Introduction
Notably, the rise of life expectancy at
the end of the 20th century results in a myriad of economic consequences
worldwide that led to many of the scholars indicating a positive correlation
between economic growth and life expectancy (Szreter, 1997). To support the
literature, Aghion et al. (2010) created a theoretical model premised at
indicating growth of most economies is dependent on the level and growth rate
of life expectancy. Subsequently, the link between health and economic growth
is explained in the human capital theory. The theory predicts that higher life
expectancy is salient in promoting earning skills and improves the performance
of labour (Oster et al., 2013). In contrast, for the longest time, the
processes of rapid economic growth appear to be well entrenched with the
enhancements in the prosperity and health within the communities. In other
words, it pinpoints that economic growth is a prerequisite for development. The
impact of economic growth on life expectancy is deduced by income inequality.
According to Wilkinson and
Pickett (2006) cited in Dorling (2014), a higher level of income
inequality is detrimental to the health sector. The unprecedented inequality is
evident in the contemporary world and it unravels unjustly. In particular
high-income inequality curtails the freedom of individuals on the lower end of
the pyramid. Fundamentally, healthy individuals can purchase better medical
care, foodstuff and justice while the under-privileged are struggling to get
basic needs much less unalienated lives. Elongated life expectancy is linked
with investment in public expenditure on health care and successfully reduction
of the income inequalities. Therefore, income inequalities form the basis of
health inequalities. By definition health inequalities “is the difference of
the care that people receive and the opportunity they have to lead healthy
lives, both of which can contribute to their health status” (world health
organization, 2018). This essay argues that economic growth produces critical
challenges and threats to the health and the general welfare of the individuals
in the community, thus vital in addressing life expectancy.
Health programs
A fundamental health program is a salient
determinant of life expectancy. According to Kabir (2008), there is a positive
relationship between primary health care expenditure and general health status.
On the same depth, research conducted by World Bank (2004) shows a positive
correlation between life expectancy and per capita income for the upcoming
economies countries. Many of the developing countries have low national income
hence forced to spend low on public expenditure on health. Based upon the
European empirics, an increment in the health input results in an increase in
the health outcomes that are vital in shaping life expectancy (Wilkinson, 2008).
However, once the threshold level of the per capita income, the correlation
between life expectancy and social well-being becomes insignificant. In other
words, a further rise in income is disintegrated to life expectancy gains.
Furthermore, though there is a direct correlation between health and income of
individuals at the threshold level, they are lack consistency. In the case of
Canada, Cemieux's research found out that lower health expenditure is related
to low life expectancy and also an increase in the infant mortality rate
(Cemieux et al 1999). In the same measures, urbanization seems to be a core
indicator of life expectancy for both emerged and developing economies. Since
there is a tendency for high economic growth in the urban areas, the public
health spending is higher eventually making the population in the urban areas
have better medical care. Also, urban areas are enjoying improved
socio-economic infrastructure, central to the health system. Based on the empirical data from Africa and
Asia, study outcomes indicate areas, mostly urban areas where they are easy
accessibility of safe drinking water, life expectancy is higher and lower in
areas with scarce safe water for drinking.
Improvement of health
sector and economic development
There
is growing consensus that improving the health sector can indirectly relate to
the improvement in economical development. For instance, the fight against
malaria in the sub-African Sahara has balloon the per capita growth rate by at
least 20% annually (Gallup et al 2000). Marital
mortality is vital in the health inequality. Its health indicators reveal wide
gaps between the rich and under-privileged people in the societies. Emerging
economies nations contribute to 99% of the early childhood and maternal deaths
across the globe. In comparative study, women in Chad have a risk of maternity
death at that ratio of 1:16 while women in Sweden have ration of 1:10,000.
According to study be WHO (2018) “in today’s world, poor health has
particularly pernicious effects on economic development in sub-Saharan Africa,
South Asia, and pockets of high disease and intense poverty elsewhere” (p. 24)
and “...extending the coverage of crucial health services... to the world’s
poor could save millions of lives each year, reduce poverty, spur economic development
and promote global security” (p. i)[1].
