An Analysis of Life Expectancy Factors Across Nations in 2024
Kavita Roy1, Khritish Swargiary2
Email: Kavitaroy811@gmail.com, Khritish@teachers.org
Abstract
This research study aimed to explore the intricate relationship among various factors including life expectancy, birth and death rates, infant mortality, economic growth, and universal healthcare provision. Utilizing a combination of quantitative analysis and comprehensive review analysis, data from reputable sources such as the World Bank, the United Nations, and the World Health Organization were gathered, encompassing crucial variables like life expectancy at birth and healthy life expectancy (HALE) at birth. The research procedure followed a systematic approach encompassing data collection, analysis, and interpretation, employing quantitative techniques to discern trends, correlations, and patterns within the data. Concurrently, an exhaustive review analysis was undertaken to synthesize existing literature from scholarly articles, reports, and publications related to the subject matter. Integrating both quantitative data analysis and review analysis enabled a thorough exploration of the interrelationships among the variables under scrutiny, offering valuable insights into population health outcomes and economic development dynamics. By triangulating findings from these complementary approaches, the study aimed to provide evidence-based guidance for policymaking and intervention strategies aimed at enhancing global health and well-being. The subsequent research analyses provided comprehensive insights into key aspects of global health and economics, emphasizing the diverse economic profiles within high-income countries, the widespread acceptance and adoption of universal health coverage principles worldwide, significant variations in infant mortality rates across countries, and pronounced disparities in life expectancy reflective of divergent healthcare accessibility and socio-economic circumstances. Together, these research studies contribute to a holistic understanding of the complex interdependencies between economics, healthcare, and societal well-being, providing valuable insights for shaping policies and interventions on a global scale.
Introduction
Life expectancy, a pivotal metric crucial for research and policy formulation, represents the average number of years an individual within a specific population group can expect to live. However, delving into this seemingly straightforward concept reveals complexities, notably in distinguishing between cohort and period life expectancy. Cohort life expectancy pertains to the average lifespan of a group born in a particular year, calculated by determining the average age at death among its members. Yet, as mortality data for an entire cohort is only ascertainable when all its members have passed away, statisticians often resort to projecting future mortality rates based on historical data to estimate this metric. Conversely, period life expectancy reflects the projected average lifespan of a hypothetical cohort subjected to prevailing mortality rates during a specified period, typically a year. While period life expectancy offers insights into mortality patterns at a given point in time, it overlooks temporal shifts in mortality rates. For instance, Japan's life expectancy in 2005 was recorded at 82.3 years, indicating the anticipated lifespan for a cohort exposed to Japan's mortality rates in that year, assuming these rates remain constant. However, subsequent data revealed Japan's period life expectancy in 2019 surged to 84.6 years, signifying an improvement in mortality patterns over the period. Despite their significance, period life expectancies often underestimate cohort life expectancies due to the progressive decline in mortality rates across eras of modern development (Esteban Ortiz-Ospina, 2017). Additionally, life expectancy serves as a crucial metric in aging studies, providing insights into the relationship between aging processes and the longevity of a species. Longevity, akin to fecundity in relation to fertility, represents a latent biological trait within a population. While life expectancy offers a statistical perspective derived from data, longevity remains a theoretical construct, necessitating additional physiological insights or biological theory for accurate inference. The interplay between life expectancy and longevity becomes intricate, particularly when environmental factors influence longevity, as proposed by the techno-physiological evolution model of Fogel and Costa. This complexity underscores conceptual and methodological challenges, necessitating the consideration of health changes preceding death for a comprehensive analysis. Addressing these complexities is paramount for projecting long-term life expectancy trends, essential for predicting population growth, aging rates, and the viability of social programs like Medicare and Social Security (K.G. Manton, 2007). Furthermore, demographic measures such as the birth rate, case fatality rate, crude birth rate, crude death rate, and infant mortality rate (IMR) play significant roles in understanding population health dynamics. The birth rate refers to the number of live births per 1000 estimated mid-year population within a given year, while the case fatality rate represents the proportion of individuals diagnosed with a specific disease who pass away within a designated period as a result of contracting that illness. Both the crude birth rate and crude death rate reflect demographic measures, with the former indicating the number of births per 1000 estimated mid-year population and the latter denoting the number of deaths per 1000 estimated mid-year population in a particular location over a single year. Additionally, the infant mortality rate (IMR) signifies the number of infant deaths per 1000 live births during the year. These definitions, as outlined by the National Health Profile (NHP) and the Central Bureau of Health Intelligence, elucidate key terminology essential for understanding population health dynamics. Economic growth, as explained by the Reserve Bank of Australia, signifies the expansion of a nation's economy over time, primarily measured by the increase in the total production of goods and services, known as gross domestic product (GDP). This growth can be evaluated in two primary terms: nominal and real. Nominal economic growth encompasses the rise in the dollar value of production, considering changes in both production volume and prices of goods and services. However, economists often prioritize real economic growth, which isolates changes in production volume from price fluctuations, offering a more accurate portrayal of a country's actual production levels across various timeframes. The measurement of GDP involves intricate processes conducted by statistical agencies such as the Australian Bureau of Statistics (ABS). Data from households, businesses, and government entities are collected periodically, facilitating the calculation of GDP through three distinct perspectives: production (GDP(P)), income (GDP(I)), and expenditure (GDP(E)). GDP(P) reflects the total value added from goods and services produced, while GDP(I) captures the income generated by employees and businesses, adjusted for taxes and subsidies. Conversely, GDP(E) quantifies the total expenditure by consumers, businesses, and governments on final goods and services. Despite the structured methodologies employed by statistical agencies, estimating GDP remains a complex task due to inherent limitations in data availability and potential measurement errors. Nevertheless, these diverse approaches provide complementary insights into a nation's economic performance, aiding policymakers and analysts in understanding the dynamics of economic growth and formulating effective policies and strategies to foster sustainable economic development. As elucidated by the World Health Organization (WHO) in 2020, free