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6th
International Disaster and Risk Conference IDRC 2016
‘Integrative Risk Management – Towards Resilient Cities‘ • 28 Aug – 1 Sept 2016 • Davos • Switzerland
www.grforum.org
An Analysis of Perception to Natural
Disasters of the Elderly in Beijing
Shujuan Cui , Liang Cai , Ailun Guo , Jing’ai Wang
Beijing Normal University, China
29/8/2016
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6th
International Disaster and Risk Conference IDRC 2016
‘Integrative Risk Management – Towards Resilient Cities‘ • 28 Aug – 1 Sept 2016 • Davos • Switzerland
www.grforum.org
Outline
• Background
• Objective & Key questions
• Data & Method
• Results
6th
International Disaster and Risk Conference IDRC 2016
‘Integrative Risk Management – Towards Resilient Cities‘ • 28 Aug – 1 Sept 2016 • Davos • Switzerland
www.grforum.org
Background
• serious losses of natural disasters
• Ignorance of the human system
• perception impact on disaster reduction
• perception vary with each individual
• Selodom study of
difference among the elderly
6th
International Disaster and Risk Conference IDRC 2016
‘Integrative Risk Management – Towards Resilient Cities‘ • 28 Aug – 1 Sept 2016 • Davos • Switzerland
www.grforum.org
Objective & Key questions
• What indexes can be used to describe the perception?
• What demography characteristics can influence the
perception of the elderly? And how?
• What are the difference between the perception of the
elderly and the “real” situation?
6th
International Disaster and Risk Conference IDRC 2016
‘Integrative Risk Management – Towards Resilient Cities‘ • 28 Aug – 1 Sept 2016 • Davos • Switzerland
www.grforum.org
• Based on the literatures and complex network analysis, it can
be divided into to 2 categories:
• The indexes of perception (Data & Method 1-1)
• The indexes of demography characteristics (Data & Method 1-
2)
Data & Method 1:Indexes
6th
International Disaster and Risk Conference IDRC 2016
‘Integrative Risk Management – Towards Resilient Cities‘ • 28 Aug – 1 Sept 2016 • Davos • Switzerland
www.grforum.org
Index Question Option Value
Perception
describe
Perception
of disaster
types
1.Which disaster is
the most severe in
your area?
A earthquake B drought
C rainstorm and flood D sandstorm
E haze F others G none
7 kinds
Index of
perception
disaster
experience
2. Which disaster is
the most severe in
your experience?
A earthquake B drought
C rainstorm and flood D sandstorm
E haze F others G none
The times of the
disaster
experience
disaster
knowledge
3.Do you think it is
necessary to have
some material
preparation for
disasters?
A unnecessary B necessary but not
prepared C necessary
1,2,3
5. Do you have a
contingency plan for
disasters?
A no B yes 1,2
6. Which disaster
reduction activity
have you ever
participated in
your community?
A drill B reading the Bulletin board
C reading the leaflet D training and
lectures E none
ABCD +1
disaster
preparedness
7.What should you
do when
earthquake happen?
A run out B jump out the building
C hide on the balcony or by the window
D escape through elevator E hide in a
small space F hide in a trigonum
G others H. don’t know
AEF +1
BCDGH 0
8. What should you
do when flood
happen?
A transfer to higher places
B wait for rescue
C transfer through water D. others
E don’t know
AB +1
CDE 0
Index of
demography
location 9.Your home
location is?
Area1:1
Area2:2
age 10.Your age is? 60、61、62……
gender 11.Your gender is? A.male Bfemale 1,2
education 12.Your education
level is?
A. illiteracy B. primary school C. middle
school D. high school E. college and
higher level
1,2,3,4,5
6th
International Disaster and Risk Conference IDRC 2016
‘Integrative Risk Management – Towards Resilient Cities‘ • 28 Aug – 1 Sept 2016 • Davos • Switzerland
www.grforum.org
Data & Method 1-1:Indexes
Tab.1 The indexes and code for perception
Tab.2 The correlation of the perception indexes
Index Code Indicator Code
Disaster
experience
E Disaster experience E
Disaster
preparedness
P
Material preparation 𝑃𝑃𝑟𝑒𝑝𝑎𝑟𝑒𝑑𝑛𝑒𝑠𝑠
Emergency plans 𝑃𝑃𝑙𝑎𝑛
Activity participation 𝑃𝐴𝑐𝑡𝑖𝑣𝑖𝑡𝑦
Disaster
knowledge
K
Knowledge of earthquake 𝐾 𝐸𝑎𝑟𝑡ℎ𝑞𝑢𝑎𝑘𝑒
Knowledge of flood 𝐾𝐹𝑙𝑜𝑜𝑑
E P K
E 1.000
P .015 1.000
K .049* .301** 1.000
6th
International Disaster and Risk Conference IDRC 2016
‘Integrative Risk Management – Towards Resilient Cities‘ • 28 Aug – 1 Sept 2016 • Davos • Switzerland
www.grforum.org
Data & Method 1-1:Sampling method
• The sampling method is random sampling in the places where
there is lots of elderly people, such as the parks, the streets,
the supermarket and recreation center for the senior citizens.