Although
the evidence supporting this range may not be conclusive, they are numerous
macro studies that indicate dealing with diseases has collaboration with
increased economic growth. Arguably, life expectancy is amongst the core
factors that measure population health conditions and rate of the economic
growth. A holistic view of the world indicates that developed countries have
higher life expectancy compared to developing countries. In effect, it is indicated by the country
fixed effects. Therefore, countries with greater declines in mortality which
results in a higher life expectancy have a slight decrease in the GDP per
capita (Acemoglu et al 2007). With improved health sector, where there is experience
of improved infrastructure most of the people tend to be productive and
participate in the economic activities. For instance, there has been an
increase in income level and positive changes in life expectancy in Bangladesh
(Ahmed et al 2020). Though there is not
a conclusive analogy on the difference in life expectancy, some of the reasons
include but are not limited to an increase in the labor force, an increase of
spending on public health and an increase in the elementary school enrolment
rate. In a nutshell, healthy people will tend to increase their income level by
being more productive, physically more energetic and being more mentally. Also,
the aspect of increasing economic development is through savings as people are
living long life they have a tendency of investing more compared to those with
short lifespan. For instance, a 10-year rise in longevity is shown as the rise
in 4.5% in savings (Bloom et al 2008).
Finally, with a reduced level of mortality hence an increase in life
expectancy, there is an increase in the education level. Fundamentally, healthy
people prefer to invest more in the approaches to improve their skills to
improve their earnings than those who are not healthy. Furthermore, healthier
children can attend schools and participate more in learning and have higher
cognition than non-healthier one.
Unequal
societies
Poor
health that is connected with low social status is prevalent in unequal
societies. In other words, it can be supported by the high homicide and
mortality rates. Countries which are having high and increasing income
inequalities do not experience a similar rate in life expectancy (Dorling 2015).
These countries eventually record lower rankings when the international ranking
comparisons are created. For instance, due to adverse 2008 economic meltdown,
some nations such as Iceland have experienced economic shock that led to
unprecedented unemployment rates. Therefore, the unprecedented event has
revealed how the high rates of economic inequalities have a severely damaging
impact on society and in the long run on life expectancy. Contrary, to the situation in Iceland, in
Denmark the income inequalities are very low and this will bridge the gap of
wealth inequalities which in return will impact positively on the health
inequalities (Pickett et al 2015). With
a more equitable income, many people can have healthier behavior and a better
plan for society is extensive. Thus, the existence of large structural
mortality is a prerequisite to the reduction of the mortality rate. With Denmark becoming more income equitable,
many of its citizens are not falling victim to health inequalities (Nowatzki,
2012). Notably, the mortality rate reacts faster to social change than the
reaction of the overall life expectancy (Bluehler et al 2012). According to
Pickett and Wilkinson (2015), although some of the studies have indicated the
existence of the relationship between economic inequality and poor health, few
of the studies have failed. Therefore, this study is best indicated using the
geographical area of study; like in the case of Denmark, in comparing the
inequalities within the states in the USA, health is worse in the most unequal
parts of the city in comparison to more equal wards. The use of the hypothesis is vital since it
advocates for a correct prediction since uses the available data to rank the
performance of various countries based on inequalities. The inequalities hypothesis dreams for its
predictions to be proved correct and help in the ranking of countries in case
they are a fall or rise in inequalities.
In a nutshell, greater economic equality help in the elevation of the
social capital vital for a better managed and run healthy service.
McKeon theoretical
explanation
Life
expectancy is an important measure of the individual’s health status and it is
closely related to their socio-economic situations. For instance, in the UK,
there is a systematic relationship between deprivation and life expectancy.