health care (FHC) policies have emerged as significant strategies aimed at reducing financial barriers to accessing health services, particularly in regions such as western Africa where they have gained traction over the past decade. These policies, often referred to as "politiques de gratuité," entail the elimination of formal user fees at the point of service delivery and can encompass a variety of approaches, including covering all health services, specific population groups, or selected services for vulnerable demographics. Despite their potential to expand coverage and contribute to the goal of universal health coverage (UHC), the impact of FHC policies remains mixed, with evidence suggesting varying degrees of success in terms of both financial protection and utilization of health services. Defined by their objective to mitigate financial obstacles, FHC policies typically target services essential for vulnerable populations, such as antenatal care, assisted deliveries, and health services for specific age groups. These policies often rely on geographic or demographic criteria rather than income assessment to determine eligibility for free health services, thereby prioritizing access for low-income groups. However, the implementation of FHC policies necessitates careful consideration of resource allocation and trade-offs, as governments must prioritize specific services or population groups due to budget constraints. While FHC policies aim to increase service utilization and improve financial protection, their effectiveness hinges on several factors, including adequate funding, transparent communication, and robust health service delivery systems. Challenges such as informal payments for scarce supplies and potential demotivation among health workers underscore the importance of comprehensive planning and preparation. Moreover, the distributional impact of FHC policies warrants attention, as evidence suggests that better-off populations may disproportionately benefit from public funding, exacerbating existing inequalities in access to health care. In response to these challenges, WHO emphasizes the need for preparatory measures and complementary interventions to ensure the success of FHC policies. Adequate financial resources must be allocated to health facilities to offset revenue losses and accommodate increased service utilization. Additionally, effective provider payment methods and mechanisms for addressing barriers to access among the poor are essential components of successful implementation. Furthermore, efforts to strengthen health systems and promote synergy between FHC policies and broader health financing strategies are crucial for advancing the goal of UHC. While FHC policies may not always benefit the poor as much as targeted fee exemptions based on income assessment, their feasibility and potential as catalysts for broader health reforms make them valuable instruments in the pursuit of UHC. By aligning with strategic visions and prioritizing equity, well-designed and implemented FHC policies can play a pivotal role in expanding access to essential health services and improving health outcomes for all. Universal health coverage (UHC), elucidated by the World Health Organization (WHO) in 2023, encapsulates the notion that all individuals should have access to comprehensive and high-quality health services without encountering financial hardship. This entails a spectrum of essential health services, spanning from health promotion to prevention, treatment, rehabilitation, and palliative care, across the entire lifespan. The delivery of these services necessitates a proficient and equitably distributed healthcare workforce, equipped with adequate resources and supportive working conditions. By shielding individuals from the financial repercussions of out-of-pocket health expenses, UHC aims to prevent individuals from falling into poverty due to healthcare costs, safeguarding their economic stability and that of their families. The pursuit of UHC aligns with the Sustainable Development Goals (SDGs) set forth by nations globally in 2015, emphasizing health as a fundamental element intertwined with the social, economic, and environmental dimensions of sustainable development. Despite the aspirational goals set forth by the SDGs, progress towards UHC has encountered challenges, particularly exacerbated by the COVID-19 pandemic. Prior to the pandemic, advancements in expanding service coverage were already decelerating, with the UHC service coverage index registering only marginal gains by 2019, stagnating at this level through 2021. This stall in progress left approximately 4.5 billion people without full access to essential health services. Furthermore, the incidence of catastrophic out-of-pocket health spending steadily rose, exceeding one billion people by 2019 and plunging millions further into extreme poverty. Inequalities persist as a fundamental obstacle to achieving UHC, with disparities prevalent within countries, particularly concerning access to reproductive, maternal, child, and adolescent health services. The COVID-19 pandemic exacerbated these challenges, disrupting essential services in the majority of countries and exacerbating existing health inequities. In response to these challenges, WHO advocates for the reorientation of health systems towards a primary health care (PHC) approach, characterized by inclusivity, equity, cost-effectiveness, and efficiency. PHC facilitates universal access to health services, tailored to individuals' everyday environments, and encompasses a comprehensive range of interventions, thereby enhancing coverage and financial protection. Leveraging PHC has the potential to yield significant health gains, with an estimated increase in global life expectancy by 3.7 years by 2030. Strengthening health systems based on PHC principles is deemed essential to achieving measurable health impact and advancing towards UHC. Measuring progress towards UHC is imperative for tracking advancements and identifying areas for improvement. Two key indicators are utilized for this purpose: coverage of essential health services and catastrophic health spending. These metrics provide insights into the extent to which individuals are accessing needed healthcare services without experiencing financial hardship. WHO's commitment to UHC is entrenched in its mandate to uphold health as a fundamental human right, as enshrined in its 1948 Constitution. Collaborative efforts with various partners, including UHC2030, the UHC Partnership, and the Global Action Plan for Healthy Lives and Well-being for All, are pivotal in advancing the agenda of UHC worldwide. Through strategic partnerships and concerted efforts, WHO endeavours to catalyse progress towards UHC, ensuring that health services are accessible and equitable for all individuals, irrespective of their socio-economic status or geographic location. In order to comprehensively grasp the intricate relationships between life expectancy, birth and death rates, infant mortality, economic growth, and the provision of universal free healthcare, it is imperative to delve into the depths of the literature available on these subjects. By examining the existing literature, we can gain insights into how these factors interplay with one another and the ramifications they have on populations and nations worldwide. Understanding these dynamics entails exploring both the positive and negative effects they exert, ranging from improvements in overall population health and well-being to challenges such as economic burdens and disparities in healthcare access. Through a thorough review of literature, we can identify trends, patterns, and potential areas for further research analysis, enabling us to advance our understanding of these critical issues and contribute to the development of informed policies and interventions aimed at promoting better health outcomes and sustainable development on a global scale.
