932516 716575 10295971 742797 10281605 741760
11111588 1BG Bulgaria 5.5 1970210 109267 2010692 111513 2075318 115097 2185254 121194 2239622 124209
3882352 0HR Croatia 6.2 1817484 113335 1884346 117505 2000162 124727 2101438 131042 2049300 127791
11111560 0CY Cyprus 6.8 900545 61096 865895 58746 1088055 73818 1198545 81314 1094678 74267
4153760 3CZ Czech Republic 5.6 2554602 143644 2735362 153808 3002402 168824 3466656 194928 3662600 205946
4726864 1DK Denmark 6.3 1458007 91479 1567039 98319 1778092 111561 1914583 120125 1940503 121751
11648511 2EE Estonia 6.7 1147597 76415 1327551 88398 1616461 107636 1323098 88101 1351335 89982
12648303 1FI Finland 6.5 1444118 94083 1588400 103483 1770853 115369 1826949 119024 1883673 122719
2240256 2FR France 7.5 15919400 1189143 17410656 1300536 20286753 1515374 21947271 1639411 22285501 1664676
4393040 0DE Germany 7.0 21808055 1529756 23338019 1637077 27410070 1922717 27984373 1963002 27887307 1956193
10110156 3GR Greece 6.9 2822336 194759 2950377 203595 3253052 224481 3560572 245702 3553092 245186
11111486 1HU Hungary 6.2 2361344 145382 2498082 153800 2635042 162233 2967403 182695 3065300 188723
17129843 0IE Ireland 6.2 796220 49113 895884 55260 1115266 68792 1339015 82593 1398299 86250
3446370 0IT Italy 7.7 15995248 1233182 17094728 1317948 20106540 1550149 22529769 1736972 23216182 1789893
11111870 1LV Latvia 6.9 490664 33773 503243 34639 511328 35196 508326 34989 506159 34840
11111847 2LT Lithuania 6.4 706957 45372 727451 46687 755477 48486 725782 46580 645532 41430
2430042 3LU Luxembourg 6.7 130802 8797 152061 10226 203439 13682 239032 16075 271749 18276
2430175 0MT Malta 5.1 215378 11045 236733 12140 225259 11551 261076 13388 261370 13403
4153834 3NL Netherlands 6.3 3836242 239883 4310409 269533 5217229 326237 5499698 343900 5503402 344132
11111820 1PL Poland 6.2 8206055 505713 9267907 571151 10246282 631445 11416453 703559 12502826 770509
15975092 1PT Portugal 6.9 3046893 210531 3294437 227635 3588317 247942 3958200 273499 4018981 277699
11111529 0RO Romania 5.7 4614008 263823 4868559 278378 5275379 301639 5863575 335271 6127605 350368
11111509 0SK Slovakia 5.5 1079058 59106 1220584 66859 1425356 78075 1666078 91261 1840684 100825
3498815 3SI Slovenia 6.5 683946 44520 784316 51053 814996 53050 941813 61305 933158 60742
16512072 0ES Spain 7.5 10722418 800988 11626015 868489 14085843 1052243 16778380 1253382 17136414 1280128
6019577 0SE Sweden 7.1 2429771 171903 2594518 183559 2964804 209756 3177482 224803 3458441 244681
23673283 1GB United Kingdom 7.0 14284208 1001253 15611237 1094271 18652264 1307432 20429047 1431976 22151411 1552705
EU (28 countries) 7.0 131953179 9236723 142453174 9971722 164973649 11548155 179282302 12549761 184610323 12922723

24. EU28 Country Population 2015 and 2050

25. Dementia Estimate for EU28 Countries 2015 and 2050

26. Total Dementia Change 2015-2050 in EU28

27. Treemap for Dementia by EU28 in 2050

29. Projected AD Prevalence in NSW – No Change Scenario 1
One of Three Scenarios Modelled – No change, small decrease and an effective clinical
intervention

30. Spatial Modelling
Projected AD Scenario 1 by SA2 for Sydney Metro in 2027

31. Scenario 1 Data and Residential Aged Care Facility
Locations for Metropolitan Sydney

32. Modelling Demography, Epidemiology and
Systemic Infrastructure – Ambulance Stations

33. Estimated Total Cost of Formal Care in Metropolitan
Sydney in 2027 by SA2

34. Spatial Accessibility to Health Services by SA2 x Individual
Services and an All Services Index

35. Spatial Accessibility: RACFs and SA2s (5kms)

36. And Interactive Data Visualisation

37. Demographic Complexity and Data Visualisation

38. Comparability Over Time: 2020 and 2032

39. Localisation and Monitoring Change Over Time

40. Adding Infratsructure

41. Modelling Chronic Disease(s) and Geographic Impact

42. Ageing and ‘Exposure’ Risks
• Life courses matter in determining overall life expectancy, morbidity
and mortality
• Location is fundamental to many exposure risks e.g. toxic exposures,
discriminatory treatment, deprived areas (often policy choices, not
‘natural’)
• Scale factors in here too – background risks factors (and vulnerability
status) through to microgeographies – e.g. safety in the community
and in residential care
• More on this in my final session e.g. environmental justice and
environmental racism

43. Man-Made Hazards in Metro Sydney
(and these are the legal/identified stuff…EPA Data 2012
illegal dumping is a growing problem nationally and internationally)

44. Aged 65+ and Contamination Sites

45. Conclusion
• The scientific understanding of age, ageing and population ageing are
in their early stages – developmental knowledge base
• Population ageing is dynamic and variable over space and time
• Chronic disease is also a mutable concept with significant systemic
implications
• Covid-19 makes any simple health transition theory redundant and
adds to the complexity of chronic disease and ageing – long Covid
• Spatial concepts, tools and technologies have a contribution to make
to a better aged care system
• Chronic disease is a geographic phenomenon