Factors influencing life expectancy at birth in japan from 1970 2017

World Bank 1997 pointed out that there is a strong positive relationship between life expectancy and per capita income in the case of developing countries.. Wilkinson 1996 explained afte

Health is one of the most priceless assets of human being has It permits us to fullydevelop our capacities Whenever this asset erodes, it indicates physical and emotionalweakening, causing obstacles in the lives of people Therefore, human beings havecontinuously sought to improve their skills and to reach a life that is more and moredignified; for this reason, improvement in health has always been, today as in the past,one of the most important social objectives (AESS, 2015)

To assess this regard, it can’t help mentioning the life expectancy at birth index It’sthe determinant of HDI, the human development index, a synthetic measure reflectinghuman development in terms of income, knowledge, and health and this index assessesthe level of socio-economic development of countries and territories Therefore, it iscrucial to identify the factors which contribute to the health of the population in generaland the life expectancy in particular The information on the nation’s health status helpspolicymakers and practitioners in their search for cost-effective mechanisms, providinghealth services and reallocation of health resources to optimize the gains from healthexpenditures (AESS, 2015)

In almost all parts of the world, improvements in health and sanitation conditions,better living standards, higher educational attainments, and advancements in medicaltechnologies are enabling people to live longer Compared to other countries, Japan leadsthe world (V Yong & Y Saito, 2009) , of which the position remained the highest lifeexpectancy at birth index country, and even regularly increasing year by year

Historically, there have been a lot of scientists, researchers, experts implementingthese relevant to this topic On the other hand, Japanese people always make the wholeworld admired not only by the innovative inventions with extremely high applicabilitybut also by cultural beauty, good manners, daily habits, and lifestyles All of these havecreated a living environment, the prerequisite for the highest life expectancy at birthindex in the world

However, there are not many studies that have used quantitative research methods tolearn about the factors affecting life expectancy at birth in Japan to identify the level ofinfluence of those factors in detail This study is one of very few studies which have

investigated the effects of Nurses and midwives, School enrollment, tertiary, Population density, Communications, computer, etc - the development of technical science, Forest

area, Daily smokers in Japan on life expectancy The data in previous studies are often

taken from old data sources, not updated to the present time, 2019 That makes the results

of research and analysis no longer accurate, causes bad influence to recommendations,suggestions after the investigation in the study Moreover, using time-series data method

to clarify the relation between those indicators and is life expectancy even rarer

Because of such shortcomings, it is difficult for other countries with the same level

of economic development to draw lessons from Japan Other developed countries likeChina, America, Germany all have a much lower life expectancy index The Japanesecan teach the world how to get a healthy and happy life from their wonderful culture

Therefore, we chose this highly urgent topic “Factors influencing life expectancy

at birth in Japan from 1960 to 2017” The objective of our assignment is to investigate the indicators and make recommendations, suggestions for other countries to improve the

health living standard and develop the country

LITERATURE REVIEW

There are many studies that investigated the determinants of life expectancy and

their dimensional influence on the issue Grossman (1972) investigated that inflation has

a negative relationship with life expectancy, and household welfare is largely disturbed

with rising prices Rogers (1979) first time gave a conceptual framework for life expectancy and income Robert Barro (1996) studied a panel of 100 countries from 1960

to 1990 and found that the growth rate of real per capita GDP was associated with longer

life expectancy World Bank (1997) pointed out that there is a strong positive relationship between life expectancy and per capita income in the case of developing countries.

Davies and Kuhn (1992) found health intake and availability of food determine the

health outcomes They concluded that investment in the health sector, social security

programs would decide life expectancy Mahfuz (2008) focused on primary health care

program as an important determinant of life expectancy On the base of his study, heconcluded that there is a positive relationship between primary health care spending andhealth status

Hill and King (1995) and Gulis (2000) investigated that education especially female education plays an important role in improving the overall life expectancy Williamson and Boehmer (1997) studied that educational status improves female life expectancy

dramatically, their study is based on 97 cross-sections

Anand and Ravallion (1993) investigated that there is a positive and significant

relationship between life expectancy and per capita GNP, but it works through nationalincome and public expenditures on health They mentioned that when public expenditures

on health and poverty used as independent variables with per capita GNP the results are

inverse to the first model Wilkinson (1996) explained after achieving a threshold level of

per capita income, the relationship between life expectancy and standard of living todisappear and further increase in income is not attached to life expectancy gains Hementioned a direct relationship between health and income of the people at thresholdlevel and there is no consistent relationship between them

In a statistical analysis of life expectancy across countries using multiple regression,

Tony Smith (2000) regressed Life Expectancy at Birth with a wide range of economic and

social variables as below:

❖ Economy:

1 GNP per capita ($US) 1995;

2 GNP per capita annual growth rate (%) 1980-1995;

3 Real GDP per Capita ($ Purchasing Power Parity) 1995;

4 Average Annual Rate of Inflation (%) 1995;

5 Country Development (1=developed, 0=underdeveloped)

❖ Population Characteristics:

