Longevity Industry Dashboards

Longevity Governance

Dashboard

Big Data Comparative Analysis: Healthy Longevity in 50 Regions 

The Network Graph is used to display relations between various factors that determine Longevity. All parameters are divided into six pillars: general economic conditions, mortality rates, lifestyle factors, environment, demography and healthcare.

The graph itself visualizes how metrics are interconnected with each other. The relationship between them are displayed with lines. Bold arrows indicate direct impact on health longevity, which is determined as difference between life expectancy at birth and health-adjusted life expectancy. Dashed lines reveal multicollinearity, a state of very high intercorrelations or inter-associations among the independent variables, factors across different groups.

Comparative Longevity Analysis

The Network Graph is used to display relations between various factors that determine Longevity. All parameters are divided into six pillars: general economic conditions, mortality rates, lifestyle factors, environment, demography and healthcare.
The graph itself visualizes how metrics are interconnected with each other. The relationship between them are displayed with lines. Bold arrows indicate direct impact on health longevity, which is determined as difference between life expectancy at birth and health-adjusted life expectancy. Dashed lines reveal multicollinearity, a state of very high intercorrelations or inter-associations among the independent variables, factors across different groups.

Conceptual Model of the Gap Determinants

The determinants of the gap between life expectancy and HALE are complex and comprise multiple policy domains. One basic but important conceptual model that can be used to illustrate the breadth of these determinants is shown above. The determinants are presented in a set of boxes, the size of which represents the strength of relationship with gap and the color represents its significance.
The biggest box belongs to general economic conditions that have important long-term health effects. The next box contains society's basic health institution, which can both sustain and impair a healthy existence. The next сell emphasizes the critical role of living conditions. The box below to the living conditions highlights the importance of individual behavioral choices (cigarette smoking, risk-taking behaviors) in the determination of the gap between life expectancy and HALE. The last box but not the least implicates the assessment of causes of death contribution to the gap.

Because of the issue of multicollinearity as all the mentioned factors are interconnected we will build five different models
to identify unmixed impact of each individual group of factors on the gap.

Methodology of Multiple Linear Regression Analysis

Multiple linear regression analysis is a quantitative method used to test the nature of relationships between a dependent variable and two or more independent variables.

Dependent and Independent Variables
The variable whose value is to be predicted is known as the dependent variable and the ones whose known values are used for prediction are known independent (exploratory) variables. Sometimes the dependent variable is also called endogenous variable, criterion variable, prognostic variable or regressand. The independent variables are also called exogenous variables, predictor variables or regressors.

Significance and Goodness of Fit
At the center of the multiple linear regression analysis lies the task of fitting a single line through a scatter plot. More specifically, the multiple linear regression fits a line through a multi-dimensional cloud of data points. Variables are evaluated by what they add to the prediction of the dependent variable which is different from the predictability afforded by the other predictors in the model. The F-test is used to assess whether the set of independent variables collectively predicts the dependent variable. R-squared—the multiple correlation coefficient of determination—is reported and used to determine how much variance in the dependent variable can be accounted for by the set of independent variables. Beta coefficients are used to determine the magnitude of prediction for each independent variable. For significant predictors, every one unit increase in the predictor, the dependent variable will increase or decrease by the number of unstandardized beta coefficients. A standardized beta coefficient compares the strength of the effect of each individual independent variable to the dependent variable. The higher the absolute value of the beta coefficient, the stronger the effect.

Basic Modeling Assumptions
● Assumption of linearity. There is a linear relationship between dependent and independent variables.
● Assumption of homoscedasticity. Data values for dependent and independent variables have equal variances.
● Assumption of absence of collinearity or multicollinearity. There is no correlation between two or more independent
variables.
● Assumption of normal distribution. The data for the independent variables and dependent variable are normally
distributed.

Economic Instability and Gap between HALE and Life Expectancy

The Consumer Price Index (CPI) is a measure of the average change over time in the prices paid by consumers for a market basket of consumer goods and services. CPI characterises prices instability and economic instability in general as rapid inflation indicates recession or systemic crises.
The graph shows that increase of CPI contributes to increase in gap between life expectancy at birth and HALE. The lowest level of CPI in 2016 was observed in Singapore and the highest was in Iran.

