Disparities in exposure to climate change

By Matt Burdett, 12 March 2018

On this page, we look at disparities in exposure to climate change risk and vulnerability, including variations in people’s location, wealth, social differences (age, gender, education), and risk perception.

  • Dhaka, Bangladesh: High levels of poverty, and a city that is only just above sea level, make the people of Dhaka highly vulnerable to the impacts of climate change.

What is risk and vulnerability?

Vulnerability, in a geography context, refers to the potential harm that people and property might receive due to a hazard event. The IBDP Geography Subject Guide defines vulnerability as: “The susceptibility of a community to a hazard or to the impacts of a hazard event” (IBO, 2009).

Therefore, the vulnerability of people depends on more than just the hazard. For example, an older population is more vulnerable than a youthful population; a very young (child) population is more vulnerable than an adult population. The vulnerability of a person can be assessed using three key ideas:

  • How sensitive is a person to the hazard? Will they be harmed a little, or a lot?
  • How exposed is a person to the hazard? Are they likely to be affected, or not?
  • How far can the person adapt to the hazard? Can they take steps to reduce their sensitivity or exposure?

This is different to ‘risk’ which is: “the probability of a hazard event event causing harmful consequences (death, injury, loss of property, damage to environment, etc.)” (IBO, 2009).

The ability of a population to adapt to a hazard or disaster is called by several terms including resilience, capability and coping capacity. The coping capacity is the ‘means why which people use the available resources and their abilities to face hazardous events’. Therefore, disasters occur when the full use of available resources still does not meet the needs of the people to face the disaster without outside help.

These factors – sensitivity, exposure and adaptive capacity – vary significantly from place to place and person to person. For example, the infographic below shows weather-related deaths by country as both proportions of the total population and as an absolute value. It is apparent that many of these countries are relatively small and relatively poor – yet, France and Spain also make it onto the list. This emphasises the importance of looking at the links between several factors, as discussed on this page.


  • Weather-related fatalities by country. Source: Times of India, 2017.

Variation by location

Depending on where a person is, they will have a different level of exposure to climate change. For example, someone living on a low-lying coastline is more exposed to sea level rise than someone living in a mountainous area. The map below shows the predicted level of future vulnerability to climate change.

  • Vulnerability to climate change. Source: Maplecroft, 2017.

In general, the pattern of exposure is related to location: the areas nearest to the equator are likely to experience the highest levels of climate threat, mainly because these are the areas which are likely to experience temperatures that are too high for agriculture. There is also a possible link to economy, as many of these countries are simultaneously in low and middle income countries.

Variation by wealth

The vulnerability of countries to future potential harm is, however, strongly related to economy. Countries that are wealthy have higher adaptive capacity because they can pay for social services, engineering and other mitigation strategies.

However, it’s not so straight forward as this. Countries that are wealthy can still experience big climate impacts. This is shown on the map below, where exposure is measured through ‘risk’ which refers to the actual harm inflicted upon each country by extreme weather events between 1997 and 2016. Although no individual event can be directly linked to climate change, they are likely to become more frequent and severe in the future.

  • World Map of the Global Climate Risk Index for 1997–2016. Source: Germanwatch, 2018.

This is a complicated picture. The harm done by climate change depends not only on exposure but also sensitivity and adaptive capacity, and can be skewed by specific failures in these areas. The example of France illustrates this. It appears to have a high vulnerability according to the map above, but this is because of a very specific event. In 2003, a heatwave affected much of Western Europe and killed over 4000 people in Paris and around 30,000 over the entire country. Temperatures rose above 38℃ during the day. France was therefore exposed to the hazard, but it might be expected that France, as a very wealthy country, might have coped better. However:

  • Elderly people are especially sensitive to heat. The vast majority of the deaths were from people over 65 years old.
  • Under normal conditions, France has the capacity to adapt to conditions by moving elderly people to air conditioned places. But because it happened in August, when most families are away on holiday, many elderly people were left behind and did not have the support they would normally receive.

Therefore, we can say that although countries may be exposed to climate change, the way they are affected might vary in unexpected ways.

  • Regional breakdown of vulnerability to climate change. Source: Maplecroft, 2017.

The graph above shows, however, that the future vulnerability of countries to climate change is strongly linked linked to economy: a significantly larger proportion of low income countries will be vulnerable to climate change as the impacts are more strongly felt in the future.

Variation by social indices


Older people and children are more vulnerable to climate change because they have higher sensitivity to changing climate. Older people are more susceptible to disease and stresses from lack of water or food, and they have reduced mobility so they can’t move away from a hazard such as a flood as easily as younger people. For example, over 40% of deaths caused by Typhoon Haiyan in the Philippines in 2013 were from people over 65 despite being only 8% of the affected population. This doesn’t just affect low and middle income countries: after 2005’s Hurricane Katrina in the USA, 50% of deaths were found to be from people over 75 years of age. The World Health Organisation has suggested that climate change will cause 38,000 extra deaths per year by 2030 (Byrne and Harris, 2015), and in Superstorm Sandy nearly 50% were over 65 years of age. This is partly because of a disproportionate number of elderly people living in hazard prone areas, with 20% of the USA’s aging population living in areas which experienced tropical storms in the last decade (EPA, 2016).

