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Planetary Health and Mental Health Nexus: Benefit of Environmental Management Cover

Planetary Health and Mental Health Nexus: Benefit of Environmental Management

Open Access
|Jul 2023

Figures & Tables

Figure 1

Methodological framework to explore the economic relationships between the prevalence and costs of mental health and selected environmental factors.

Table 1

Definitions and sources of data used in the country level analysis.

VARIABLEDEFINITIONSOURCEMEANS.D.
DALY rateNumber of mental health DALYs per 100,000 people 2019Global Burden of Disease1,689.59328.27
GDP per capitaGross Domestic Product per capita 2019 (USD; thousands)World Bank17.3424.04
InequalityIndex of inequality (0–10)INFORM Risk4.041.95
Healthcare inaccessibilityIndex of inaccessibility to healthcare (0–10)INFORM Risk4.132.45
Hazard exposureComposite index comprising data on hazards, exposure, vulnerability and coping capacity (0–10)INFORM Risk3.751.77
Air pollutionPM2.5 mean annual exposure (micrograms per cubic meter)World Bank27.0818.83
Access to green spaceProportion of population living in urban areas (%)World Bank60.5623.41

[i] See Appendix 1, Table A1.1 for further information.

Table 2

Statistically significant relationships from regression model of rates of mental disorders as a function of environmental, economic and socio-economic factors.

REGRESSION COEFFICIENT
GDP per capita3.57
Income inequality38.07
Healthcare inaccessibility–94.06
Hazard exposure to extreme natural disasters42.68
Air pollution2.12
Access to open (green) space3.53

[i] Note: Dependent variable is the number of DALYs per 100,000 people.

Full regression model is given in Appendix 1, Table A1.2.

Figure 2

Categorisation of mental illness used to quantify the relationship between the costs of mental illness and a set of explanatory variables, including environmental factors.

Table 3

Definitions and sources of data used in the cost of illness analysis.

VARIABLEDEFINITIONSOURCEMEANS.D.
Cost/DALY (ln)Cost of illness per DALY (USD; PPP adjusted; 2020 price level; natural log)Adapted from Christensen et al. (2020)6.502.61
Severe disordersBinary variable indicating severe disorder (1 = severe; 0 = common)Christensen et al. (2020)0.210.41
Productivity costsBinary variable indicating measure of productivity loss (1 = productivity loss; 0 = other costs)Christensen et al. (2020)0.090.29
Societal costsBinary variable indicating measure of societal costs (1 = societal costs; 0 = other costs)Christensen et al. (2020)0.460.50
GDP per capita (ln)GDP per capita (USD; PPP adjusted; 2020 price level; natural log)World Bank10.800.55
Hazard exposureComposite index natural hazards (0–10)INFORM Risk3.361.79
Air pollutionProportion of population exposed to PM2.5 air pollution levels exceeding WHO guideline valueWorld Bank11.586.28
Access to green spaceProportion of population living in urban areasWorld Bank78.4610.40

[i] PPP = Purchasing Power Parity.

Table 4

Cost of mental illness and development disorders, categorised by type of disorder.

MEAN COST (US$/DALY)
Common disorders4,849
Severe disorders11,399
Childhood disorders62,071
Childhood + development disorders1,120
Total13,940

[i] Note: Data taken from 48 countries in Christensen et al. [30].

See Appendix 1, Table A1.3 for further statistical results.

Table 5

Cost of mental illness and development disorders, categorised by type of cost.

MEAN COST (US$/DALY)
Healthcare costs2,072
Productivity losses9,210
Total societal costs25,862
Other costs7,036
Total13,940

[i] Note: Data taken from 48 countries in Christensen et al. [30].

See Appendix 1, Table A1.4 for further statistical results.

Table 6

Relationships from regression model of costs of mental illness as a function of environmental, economic and socio-economic factors.

REGRESSION COEFFICIENT
Severe disorders1.86
Productivity costs1.76
Societal costs2.56
GDP per capita (ln)0.57
Hazard exposure0.16
Air pollution–0.01
Accessibility to green space0.00

[i] Note: Dependent variable is US$ per DALY at 2020 price level.

Statistically significant relationships are given in bold.

Full regression model is given in Appendix 1, Table A1.5.

Table 7

Estimated additional annual total cost of mental illness attributable to climate change, air pollution and access to green space, by World Bank region.

WORLD BANK REGIONCOST(US$ MILLIONS, 2020 PRICE LEVEL)
20302050
CLIMATE CHANGE COSTAIR POLLUTION COSTGREEN SPACE COSTTOTAL COSTCLIMATE CHANGE COSTAIR POLLUTION COSTGREEN SPACE COSTTOTAL COST
East Asia & Pacific9,7391,6662,49013,89679,12810,91915,318105,366
Europe & Central Asia1,679542171,95015,5244761,85117,851
Latin America & Caribbean1,187181631,3689,4601011,11410,674
Middle East & North Africa1,4943121891,99521,2293,3702,54527,143
North America2,422111902,62222,612851,59824,295
South Asia4,92817,11079822,83663,411236,46411,133311,008
Sub-Saharan Africa1,799853332,21733,9188585,47140,247
Global23,24819,2554,38046,884245,282252,27339,029536,584
Figure 3

Estimated additional total annual cost of mental illness attributable to climate change, air pollution and access to green space.

Notes: Groupings are following World Bank regional classifications.

Figure 4

Percentage change in annual societal costs of mental illness attributable to changes in climate hazards, air pollution and access to green space in 2050 relative to 2020.

DOI: https://doi.org/10.5334/aogh.4079 | Journal eISSN: 2214-9996
Language: English
Submitted on: Feb 6, 2023
Accepted on: May 26, 2023
Published on: Jul 24, 2023
Published by: Ubiquity Press
In partnership with: Paradigm Publishing Services
Publication frequency: 1 issue per year

© 2023 Pushpam Kumar, Luke Brander, Manasi Kumar, Pim Cuijpers, published by Ubiquity Press
This work is licensed under the Creative Commons Attribution 4.0 License.