Unemployment and Healthy Longevity

High unemployment leads to reduction of health-adjusted life expectancy. Countries with low unemployment (close to natural level of unemployment) have higher HALE. Hgh unemployment rate leads to social disproportions and unaffordability of basic basket of goods and services.
 
But calculations also show that increase in unemployment leads to decrease in gap. Such inverse relations can be explained parameters. Both life expectancy and HALE are modeled indicators, but HALE is inertial by nature and has lower elasticity comparing to life expectancy.

Public Healthcare Expenditure and Out-of-pocket Expenditure

As a result of the study, we found out, that mentioned above dimensions of national healthcare systems have a significant impact on the gap and its change. Every single unit rise of domestic private health expenditures leads to 0.044 years or 16 days decrease in the gap between life expectancy and HALE. It is necessary to pay attention to the sign of the coefficient for “Public health care expenditure” as it shows that increase in the level of public expenditure can cause the gap to increase. This indicates health care system inefficiency. In general, the variance of healthcare peculiarities explains 24.1 % of the gap variance. According to F-test and p-value, this model is significant. Therefore, there is enough evidence in the data to suggest that the linear relation between the gap and healthcare systems exists. The standard error of estimate measures that on average prediction values of the model and actual values of the gap differ by 0.718 years.

Public Healthcare Expenditure and Out-of-pocket Expenditure

Unregulated direct charges often constitute a major access barrier to needed health care and contribute to high out-of-pocket payments generating problems of financial protection. Out-of-pocket payments absorb household’s financial resources and make healthcare unaffordable for low socioeconomic groups as a result large discrepancies appears in healthcare status. In contrast, public spending on health is central to universal health coverage and social protection, but there is no clear trend of. In the United States high healthcare expenditure is a result of high administrative cost and corruption in healthcare.

Healthcare Accessibility

The balance of medical facilities and healthcare professionals is vital to provide high-quality healthcare services. Countries that are below the circle and extreme outliers, such as Cuba and China face problems of staff shortage, long waiting time or both of them.
 
A key issue is that the supply of doctors has not kept pace with demographic trends and the increasing demands of an ageing population. Timeliness of healthcare services closely relates to staff shortage. These problems hinders governments to focus efforts on care-delivery improvements.

Ageing Population and Current Healthcare Expenditure

The total-age-dependency ratio is the ratio of the sum of the number of young and the number of elderly people at an age when both groups are generally economically inactive, (i.e. under 15 years of age and aged 65 and over), compared to the number of people of working age (i.e. 15-64 years old). Steady increase in share of old age group in the population leads to increase in financial burden. The youngest population across chosen countries live in South Africa and Qatar. The oldest nations are in Israel and Japan, where the value of age dependency ratio is bigger than 600 elderly people per 1000 of people of working age. High values of current healthcare expenditures in the United States and Switzerland show that healthcare is enough expensive in both countries and private insurance providers set high fees.

Gap between HALE and Life Expectancy and Living Conditions

An important factor that determines life expectancy and HALE is a general environmental condition. In particular, we focused on living conditions including the level of using at least basic sanitation services (%), level of using at least basic drinking water services (%), ambient and household air pollution.
 
According to our research and computed standardised beta coefficients, the highest strength of the effect belongs to the level of using at least basic drinking water. Every single unit increase in the percentage of people using at least basic drinking water services provided the other factors remain constant, leads to 0.110 years or 40 days gap increase. It can be explained by the fact that life expectancy at birth will change at a faster pace that HALE. We can draw the opposite conclusion regarding ambient and household air pollution: here HALE will increase or decrease in faster pace than life expectancy.
 
Adjusted R-squared shows that 18.0 % variance in the dependent variable can be accounted for by the set of environment condition variables. According to F-test and p-value, this model is significant. Therefore, there is enough evidence in the data to suggest that the linear relation between the gap and general living conditions exists.

