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The purpose of this paper is to investigate the trend of life expectancy in Bangladesh and find the effect of eliminating the causes of diseases on life expectancy statistics.

Data consisted of 1,530 deaths in 2000, 1,582 deaths in 2004 and 1,514 deaths in 2008 that were collected from the Health and Demographic Surveillance System of International Centre for Diarrheal Disease Research, Bangladesh. Trends in life expectancy after eliminating the cause of diseases were examined by a Single Decrement Life table.

The expectation of life for both male and female presented differing patterns. Results showed that life expectancies were greatly reduced in the presence of all groups of non-communicable diseases (NCDs) in the community, whilst life expectancies were significantly improved if all NCDs within all disease groups were completely eliminated. The life expectancies in the presence of NCDs showed lowest expected years among all the present diseases groups and the life expectancies eliminating NCDs showed highest expected years among all the eliminating diseases groups. The results indicated that 10.99 years of life would be added to life expectancy at birth for the male population and 8.82 years for the female population in 2008 if NCDs were eliminated.

The findings of this study provide useful information which could contribute to a more effective allocation of targeted funding for developing public health programs. Lowering mortality by eliminating major groups of diseases results in higher life expectancy ratings. Specifically, the relative impacts of eliminating cardiovascular diseases and respiratory diseases, as compared with eliminating neoplasms.

This study aims to explain the role of health on economic growth for OECD countries in the context of sustainable development. Accordingly, the study investigates the relationship between health and economic growth in OECD countries.

This study employed cluster analysis and econometric methods. By cluster analysis, 12 OECD countries (France, Germany, Finland, Slovenia, Belgium, Portugal, Estonia, Czech Republic, Hungary, South Korea, Poland and Slovakia) were classified into two clusters as high and low health status through health indicators. For panel threshold analysis, the data included growth rates, life expectancy at birth, export rates, population data, fixed capital investments, inflation and foreign direct investment for the period of 1999–2016.

The study determined two main clusters as countries with high health status (level) and low health status (level), but there was no threshold effect in clusters. It was concluded that an increase in the life expectancy at birth of countries with higher health status had no significant impact on economic growth. However, the increase in the life expectancy at birth of countries with lower health status influenced economic growth positively.

This study used data that including period of 1999–2016 for OECD countries. In addition, the study used cluster analysis to determine health status of countries, and then panel threshold analysis was preferred to explain significant relations.

This study showed that the role of health on economic growth can change toward country groups as higher and lower health status. It was proved that higher life expectancy can influence economic growth positively in countries with worse or low health status. In this context, developing countries, which try to achieve sustainable development, should improve their health status to achieve economic and social development at the same time.

This study investigates the impact of total health expenditure on life expectancy in a panel of 43 African countries from 2000 to 2018.

The dynamic panel generalized method of moments (GMM) estimation method developed by Arellano and Bond (1991) is used in this study. This approach generates estimates that are heteroskedasticity and autocorrelation consistent, as well as controls for unobserved time-invariant country-specific effects and eliminates any endogeneity in the panel model.

The results reveal that health expenditure on its own has a positive significant influence on life expectancy. However, health expenditure via the moderating effect of government effectiveness reduces life expectancy. The authors also observe that school enrollment and the level of economic activity significantly drive life expectancy.

The study is limited to 43 out of 54 African countries, and it covers a period of 18 years: 2000 to 2018.

The authors argue that larger health expenditure will aid in improving the life expectancy rate in Africa. However, in practice, this would be difficult given the needs of other priority sectors.

Since most developing countries' health expenditures are small, a policy option is that healthcare services should be subsidized such that the poorest people can also access them.

The study differs from the previous attempts, and with this, the authors contribute significantly to the literature. First, to the best of the authors’ knowledge, the authors are unaware of any study considering the role of government effectiveness as a moderating factor in investigating the effect of health expenditure on life expectancy in the African context. Thus, the authors fill a yawning gap in the literature. Second, the authors employ a recent dataset with larger sample size. Finally, to address the problem of endogeneity and simultaneity bias, the authors use the system GMM technique.