6 Urban population (% of total) 1995;

7 Urban population annual growth rate (%) 1970-1995;

8 Annual population growth rate (%) 1970-1995

18 Telephone Lines (per 1000) 1995;

19 Electricity Consumption per Capita (kwh) 1995;

20 Commercial Energy Use per Capita (kg) 1994

❖ Education:

21 Adult Literacy Rate (%) 1996;

22 School Enrollment Rate (%) 1995 - Combined first-second and third-level

❖ Environment:

24 Access to Sanitation (% of population) 1990-1996;

25 Forest & Woodland (% of land area) 1995;

26 Annual Rate of Deforestation (%) 1990-1995;

27 CO2 Emissions per Capita (Metric tons) 1995

After the experiment with 27 variables reflecting the diverse components of life,Tony removed variables such as GDP in PPP, telephone lines, urban growth, literacy,contraceptive prevalence rate, commercial energy use, radios, and country development(dummy variable) By removing variables with high multicollinearity, he increased thesignificance of factors such as GDP per capita, fertility rate, school enrollment rate, andpopulation growth whose consequence was muted due to the multicollinearity problem.According to this study, GDP per capita, fertility rate, school enrollment rate, andpopulation growth showed a high-level effect on life expectancy at birth through theregression method

Gulis (2000) studied factors influencing life expectancy of 156 countries in the world He concluded that income per capita, public health spending, safe drinking water; calorie intake and literacy are the main determinants of life expectancy Hussain (2002)

investigated the determinants of life expectancy by using the cross-sectional data of 91developing countries of the world, with the help of multiple OLS through fertility rate,per capita GNP, adult literacy rate and per capita calorie intake; he studied thisrelationship both in linear as well as log linear model

World Health Statistic (2010) suggested that Health workforce, infrastructure, and

essential medicines may affect life expectancy at birth This section presents data on theresources available to the health system – this includes physicians; nurses and midwives;other health-care workers; and hospital beds These factors are essential in enablinggovernments to determine how best to meet the health-related needs of their populations

Abdalali (2015) investigated the effects of inflation and unemployment, gross capital formation and economic development level (as economic factors), urbanity (as a

social factor) and CO2 emission (as an environmental factor) on life expectancy usingpanel data method Through the results, the economic indices used in this study have aremarkable impact on life expectancy as well as urbanization

Chhabli (2018) pointed out several socio-demographic, disease prevention indicators,

lifestyle and health financing components that have some association with life expectancy

Based on the result, sanitation coverage, child vaccination, and population growth aresignificantly associated with life expectancy at birth.

Amiri & Solankallio (2019) collected data from 35 OECD countries to investigate the relationship between nurse staffing and life expectancy at birth They stated that there

were meaningful relationships from nurse staffing to life expectancy at birth The role ofnursing characteristics in increasing life expectancy varied among different health caresystems of OECD countries and on average was determined at the highest level in Japan.Hence, among OECD countries, the highest effect of practicing nurses on increasing thelife expectancy indicators have been investigated in Japan

Rei & Takeshi (2019) made a comparison of equity preferences for life expectancy

gains between Japan and Korean The study indicates that non-smokers tend to have ahigher life expectancy Therefore, smoke status has a close association with lifeexpectancy in Japan

METHODOLOGY & DATA

1 Theoretical framework of the study

1.1 Method used in research

To implement this topic, our group makes hypotheses about the factors related tolife expectancy at birth in Japan from 1960 to 2017 Japanese society had a lot offluctuations since the late 1970s Because of the economic crisis, the birth rate of Japan atthat time dropped significantly, affecting the average life expectancy But recently, thegovernment has taken reforms to reverse the population situation

Method of constructing econometric models: Going from studying economics, social and environmental assumptions related to the current medical issues, then construct

an econometric mathematical model by defining the mathematical function form of themodel with variable factors influence life expectancy at birth in Japan

Method of Functional estimation: Our group use Gretl software to run model

regression by using the Ordinary Least Squares method (OLS) to estimate the parameters

of multivariate regression models The OLS least squares method is a simple, easy tounderstand and implement method; give us the optimal estimates, the properties that wewant Parametric estimates by the OLS method have the following properties: Linear, Notdeviate, There is the smallest variance in the class of non-biased linear estimates

Method of Hypothesis test: From Gretl software we easily: Consider the differential

magnification molecule VIF to identify Multi-collinearity Use the White test to testHeteroskedasticity Conducting Robust tests to identify the Autocorrelation Use the Ftest to evaluate the fit of the model and the t-test to estimate the confidence interval forthe parameters in the model

Our group proceeded to interpret the regression results, subsequently, makeforecasts, analysis and finalize essays

1.2 Build theoretical models

According to previous studies all over the world, in order to test the influence offactors on life expectancy, our team applied the theoretical basis as mentioned andproposed the following mathematical model:

lifeexp = f (nurse, schenr, popden, comserv, frstarea, smkr)

lifeexp = β 1 + β 2 * nurse + β 3 * schenr + β 4 * popden + β 5 * comserv + β 6 * frstarea + β 7 * smkr + U i