Improved Water Sources and Healthy Longevity

Improved drinking water source is a source that, by nature of its construction, adequately protects the water from outside contamination, in particular from faecal matter. Bad water supply causes the burden of communicable diseases and increases the risk of premature death, such a situation is observed in big cities and remote areas in South Africa, Indonesia, India, Brazil. Waterborne diseases are caused by drinking contaminated or dirty water. Contaminated water can cause many types of diarrheal diseases, including Cholera, and other serious illnesses such as Guinea worm disease, Typhoid, and Dysentery. Water related diseases cause 3.4 million deaths each year.

Ambient Air Pollution

Increase in ambient air pollution, concentration of fine particulate matter (PM2.5) contributes to exponential growth of ambient and household air pollution attributable death rate (per 100 000 population). The highest level of death ration is in India and China, the biggest industrial producers in the world. Diseases as a result of the pollution include acute lower respiratory infections, chronic obstructive pulmonary disease, stroke, ischemic heart disease, and lung cancer. The highest level of ambient air pollution across chosen countries is in Qatar. However Qatar’s pollution readings are some of the worst in the world, the number of deaths attributed to poor air quality is not as high. So, air pollution has health impacts even at very low concentrations.

Gap between HALE and Life Expectancy and Lifestyle Factors

The above factors indicating general lifestyle such as the prevalence of undernourishment, smoking, overweight among adults and alcohol consumption have a significant impact on the gap prediction. According to the standardised beta coefficient values, we can not highlight any dimension as the most powerful.
 
For instance, every single unit rise of overweight prevalence leads to 0.014 years or 5 days decrease in the gap between life expectancy and HALE. The effect of total alcohol consumption is the same: every single unit increase provided the other factors remain constant, leads to 0.038 year or 14 days decrease in the gap.
 
In general, the variance in lifestyle factors determines 15.5 % variance in the gap between life expectancy and HALE. The overall F-test defines that an assumed linear relationship is statistically significant whereas p-value for the model is less than the accepted significance level.

Obesity and Health-adjusted Life Expectancy

There is negative correlation between both HALE and life expectancy and prevalence of obesity. Singapore have the highest level of HALE and one of the lowest obesity rate, which is a result of compound impact of high quality of life, healthier behaviour and effective healthcare policies that tackle the rising burden of non-communicable diseases. The most recently available data from both the OECD and the WHO indicate that the U.S. has the greatest prevalence of obesity among high-income countries. Over a third of the U.S. is obese, compared to just over a fifth on average in comparable countries. The higher-than average rates of obesity across observed countries may contribute in some ways to the higher disease burden from cardiovascular conditions. Though rates of disease burden caused by these conditions have improved across countries, they still cause fairly large negative impact on HALE.

Alcohol Consumption and Gap between Life Expectancy and HALE

The graph shows that higher alcohol consumption leads to increase in gap between life expectancy at birth and health-adjusted life expectancy. Alcohol abuse cause increase in risk of premature deaths and it prevails among younger population (South Africa is an evidence). Higher alcohol consumption is associated with a greater risk of stroke, heart failure, and fatalities due to high blood pressure or a bulging or ruptured aorta.
 
Countries that consume less alcohol or more than global average are exposed to disaster of non-communicable diseases. So, any amount of drinking appeared to increase these risks.

Alcohol Consumption and Gap between Life Expectancy and HALE

The graph shows that higher alcohol consumption leads to increase in gap between life expectancy at birth and health-adjusted life expectancy. Alcohol abuse cause increase in risk of premature deaths and it prevails among younger population (South Africa is an evidence). Higher alcohol consumption is associated with a greater risk of stroke, heart failure, and fatalities due to high blood pressure or a bulging or ruptured aorta.
 
Countries that consume less alcohol or more than global average are exposed to disaster of non-communicable diseases. So, any amount of drinking appeared to increase these risks.

Smoking and Life Expectancy

Smoking is one of the biggest causes of preventable deaths. The poisons from the tar in cigarettes enter your blood. These poisons then make blood thicker, and increase chances of clot formation. Smoking damages heart and blood circulation, increasing the risk of conditions such as coronary heart disease, heart attack, stroke, peripheral vascular disease (damaged blood vessels) and cerebrovascular disease (damaged arteries that supply blood to your brain).
 