In poorer countries, young people are also highly vulnerable. Malaria already kills more children than adults – over 6% of the 438,000 deaths in 2015 were in children under 5 years old. Children are also more likely to die of food related disease – there were 530,000 children under 5 killed by diarrhoea in 2015. This is partly because youthful populations are more concentrated in areas where flooding and vector-borne diseases (such as malaria, carried by the ‘vector’ of a mosquito) occur. Over 160 million children live in areas of drought. (UNICEF, 2015) This is partly because of the larger number of children living in areas that are exposed to climate change:

  • Population under 18 years of age per sq km (2015). Source: UNICEF, 2015.

The maps below are taken from UNICEF’s 2015 report, “Unless we act now: The impact of climate change on children”. They demonstrate the disproportionate impact of climate change on children.

  • Children living in areas of high or extremely high drought severity. Source: UNICEF, 2015.

  • Children living in flood occurrence zones. Source: UNICEF, 2015.


Women are also disproportionately affected by climate change, with UN estimates suggesting that over 80% of the people forced to leave their homes due to climate change are female – yet only 30% of climate change policy makers are female (Halton, 2018).

The following information is sourced from a UN Development Programme publication ‘Gender and Climate Change’ (Habtezion, 2016). Women are, in general, more vulnerable because:

  • Women earn 24% less than men, so they have less economic coping capacity
  • Women are less well represented in politics with only 22% of seats in parliaments globally, so they have less power to make climate focused decisions
  • Women are often less educated than men, which can affect child mortality too: for every additional year of education on the part of women, child mortality goes down 9.5%


Improved education is likely to reduce the vulnerability of people to climate change for four main reasons (Striessnig, Lutz, and Patt, 2013):

  • More education implies better access to information and therefore early warning systems
  • Better education leads to a willingness to change risky behaviour, and to rely less on personal biases
  • Health tends to improve with education, so people are less sensitive to climate change impacts
  • Education leads to more income, so more coping capacity

Striessnig, Lutz, and Patt (2013) found that improving education could reduce deaths from climate change by 60% a year once indirect impacts are factored in (such as a reduction in the total fertility rate). The graph below shows the impact of education on climate related deaths (red lines show a rapid increase in education, blue lines show a moderate increase) based on work by Lutz, Muttarak and Striessnig in 2014 (McSweeney, 2014).

Lutz Et Al (2014) Fig2

  • Predicted number of disaster deaths (in millions) per decade with rapid expansion of education (SSP1) and limited expansion (SSP3). The graph shows three scenarios of changing extreme events: no change (solid line), a 10 percent increase (dashed line) and a 20 per cent increase (dotted line). Source: McSweeney, 2014.

Risk perception

‘Risk’ is: “the probability of a hazard event event causing harmful consequences (death, injury, loss of property, damage to environment, etc.)” (IBO, 2009). However, the way people perceive risk is very important. People who see their lives as having a high level of risk are likely to do something about it; people who think there is not much risk are likely not to take actions.

The two diagrams below show this in diagram form. They demonstrate how the decision making process works with regard to the perception of risk. Ultimately, the more the person thinks there is a high risk, the more actions they will take.

Image result for model of human perception and response to natural hazards

  • Model of human perception and response to natural hazards. Source: Kates, 1971.

Image result for model of human perception and response to natural hazards

  • The ‘Threshold of Awareness’: Absorption of and adjustment to environmental stress. Source: Kates, 1971.

Van der Linden (2015) assessed the factors that affect the perception of risk due to social and psychological factors. As shown in the diagram below, the factors are wide-ranging and the simple ‘knowledge’ of the risk is only one element of the calculation of risk. This means that even if people know about climate change, this knowledge will only be one part of their decision making. This can help to explain why people consistently vote for governments that implement policies that continue to cause climate change, or policies that will slow climate change but at a very gradual rate compared to the significant change that is required.

In practical terms, the risk from climate change has to compete with worries about other things such as terrorism and the state of the economy. The graph below shows what people worldwide consider to the main risk to their country. Despite climate change affecting billions, Islamic militancy appears to have a higher percentage of people considering it a risk.

  • Global perception of risk from various causes. Source: Poushter and Manevich, 2017.

The map below shows the top perceived risk to the countries surveyed. Central and South America perceive climate change as the top risk. This could be for several reasons, including a focus on the part of governments in these countries to focus their efforts on environmental issues, which might be due to their reliance on agricultural products which will suffer if climate change is severe.

  • Global perception of risk from various causes. Source: Poushter and Manevich, 2017.

An interesting extra question is how the level of risk varies according to political viewpoints. The graph below shows that people who are more right-wing are likely to be more concerned by terrorism, while people who are more left-wing are likely to be concerned by climate change. There are many possible explanations for this, but all are controversial and highly debatable! They include media coverage, distrust of international orgainsations, a growing divide between those who do and don’t trust the scientific consensus, and the economic imperative to make profit. All these can lead to a short-term view of climate change and a belief that the future will find mitigation strategies. It can also lead to a healthy scepticism of information that is presented as fact, but is in fact forecast.

