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FREE ESSAY ON LIFE EXPECTANCY

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Haiti Life Expectancy
A table on the life expectancy and mortality rate for people in Haiti. -- 4,500 words;

Life Expectancy And Technology
A look at the social effects of prolonging life. -- 525 words;

Birth Rates, Death Rates and Life Expectancy
A look at the use of demographic indicators in determining the status of the world's human population. -- 1,250 words; APA

End-of-Life Decision-Making
A review of Kerry Bowman's "Communication, Negotiation, and Mediation: Dealing with Conflict in End-of-Life Decisions". -- 1,750 words; APA

Families' Experiences and Life-Support Withdrawal
An examination of families' experiences when deciding to remove life-sustaining interventions in the intensive care unit (ICU). -- 3,164 words; APA

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LIFE EXPECTANCY

The environmentalist view of the energy intensity is based on the legacy of the I = P?A?T
equation in which environmental Impact equals Population, multiplied by Affluence, and
further multiplied by Technology (Earth Report 2000: Revisiting the True State of the
Planet. 1999). The further desegregation of this formula implies that energy intensity
can be looked upon as an integrative variable describing the impact of both technology
and affluence. 
Bruce et al. (1996) argue that intensity is inversely related to efficiency. Improving
efficiency reduces the amount of energy required to provide a given output, i.e. an
output of the same quality and quantity. In real life, though, the precise nature of the
output is unknown, hence intensity is a proxy for efficiency. The Kaya Identity is an
expression that is introduced by Bruce et al. (1996) to describe the relationship among
the factors that influence trends in energy-related carbon emissions: C = (C / E) ? (E /
GDP) ? (GDP / POP) ? POP. The formula links total energy-related carbon emissions (C) to
energy (E), the level of economic activity as measured by Gross Domestic Product (GDP),
and population size (POP). The first two components on the right-hand side represent the
carbon intensity of energy supply (C/E) and the energy intensity of economic activity
(E/GDP). Economic growth is viewed from the perspective of changes in output per capita
(GDP/POP). At any point in time, the level of energy-related carbon emissions can be seen
as the product of the four Kaya Identity components - energy intensity, carbon intensity,
output per capita, and population size.
In fact, growth in energy intensity in industrialized countries has historically lagged
behind economic growth, whereas the two are more closely correlated in developing
countries. As a country's energy intensity changes, so does the influence of a given
level of economic activity on carbon emissions. Increased energy use and economic growth
generally occur together, although the degree to which they are linked varies across
regions and stages of economic development (Mies 2000). 
In CCEE, the energy situation is characterized - when compared with CWE - by very high
energy and electricity intensities. According to Urge-Vorsatz and Szeszler (1999), this
situation can be attributed to three main elements: 
a) The largest part of the GDP is due to industrial production, with an emphasis on heavy
industries (iron and steel, chemicals, machinery) which are big energy consumers.
b) The very low level of energy efficiency of end-use devices, equipment and appliances
is aggravated by the lack of maintenance and the obsolescence of the equipment. 
c) The economic crisis which the CCEE countries have been enduring since 1989-1990: a
deep slow down in industrial production, a lack of investment in the energy sector, the
non-payment of energy by the consumers, in particular in the energy sector itself. 
Alongside with the energy efficiency gap between CCEE and CWE, the life expectancy gap
exists. Hertzman et al. (1996) show diverging trends in life expectancy becaming evident
in the mid-1970s, and the gap continued to widen in the 1980s for all major causes of
death, particularly cardiovascular diseases. The situation is worse in the Newly
Independent States than in the CCEE, and worst in the Central Asian countries (Nanda et
al. 1993). There is no single reason for the health gap - Walberg (1998) points out - but
contributory factors include the increasing prevalence of major risk factors in the
quality of environment. 

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