role of income per capita in the determination of mortality rates

role of income per capita in the determination of mortality rates

Introduction

The differences in health statuses among individuals and population groups cause a persistence challenge to all the concerned practitioners. The efforts towards improving health and overall well-being of populations always face continuous derailing in terms of the causes responsible for such major variations. Finding a reliable solution to raise the general level of health in societies is critical. The most common causes of the differences are genetic and environmental factors. Since the environment is viable to metamorphosis, most researchers focus on significant factors such as disease prevalence, income, standards of education, income, occupation, and other factors dependent on modification. Most of the studies have indicated strongly that the variations in infant mortality are directly to prevailing economic conditions of a society. The level of socioeconomic standards further determine other minor factors such as hygiene and nutrition, which in turn affect the rates of infant mortality.

The extent to which income per capita affects the economic conditions of nations is closely attached to health standards. For this reason, most surveys on the topic focus on Gross Domestic Product as a major determinant to health outcomes. As a result, wealthier nations emerge as healthier places proving that economic growth is reflected by health gains. The simple explanation is that the positive effect on health standards arises from the capability of the population to invest in the health of their family. The focus of this study shall, therefore, be to highlight the role of income per capita in the determination of mortality rates. Specifically, it argues that a rise in income per capita leads to reduction in mortality rates around the world.

Background

The health of countries has been dependent on a range of factors across the spectrum. Country-specific factors, including literacy rates, nutrition, and availability of healthcare services, have driven the mortality rates of the countries. There are also homogeneous factors, which contribute to the overall health of a country’s residents. According to Lynn and Yadav (2015), medical technology is responsible for critical changes specific to a country. Considering the early twentieth century, there have been considerable changes among such exogenous factors. Over the years, the use of income per capita to explain health outcomes has diminished due to rapid changes in globalization. Higher standards of technology diffusion is a result of globalization. The role of income per capita may not be relevant as more countries adopt the latest technological advancements.

Geographical locations of countries have also been a significant factor in the determination of the relationship between income and health. For example, nations located in topics such as the Sub-Saharan African countries are vulnerable to certain diseases such as malaria, which is responsible for the highest number of deaths in the region. Other diseases such ebola cause serious damage to the economies of the countries.

Theories of Economic Growth

There are varying models, which explain economic growth, such as the mercantilism, classical, neo-classical, endogenous, and Keynesian demand-side alternatives. The mercantilism is the oldest and was popular during the industrial revolution. According to O’Hare, Makuta, Chiwaula, and Bar-Zeev (2013), it is not entirely a theory of economic growth but focused on the accumulation of gold and increase of exports as a means of achieving prosperity in a country.

A more elaborate theory emerged towards the end of the eighteenth century, which argued that several factors determined economic growth. They included, but not limited to the role of markets, the productivity of labor, role of trade, and the increase of scale. This original version was advanced later in the twentieth century to include technology changes.

The most popular and debated theory was the neo-classical model which suggested that increased capital and labor led to diminishing returns. The authors argued that increased capital only brought temporal changes, which were not entirely effective in economic growth. Most importantly, it acknowledges the role of technology changes towards productivity and labor. Critics of this theory note that it fails to explain why countries have different levels of investment. Moreover, it does not explain how to improve the rates of technological advancements.

Child Mortality

Child mortality has been used for a long time as a measure of health status in countries. Emerging economies, especially in Sub-Saharan countries, are the most prevalent to child mortality. However, the current progress over the past decade has seen an estimated 2.5 million decrease in the mortality rates (Bishai, Cohen, Alfonso, Adam, Kuruvilla & Schweitzer, 2016). Reeves, Gourtsoyannis, Basu, McCoy, McKee, and Stuckler (2015) found that the poor countries of Sub-Saharan Africa carry the heaviest burden of Child deaths in the world. The study also showed that South Asia has the closest rates in the poorest regions. The authors concluded that higher-income countries had higher life expectancy as opposed to poorer with lower living standards. The wealth in industrialized countries correlated with better health outcomes. The extent to which the impact is experienced in different regions and the influence on other underlying socioeconomic factors such as wealth distribution determine the overall child mortality.