  • Global perception of risk from various causes. Source: Poushter and Manevich, 2017.


Byrne and Harris, 2015. HelpAge Position Paper: Climate change in an ageing world. Via https://reliefweb.int/sites/reliefweb.int/files/resources/COP21_HelpAge_PositionPaper_Final_0.pdf Accessed 12 March 2018.

EPA, 2016. Climate Change And The Health Of Older Adults. https://www.cmu.edu/steinbrenner/EPA%20Factsheets/older-adults-health-climate-change.pdf Accessed 12 March 2018.

Germanwatch, 2018. Climate Risk Index https://germanwatch.org/en/download/20432.pdf via https://germanwatch.org/en/14638 Accessed 12 March 2018.

Halton, 2018. Climate change ‘impacts women more than men’. http://www.bbc.com/news/science-environment-43294221 Accessed 12 March 2018.

Habtezion, 2016. Overview of linkages between gender and climate change. UNDP. http://www.undp.org/content/undp/en/home/librarypage/womens-empowerment/gender-and-climate-change.html

IBO, 2009. Diploma Programme Geography Guide. International Baccalaureate, Cardiff.

Kates, 1971. Via Perception Of Hazards And Extreme Events. http://www.lancaster.ac.uk/staff/gyaccp/hazards/chap4.htm Accessed 13 March 2018.

Maplecroft, 2017. Climate Change Vulnerability Index 2017 via https://reliefweb.int/report/world/climate-change-vulnerability-index-2017 Accessed 12 March 2018.

McSweeney, 2014. Education is “top priority” for climate change adaptation, study shows. https://www.carbonbrief.org/education-is-top-priority-for-climate-change-adaptation-study-shows Accessed 13 March 2018. Based on Lutz, Muttarak and Striessnig, 2014. Universal education is key to enhanced climate adaptation. Science. 28 November 2014. Vol. 346 no. 6213 doi:10.1126/science.1257975

Poushter and Manevich, 2017. Globally, People Point to ISIS and Climate Change as Leading Security Threats. http://www.pewglobal.org/2017/08/01/globally-people-point-to-isis-and-climate-change-as-leading-security-threats/

Striessnig, Lutz, and Patt, 2013. Effects of educational attainment on climate risk vulnerability. Ecology and Society 18(1): 16. https://www.ecologyandsociety.org/vol18/iss1/art16/ Accessed 13 March 2018.

Times of India, 2017. Countries most affected by extreme weather. https://timesofindia.indiatimes.com/world/countries-most-affected-by-extreme-weather/articleshow/61981190.cms Accessed 12 March 2018.

UNICEF (United Nations Children’s Fund), 2015. Unless we act now: The impact of climate change on children. https://www.unicef.org/publications/files/Unless_we_act_now_The_impact_of_climate_change_on_children.pdf Accessed 12 March 2018.

van der Linden, 2015. The social-psychological determinants of climate change risk perceptions: Towards a comprehensive model. Journal of Environmental Psychology, 41, 112–124.. Via van der Linden, 2017. Determinants and Measurement of Climate Change Risk Perception, Worry, and Concern. Accessed at http://climatescience.oxfordre.com/view/10.1093/acrefore/9780190228620.001.0001/acrefore-9780190228620-e-318#acrefore-9780190228620-e-318-bibItem-0237 Accessed 12 March 2018.

Disparities in exposure to climate change: Learning activities


  1. Define the term ‘vulnerability’. [2]
  2. Outline the three factors that contribute to vulnerability. [2+2+2]
  3. What does ‘coping capacity’ refer to? [2]
  4. Describe the global variation in vulnerability due to location. [3]
  5. With reference to examples, suggest reasons why some places are more vulnerable than others. [4]
  6. Outline the general relationship between wealth and vulnerability to climate change. [2]
  7. Explain why this relationship is not linear. (Explain why just because a country has a high level of wealth, it is not necessarily protected from the impacts of climate change.) [4]
  8. Explain why the elderly are especially vulnerable to climate change. [3]
  9. State three factors that make children especially vulnerable to climate change. [3]
  10. Outline and suggest reasons for the relationship between gender and vulnerability. [4]
  11. Describe the variation in deaths from climate change in relation to education. [3]
  12. Explain how greater education levels contribute to fewer climate deaths.
  13. Define ‘risk perception’ in your own words. [2]
  14. What factors contribute to a person’s perception of the risk of climate changes? [5]
  15. Suggest reasons for the apparent link between a person’s ideological viewpoint and their perception of the risk from climate change. [4]
  16. Suggest reasons why this apparent link may not be true in all cases. [4]

Other tasks

Visit http://www.carbonmap.org/# and look at the variety of metrics that can be displayed. Can you draw any links between different aspects? If so, does correlation mean causation, and why?

Going further

The vulnerability to climate change can be seen as a general trend, but more often is seen through specific incidents. Is this a valid approach? Look at the graphs below. Do you think there is a link between countries that experience specific climate related events, versus using only generalised statistics?