The number of the sample is calculated as the formula.
n =
𝑍2 𝑝(1 − 𝑝)
4𝑒2
• The confidence level is 95%, Z = 1.96, p = 0.5, e = 4%. 1235
effective questionnaires are obtained eventually.
6th
International Disaster and Risk Conference IDRC 2016
‘Integrative Risk Management – Towards Resilient Cities‘ • 28 Aug – 1 Sept 2016 • Davos • Switzerland
www.grforum.org
Data & Method1-1: Study areas
Mountain areas
The plain areas
Town, village
Downtown area
Low-level of economic
High-level economic
Drought Flood …
Haze Flood …
Left-behind elderly people
6th
International Disaster and Risk Conference IDRC 2016
‘Integrative Risk Management – Towards Resilient Cities‘ • 28 Aug – 1 Sept 2016 • Davos • Switzerland
www.grforum.org
Data & Method 1-2: Demography characteristics
Tab.3 The demography characteristics of respondents
Tab.4 The correlation of demography characteristics
Age 60-64 65-69 70-74 75-79 80-84 ≥85 Gender male female
318 238 267 197 164 39 595 531
Education illiteracy
primary
school
middle
school
high
school
college
or above
Location Area1 Area2
160 386 300 177 199 609 626
Age Location Gender Education
Age 1.000
Location -.279** 1.000
Gender .005 .016 1.000
Education -.023 -.434** .162** 1.000
6th
International Disaster and Risk Conference IDRC 2016
‘Integrative Risk Management – Towards Resilient Cities‘ • 28 Aug – 1 Sept 2016 • Davos • Switzerland
www.grforum.org
Data & Method 2:Perception bias index
• Difference between perception and the real situation
• Q: Which disaster is the most severe in your area?
• Difference between the percentage of a certain disaster in a
group (result of the questionares) and the percentage of the
frequency in Beijing (statistics in record).
PER = (𝑋𝑖𝑗 − 𝑌𝑗)2
× 𝐖
𝑋𝑖𝑗: the percentage of disaster j in group I;
𝑌𝑗: the percentage of disaster j in Beijing;
W: the sequence of disaster frequency in Beijing.
W of Haze, rainstorm and flood, drought,
sandstorm and earthquake are 5, 4, 3, 2, 1 respectively.
Fig.2 The percentage of disasters frequency in Beijing
6th
International Disaster and Risk Conference IDRC 2016
‘Integrative Risk Management – Towards Resilient Cities‘ • 28 Aug – 1 Sept 2016 • Davos • Switzerland
www.grforum.org
Results 1-1: Disaster experience
Demograp
hy index
Group E
Range of
different group
Sig.
Location
Area1 0.194
0.115 0.000
Area2 0.309
Gender
Male 0.253
0.059 0.004
Female 0.279
Education
Illiteracy 0.235
0.075 0.000
Primary
school
0.295
Middle
school
0.266
High
school
0.286
Collage
or above
0.22
Age
60-64 0.307
0.108 0.000
65-69 0.263
70-74 0.251
75-79 0.202
≥80 0.199
Fig.3 The disaster experience index in different groups
6th
International Disaster and Risk Conference IDRC 2016
‘Integrative Risk Management – Towards Resilient Cities‘ • 28 Aug – 1 Sept 2016 • Davos • Switzerland
www.grforum.org
Results 1-2:Disaster preparedness
Demograp
hy index
group P
Range of
different group
Sig.