The Epidemiologic Transition can help us understand a fundamental puzzle about aging. The puzzle stems from two seemingly contradictory facts. The first fact is that death rates from noninfectious degenerative maladies – the so-called diseases of aging – increase as people age. It seems to be at odds with the historical fact that for nearly a century in which people were aging more than ever before, the aggregate rates of such diseases have been decreasing. In what sense can both be true? Crucial to resolving the puzzle are the age-profiles of such diseases in cohorts that grew up in the different regimes of the Transition. For each cohort, noninfectious diseases had increased with age, resulting in an upward-sloping age profile, which affirms the first fact. As the regimes were transitioning from the Malthusian to the modern one, however, the profiles of successive cohorts had been shifting downward: death rates from noninfectious diseases were shrinking at each age, signifying the newer cohorts’ greater aging potentials. The shifting profiles had been renewing the cohort mix of the population, shaping the century-long descent of such diseases in aggregate, giving rise to the historical fact. The profiles had shifted early in the cohorts’ adult years, associating closely with the newer epidemiologic conditions in childhood. Those conditions appear to be a circumstance under which aging potentials of cohorts could be misgauged, including in one troubling episode in the first half of the nineteenth century when the potentials had reversed.

The aim of this research is to investigate the causal relationship between trade openness (TO) and life expectancy (LE) at birth in Latin American countries over the period of 1980–2014.

The bootstrap panel Granger causality test proposed by Emirmahmutoglu and Kose (2011) was used to determine the direction of causality in the presence of cross-sectional dependency and heterogeneity among Latin American countries. Also, four different tests were employed in order to determine the cross-sectional dependency and slope homogeneity. The stationarity properties of variables were inspected by employing a unit root test.

The findings indicated that Granger causality existed between TO and LE, at birth which was running from the former to the latter for panel. On a country basis, TO Granger caused LE at birth for countries with low level of economic development and higher taxes on income and profits.

This study provides new insights for policymaking regarding the role of TO in achieving comprehensive economic reforms to increase LE at birth during a period of intense trade rivalry across nations.

Although research in the literature has mainly focused on the impact of TO on LE at birth with panel data, most studies ignored the regional effects. It is the authors’ concern that the direction of causality can be country-specific and have regional characteristics. In this regard, instead of dividing countries for a specific region into two parts such as developing and developed, the authors investigated the pattern of trade–health link for a specific region, Latin America.

Knowledge about current size and structure of a country's population is needed for the formulation and implementation of policies and programs in almost all sectors of public life. The purpose of this paper is to provide population projection for Oman, using population census and family health survey data.

Component method is used for projecting future population of Oman. Population Census data of 2003 by sex and by five‐year age groups were used. The base life expectancy of Oman is assumed to be 73 years and the base total fertility considered as 5.1 children per woman.

Depending upon the achievement of replacement fertility by the year 2025 or 2030 or 2035 the population of Oman in 2050 will vary from 4.5 million to 5.0 million. The different scenarios of population projection indicate that the population of Oman will not be stabilized before 2100.

Population projection depends on assumptions about mortality, fertility, base life expectancy and migration. If these assumptions change then the projections will also change.

Because of high fertility in the past, women in the reproductive ages will increase for up to several decades. Thus, population growth will continue because of momentum effect, even if Oman achieves replacement fertility say in 2030. The age at marriage will increase.

The rapid socio‐economic development and increased women empowerment will create a new outlook and ideas about lifestyles, leading to a decline in fertility. The decline in fertility is strongly related to social, health, education, employment opportunities of women and economic development, which through a variety of mechanisms, reduces the fertility desired and increases the fertility regulation through contraception, birth spacing and increased age at marriage of females. Because of increase in life expectancy and falling birth rate, the absolute number of the elderly population will have enormous impact on health care needs and hospitalization.

This paper deals with the population projection of Oman. Timely and accurate information about population trends is crucial for the socio‐economic development of a country. Knowledge about current size and structure of a country's population is needed for the formulation and implementation of policies and programs in almost all sectors of public life such as health, education and employment.

Background: This study aimed to appraise the monetary value of human life losses associated with COVID-19 in Turkey. To our knowledge, it is the first study in Turkey to value human life losses associated with COVID-19.

Methods: A human capital approach (HCA) model was applied to estimate the total monetary value of the 4,807 human lives lost in Turkey (TMVHL) from COVID-19 by 15 June 2020. The TMVHL equals the sum of monetary values of human lives lost (MVHL) across nine age groups. The MVHL accruing to each age group is the sum of the product of discount factor, years of life lost, net GDP per capita, and the number of COVID-19 deaths in an age group. The HCA model was re-calculated five times assuming discount rates of 3%, 5%, and 10% with a national life expectancy of 78.45 years; and the world highest life expectancy of 87.1 years and global life expectancy of 72 years with 3% discount rate.