The level of smoking varies significantly across countries. Cigarettes cause harmful impact on health even at very low consumption.

Gap between HALE and Life Expectancy and Causes of Deaths

As a result of our research, the mentioned above reasons of death have a significant impact on the gap and its change. The highest prediction power belongs to communicable diseases and maternal, prenatal and nutrition conditions. The sign of its coefficient emphasizes that increase in a number of deaths caused by illnesses that result from the infection (HIV, hepatitis A, B and C, measles, salmonella) leads to 0.104 year decline in the gap - the fact that life expectancy at birth will decrease at a faster pace than HALE (health-adjusted life expectancy). The same conclusion we can make regarding non-communicable diseases.
 
In general, the variance in causes of death determines 32.3 % variance in the gap between life expectancy and HALE. The overall F-test defines that an assumed linear relationship is statistically significant whereas p-value for the model is less than the accepted significance level.

Communicable diseases and Life Expectancy

Worldwide, developed and developing countries are facing the double burden of communicable and noncommunicable diseases. However, developing countries are more exposed and more vulnerable due to a multitude of factors, including geographic, demographic and socio-economic factors.
 
Burden of communicable diseases prevails in developing and low-income countries. South Africa, India and Indonesia face the challenge to reduce deaths from communicable diseases and maternal, prenatal and nutrition conditions in younger age group (15-34 years).

Methodology of Analysis of Variance (ANOVA)

Analysis of variance (ANOVA) is a quantitative method used in statistics that splits an observed aggregate variability found inside a data set into two parts: systematic factors and random factors. The systematic factors have a statistical influence on the given data set. while the random factors do not. The ANOVA test used to determine the influence that independent variables have on the dependent variable in a regression study.
 
Dependent and Independent Variables
The dependent variable must be a continuous (interval or ratio) level of measurement. The independent variables must be categorical (nominal or ordinal) variables. A one-way ANOVA has just one independent and one dependent variable. MANOVA is used when there are two or more dependent variables.
 
Statistical Significance
The purpose of analysis of variance is to test for significant differences between means in different groups or variables, usually arranged by an experimenter in order to evaluate the effects of different treatments or experimental conditions on one or more outcome measures. The null hypothesis for an ANOVA is that there is no significant difference among the groups (the mean is the same). The alternative hypothesis assumes that there is at least one significant difference among the groups. To determine whether a set of means are all equal F-test is calculated. The test statistic is a measure that allows us to assess whether the differences among the sample means (numerator) are more than would be expected by chance if the null hypothesis is true. In general, if the p-value associated with the F is smaller than accepted level of significance (the most common is 0.05), then the null hypothesis is rejected and the alternative hypothesis is supported.
 
Basic Modeling Assumptions
● The population from which samples are drawn should be normally distributed.
● Independence of cases: the sample cases should be independent of each other.
● Homogeneity of variance: the variance among the groups should be approximately equal.
 
Research Question the MANOVA Examines
Are there any significant differences in economic, healthcare system, demographiс and environmental indicators across the countries by HALE level: low, medium and hig

Variance of Economic Factors across Groups of Countries

Multivariate ANOVA (MANOVA) extends the capabilities of analysis of variance by assessing multiple dependent variables simultaneously. This provides studying any interaction between the factors and increases the model's efficiency.
 
To verify the assumption about the differences in the level of economic development across countries we have included characteristics of general economic conditions into the MANOVA model. The main results are presented in the table. According to our research and computed F-ratios for each indicator statistically significant differences across groups of countries by HALE level can be observed for GDP per capita, urbanisation rate and degree of income inequality (Gini coefficient).
 
In general, we can determine that high HALE is of developed countries (Austria, France, Norway, Spain, Singapore, Switzerland). The longer health adjusted life expectancy the higher the standard of living and its quality. And this is not a reason but a consequence of developing infrastructure, advanced education system, wider range of services and their availability.