LITERATURE REVIEW
The study, titled "World Population Review and Study of Global Health Insights: Triumphs & Trials Unveiled, 2024," presented a comprehensive analysis of global life expectancy trends. Drawing on data from the United Nations, the study elucidated the factors influencing longevity across populations. Life expectancy at birth served as a pivotal indicator, reflecting overall mortality rates and highlighting the interplay of genetic predispositions, gender disparities, and lifestyle determinants, encompassing hygiene practices, dietary habits, cultural influences, access to healthcare, and socio-economic conditions. In 2024, the global population dynamics continued to manifest in the staggering numbers of births and deaths occurring each day. With an estimated birth rate of 368,144 births per day, the world witnessed a constant influx of new lives entering the human tapestry. This translates to approximately 15,339 births every hour, 256 births per minute, and a remarkable 4.26 births per second. Conversely, amidst the cycle of life, the inevitability of death persisted with the world's death rate standing at 166,859 deaths per day. This sombre statistic translates to approximately 6,952 deaths every hour, 116 deaths per minute, and 1.93 deaths per second. These figures, while numerical, encapsulate the profound rhythms of existence, portraying the ceaseless flux of life and mortality on a global scale. They serve as poignant reminders of the fragility and resilience inherent in the human experience, prompting contemplation on the interconnectedness of all lives and the significance of each passing moment in the grand tapestry of existence. As of 2023, the global life expectancy stood at 70.8 years for males and 76.0 years for females, with an average of 73.4 years. Disparities were evident, spanning from 57.7 years in Western Africa to 82.7 years in Western Europe. The study underscored a positive global trend, with an increase of 5.5 years in average life expectancy between 2000 and 2016. Notably, improvements in child survival rates and expanded access to antiretroviral treatments for HIV/AIDS emerged as significant contributors to this upward trajectory. 10 Countries with the Longest Life Expectancies (United Nations 2023) Country Life Expectancy (Years) Monaco 87.14 Hong Kong 85.96 Macau 85.65 Japan 85.08 Liechtenstein 84.92 Switzerland 84.52 Singapore 84.39 Italy 84.35 South Korea 84.26 Spain 84.19 10 Countries with the Shortest Life Expectancies (United Nations 2023) Country Life Expectancy (Years) Nigeria 54.11 Chad 54.12 Lesotho 55.10 Central African Republic 56.10 South Sudan 57.10 Somalia 58.11 Ivory Coast 60.30 Guinea 60.71 Mali 60.84 Burkina Faso 61.08 The above table underscored the concentration of lower life expectancies in African nations, attributed to challenges such as food insecurity, prevalent diseases including HIV/AIDS and malaria, and specific health concerns like measles, cholera, and monkeypox. Despite these challenges, positive trends were observed, with the WHO African Region experiencing a remarkable increase of 10.3 years between 2000 and 2016, primarily due to improved treatments for HIV and malaria. The study anticipated further advancements in healthcare access, projecting continued increases in life expectancy across African countries. Exploring beyond life expectancy, the study delved into healthy life expectancy (HALE), which tended to be notably shorter than overall life expectancy due to health declines in later years. For instance, in the United States, the average life expectancy was 78.5 years in 2019, while healthy life expectancy during the same year was 66.1 years. Profiles of countries with the longest life expectancies revealed diverse factors contributing to their longevity. Monaco, with the longest estimated life expectancy globally in 2023, boasted an average of 87.01 years, attributed to factors such as the Mediterranean diet, state-funded healthcare, and high disposable incomes promoting healthy lifestyles. Hong Kong, despite being a Special Administrative Region of China, held the second-highest life expectancy globally (88.66 years for females, 83.00 for males in 2023), credited to rapid economic development, robust education, low infant mortality, and efficient child healthcare. Macau, as the second Special Administrative Region of China, claimed the third-highest life expectancy in 2023 at 85.51 years, owing to a clean environment, strong education, easy healthcare access, and a robust economy. Japan, with a life expectancy of 87.97 years for females and 81.91 years for males, credited its high longevity to a diet rich in fruits, vegetables, and seafood, along with early investments in public health and universal health insurance. Liechtenstein, a small European micronation, boasted an average life expectancy of 84.95 years, emphasizing high quality of life, free healthcare, and economic prosperity as contributing factors. Switzerland, with an average life expectancy of 84.38 years, attributed its longevity to active lifestyles, satisfaction, a diet rich in dairy and dark chocolate, and substantial healthcare spending. Singapore, ranking seventh globally in life expectancy (84.27 years), showcased low mortality rates and effective healthcare as contributors to its citizens' well-being. Italy, with the eighth-highest life expectancy (84.20 years on average), experienced slight decreases attributed to economic disparities, yet maintained a higher life expectancy in economically developed regions. Vatican City, as the smallest country, had the ninth-longest life expectancy globally (84.16 years), with unique demographics and a population mostly comprising Catholic clergymen. South Korea, rounding out the top 10, exhibited a rapidly growing life expectancy (84.14 years in 2023), propelled by improved nutrition, enhanced healthcare access, and increased focus on health and social care. The study concluded by noting that Monaco held the world's longest life expectancy, while the United States was ranked 40th globally in life expectancy. These findings underscored the intricate interplay of various factors influencing life expectancies and emphasized the imperative for continued efforts to improve healthcare access and address socio-economic disparities worldwide. As per the Organisation for Economic Co-operation and Development (OECD), life expectancy at birth was defined as the average lifespan a newborn could anticipate, assuming that current death rates remained unchanged. However, it was essential to note that the actual lifespan of any specific birth cohort could not be precisely predicted beforehand. If mortality rates were decreasing over time, actual life spans would surpass the life expectancy calculated based on current death rates. This metric served as one of the most commonly used indicators of health status, providing insights into societal well-being and healthcare effectiveness. Increases in life expectancy at birth could be attributed to various factors, including advancements in living standards, adoption of healthier lifestyles, improvements in education, and enhanced access to high-quality