Also known as social gradient in the health realm, it indicates that men
residing in the least deprived areas as from the birth time are expected to
increase their lives by at least 9 years (Williams et al 2020). The
inequalities are not constant and they tend to increase from time to time.
According to McKeon on the theoretical explanation, the population growth rate
in the 1770 period was attributed to the decline in the mortality rate that was
mainly from infectious diseases (Cogrove 2002 & Mckeown et al 1962). On the other hand, the decline was attributed
to the improved economic conditions connected to the industrial revolution that
forms the ground for the rising living standards. The concept improved the
nutritional conditions and boosted the resistance to diseases in effects
increasing life expectancy. Fast forward, the gap in life expectancy in Britain
is increasing. Between 2012-14 and 2015-17, the gap has risen by 0.3 yrs for
men and 0.5 yrs for ladies (Williams et al 2020). In the same regard, the life
expectancy for females in the most deprived areas has reduced to close to 100
days during that research period. The life expectancy at birth is heavily
affected by the mortality rate. With most of the countries improving their
health system, improving economic activities and raise in the standard of
living, there is a decline in the mortality rate.
Social determinant
Doctor’s
action in social determinant indicates that poor people have poor health, a key
factor to curtail life expectancy. The
social gradient initiative in England implies that action to improve health and
minimize inequalities has to occur at the social level and is not relatable to
individual adjustments (Marmot 2017). In the classification of people in
degrees of affluence and deprivation, poor health also varies depending on the
position. It illustrates that health inequalities vary from one country to
another. Precisely, the country with people with a university education has
smaller differences in life expectancy than the country with little university
education (Marmot 2013). It is since
most of the university graduates tend to get quality jobs with decent salaries,
enabler to the improvement of the standard of living. Therefore, the following
are the action on social determinants of general health. To begin with, children should be given the
best start in life. Since there is a correlation between life expectancy and
economic growth, well-off families will tend to provide their children with the
best medical care that will impede them from falling sick to many diseases.
Secondly, is the aspect of education where university education imparts the
learners with the uttermost skills prerequisite to get a good-paying job. Thus,
the subject should be in a position to improve their lifestyle and provide for
them better medical care (WHO, 2008). It is the reason that the mortality rate
in an advanced economy is insignificant while in the developing countries the
rate is still at unprecedented levels. Thirdly, there should be the provision
of the minimum wage. Minimum wage helps in mitigating the problem of income
inequalities that leads to health inequalities. When there is a huge gap
between the top and lower earners, it creates inequitable societies. Eventually, it forms the basis of the
creation of unequal wards within cities (Siegrist et al 2009). Finally,
economic prosperity leads to healthy living and good working conditions. With
financial power, an individual can spend on a good place to live that ensures
his or her good health is central to life expectancy. Therefore, social
determinists indicate the significant factors that should be encouraged and
practiced by everyone in society.
Conclusion
In a nutshell, income inequalities play a
vital role in health inequalities. Most
of the developing countries with a sizable economic and are unable to invest
heavly in the health sector leading to a weak and obsolete system to cope with
the ever-changing dynamic of diseases and other health complications.
Therefore, health inequalities lead to the fall of life expectancy. Life
expectancy cannot be directly being linked with economic activities but to some
extent, it has indicated a strong correlation.
One of the key aspects that determine life expectancy is the primary
health program. The aspects are linked with the expenditure on the system and
how effective it will tend to be hence poor health correlates with inequitable
societies. The inequalities in income as the result of factors such as the high
rate of unemployment makes some areas develop negative behaviors that are
impeder for an elongated life expectancy.
Society in effect is marred with a high mortality rate that reduces the
life expectancy at birth. The variables are well decided using the European and
developing countries metric that indicates how industrialization is integral
for the well-being of the health sector.