Human Development Index vs Global Gender Gap

The Human Development Index (HDI) is a summary measure of average achievement in key dimensions of human development: a long and healthy life, being knowledgeable and have a decent standard of living. The Global Gender Gap Report benchmarks countries on their progress towards gender parity across four thematic dimensions: Economic Participation and Opportunity, Educational Attainment, Health and Survival, and Political Empowerment.
 
All specified dimensions are important to compare countries with the same level of GNI per capita and find out how they can end up with different human development outcomes.

Variance of Health Financing and Service Delivery across Groups 89 of Countries

Base on the analysis of variance we have proved that healthcare funding and resourcing significantly differ across groups of countries by HALE level. According to our results in the table above, there are wide disparities in both health expenditures per capita between the groups (to a greater extent they are serviced by general government health expenditures) and the number of medical staff.

Variance of Health Financing and Service Delivery across Groups 89 of Countries

It is of fundamental importance to examine demographics in the context of health adjusted life expectancy. The main outcome of demographic processes is the distribution of the total population by age and gender which in turn determines features of population survival and reproduction mode.
 
According to our research and computed F-ratios for each indicator statistically significant differences across groups of countries by HALE level can be observed for crude birth rate and total fertility as measures of reproductive health, old-age dependency ratio and ageing coefficient as indicators of population ageing.
 
In general, we can define that high HALE is of countries with low birth rate far below the limit of simple reproduction and the oldest population. Fertility rate in developing countries with lower HALE level is on average higher (1.96 child per woman in comparison with 1.64) that slow down ageing process and reduces demographic burden borne by the working-age population.

Crude Birth and Death Rates

Many African countries have a very high crude birth rate, and women in those countries have a high total fertility rate, meaning they give births to many children in their lifetime. Countries with a low fertility rate (and low crude birth rate of 10 to 12 in 2016) include European nations, the United States, and China. Crude death rate has been falling around the world due to longer life spans brought about by a better food supplies and distribution, better nutrition, better and more widely available medical care (and the development of technologies such as immunizations and antibiotics), improvements in sanitation and hygiene, and clean water supplies. Much of the increase in world population over the last century overall has been attributed more to longer life expectancies rather than an increase in births.

Variance of Ecological Conditions across Groups of Countries

According to our study and computed p-values for each indicator statistically significant differences across groups of countries by HALE level can be observed for percentage of people using at least basic sanitation, drinking water services and ambient air quality, which estimates the occurrence of pollutants high enough concentrated to affect the environment and population health (it increases the risk of respiratory infections, heart disease, stroke, and lung cancer).
 
In general, we can determine that low HALE is caused by worse general living conditions in the group of low-income countries where populations are the most impacted. The prevalence of basic sanitation services and clean drinking water as well as anthropogenic climate and ecosystem changes contribute to the health of the population and specify its mortality mode.

Sanitation Facilities and Life Expectancy

Some 827 000 people in low- and middle-income countries die as a result of inadequate water, sanitation, and hygiene each year, representing 60% of total diarrhoeal deaths. Poor sanitation is believed to be the main cause in some 432 000 of these deaths. Diarrhoea remains a major killer but is largely preventable. Better water, sanitation, and hygiene could prevent the deaths of 297 000 children aged under 5 years each year. Open defecation perpetuates a vicious cycle of disease and poverty. The countries where open defection is most widespread have the highest number of deaths of children aged under 5 years as well as the highest levels of malnutrition and poverty, and big disparities of wealth.

Variance of Mortality Rates by Causes across Groups of Countries

Base on the analysis of variance we have proved that the number of deaths attributed to road traffic, non-communicable diseases (cancers, cardiovascular and chronic respiratory diseases), household and ambient air pollution, unsafe water and sanitation significantly differ across groups of countries by HALE level. According to our results in the table above, a low HALE level is related to the high mortality rate. That is supported by the previously analysed standard of living and its quality, health funding and resourcing, general ecological conditions.