healthcare services. This indicator was presented both in total and disaggregated by gender, offering a comprehensive perspective on population health outcomes and disparities. Moreover, it was measured in years, facilitating comparisons and analyses across different demographic groups and geographical regions. The relationship between healthcare expenditure and key health indicators in Korea, namely the infant mortality rate and life expectancy at birth. With the steady rise in income levels observed in both developed and emerging economies like Korea, there was a corresponding rapid increase in healthcare expenditure. The study endeavoured to shed light on the determinants of healthcare expenditure and its impact on these critical health outcomes. By employing analytical techniques such as the Granger causality test and Ordinary Least Squares (OLS), the study examined the effects of various forms of healthcare expenditure, as well as the number of physicians and hospital beds, on infant mortality rate and life expectancy at birth. The findings suggested that the infant mortality rate was primarily influenced by the healthcare system itself over the long term, underscoring the importance of a robust healthcare infrastructure in improving infant health outcomes. Conversely, life expectancy at birth appeared to be immediately impacted by the availability of health-related facilities such as physicians and hospital beds in the short term. This highlighted the necessity of accumulating physical capital, including life-prolonging medical technologies, to enhance life expectancy. Moreover, the study identified that increasing healthcare expenditure could enhance efficiency in healthcare delivery through two main mechanisms. However, it was acknowledged that the study's findings had limitations in terms of generalizability, and future research could explore the topic further by employing structural equation modeling and incorporating a wider range of independent variables to delve deeper into the socio-economic impacts of healthcare expenditure. Overall, the study provided valuable insights into the complex interplay between healthcare expenditure, healthcare infrastructure, and key health indicators, offering implications for policymakers and stakeholders in healthcare system planning and resource allocation in Korea and potentially other similar contexts ("Effects of Health Care Expenditure on the Infant Mortality Rate and Life Expectancy at Birth in Korea" by Hyun-Jae Rhee). Whereas the interplay between health resources and health outcomes across countries delineated by income levels and geographical positions offered valuable insights. The primary objective of this study was to scrutinize the correlation between life expectancy at birth and health expenditure per capita within distinct groups of countries characterized by varying development statuses and geographic locations. Employing panel data analysis via the fixed effects model, the study unveiled that disparities in healthcare expenditures elucidated the divergent outcomes observed within healthcare systems across different groups of countries, stratified by income levels and geographical regions. These findings corroborated prior research indicating a close nexus between health status and health expenditures. Particularly striking was the discernible trend observed among developed nations, where a significant uptick in health expenditures per capita correlated with heightened longevity, with European nations showcasing the most elevated longevity rates. Moreover, the research underscored the widening gap in health expenditure variation over time, especially pronounced between developed and developing nations. However, it was crucial to acknowledge the limitation of the study, which solely focused on the impact of health expenditure as a determinant factor due to data constraints. Future research endeavours should encompass a broader spectrum of factors, encompassing individual lifestyle choices, educational attainment, and income levels, to yield a more comprehensive understanding. Additionally, the exploration of alternative indicators such as healthy life expectancy could offer enhanced insights. In sum, the findings accentuated the imperative for health policies to pivot towards mitigating health inequalities among nations worldwide, advocating for concerted efforts in this direction (Jaba, Balan, and Robu, 2014). Similarly, the study explored the intricate nexus between life expectancy, public healthcare expenditure, and economic growth, particularly focusing on Nigeria. It elucidated that governments prioritized enhancing health outcomes as a means to augment labor market productivity and overall economic performance. Empirical evidence underscored the pivotal role of individuals' health in contributing significantly to the economy, with healthier populations often exhibiting higher levels of workplace productivity, leading to increased incomes and investments in personal development and education. This aligned with the World Health Organization's comprehensive definition of health, emphasizing the importance of physical and mental well-being. The study further underscored the correlation between human capital and economic growth, highlighting that countries with healthier populations tended to experience greater economic prosperity. Against the backdrop of global trends, the study delved into Nigeria's healthcare landscape, revealing fluctuations in life expectancy over time and emphasizing the urgent need for strategic interventions to bolster the nation's healthcare system and promote longevity. Economic growth, measured by gross domestic product (GDP), was intricately linked to life expectancy, with investments in both physical and human capital playing crucial roles in driving prosperity. Drawing on empirical literature and econometric analysis, the study elucidated the complex relationship between public health spending, life expectancy, and economic growth in Nigeria. It identified a long-term relationship among these variables, emphasizing the positive impact of life expectancy on economic growth. However, the study revealed a negative relationship between public health spending and economic growth, suggesting the need for strategic allocation of healthcare resources to maximize their effectiveness. The findings underscored the importance of government financing in healthcare infrastructure and human capital development to promote both health and economic prosperity. In light of these findings, the study proposed several policy recommendations, including sustained government investment in the healthcare sector, implementation of health orientation programs to improve public health awareness, and policies aimed at curbing exploitation in the private healthcare sector. Overall, the study underscored the critical role of healthcare investment in driving economic growth and fostering a healthier, more prosperous society in Nigeria (Nurudeen Abiodun Lawal, Olaide Opeloyeru, and Adegbola Omobolanle, October 2023). As per global study conducted by the World Health Organization (WHO), the analysis of healthy life