In a nutshell, the patterns and
trend of economic development may not be well entrenched in explaining life
expectancy, but the use of MCkewon's theoretical explanation aid in exposition
how industrialization led to the decline in the mortality rate and increase in
the population. In a nutshell, the social determinates of life in one way or
another will impact positively an individual life. They include but are not
limited to granting children the best start of life, provision of quality
education to improve skills, provision of quality education and creation of the
minim income to reduce the aspect of income inequalities.
[1] World health organization (2014)
references
Aghion, P., Howitt, P. and Murtin, F.,
2010. The relationship between health and growth: when Lucas meets
Nelson-Phelps (No. w15813). National Bureau of Economic Research.
Ahmed, S.A.S., Ajisola, M., Azeem, K.,
Bakibinga, P., Chen, Y.F., Choudhury, N.N., Fayehun, O., Griffiths, F., Harris,
B., Kibe, P. and Lilford, R.J., 2020. Impact of the societal response to
COVID-19 on access to healthcare for non-COVID-19 health issues in slum
communities of Bangladesh, Kenya, Nigeria and Pakistan: results of pre-COVID
and COVID-19 lockdown stakeholder engagements. BMJ global health, 5(8),
p.e003042.
Acemoglu, D., & Johnson, S. (2007). Disease
and development: the effect of life expectancy on economic growth. Journal
of political Economy, 115(6), 925-985.
Bloom, D.E. and Canning, D., 2008. Population
health and economic growth. Health and growth, 53.
Crémieux, P.Y., Ouellette, P. and Pilon, C.,
1999. Health care spending as determinants of health outcomes. Health
economics, 8(7), pp.627-639.
Colgrove, J., 2002. The McKeown thesis: a
historical controversy and its enduring influence. American journal of
public health, 92(5), pp.725-729.
Dorling, D., 2015. The mother of underlying
causes–Economic ranking and health inequality. Social Science &
Medicine, 128, pp.327-330.
Gallup, J.L. and Sachs, J.D., 2000. The
economic burden of malaria.
Kabir, M., 2008. Determinants of life
expectancy in developing countries. The journal of Developing areas,
pp.185-204.
Mahyar, H., 2016. Economic growth and life
expectancy: The case of Iran. Studies in Business and Economics, 11(1),
pp.80-87.
Marmot, M., 2013. Health inequalities
in the EU. Final report of a consortium. European Commission Directorate-General
for Health and Consumers.
Marmot, M., 2017. The health gap: doctors and
the social determinants of health. Scandinavian Journal of Public
Health, 45(7), pp.686-693.
McKeown, T. and Record, R.G., 1962. Reasons for
the decline of mortality in England and Wales during the nineteenth
century. Population studies, 16(2), pp.94-122.
Nowatzki, N.R., 2012. Wealth inequality and
health: a political economy perspective. International Journal of
Health Services, 42(3), pp.403-424.
Oster, E., Shoulson, I., & Dorsey, E.
(2013). Limited life expectancy, human capital and health investments. American
Economic Review, 103(5), 1977-2002.
Pickett, K.E. and Wilkinson, R.G., 2015. Income
inequality and health: a causal review. Social science & medicine, 128,
pp.316-326.
Siegrist, J., Benach, J., McKnight, A.,
Goldblatt, P. and Muntaner, C., 2009. Employment arrangements, work conditions
and health inequalities. Report on new evidence on health inequality
reduction, produced by Task group, 2.
Szreter, S., 1997. Economic growth, disruption,
deprivation, disease, and death: on the importance of the politics of public
health for development. Population and development review,
pp.693-728.
WHO Commission on Social Determinants of Health
and World Health Organization, 2008. Closing the gap in a generation:
health equity through action on the social determinants of health: Commission
on Social Determinants of Health final report. World Health Organization.
World Health Organization, 2004. Fifty Years of
the World Health Organization in the Western Pacific Region. Report of
the Regional Director to the Regional Committee for the Western Pacific.
World Health Organization, 2018. World
health statistics 2018: monitoring health for the SDGs, sustainable development
goals. World Health Organization.
World Bank, 1997. World development report 1997: T
