Ageing of industrialised countries is changing the demographic structure of modern societies, and has a significant effect on all aspects of society. The US Census Bureau (www.census.gov/), for example, predicts that by 2020 the number of people over the age 100 will increase by more than 200% from 71,000 to 241,000 in the next 15 years. The sustainable development paradigm was formalised by the Brundtland report in 1987 (Brundtland, 1987). This paradigm requires a development that ensures that future generations are left with the same or better possibilities for their own development. In order to meet this sustainability challenge, a balanced development of economy, environment and social system a required (Sitarz, 1993). The indicators of sustainable development measure the success of the sustainability challenge. These indicators measure economic, societal, environmental, and institutional development. They are usually grouped according to the pressure-state-response model. The goal is to assess the current state of development as accurately as possible, take into account the pressures on economic, environmental and social systems, and help decision makers in creating effective and efficient response to these pressures, so that the state of economy, environment and society improves over time. This is difficult, however, because society is a very complex system with a non-linear dynamic. The most broadly used system of environmental sustainability indicators is the the Environmental Sustainability Index — ESI (Esty et al., 2005). The climate system alone, for example, is extremely sensitive, and even single effects can have significant economic consequences, such as the 1815 Tambora volcano eruption in Indonesia, which decreased the amount of sunlight and therefore caused famine in a large part of Europe in 1815. This became known as the year without summer (see, for example, www.volcanolive.com/tambora.html).
In addition to indicators of sustainable development there are many indices which have been designed to measure the quality of life. GDP is one of the oldest and most broadly measured indices, which is useful to compare the economic development of different countries. however, it has some important disadvantages, so that an increase in GDP is not always directly related to the quality of life. Many other indices for measurement of the quality of life have been designed, among which the Human Development Index by UNDP is the most well known. In this work we are also taking into account subjective assessments of the quality of life such as measures of happiness and life satisfaction (Veenhoven, 1996, 2002, and 2004). It has been shown that measures of happiness and life satisfaction are positively correlated with the Environmental Sustainability Index and its components (Zidanšek, 2003 and 2005).
2. Subjective measurement of quality of life
It has been demonstrated by many authors that the subjective quality of life is positively correlated with many aspects of development. Inglehart and Klingemann (2000) demonstrated for example that happiness is related to culture, Ott (2000) showed that happiness is related to freedom, while Schyns (2002) showed that life satisfaction is also related to wealth. Kirkcaldy et al. (2004) showed that education is also related to happiness. Since all these issues are interrelated, it is reasonable to expect a very complex network of interactions, so that, for example, improved education increases wealth, which in turn increases life satisfaction. extracting the influence of each individual parameter on happiness and life satisfaction is therefore very difficult. It is however possible to determine which parameters are optional and which are absolutely necessary. According to Diener and Seligman (2002), the only determinant which is necessary for happiness are good social relations. All other factors are optional.
Seligman (1991) described a practical method to learn optimism. He claims that optimism improves success in most professions. Professional success of course depends on many factors, which are positively correlated with happiness and life satisfaction. It would therefore be reasonable to expect that improved optimism could also enhance individual happiness and life satisfaction.
Inequality Adjusted Life Satisfaction (IALS) is measured as a linear combination of the mean and the standard deviation of the distribution of life satisfaction in a nation as (Veenhoven, 2004):
IALS = 9.60 (m – 0.414 s) + 4.1
Here m stands for the average value of life satisfaction from the survey and s is the standard deviation of m. Individuals were asked to rate their happiness on a scale from 0 to 10, where 10 corresponds to maximum happiness and 0 to lowest happiness (Veenhoven, 2004).
Aleksander Zidanšek: J. Stefan Institute, Jamova 39, 1000 Ljubljana, Slovenia, email@example.com.
1 Brundtland, G. H. et al. (1987): Our Common Future, World Commission on Environment and Development, Oxford University Press, Oxford.
Tags: ageing, quality of life, sustainable development