Location
Area1 0.768
0.108 0.000
Area2 0.660
Gender
Male 0.647
0.099 0.000
Female 0.746
Education
Illiteracy 0.471
0.389 0.000
Primary
school
0.615
Middle
school
0.711
High
school
0.860
Collage
or above
0.700
Age
60-64 0.758
0.181 0.000
65-69 0.702
70-74 0.721
75-79 0.662
≥80 0.576
Fig.3 The disaster preparedness index in different groups
6th
International Disaster and Risk Conference IDRC 2016
‘Integrative Risk Management – Towards Resilient Cities‘ • 28 Aug – 1 Sept 2016 • Davos • Switzerland
www.grforum.org
Results 1-3: Disaster knowledge
Demograp
hy index
group K
Rangeof
different group
Sig.
Location
Area1 0.336
0.009 0.669
Area2 0.332
Gender
Male 0.325
0.015 0.000
Female 0.341
Education
Illiteracy 0.275
0.116 0.000
Primary
school
0.306
Middle
school
0.361
High
school
0.390
Collage
or above
0.332
Age
60-64 0.348
0.082 0.000
65-69 0.337
70-74 0.328
75-79 0.318
≥80 0.265
Fig.3 The disaster knowledge index in different groups
6th
International Disaster and Risk Conference IDRC 2016
‘Integrative Risk Management – Towards Resilient Cities‘ • 28 Aug – 1 Sept 2016 • Davos • Switzerland
www.grforum.org
Demograph
y index
group
perception
bias index
Range of
different group
Location
Area1 0.587
0.128
Area2 0.715
Gender
Male 0.225
0.009
Female 0.234
Education
Illiteracy 0.721
0.525
Primary
school
0.369
Middle
school
0.277
High school 0.196
Collage or
above
0.519
Age
60-64 0.311
0.197
65-69 0.362
70-74 0.279
75-79 0.358
≥80 0.165
Fig.4 The perception
sequence of disasters
in different groups
Results 2: Perception bias index
6th
International Disaster and Risk Conference IDRC 2016
‘Integrative Risk Management – Towards Resilient Cities‘ • 28 Aug – 1 Sept 2016 • Davos • Switzerland
www.grforum.org
Brief Summary
• Three indexes to describe perception: E, P, K
• The influence of demography characteristics to perception
(E-location, age; P-education, age; K-education, age)
• perception bias
(education, age, location)
• Perception to different types of disaster
(haze, drought……influenced by demography characteristics)
6th
International Disaster and Risk Conference IDRC 2016
‘Integrative Risk Management – Towards Resilient Cities‘ • 28 Aug – 1 Sept 2016 • Davos • Switzerland
www.grforum.org

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Impact of a Collective Action in a Disaster-affected Community to Site a Temp...
 

An Analysis of Perception to Natural Disasters of the Elderly in Beijing, Shujuan CUI

  • 1. 6th International Disaster and Risk Conference IDRC 2016 ‘Integrative Risk Management – Towards Resilient Cities‘ • 28 Aug – 1 Sept 2016 • Davos • Switzerland www.grforum.org An Analysis of Perception to Natural Disasters of the Elderly in Beijing Shujuan Cui , Liang Cai , Ailun Guo , Jing’ai Wang Beijing Normal University, China 29/8/2016 Please add your logo here
  • 2. 6th International Disaster and Risk Conference IDRC 2016 ‘Integrative Risk Management – Towards Resilient Cities‘ • 28 Aug – 1 Sept 2016 • Davos • Switzerland www.grforum.org Outline • Background • Objective & Key questions • Data & Method • Results
  • 3. 6th International Disaster and Risk Conference IDRC 2016 ‘Integrative Risk Management – Towards Resilient Cities‘ • 28 Aug – 1 Sept 2016 • Davos • Switzerland www.grforum.org Background • serious losses of natural disasters • Ignorance of the human system • perception impact on disaster reduction • perception vary with each individual • Selodom study of difference among the elderly
  • 4. 6th International Disaster and Risk Conference IDRC 2016 ‘Integrative Risk Management – Towards Resilient Cities‘ • 28 Aug – 1 Sept 2016 • Davos • Switzerland www.grforum.org Objective & Key questions • What indexes can be used to describe the perception? • What demography characteristics can influence the perception of the elderly? And how? • What are the difference between the perception of the elderly and the “real” situation?
