Health Development of Asia-Pacific Region

NB: We do not resell your papers. Upon ordering, we do an original paper exclusively for you.

NB: All your data is kept safe from the public.

Table of Contents

Introduction
Region of Focus
Variables of Interest
Hypothesis
Summary of Results
Interpretation of Results
Conclusion
Works Cited

Introduction

The health development of regions occurs over time, depending on a wide range of political, economic, and demographic variables. Asia, in particular, has seen an incredible rise in health-related statistics largely due to economic growth that has affected the region. The health variables discussed in this report are life expectancy and child mortality that are directly correlated with the financial well-being of nations. It is hypothesized that these health variables have improved and will continue to improve with time in relation to economic growth and development of quality of life.

Region of Focus

The region of focus for this report will be Asia and the Pacific. It was selected due to a number of reasons. The region has the highest concentration of the global population of approximately 4.3 billion people. It has also seen an unprecedented level of economic growth with the percentage of the global GDP rising from 30.1% to 42.6% in the last 17 years and 780 million rising out of poverty (Asian Development Bank). The region which has traditionally been known for highly impoverished conditions has seen a rise in a variety of areas such as education, employment, quality of life, and the Human Development Index.

Health variables such as life expectancy and years of healthy life in Asia have been statistically lower than in most of other regions. There are also significant disparities between life expectancy and observed life years, differences among genders, and the overall health performance across the region as some parts of Asia are disproportionally better than others (The Institute for Health Metrics and Evaluation). Therefore, it seemed warranted for further research and introduced a topic which was relevant to the issue of health and wealth.

Variables of Interest

The primary health variable of interest is life expectancy at birth. It is a measure of a number of years that a human is expected to live considering that patterns of mortality and death rates at their birth do not change throughout their life. Life expectancy demonstrates the ability of a country’s health system to prevent, treat and cure illness as well as serving as a reflection of social and environmental factors. Life expectancy is considered to be a fundamental indicator of health and social development in countries and by most international organizations. This variable is advantageous as it is well-defined and widely accepted, being a commonly recorded statistic in all areas of the world allowing for greater data availability (World Health Organization).

The second variable to consider is child mortality. It is a statistic which records the number of children that die under the age of 5 per 1000. Leading up to the 20th century, child deaths were common, even in developed nations. Ever since the 1960s with greater international industrialization and progress in the health sector, child mortality has dropped to 4.3% globally, which is still considered high (Roser). Child mortality is believed to be a byproduct of poverty and lack of access to proper healthcare. Some of the leading contributors to child deaths include birth complications, infant mortality, and basic preventable or treatable diseases such as pneumonia. Some impoverished or developing countries have demonstrated tenfold reductions in this variable over the decades.

Finally, it is important to consider the factor which these health variables will be measured against, and that is income. The average (per capita) income is a measure of the annual salary that an individual would on average earn. However, the method of its calculation is often criticized for failing to consider disparities in income distribution and costs of living. The Gapminder tool offers income as gross domestic product per person in a country adjusted for purchasing power parity (PPP) which is a more accurate measure. PPP offers a more prolific analysis of measuring prosperity in consideration of economic variables in different countries or regions without taking into account distorting exchange rate variations. Income is an important variable since it is directly linked to the quality of life and is an optimal indicator of socioeconomic status which is vital in health research.

Hypothesis

The hypothesis is that the variable of life expectancy will increase with time proportionate to the average income and other indicators of wealth. Likewise, child mortalities should decrease over time in correlation with income and wealth. This hypothesis has been made based on speculation and logical assumptions that improvements in income and prosperity of the region will lead to an improvement in health indicators. It is likely that countries will invest in human capital aspects such as life expectancy and health through infrastructure and healthcare provision. Similar trends have occurred historically and in other regions of the world, thus it is believed that such tendencies would be followed in this instance. One can assume that there will be a set level of disparity among Asian countries that are more industrial such as Australia, China, Japan, and Singapore in comparison to poorer and politically unstable nations. It may also be important to consider cultural and behavior trends that are independent of economic indicators that may nevertheless impact health trends.