expectancy at birth revealed a noteworthy progression over the past two decades, signifying substantial advancements in healthcare and public health strategies. The findings demonstrated a commendable rise of ▲ 5.36 years, depicting a positive trend from 58.3 years in 2000 to 63.7 years in 2019. This increase indicated not only an extension in overall lifespan but also a considerable portion of those years being lived in good health. The upward trajectory in healthy life expectancy underscored the efficacy of interventions aimed at disease prevention and management, promotion of healthier lifestyles, and enhancement of medical care accessibility. The data highlighted collaborative efforts among governments, healthcare systems, and international organizations in tackling diverse health challenges, emphasizing a collective dedication to improving both longevity and quality of life on a global scale. As nations confronted evolving health landscapes and emerging global health threats, the observed rise in healthy life expectancy offered promising evidence of progress. It emphasized the persistent need for comprehensive and sustainable health initiatives to further enhance the well-being of populations worldwide. Year Healthy Life Expectancy (Years) 2000 58.3 2019 63.7 The data above illustrated the progression of healthy life expectancy from 2000 to 2019, showcasing a notable increase over the analysed period. The research study, based on data from "The World by Income and Region - World Bank," "Historical classification by income - World Bank," "GNI per capita, Atlas method (current US$)," "GNI per capita, PPP (current international $) - World Bank," and "World Bank Country and Lending Groups - World Bank," offered a comprehensive analysis of the classification of countries into high-income economies for the year 2024. According to the World Bank's categorization, high-income economies were defined as those with a Gross National Income (GNI) per capita exceeding $13,206 in 2023, encompassing 81 countries globally, reflecting varying degrees of economic strength and stability. The study emphasized the dynamic nature of high-income classification, noting shifts observed in the 2023 financial year, with stalwart high-income nations like the United States maintaining their status while newcomers such as Panama and Romania joined the cohort, and others like Palau transitioned to upper-middle-income status. A critical metric employed in this analysis was GNI per capita, serving as a measure of a nation's overall income relative to its population, providing a comprehensive snapshot of economic vitality. Furthermore, the study explored the correlation between income classification and overall development, highlighting parallels between the World Bank's income categories and the United Nations' development classifications. High-income economies often aligned with developed nations, while lower-income categories typically encompassed developing or less-developed countries. Methodologically, the study underscored the annual update of income categories by the World Bank, ensuring alignment with the latest available data, such as the 2024 financial year rankings reflecting data from the preceding calendar year, thereby ensuring relevance and accuracy in assessing countries' economic statuses. In conclusion, the research provided a nuanced understanding of high-income classification, elucidating the intricate interplay between economic indicators, development levels, and global economic dynamics. World Bank GNI per capita income thresholds for FY2024 Income Category Thresholds Low income ≤ $1,135 Lower middle income $1,136 - $4,465 Upper middle income $4,466 - $13,845 High income > $13,845 In the study that Infant Mortality Rate (IMR) across various countries, data from multiple sources including UNICEF Data Warehouse, CIA World Book, and Wikipedia's list of countries by infant and under-five mortality rates were analyzed. IMR, a crucial population metric, tracked the deaths of newborn and sometimes unborn children, providing insights into the health and well-being of a population. The rate was typically measured as the number of infant deaths per 1,000 live births, with higher rates often associated with factors like poverty, inadequate healthcare, malnutrition, and underdeveloped infrastructure, prevalent especially in underdeveloped and developing countries. Globally, the leading causes of infant mortality included neonatal encephalopathy, infections, complications of preterm birth, lower respiratory infections, and diarrheal diseases. Despite significant advancements in healthcare, the global IMR had shown a notable decline over recent decades, dropping from approximately 140 per 1,000 live births in the 1950s to 27.4 in 2020. Examining the data from UNICEF 2020, the ten countries with the highest IMR included Sierra Leone, Central African Republic, Somalia, Nigeria, Chad, Guinea, DR Congo, South Sudan, Mali, and Niger. Conversely, the countries with the lowest IMR included San Marino, Monaco, Estonia, Japan, Slovenia, Finland, Singapore, Norway, Montenegro, and Sweden. In the context of the United States, IMR was mainly influenced by congenital disabilities, pre-term birth, low birth weight, maternal complications during pregnancy, Sudden Infant Death Syndrome (SIDS), and injuries. As of 2020, the IMR in the US was recorded at 5.44 deaths per 1,000 live births, ranking 50th globally. However, it was crucial to note that the apparent discrepancy between the US and other countries was partly due to variations in how IMR statistics were compiled. The US definition of infant death encompassed a broader timeframe, including any death occurring from the start of pregnancy through the child's first birthday, unlike some other countries which only considered deaths within the first 42 days after birth. This broader definition likely contributed to the higher IMR reported in the US compared to other developed nations like Sweden, Japan, and Australia. Moreover, differences in defining infancy, inclusion of stillbirths and miscarriages, and variations in reporting practices across countries further complicated international comparisons of IMR. Despite these challenges, any IMR above 0.0 warranted attention, and efforts to improve infant health outcomes remained a global priority. The data presented was compiled by UNICEF, while estimates for 2023 were sourced from the CIA World Book. It is important to note that CIA data for Palestine specifically referred to the Gaza Strip, with slightly higher totals reported for the West Bank at 16.1. While the US ranked 50th in terms of IMR globally, the intricacies of data collection methodologies and definitions underscored the need for cautious interpretation when making international comparisons of infant mortality rates. A study into the complexities surrounding the estimation of life expectancy (LE) and infant mortality rates (IMR) for Australian Aboriginal populations, highlighting the challenges posed by inadequate mortality and population data. Despite overall improvements in LE and IMR for both Aboriginal and non-Aboriginal populations in Australia, accurate