  • 5. 6th International Disaster and Risk Conference IDRC 2016 ‘Integrative Risk Management – Towards Resilient Cities‘ • 28 Aug – 1 Sept 2016 • Davos • Switzerland www.grforum.org • Based on the literatures and complex network analysis, it can be divided into to 2 categories: • The indexes of perception (Data & Method 1-1) • The indexes of demography characteristics (Data & Method 1- 2) Data & Method 1:Indexes
  • 6. 6th International Disaster and Risk Conference IDRC 2016 ‘Integrative Risk Management – Towards Resilient Cities‘ • 28 Aug – 1 Sept 2016 • Davos • Switzerland www.grforum.org Index Question Option Value Perception describe Perception of disaster types 1.Which disaster is the most severe in your area? A earthquake B drought C rainstorm and flood D sandstorm E haze F others G none 7 kinds Index of perception disaster experience 2. Which disaster is the most severe in your experience? A earthquake B drought C rainstorm and flood D sandstorm E haze F others G none The times of the disaster experience disaster knowledge 3.Do you think it is necessary to have some material preparation for disasters? A unnecessary B necessary but not prepared C necessary 1,2,3 5. Do you have a contingency plan for disasters? A no B yes 1,2 6. Which disaster reduction activity have you ever participated in your community? A drill B reading the Bulletin board C reading the leaflet D training and lectures E none ABCD +1 disaster preparedness 7.What should you do when earthquake happen? A run out B jump out the building C hide on the balcony or by the window D escape through elevator E hide in a small space F hide in a trigonum G others H. don’t know AEF +1 BCDGH 0 8. What should you do when flood happen? A transfer to higher places B wait for rescue C transfer through water D. others E don’t know AB +1 CDE 0 Index of demography location 9.Your home location is? Area1:1 Area2:2 age 10.Your age is? 60、61、62…… gender 11.Your gender is? A.male Bfemale 1,2 education 12.Your education level is? A. illiteracy B. primary school C. middle school D. high school E. college and higher level 1,2,3,4,5
  • 7. 6th International Disaster and Risk Conference IDRC 2016 ‘Integrative Risk Management – Towards Resilient Cities‘ • 28 Aug – 1 Sept 2016 • Davos • Switzerland www.grforum.org Data & Method 1-1:Indexes Tab.1 The indexes and code for perception Tab.2 The correlation of the perception indexes Index Code Indicator Code Disaster experience E Disaster experience E Disaster preparedness P Material preparation 𝑃𝑃𝑟𝑒𝑝𝑎𝑟𝑒𝑑𝑛𝑒𝑠𝑠 Emergency plans 𝑃𝑃𝑙𝑎𝑛 Activity participation 𝑃𝐴𝑐𝑡𝑖𝑣𝑖𝑡𝑦 Disaster knowledge K Knowledge of earthquake 𝐾 𝐸𝑎𝑟𝑡ℎ𝑞𝑢𝑎𝑘𝑒 Knowledge of flood 𝐾𝐹𝑙𝑜𝑜𝑑 E P K E 1.000 P .015 1.000 K .049* .301** 1.000
  • 8. 6th International Disaster and Risk Conference IDRC 2016 ‘Integrative Risk Management – Towards Resilient Cities‘ • 28 Aug – 1 Sept 2016 • Davos • Switzerland www.grforum.org Data & Method 1-1:Sampling method • The sampling method is random sampling in the places where there is lots of elderly people, such as the parks, the streets, the supermarket and recreation center for the senior citizens. The number of the sample is calculated as the formula. n = 𝑍2 𝑝(1 − 𝑝) 4𝑒2 • The confidence level is 95%, Z = 1.96, p = 0.5, e = 4%. 1235 effective questionnaires are obtained eventually.