Incidence of Tuberculosis

Despite a concerted global effort to reduce the burden of tuberculosis, it still causes a large disease burden globally. Strengthening of health systems for early detection of tuberculosis and improvement of the quality of tuberculosis care, including prompt and accurate diagnosis, early initiation of treatment, and regular follow-up, are priorities. Countries with higher than expected tuberculosis rates for their level of sociodemographic development should investigate the reasons for lagging behind and take remedial action. Efforts to prevent smoking, alcohol use, and diabetes could also substantially reduce the burden of tuberculosis.

Countries with High HALE and Life Expectancy:

General Summarised Description

Among chosen countries Singapore is the second by life expectancy and has the longest span of living in a good health (HALE) in 2016. Singapore topped the world in life expectancy in 2017 with an expected lifespan at birth of 84.8 years, surging ahead Japan by more than half a year. The average Singaporean also enjoys the longest span of living in good health - 74.2 years - but there has also been a rise in the number of unhealthy years people here live. Among the most important reasons of high HALE in Singapore are relatively young population, effective healthcare system, developed infrastructure and stable economic conditions. In 2016 Japan has the highest LE. The reason is that government is creating a health- and hygiene-conscious culture. This ranged from childhood vaccination programmes and the introduction of universal health insurance, to campaigns to reduce salt consumption, and the use of medication to reduce blood pressure. Another factor might be the lifestyle that Japan’s older population enjoy. Retirees in Japan stay active, and many older people continue working by choice rather than economic necessity. One more factor is eating habits and well-being. Luxembourg is also among leading countries by average life expectancy and HALE. These figures show high standard of living in Luxembourg based on Luxembourg's unspoilt environment, on its medical coverage and the quality of services provided.

Countries with High HALE and Life Expectancy:

Healthcare System Overview

Countries with High HALE and Life Expectancy:

Healthcare System Overview

Countries with High HALE and Life Expectancy:

Body Weight and Physical Estimates

Data from the World Health Organisation (WHO) estimates that the overall burden of disease in developed countries, such as Luxemburg, Austria, Norway, Sweden, Canada, Switzerland, Japan (measured in terms of DALYs) could be attributed to behavioural risk factors – including smoking, alcohol use, diet, and physical inactivity, with smoking and dietary risks contributing the most.

Countries with High HALE and Life Expectancy:

eHealth Efficiency

The further development and implementation of information technologies and e-health to improve healthcare delivery and patients’ satisfaction

Estonia

The Electronic Health Record (e-Health Record) is a nationwide system integrating data from Estonia’s different healthcare providers to create a common record every patient can access online.
 
Functioning very much like a centralized, national database, the e-Health Record actually retrieves data as necessary from various providers, who may be using different systems, and presents it in a standard format via the e-Patient portal. A powerful tool for doctors that allows them to access a patient’s records easily from a single electronic file, doctors can read test results as they are entered, including image files such as X-rays even from remote hospitals.
 
Patients have access to their own records, as well as those of their underaged children and people who have given them authorization for access. By logging into the e-Patient portal with an electronic ID-card, the patient can review doctor visits and current prescriptions, and check which doctors have had access to their files.

Canada

Health Canada's priorities and efforts have focused on addressing policy issues and challenges in mainstreaming eHealth services within Canada's health care system and in measuring progress in the deployment and investment of these services.
 
A fundamental building block of all these applications is the Electronic Health Record, which allows the sharing of necessary information between care providers across medical disciplines and institutions. Other important uses of eHealth are found in the areas of continuous medical education and public health awareness.
 
eHealth is an essential element of health care renewal: its application to Canada's health care system will result in benefits to Canadians through improvements in system accessibility, quality and efficiency. The Government of Canada has been making investments in this area since the 1997 Federal Budget, including federal commitments towards First Ministers Agreements (September 2000 and 2003). A key factor in the success of the Government's work is its strong commitment to collaboration.

Countries with Medium HALE and Life Expectancy:

General Summarised Description

In the above groups Malta is a leading country by average HALE; Netherlands has the highest average life expectancy among chosen countries - 81,6 years. This is 1.3 years less than the previous group leading country. China has the lowest difference between HALE and life expectancy, it overtakes the USA for healthy lifespan by 2,6 years average.
 