Results: The 4807 human life losses from COVID-19 had a TMVHL of Int$1,098,469,122; and a mean of Int$228,514 per human life. Reanalysis with 5% and 10% discount rates, holding national life expectancy constant, reduced the TMVHL by Int$167,248,319 (15.2%) and Int$ 429,887,379 (39%), respectively. Application of the global life expectancy reduced the TMVHL by 36.4%, and use of world highest life expectancy increased TMVHL by 69%. However, the HCA captures only the economic production losses incurred as a result of years of life lost. It ignores non-market contributions to social welfare and the adverse effects of economic activities.

Conclusions: Additional investment is needed to bridge the persisting gaps in international health regulations capacities, universal health coverage, and safely managed water and sanitation services.

While science has researched the impact of air pollution on human health, the economic dimension of it has been less researched so far. Renewable energy consumption is an important factor in determining the level of life expectancy and reducing health expenditure. Thus, this study aims to investigate the impact of renewable energy, carbon emissions, health expenditure and urbanization on life expectancy in G-7 countries over the period of 2000–2019.

This study has adopted a novel Method of Moments Quantile Regression (MMQR). Furthermore, as a robustness check for MMQR, the fully modified ordinary least square, dynamic ordinary least squares and fixed effect ordinary least square estimators have been used.

The results indicated that renewable energy consumption, health expenditure and urbanization lead to an increase in life expectancy across all quantiles (5th to 95th), whereas higher carbon dioxide emissions reduce life expectancy at birth across all the quantiles (5th to 95th).

The empirical findings conclude that governments should recognize their potential in renewable energy sources and devise policies such as tax-related regulations, or relevant incentives to encourage further investments in this field.

This paper in comparison to the other research studies used MMQR to investigate the impact of factors affecting life expectancy. Also, to the best of the authors’ knowledge, so far no study has investigated the impact of renewable energy on life expectancy in G-7 countries.

The purpose of the study is to examine the relationship between air pollution and life expectancy considering the roles of institutional quality, agricultural output, foreign direct investment (FDI) and other socio-economic variables in Nigeria from 1981Q1 to 2019Q4.

The study employed spliced quarterly data from annual series collected from the World Bank development indicators and Central Bank of Nigeria. The dynamic multivariate models were analysed using the vector error correction mechanism (VECM), variance decomposition and Granger causality techniques.

The VECM result indicated a statistically significant adverse effect of air pollution on life expectancy. However, institutional quality, gross domestic product per capita, agricultural output, government social expenditure and school enrolment rate ameliorate the adverse health effects of air pollution, while FDI had mixed effects on life expectancy at different significance levels and at varying lag lengths. The Granger causality result revealed a uni-directional causality from air pollution to life expectancy; bidirectional causal chain between agriculture, FDI, government social expenditure and life expectancy, while a uni-directional causal linkage run from life expectancy to income per head and from school enrolment to life expectancy respectively. However, there is no evidence of causation between institutional quality and life expectancy due to weak institutional quality, but foreign direct invest causes carbon emission in a uni-directional manner in line with pollution haven hypothesis.

The study's modelling is limited by not considering the resource curse variable in the model due to paucity of data. Nigeria is the biggest crude oil exporter in Africa and ranks 13th globally with daily output of about 2.4 m barrels. Thus, the negation of resource curse in air pollution–life expectancy nexus de-emphasises the effectiveness of rich resources on health and environment. Future studies could address this limitation by incorporating resource curse in environmental-health models for Nigeria.

It is imperative for the country to adopt stringent anti-air pollution strategies that would establish a balance between FDI attraction and agricultural expansion to the benefits of her citizens' longevity. Also, education should be considered as a strategic action to enhance life expectancy through expansion in the provision, accessibility and affordability to improved school enrolment rate. The choice of quarterly time series over annual data helped to establish the current relationship between air pollution and life expectancy using efficient estimators.

The study contributes to literature by disaggregating yearly series into quarterly series, which has implications for the efficiency of the estimates, unlike earlier studies which ignored this fundamental process. The result of this study produced reliable policy direction for improvement in life expectancy in an emerging economy since quarterly estimates are more robust and reliable for forecasting than its yearly counterpart. The outcome of the study extended the original tenets of the Grossman's health stock theory using the environmental Kuznets curve (EKC) and pollution haven hypotheses (PHH).