In the model:

❖ Independent variables: lifeexp

= Life expectancy at birth

❖ Dependent variables:

nurse = Nurses and midwives

schenr = School enrollment, tertiary

popden = Population density

comserv = Communications, computer, etc

frstarea = Forest area

smkr = Daily smokers in Japan

2.1 The method of data collection

Our team collects data on variables based on a variety of sources, which have been verified to be highly accurate The data on life expectancy at birth in Japan from 1970 - 2017and other statistics of Nurses and midwives, School enrollment, tertiary, Population density, Communications, computer, etc - the development of technical science, Forest area were taken from the World Bank with the range from 1970 – 2017

http://microdata.worldbank.org/index.php/home Meanwhile, the data Daily smokers in Japan with the same number of years, were taken from https://ourworldindata.org/smoking https://www.cdc.gov/tobacco/data_statistics/fact_sheets/health_effects/tobacco_related_mortality/index.htm

The collected data is in the form of secondary information, collected for Japanduring the period 1970 - 2017 The dataset structure is time-series and the frequency ofthis time-series dataset is annual

The table below explains the reasons why those variables are chosen.

Table 2.2.1 Descriptive Table Independent variables

Sign Name Unit Explanation of selection & Research hypothesis

Life expectancy at birth reflects the overall mortalitylevel of a population It summarizes the mortality

Life pattern that prevails across all age groups - children

total and adolescents, adults and the elder

Sign Name Unit Explanation of selection & Research hypothesis

Japan is famous for the world's leading medicine andhealthcare system The average life expectancy ofthe Japanese people is rated highest level on the

nurse Nurses and per 1,000 planet Amiri & Solankallio (2019) found out the

midwives people highest effect of practicing nurses on increasing the

life expectancy indicators Increase the number ofdoctors, Nurses and midwives, Improve healthservices at health facilities, factors that can

improve the quality of health services, which makethe life expectancy at birth in Japan increase

Japan aims to ensure the harmonious development ofchildren in all aspects: heart, intellect, affection,spirit, attitude, value system, humanity Japan isone of the developed countries in the world with theactual illiteracy rate of 0 and 72.5% of the students

schenr School attending up to university, college and secondary.

enrollment, % gross The development of education is the basis to ensuretertiary stable social development and quality of life

Tony Smith (2000) also showed a high-level effect

of School enrollment, tertiary on life expectancy atbirth through the regression method The higher %School enrollment, tertiary is, the higher lifeexpectancy at birth in Japan reaches

Japan's population is 127.2 million, accounts for1.68% of the world's population, ranks 11th in thehundred topmost populous country in the world However,

Japan is facing the situation to be felt into the agingPopulation people per

comserv ations, service cutting-edge innovations, which are favorable

computer, imports, conditions for knowledge development and nationaletc BoP medical system It’s obviously that the Japanese

population made great strides in achieving higher

levels of life expectancy inferred the improvement

of technology in the modern world

Agents may invest in environmental care, depending

on how much they expect to live In turn,environmental conditions affect life expectancy Theproportion of forest land covered by a country is an

frstarea Forest area ‰ of land important environmental security indicator Forests

area provide human with the abundant resources, oxygen

and absorb CO2 emission It ensures our life,protects human health Increase in the proportion

of the Forest area has positive effect on lifeexpectancy of Japaneses

According to data and statistic from Centers forDisease Control and Prevention, Life expectancy forsmokers is at least 10 years shorter than for

Daily nonsmokers Quitting smoking before the age of 40

million reduces the risk of dying from smoking-related

Table 2.2.2: Summary Statistics, using the observations 1970 – 2017

(Source: the team synthesized under the support of Gretl software)

From the table, we can easily see that:

❖ Life expectancy at birth of Japanese from 1960 to 2017 fluctuates from 71.95 to 84.100, the average value is 79.415, the mean is 79.275

❖ Numbers of Nurses and midwives in Japan per 1,000 people from 1960 to 2017 fluctuates from 5.567 to 11.638, the average value is 7.0945, the mean is 7.943

❖ School enrollment, tertiary index (% gross) reflect quality of education from 1960

to 2017 fluctuates from 0.17200 to 0.65800, the average value is 0.35750, the mean

is 0.40698

❖ Population density (hundred people per sq km of land area in Japan) from 1960 to

2017 fluctuates from 2.8455 to 3.5134, the average value is 3.4215, the mean is3.3409

❖ ‰ of service imports, BoP, Communications, computer, etc show the development

of technical science from 1960 to 2017 fluctuates from 3.0171 to 6.3172, theaverage value is 4.2975, the mean is 4.3630

❖ ‰ of land area covered with Forest in Japan from 1960 to 2017 fluctuates from 6.8247 to 6.8484, the average value is 6.8387, the mean is 6.8390

❖ Number of Daily smokers in Japan from 1960 to 2017 fluctuates from 21.734 to 33.059, the average value is 31.757, the mean is 29.809