Maltese people spend on average 90% of their lifespan in good health, longer than in any other EU member state. The increase in healthy lifespan was mainly driven by a reduction in premature deaths from cardiovascular diseases, though these remained the leading cause of death for both Maltese men and women. Cancer is the second highest cause of death followed by respiratory diseases and diseases of the nervous system. However, according to numerous studies, prevalence obesity remains the highest in the EU, representing a significant public health challenge.
 
China is still developing: recently improvements in the provision of public health services, particularly in infant and maternal health, have been the biggest factors in raising life expectancy.
 
In Netherlands people are living longer than ever before, but according to the World Health Organisation (WHO) they are not living healthier lives - the difference between HALE and life expectancy is comparatively high.

Countries with Medium HALE and Life Expectancy:

Healthcare System Overview

Universal health care schemes

Germany

Germany has a universal multi-payer health care system scheme for by a combination of:
  • statutory health insurance (Gesetzliche Krankenversicherung);
  • private health insurance (Private Krankenversicherung).
 
Social health insurance system is decentralized with private practice physicians providing ambulatory care, and independent, mostly non-profit hospitals providing the majority of inpatient care. Employers pay for half of their employees' health insurance contributions, while self-employed workers pay the entire contribution themselves.
 
Approximately 90% of the population is covered by a statutory health insurance plan.The rest are covered by private health insurance.

Netherlands

The Netherlands has a dual-level system. All primary and curative care is financed from private compulsory insurance. Long term care is covered by social insurance funded from taxation. According to the WHO, the health care system in the Netherlands was 62% government funded and 38% privately funded.
 
Hospitals in the Netherlands are also regulated and inspected but are mostly privately run and not for profit, as are many of the insurance companies. Patients can choose where they want to be treated. Insurance companies can offer additional services at extra cost over and above the universal system laid down by the regulator, e.g., for dental care. Persons with low incomes can get assistance from the government if they cannot afford these payments.

Costa Rica

Universal healthcare and pensions are run by the Caja Costarricense de Seguro Social (CCSS). By covering all population groups through the same system, Costa Rica has avoided social insurance stratification. CCSS is funded by a 15 percent payroll tax, as well as payments from retiree pensions. Taxes on luxury goods, alcohol, soda, and imported products also help to cover poor households who do otherwise pay into the system. All CCSS funds are merged into a single pool, which is managed by the central financial administration of CCSS.
 
Through the CCSS, health care is essentially free to nearly all Costa Ricans. Private health care is also widely available and INS offers private health insurance plans to supplement CCSS insurance.

Countries with Medium HALE and Life Expectancy:

Healthcare System Overview

Private health insurance

Czech Republic

Private health insurance is available in the Czech Republic. However, it may entail more paperwork on application compared to public health insurance.
 
There is always a possibility that some public hospitals and doctors might not recognise the insurance provider and may require the patient to make payment for any treatment up front. This may create a financial burden for the patient, especially when involving major surgeries.
 
Some private health insurance companies may require medical checks for their insurance. These checks may include blood tests as well as just simple questions about smoking and allergies.

Portugal

Private healthcare is available in Portugal but it tends to be costly.
 
Private clinics are available especially in the more densely populated tourist areas. Many foreigners or expats choose to opt for private healthcare insurance to cover private medical treatment, as they feel that the Portuguese State healthcare is inadequate to fulfill their needs.
 
The state healthcare service provides free or subsidised medical and dental treatment, including care and treatment by GPs and consultants, hospital care, laboratory services, subsidised prescription medicine, maternity care, surgical appliances and emergency ambulance transportation.

China

Due to a variety of factors, the quality of medical care is continuously improving in China, especially after the Chinese government started allowing foreign entities to invest in private hospitals in 2012. Expats seeking treatment in China will likely find that the quality of healthcare varies significantly between institutions. This, combined with an imposing language barrier, may make it hard to navigate around the country’s public healthcare system. However, fees charged in private and international facilities are often very expensive, and sometimes even more expensive than the fees charged in the US. Expats are advised to secure private medical insurance in China to offset these potentially high costs.

