Economic implications of climatechange on human health throughundernourishment
Tomoko HASEGAWA
The 21st AIM international workshop, 15/11/2015

0Our earlier studies
Socio-economic
conditions

Climate change
Adaptation
Hasegawa et al., 2014, EST

Mitigation
Hasegawa et al., 2015, EST
Hasegawa et al., 2015,ERL

Undernourishment/Population at risk ofhunger
Health impacts throughundernutrition

Ishida et al., 2014

Economic impacts/
implications

 Now we are here!
Hasegawa et al.,under review
1Future hunger risk in this century2Our earlier studies
Socio-economic
conditionsClimate change
Adaptation
Hasegawa et al., 2014, ESTMitigation
Hasegawa et al., 2015, EST
Hasegawa et al., 2015,ERL

Undernourishment/Population at risk ofhunger
Health impacts throughundernutrition

Ishida et al., 2014

Economic impacts/implications

 Now we are here!
Hasegawa et al.,under review
3Consequences of mitigation on undernourishment

Hasegawa et al. 2015

4

Health burden due to childhood undernutrition

Ishida et al. 2014

5

Our earlier studies
Socio-economic
conditions

Climate change
Adaptation
Hasegawa et al., 2014, EST

Mitigation
Hasegawa et al., 2015, EST
Hasegawa et al., 2015,ERL

Undernourishment/Population at risk ofhunger
Health impacts throughundernutrition

Ishida et al., 2014

Economic impacts/implications

 Now we are here!
Hasegawa et al.,under review
6Research question“How large is climate change impact on human health throughundernourishment?”• Economic impacts of decreases in labor force and population, andadditional healthcare cost
• Value of lives lost.
Human health
Extreme heat
Change in vector habitat
Climatechange• Death and disease• Labor force productivity• Medical services

Agriculture & FoodCropproduction• Undernourishment• Child underweight

Economicimpact＜Role of this study＞
Economic
impact/implications• Death and disease• Medical service• Labor force

Economic impact
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Disability-Adjusted Life Years (DALY)• DALY is years of "healthy" life lost weighted by disability and mortality (Murray 1996).
• DALYs have been used by WHO as a measurement of disease burden.
• DALY have information of risk factor and disease or disability• E.g. ：risk factor → disease or disability• childhood underweight → malaria•tobacco→ lung cancer

8Childhood underweight is
the highest risk factor of disability
in low income regions
source: WHO 20099

Major causes of death in children under 5 years old(Shaded area: contribution of undernutrition to each cause of death)百日咳
出生時の呼吸停止、心的外傷

早産（未熟）児下痢

新生児への深刻な感染
はしか
栄養の欠乏
その他感染症マラリア

source: WHO http://www.who.int/healthinfo/global_burden_disease/GlobalHealthRisks_report_full.pdf

source: WHO 200910

Modeling framework
2 socioeconomic
conditions

Change in crop yield

AIM/CGE model
Food market• Food calorie intake• Population at risk of hunger• Income• GINI
coefficient

the Prevalence ofUndernourishment(PoU)

Stunting module(Lloyd et al., 2011, Ishida et al., 2014)
Proportion of children
under 5 year of age
stuntedHouseholdexpenditure

DALY module(Ishida et al., 2014)
Disability-Adjusted
Life Years (DALY)
Years Lived with
Disability (YLD)

Medical expenditure
Model/ module
Exogenous
variables
Endogenous
variables

Number of mortality

Added variables• Population at risk of hunger• DALY• Medical expenditure• Mortality• value of life lostTwo feedback• 1) Mortality fed back to populationand labor force• 2) Medical cost fed back tohousehold expenditure
Economic valueof life lostChange in• Population• Labor population

Economic effects• GDP loss
• Welfare loss

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DALY model• Ishida et al. (2014)

log(DALYt ,c , dPOPt ,c) = ϕ d + ψ d ⋅ log (Yt ,c )• t: year, c: country, d: disease;• DALY t,c,d: DALY due to disease d (year)• POPt,c: population• Yt,c: Proportion of children stunted.

12Economic value of Life lost as a result of Disability• Value of Statistical Life (VSL): an evaluation based on the WTP toavoid the risk of death.
• Approach developed by OECD (2012), where the VSL is derived
using an income adjustment.
• The value of the health risk observed in China, 2005 wasapplied to other mid- or low- income regions.

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Scenario settings• 3 climate conditions: RCP2.6, RCP8.5, No climate change• 2 socioeconomic conditions: SSP2, SSP3
• Year: 2005-2100
Climate conditions

Uncertainty• 4 crop models• 5 climate models• 3 climate conditions

Socioeconomic conditions
SSP2SSP3No changeXX

RCP8.5XX

RCP2.6X

X

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