estimations for Aboriginal populations were hindered by unreliable recording of Aboriginality in census and vital registration data. The small size of the Aboriginal population, combined with stochastic variation, further complicated estimations, leading to highly variable and uncertain outcomes. In response to these challenges, the Council of Australian Governments (COAG) proposed initiatives to close the gap in Indigenous disadvantage, including reducing the LE gap within a generation and halving mortality rates for Aboriginal children under 5 within a decade. However, despite some documented improvements, accurate measures of Aboriginal mortality remained elusive, hindering the assessment of progress towards these goals. Various methods were employed to estimate Aboriginal mortality and LE in the absence of reliable data, but these methods often lacked transparency and were based on assumptions that could not be easily tested. The indirect methods used by the Australian Bureau of Statistics (ABS) and others yielded inconsistent results, further complicating efforts to accurately quantify Aboriginal mortality and LE. While direct methods offered potential improvements, challenges persisted, including under-identification of Aboriginality in both death registrations and census data. Despite efforts to enhance data quality through improved linkage and inclusion of additional data sources, such as hospital admission records and Aboriginal Medical Services, challenges remained in accurately quantifying Aboriginal mortality and LE. The limitations of existing methods underscored the need for ongoing efforts to improve data quality and develop more robust estimation techniques. Without reliable data, accurate comparisons between Aboriginal and non-Aboriginal populations and assessments of longitudinal trends would continue to be challenging, emphasizing the importance of addressing these data deficiencies to effectively monitor progress and address disparities in health outcomes for Aboriginal populations in Australia. Based on the insights gained from the introduction and literature review sections, our research aimed to delve deeper into the intricate relationship between life expectancy, birth and death rates, economic conditions, and infant mortality across various countries worldwide. Utilizing the latest available data from reputable sources such as the World Bank, United Nations, and World Health Organization, we sought to conduct a comprehensive analysis of key indicators including life expectancy at birth for both males and females, total life expectancy, and healthy life expectancy (HALE) at birth (Phillips et al., 2014). By examining these datasets, our research endeavoured to uncover patterns, trends, and disparities in life expectancy and health outcomes globally, with a particular focus on understanding the influence of economic growth and socio-economic conditions on population health. Through rigorous statistical analysis and interpretation of findings, our study aimed to contribute valuable insights to the fields of public health, development economics, and social policy, ultimately informing strategies and interventions aimed at improving health outcomes and reducing health inequalities on a global scale.
METHODOLOGY
The research design adopted for this study involved a combination of quantitative analysis and comprehensive review analysis, aimed at exploring the intricate relationship among various factors including life expectancy, birth and death rates, infant mortality, economic growth, and universal healthcare provision. Data from 2024 were meticulously gathered from reputable sources such as the World Bank, the United Nations, and the World Health Organization, encompassing crucial variables like life expectancy at birth and healthy life expectancy (HALE) at birth. The research procedure followed a systematic approach encompassing data collection, analysis, and interpretation, employing quantitative techniques to discern trends, correlations, and patterns within the data. Concurrently, an exhaustive review analysis was undertaken to synthesize existing literature from scholarly articles, reports, and publications related to the subject matter. Integrating both quantitative data analysis and review analysis enabled a thorough exploration of the interrelationships among the variables under scrutiny, offering valuable insights into population health outcomes and economic development dynamics. By triangulating findings from these complementary approaches, the study aimed to provide evidence-based guidance for policymaking and intervention strategies aimed at enhancing global health and well-being (For detailed data from various sources, please refer to the appendix section).
RESULTS AND DISCUSSIONS
RESULTS AND DISCUSSIONS The graphical chart above, drawing from various World Bank sources including "The World by Income and Region," "Historical classification by income," and "World Bank Country and Lending Groups," offered comprehensive insights into the economic landscape of high-income countries and lending groups in 2024. Analysing Gross National Income (GNI) per capita figures in both current US dollars (Atlas method) and current international dollars (PPP), the study showcased the diverse economic profiles within this category. Leading the pack, the United States emerged as a formidable force with a GNI per capita of $76,770 (Atlas) and $77,950 (PPP), followed closely by economic powerhouses like Japan, Germany, and the United Kingdom, with GNI per capita figures ranging from $42,440 to $54,030 (Atlas) and $48,480 to $65,990 (PPP). Other notable high-income nations such as Canada, Australia, and Sweden demonstrated robust economic performance, boasting GNI per capita values exceeding $50,000 (Atlas) and $57,000 (PPP). Conversely, countries like Chile, Romania, and Poland exhibited lower GNI per capita figures, reflecting comparatively lesser economic prosperity within the high-income bracket. Additionally, outliers such as Luxembourg with an exceptional GNI per capita exceeding $89,000 (Atlas) and $94,000 (PPP), and Qatar with similarly high figures exceeding $70,000 (Atlas) and $110,000 (PPP), underscored the varied economic landscape even within the high-income category. The study also identified territories lacking complete data, including French Polynesia, New Caledonia, and Guam, suggesting potential gaps in the available information for certain regions. These findings provided valuable insights for policymakers, economists, and stakeholders interested in understanding the economic dynamics and disparities among high-income countries and lending groups in 2024. Countries with Universal Health Care Country Countries With Universal Healthcare India yes China yes Indonesia yes Pakistan yes Brazil yes Russia yes Mexico yes Japan yes Philippines yes Egypt yes Turkey yes Germany yes Thailand yes United Kingdom yes France yes South Africa yes Italy yes Colombia yes South Korea yes Spain yes Algeria yes Argentina yes Canada yes Morocco yes Ghana yes Peru yes Malaysia yes Australia yes North Korea yes Taiwan yes Burkina Faso yes Sri Lanka yes Chile yes