Summary of Results

The link above shows the growth of life expectancy in relation to income levels in the Asia and Pacific region leading up to 2018. The data shows that for the larger part of the 20th century, the majority of Asian countries were clustered in an area of life expectancy of 30-50 years, with some outliers such as Japan, Australia, and New Zealand which were traditionally more prosperous and had longer living populations. Toward the end of the 20th century and leading up to modern day, the region began demonstrating an upward curve as more countries were beginning to experience higher incomes and longer life expectancies as well. However, some poorer countries such as Afghanistan, North Korea, and Papua New Guinea did demonstrate mild levels of income growth whilst still improving life expectancy significantly. Nevertheless, the larger populous and industrialized nations such as India and China demonstrated significant growth. The image from the Gapminder simulation below highlights that there is an upward positive correlation curve between income and life expectancy with very few outliers going against the consistency of this trend.

The link above demonstrates the time flow of data demonstrating how child deaths have shifted over time in comparison to income. The shift is not as drastic for the whole region as with the life expectancy indicator, but it is important to consider the latter part of the 20th century and going into the 21st century. Some of Asia’s most populous countries such as China, India, and in less extreme forms, Pakistan, Indonesia, Iran, and Bangladesh all showed high rates of child mortality. At some point in the mid-20th century, both China and India demonstrated over 6 million child deaths. However, by 2015, as incomes have increased, the child mortality rates have decreased dramatically to be on par with much smaller Asian countries. Nonetheless, India still maintains the highest number of 1.2 million child deaths.

Interpretation of Results

Regarding the life expectancy simulation, it is not surprising to see such results. Various scholarly researches through the years demonstrate that individuals with higher income are able to live longer, with higher incomes living on average almost a decade older than those in poverty. The trend is seen in the model where Japan and Australia exceeded poor countries such as Afghanistan by almost 20 years. The Asia and Pacific region is one of the prime demographic examples of such straight correlation and almost linear growth due to rapid development in the last few decades. Life expectancy directly depends on income due to standards of living and access to proper healthcare services. Although more complex factors such as income mobility and cultural or environmental influences may come into play, the general tendency remains the same.

The data on child mortality also largely confirms the statistical trends and academic research on the topic. A meta-analysis of studies in developing countries calculated that an increase of 10% in the PPP of GDP per capita can lead to a decline of about 5 deaths per 1000 live births (O’Hare et al. 413). Child mortality identifies the health status of a country very well. The inverse relationship demonstrates how socioeconomic determinants of health in relation to income can be improved. This is the reason why China and India with tremendous problems of child mortality have achieved considerable success after industrialization, but still continue to struggle in rural areas where the availability of healthcare coverage, interventions, and female education, all of which play a significant role, are limited.

As stated earlier, Asia has experienced unprecedented economic growth and development in recent decades, lifting the region from extreme poverty to one of the most prosperous in the world. Recent reports confirm that most populations in Asia are living longer and healthier lives due to advancements in healthcare coverage and the availability of highly qualified care. Economic development has led to people being raised out of poverty by the millions, resulting in greater literacy (including health-related), fewer conflicts or disasters, and a focused transition on standards of living (water and food quality) and disease prevention among others (Cebula and Cherrie). Although, it should be considered that human life and medicine do have limits, and it is natural for life expectancy gains to slow even if incomes continue to rise. This is reflective of global and regional trends at all ages and survival rates. The disparities may continue due to epidemiological transitions but eventually will be addressed throughout the region through the diffusion of innovation that had previously been available only to high-income countries (Hum et al. 1).

Conclusion

It is evident that these health variables are both an indicator and an outcome of the economic development of a region. The aspects are deeply intertwined and can be seen as relevant to the investigation of a health assessment of Asia over time. The hypothesis that health variables improve over time in relation to economic growth was proven correct and has been shown to be supported by empirical and historical data.

Works Cited

Asian Development Bank. Key Indicators for Asia and the Pacific 2018 49th Edition. 2018, Web.

Cebula, Pawel, and Andrew Cherrie. “Most People in Asia Now Living Longer, Healthier Lives.”BrinkAsia. 2017, Web.

Hum, Ryan J., et al. “Are Global and Regional Improvements in Life Expectancy and in Child, Adult and Senior Survival Slowing?” PloS One, vol. 10, no. 5, 2015, pp. 1-14.

O’Hare, Bernadette, et al. “Income and Child Mortality In Developing Countries: A Systematic Review and Meta-Analysis.” Journal of the Royal Society of Medicine, vol. 106, no. 10, 2013, pp. 408-414.

Roser, Max. “Child Mortality.” Our World In Data, 2019, ourworldindata.org/child-mortality

The Institute for Health Metrics and Evaluation. Global Trends in Healthy Life Expectancy and Early Death and Disability. 2017, Web.

World Health Organization.An Overarching Health Indicator for the Post-2015 Development Agenda. 2014, Web.

Click Here To Order Now!