There are several consequences related to mortality rates in low and middle-income countries. The global health community has intensified efforts towards universal health coverage to all humanity. However, persistent challenges unique to specific regions have hampered such efforts. The World Health Organization, for example, is committed to supporting expanding services and provision of financial-risk protection to help optimize global health standards. According to Reeves et al., (2015), the current forms of strategies have not been sufficient towards addressing the challenges of health consequences. Establishing modern health systems capable of integrating complex and multi-disciplinary issues related to quality of healthcare will help improve healthcare and reduce child mortality rates.

Role of Economic Conditions on Mortality

Developed countries have experienced considerable increases in life expectancy over the past 50 years. O’Hare et al., (2013) noted that since the end of the World War, the female record life expectancy rose in both North America and European countries as well as Australia and Japan. Japan holds the longest record for life expectancy at over 86 years for women and approximately 80 years for the men. Spain, on the other hand, registered the fastest increase in life expectancy in the period beginning 1950 and ending 2009. The mortality patterns in Eastern Europe have been irregular over the past five decades because the reason was destabilized by frequent wars and stagnation in the economy. These changes prove the impact of income per capita to the rate of mortality in developed countries.

Both individual and structural issues contribute fundamentally to mortality. Apart from income from occupation, other individual factors include socioeconomic characteristics such as age, gender, and literacy. Lifestyle choices ranging from physical exercises to diet or smoking also contribute to individual factors. Structural factors, on the other hand, include the standards of living, accessibility to education and standards of healthcare services. They also include employment and the general distribution of income and wealth. All these factors contribute to mortality rates cooperatively hence difficult to distinguish and measure them separately.

There is an inverse proportionality between mortality and income. According to Guimarães, Rocha, Muzi, and Ramos, (2013), higher income per capita led people to spend more money on health products hence improving their overall health. For example, increased investment in health goods and services alongside proper housing, food, and leisure help to expose more people to better healthy living. The higher income also triggered higher life expectancy in the study, which focused on 236 countries. The economic growth of nations was, therefore, directly transforming the healthy standards of the citizens. Guimarães et al., (2013) further found out that the progress in life expectancy was aligned to access to vaccines and antibiotics, especially in the period preceding the Second World War.

Conclusion

The focus of this study was to highlight the role of income per capita in the decrease of mortality. It has observed the historical evidence from earlier studies, which relied on data on income per capita to accurately predict the rates of mortality in different regions. It has further found that the latest advancement in medical technology has overshadowed the role of income per capita. Nevertheless, it remains one of the most accurate and reliable determinants of mortality rates. It concludes that income per capita plays a key role in the determination of morality. A rise in income leads to an inverse reaction in the mortality rates in the respective countries. Although other contributing factors exit, the measure of income per capita remains important to the determination of mortality rates around the globe.

References

Lynn, R., & Yadav, P. (2015). Differences in cognitive ability, per capita income, infant mortality, fertility and latitude across the states of India. Intelligence, 49, 179-185

O’Hare, B., Makuta, I., Chiwaula, L., & Bar-Zeev, N. (2013). Income and child mortality in developing countries: a systematic review and meta-analysis. Journal of the Royal Society of Medicine, 106(10), 408-414

Guimarães, R. M., Rocha, P. G. M., Muzi, C. D., & Ramos, R. D. S. (2013). Increase income and mortality of colorectal cancer in Brazil, 2001-2009. Arquivos de gastroenterology, 50(1), 64-69

Bishai, D. M., Cohen, R., Alfonso, Y. N., Adam, T., Kuruvilla, S., & Schweitzer, J. (2016). Factors contributing to maternal and child mortality reductions in 146 low-and middle-income countries between 1990 and 2010. PLoS One, 11(1), e0144908

Reeves, A., Gourtsoyannis, Y., Basu, S., McCoy, D., McKee, M., & Stuckler, D. (2015). Financing universal health coverage—effects of alternative tax structures on public health systems: cross-national modelling in 89 low-income and middle-income countries. The Lancet, 386(9990), 274-280.

Nelson, K., & Fritzell, J. (2014). Welfare states and population health: the role of minimum income benefits for mortality. Social Science & Medicine, 112, 63-71.