Romania yes Netherlands yes Rwanda yes Tunisia yes Belgium yes Cuba yes Sweden yes Czech Republic yes Greece yes Portugal yes Israel yes Austria yes Switzerland yes Hong Kong yes Serbia yes Bulgaria yes Singapore yes Denmark yes Finland yes Norway yes New Zealand yes Costa Rica yes Ireland yes Kuwait yes Croatia yes Georgia yes Albania yes Botswana yes Trinidad and Tobago yes Mauritius yes Bhutan yes Macau yes Luxembourg yes Suriname yes Maldives yes Bahamas yes Iceland yes Seychelles yes Liechtenstein yes A comprehensive study conducted in 2024 on universal health coverage (UHC), drawing from reputable sources such as the World Health Organization and various other references, revealed a nuanced global landscape regarding the provision of universal health care. The study elucidated a diverse spectrum of implementation practices across nations, showcasing the widespread acceptance and adoption of universal health care principles worldwide. Notably, countries ranging from populous nations like India and China to smaller ones such as Belgium and Cuba had embraced universal health care systems, reflecting a commitment to ensuring access to essential health services without financial hardship. Developed nations like Japan, Germany, the United Kingdom, France, and Italy featured prominently on the list, alongside emerging economies like Indonesia, Brazil, and Russia, emphasizing the global relevance and acceptance of universal health care as a fundamental right. Furthermore, the inclusion of countries from diverse continents, including South Africa, Colombia, South Korea, and Canada, underscored the widespread recognition and adoption of universal health care. However, the study also highlighted the persistence of disparities within countries, influenced by factors such as income level, geography, and infrastructure, despite the implementation of universal health care. Nevertheless, the overarching trend observed in the data underscored a collective commitment to prioritize citizens' health and well-being by ensuring equitable access to quality health care services, regardless of socioeconomic status or geographical boundaries. Analysis of the above graphical chart data from the UNICEF Data Warehouse and World Population Review revealed a comprehensive examination of infant mortality rates (IMRs) across various countries, shedding light on diverse healthcare landscapes and socioeconomic contexts. IMR, a crucial metric measuring deaths per 1,000 live births, served as a vital indicator of a nation's healthcare system efficacy, socioeconomic conditions, and overall public health profile. India's IMR stood at 25.49 in 2021, indicating marginal improvement yet highlighting significant healthcare challenges. In contrast, China exhibited a significantly lower IMR of 5.05, demonstrating the effectiveness of its healthcare policies and economic development initiatives in improving maternal and child health outcomes. Developed nations like the United States and Japan showcased relatively low IMRs of 5.36 and 1.74, respectively, reflecting strong healthcare infrastructures and access to quality medical services. Conversely, several African nations, including Nigeria, DR Congo, and Somalia, faced alarmingly high IMRs exceeding 60 deaths per 1,000 live births, emphasizing systemic challenges in healthcare access and socioeconomic development. Across South America, Brazil and Peru reported moderate IMRs around 13, indicating ongoing efforts to enhance healthcare access, while Argentina boasted a rate below 10, reflecting comparatively better healthcare outcomes. European nations consistently exhibited low IMRs, with rates below 5 in Germany, the United Kingdom, and France, showcasing effective healthcare systems and socioeconomic stability. In the Middle East, countries like Iraq and Yemen grappled with IMRs exceeding 20, while Israel and Qatar maintained rates below 5, indicating robust healthcare infrastructures and public health measures. In conclusion, the analysis underscored global healthcare disparities shaped by healthcare systems, socioeconomic factors, and governmental policies, emphasizing the need for concerted efforts to strengthen healthcare infrastructure and improve maternal and child health outcomes worldwide. Analysis of the latest data presented on the above graphical map from "Country Comparison: Infant Mortality Rate - CIA World Book" provided crucial insights into the state of infant mortality rates worldwide in 2024. These rates served as vital indicators of a nation's healthcare system, socio-economic status, and overall well-being. The findings revealed significant disparities across countries, highlighting variations in healthcare access, quality, and social determinants impacting infant survival. Afghanistan stood out with a staggering 103.1 deaths per 1,000 live births, signaling an urgent need for enhanced maternal and child healthcare infrastructure and services. Similarly, Somalia, Central African Republic, and Sierra Leone exhibited alarmingly high rates, exceeding 80 deaths per 1,000 live births, indicative of systemic challenges in healthcare provision and socio-economic development. In contrast, countries like Japan, Iceland, and Singapore boasted remarkably low infant mortality rates, ranging from 1.5 to 1.9 deaths per 1,000 live births, showcasing the effectiveness of comprehensive healthcare systems, robust public health interventions, and socio-economic stability in safeguarding infant health. A notable trend emerged, with higher-income countries generally displaying lower infant mortality rates, underscoring the pivotal role of economic prosperity in facilitating access to quality healthcare services, nutrition, sanitation, and education, all critical factors in reducing infant mortality. However, exceptions to this trend existed, as evidenced by countries like Cuba and Costa Rica, which demonstrated relatively low infant mortality rates despite lower GDP per capita. This highlighted the significance of prioritizing healthcare investments, preventive measures, and equitable healthcare access in achieving favourable health outcomes. Moreover, regional disparities persisted, particularly in Sub-Saharan Africa, where countries faced disproportionate burdens of infant mortality compared to counterparts in Europe, North America, and East Asia, attributed to factors such as endemic diseases, limited healthcare access, inadequate maternal and child nutrition, and socio-political instability. Addressing these disparities required comprehensive multi-sectoral approaches, including investments in healthcare infrastructure, education, social welfare programs, and poverty alleviation initiatives. Targeted interventions focusing on maternal and child health, immunization coverage, prenatal care, and nutrition were imperative for reducing infant mortality and fostering sustainable development. In conclusion, the data underscored the multifaceted challenges and opportunities in global health, emphasizing the need for concerted efforts at local, national, and international levels to ensure every child's right to survival and well-being. In this comprehensive data