Countries with Low HALE and Life Expectancy:

General Summarised Description

All countries in these groups are united by a sign of unhealthy behavior of population. Analysis shows that Americans have much higher rates of smoking and obesity than their counterparts in high-income countries, therefore USA belongs to the group of Low HALE and Life Expectancy with a high gap between these indicators.
 
There are few factors which mostly affect HALE and life expectancy levels in the aforementioned countries:
1) the opioid epidemic and suicides;
2) prevalence for obesity;
3) level of healthcare expenditures;
4) income disparity across the country;
5) living standards.
 
World life expectancy continues to increase on the whole, but these countries (except the USA) are still lagging behind. In order to increase the longevity and potential of their citizens’ lives, they will require targeted aid and a focus on infrastructure and healthcare.

Countries with Low HALE and Life Expectancy:

Healthcare System Overview

Universal health care schemes

USA

The United States as a whole does not have a fully implemented universal health care system, but about 92% of its citizens have health insurance coverage as of 2017.
 
The Patient Protection and Affordable Care Act (PPACA) as amended by the Health Care and Education Reconciliation Act of 2010, sought to have expanded insurance coverage to legal residents by 2014.
 
Full implementation of the ACA was blocked when some states refused to implement Medicaid expansion that would have increased subsidies of moderately low-income households.
 
From the enactment of the ACA in 2010 until at least 2017, the portion of U.S. residents without health insurance has been decreasing.

Mexico

Public health care delivery is accomplished via an elaborate provisioning and delivery system instituted by the Mexican Federal Government. Public care is either fully or partially subsidized by the federal government, depending on the person's (Spanish: derechohabiente's) employment status.
 
Employed citizens and their dependents, however, are further eligible to use the health care program administered and operated by the Mexican Social Security Institute. The IMSS health care program is a tripartite system funded equally by the employee, its private employer, and the federal government.
 
In August 2012 Mexico achieved universal health care system.

Argentina

Health care is provided through a combination of employer and labor union-sponsored plans (Obras Sociales), government insurance plans, public hospitals and clinics and through private health insurance plans.
 
It costs almost 10% of GDP and is available to anyone regardless of ideology, beliefs, race or nationality. A system of public medical facilities is maintained by the government. The public system is highly decentralized, as it is administered at the provincial level; often primary care will be regulated autonomously by each city.
 
Since 2001, the number of Argentines relying on public services has seen an increase.Currently, about half of the population uses the public system.

Countries with Low HALE and Life Expectancy:

Healthcare System Overview

Private health insurance

Estonia

The Estonian health care system incorporates a compulsory insurance system and universal access to medical services that are made available through private health providers.
 
The Ministry of Social Affairs oversees the administration of the system with numerous agencies, public independent bodies, private health care units, hospitals, NGOs and professional associations all coordinating beneath them. Local governments have a minor, voluntary role in organizing and financing medical services. Estonia’s integrated system has received international commendation for its ability to act efficiently on health care reform, but considerable challenges still persist regarding accessibility and quality of health care.

Brazil

One of the biggest social problems in Brazil comes with the nation's healthcare service, or lack thereof. The public Brazil healthcare system is a bureaucratic nightmare and is regulated by Federal, State, and Municipal governments working together.
 
As would be expected of such a system this leads to slow treatment times, overworked medical staff, limited healthcare coverage, and lower quality treatment. Outside of the Brazilian Public healthcare system there are a number of private treatment facilities, however these tend to be much more expensive than any of the country's other medical centers but are able to provide treatment that is of a much higher quality.

Russia

The private healthcare system in Russia is able to provide extremely high quality service and treatment options, however these services are much more expensive than others.
 
Due to this high cost for treatments the Russian health insurance industry is starting to become a major force as many people want access to these higher quality services are unable to pay for treatment out of pocket health insurance is being seen as a vital necessity in Russia. This is also true for many expatriates in the country who are not willing to receive treatment at one of the nations many public hospitals, and almost all foreign nationals in Russia are discovering that the only way to truly protect themselves.