  • 9. 6th International Disaster and Risk Conference IDRC 2016 ‘Integrative Risk Management – Towards Resilient Cities‘ • 28 Aug – 1 Sept 2016 • Davos • Switzerland www.grforum.org Data & Method1-1: Study areas Mountain areas The plain areas Town, village Downtown area Low-level of economic High-level economic Drought Flood … Haze Flood … Left-behind elderly people
  • 10. 6th International Disaster and Risk Conference IDRC 2016 ‘Integrative Risk Management – Towards Resilient Cities‘ • 28 Aug – 1 Sept 2016 • Davos • Switzerland www.grforum.org Data & Method 1-2: Demography characteristics Tab.3 The demography characteristics of respondents Tab.4 The correlation of demography characteristics Age 60-64 65-69 70-74 75-79 80-84 ≥85 Gender male female 318 238 267 197 164 39 595 531 Education illiteracy primary school middle school high school college or above Location Area1 Area2 160 386 300 177 199 609 626 Age Location Gender Education Age 1.000 Location -.279** 1.000 Gender .005 .016 1.000 Education -.023 -.434** .162** 1.000
  • 11. 6th International Disaster and Risk Conference IDRC 2016 ‘Integrative Risk Management – Towards Resilient Cities‘ • 28 Aug – 1 Sept 2016 • Davos • Switzerland www.grforum.org Data & Method 2:Perception bias index • Difference between perception and the real situation • Q: Which disaster is the most severe in your area? • Difference between the percentage of a certain disaster in a group (result of the questionares) and the percentage of the frequency in Beijing (statistics in record). PER = (𝑋𝑖𝑗 − 𝑌𝑗)2 × 𝐖 𝑋𝑖𝑗: the percentage of disaster j in group I; 𝑌𝑗: the percentage of disaster j in Beijing; W: the sequence of disaster frequency in Beijing. W of Haze, rainstorm and flood, drought, sandstorm and earthquake are 5, 4, 3, 2, 1 respectively. Fig.2 The percentage of disasters frequency in Beijing
  • 12. 6th International Disaster and Risk Conference IDRC 2016 ‘Integrative Risk Management – Towards Resilient Cities‘ • 28 Aug – 1 Sept 2016 • Davos • Switzerland www.grforum.org Results 1-1: Disaster experience Demograp hy index Group E Range of different group Sig. Location Area1 0.194 0.115 0.000 Area2 0.309 Gender Male 0.253 0.059 0.004 Female 0.279 Education Illiteracy 0.235 0.075 0.000 Primary school 0.295 Middle school 0.266 High school 0.286 Collage or above 0.22 Age 60-64 0.307 0.108 0.000 65-69 0.263 70-74 0.251 75-79 0.202 ≥80 0.199 Fig.3 The disaster experience index in different groups
  • 13. 6th International Disaster and Risk Conference IDRC 2016 ‘Integrative Risk Management – Towards Resilient Cities‘ • 28 Aug – 1 Sept 2016 • Davos • Switzerland www.grforum.org Results 1-2:Disaster preparedness Demograp hy index group P Range of different group Sig. Location Area1 0.768 0.108 0.000 Area2 0.660 Gender Male 0.647 0.099 0.000 Female 0.746 Education Illiteracy 0.471 0.389 0.000 Primary school 0.615 Middle school 0.711 High school 0.860 Collage or above 0.700 Age 60-64 0.758 0.181 0.000 65-69 0.702 70-74 0.721 75-79 0.662 ≥80 0.576 Fig.3 The disaster preparedness index in different groups
  • 14. 6th International Disaster and Risk Conference IDRC 2016 ‘Integrative Risk Management – Towards Resilient Cities‘ • 28 Aug – 1 Sept 2016 • Davos • Switzerland www.grforum.org Results 1-3: Disaster knowledge Demograp hy index group K Rangeof different group Sig. Location Area1 0.336 0.009 0.669 Area2 0.332 Gender Male 0.325 0.015 0.000 Female 0.341 Education Illiteracy 0.275 0.116 0.000 Primary school 0.306 Middle school 0.361 High school 0.390 Collage or above 0.332 Age 60-64 0.348 0.082 0.000 65-69 0.337 70-74 0.328 75-79 0.318 ≥80 0.265 Fig.3 The disaster knowledge index in different groups
  • 15. 6th International Disaster and Risk Conference IDRC 2016 ‘Integrative Risk Management – Towards Resilient Cities‘ • 28 Aug – 1 Sept 2016 • Davos • Switzerland www.grforum.org Demograph y index group perception bias index Range of different group Location Area1 0.587 0.128 Area2 0.715 Gender Male 0.225 0.009 Female 0.234 Education Illiteracy 0.721 0.525 Primary school 0.369 Middle school 0.277 High school 0.196 Collage or above 0.519 Age 60-64 0.311 0.197 65-69 0.362 70-74 0.279 75-79 0.358 ≥80 0.165 Fig.4 The perception sequence of disasters in different groups Results 2: Perception bias index
  • 16. 6th International Disaster and Risk Conference IDRC 2016 ‘Integrative Risk Management – Towards Resilient Cities‘ • 28 Aug – 1 Sept 2016 • Davos • Switzerland www.grforum.org Brief Summary • Three indexes to describe perception: E, P, K • The influence of demography characteristics to perception (E-location, age; P-education, age; K-education, age) • perception bias (education, age, location) • Perception to different types of disaster (haze, drought……influenced by demography characteristics)
  • 17. 6th International Disaster and Risk Conference IDRC 2016 ‘Integrative Risk Management – Towards Resilient Cities‘ • 28 Aug – 1 Sept 2016 • Davos • Switzerland www.grforum.org