analysis of the above graphical map and chart of global life expectancy data provided by the UN, a thorough examination of trends, disparities, and potential influencing factors was conducted. The analysis elucidated a broad spectrum of life expectancies across various countries, showcasing pronounced disparities reflective of divergent healthcare accessibility, socio-economic circumstances, and overall societal well-being. Notably, the range of life expectancy spanned from as low as 54.5 years in Nigeria to a strikingly high 89.11 years in Monaco for females, and from 52.29 years in Lesotho to an impressive 85.29 years in Monaco for males. Regional clustering of life expectancies emerged, with countries in certain regions exhibiting similar longevity patterns, such as the generally lower life expectancies observed in Sub-Saharan Africa compared to those in Europe or East Asia, although exceptions like South Africa existed. Moreover, a distinct correlation between income levels and life expectancy was discernible, as high-income countries tended to boast higher life expectancies, while low-income nations, particularly in Sub-Saharan Africa, grappled with lower life expectancies due to systemic issues like limited healthcare access, heightened prevalence of infectious diseases, and entrenched poverty. Additionally, persistent gender disparities were evident, with females consistently outliving males across numerous countries, albeit with varying degrees of discrepancy. This highlighted the imperative of addressing gender-specific health concerns and ensuring equitable healthcare access for all genders. Overall, the findings underscored the intricate interplay between socio-economic determinants, healthcare accessibility, and public health policies in shaping global life expectancy outcomes. Mitigating disparities necessitated multifaceted strategies encompassing improvements in healthcare infrastructure, poverty alleviation efforts, and the implementation of inclusive, gender-sensitive health initiatives, underscoring the critical importance of collaborative endeavours among governments, international organizations, and non-governmental entities to foster healthier populations worldwide. In the extensive dataset analysis presented on the above graphical map and chart provided by the World Bank, a comprehensive analysis revealed intriguing patterns and differentials in life expectancies across nations. Notably, a discernible global trend emerged, underscoring that, on average, females tended to outlive their male counterparts, a phenomenon observed in the majority of countries. However, substantial variations existed among nations, with developed countries in Western Europe and East Asia exhibiting higher life expectancies compared to several developing nations in Africa. Hong Kong, Japan, and Switzerland stood out as having the highest life expectancies, emphasizing the impact of socio-economic development and healthcare infrastructure on longevity. Conversely, Sierra Leone, Central African Republic, and Lesotho grappled with lower life expectancies, highlighting persistent challenges in specific regions. China exhibited a noteworthy gender gap, with females enjoying a significantly longer life expectancy. India, in contrast, displayed a relatively lower life expectancy compared to other major nations, while the United States faced a marginally lower life expectancy than some of its developed counterparts. These findings underscored the multifaceted nature of factors influencing life expectancy, ranging from socio-economic disparities to regional healthcare infrastructure. Policymakers could leverage this analysis to formulate targeted strategies addressing both overall life expectancy improvements and gender-specific health interventions, particularly in regions facing pronounced challenges. Moreover, the identification of outliers and missing data underscored the need for enhanced global data collection efforts to facilitate more accurate and comprehensive health assessments on a global scale.
CONCLUSIONS
In conclusion, this research studies analysis conducted in 2024 offered valuable insights into key aspects of global health and economics. The first study provided a comprehensive overview of the economic landscape among high-income countries and lending groups, highlighting the diverse economic profiles within this category. It emphasized the dominant position of the United States, while also acknowledging the economic strength of countries like Japan, Germany, and the United Kingdom. The inclusion of outliers such as Luxembourg and Qatar underscored the varied economic landscape within the high-income category, providing crucial information for policymakers and stakeholders. The second research study explored universal health coverage (UHC) worldwide, revealing a nuanced global landscape regarding the provision of universal health care. The study showcased the widespread acceptance and adoption of UHC principles across nations, emphasizing the commitment of countries, both large and small, to ensure access to essential health services without financial hardship. Despite persistent disparities influenced by factors such as income level and geography, the overall trend indicated a collective commitment to prioritize citizens' health and well-being, making universal health care a fundamental right on a global scale. The third study delved into infant mortality rates (IMRs) across various countries, providing a comprehensive examination of diverse healthcare landscapes and socioeconomic contexts. The analysis highlighted significant variations in IMRs, with higher-income countries generally exhibiting lower rates, emphasizing the role of economic prosperity in facilitating access to quality healthcare services. However, exceptions like Cuba and Costa Rica challenged this trend, suggesting that targeted healthcare investments and preventive measures could contribute to favourable health outcomes. The study underscored the need for comprehensive multi-sectoral approaches to address regional disparities and improve maternal and child health outcomes worldwide. Lastly, the analysis of global life expectancy data revealed pronounced disparities reflective of divergent healthcare accessibility, socio-economic circumstances, and societal well-being. The findings demonstrated a correlation between income levels and life expectancy, with high-income countries generally boasting higher life expectancies. Persistent gender disparities and regional clustering of life expectancies further underscored the intricate interplay between socio-economic determinants, healthcare accessibility, and public health policies. The research emphasized the importance of collaborative efforts among governments, international organizations, and non-governmental entities to foster healthier populations worldwide. Together, these research studies contributed to a holistic understanding of the complex interdependencies between economics, healthcare, and societal well-being, providing valuable insights for shaping policies and interventions on a global scale.
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