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Why has Japan become the longest-lived country in the world? The longevity is often attributed to Japan's economic growth, but Japan experienced an extended life expectancy prior to achieving such economic growth. During and after the Second World War when the General Headquarters of the Supreme Commander for the Allied Powers was occupying Japan, the welfare administration system was drastically reformed, resulting in dramatic improvements in the hygiene status, which led to an increase in the average life expectancy in Japan. Here, this background is reviewed, along with an explanation of how Japan has become the world's longest-lived country., (© The Author(s) 2020. Published by Oxford University Press on behalf of the International Life Sciences Institute. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.)

Background: Four decades of population-based tobacco control strategies have contributed to substantial reduction in smoking prevalence in Australia. However, smoking prevalence is still double in socially disadvantaged groups compared to those that are not. But not all tobacco control strategies successfully used in the general population is effective in specific high-risk population groups. Hence, an effective way to reduce smoking in high risk population groups may include targeting them specifically to identify and support smokers to quit. In this backdrop, we examined whether tobacco control interventions at the population-level are more effective in increasing life expectancy among Australians compared to interventions targeting a high risk group or a combination of the two when smoking prevalence is reduced to 10 and 0% respectively., Methods: Using the risk percentiles approach, analyses were performed separately for men and women using data from various sources such as the 2014-15 National Health Survey linked to death registry, simulated data for high risk groups, and the Australian population and deaths data from the census. Indigenous status was simulated by preferentially assigning those who are indigenous to lower SES quintiles. The age-sex distribution of mental disorder status was simulated using its distribution from 2016 National Drug Strategy Household Survey with 25.9% of mentally ill being assigned to current smoking category and the rest to non-smoking category. The age-sex distribution of prisoners was simulated based on 2014 ABS Prisoners Australia survey with 74% of prisoners being assigned to current smoker category and the rest to non-smoker category. Homelessness status was simulated according to age, sex and indigenous status for 2011 census with all homeless being allocated to the lowest SES category. The age-sex distribution of total cholesterol level was simulated based on 2011-13 Australian Health Survey., Results: The results showed that the combined approach for reducing smoking is most effective for improving life expectancy of Australians particularly for the socially disadvantaged and mentally ill groups both of which have high fraction of smokers in the population. For those who were mentally ill the gain in ALE due to reduction of smoking to 10% was 0.53 years for males and 0.36 years for females which were around 51 and 42% respectively of the maximal gains in ALE that could be achieved through complete cessation., Conclusions: Targeting high-risk population groups having substantial fraction of smokers in the population can strongly complement the existing population-based smoking reduction strategies. As population and high risk approaches are both important, the national prevention policies should make judicious use of both to maximize health gain.

This study investigates the relationship between economic status and mortality of Korean men and women who were under and over the average national life expectancy using Cox's proportional hazard model to adjust for health status, past medical history, and age. The study subjects come from local applicants of Korean National Health Insurance who had a health examination in 2005. They were enrolled into a follow-up investigation from 2005 to 2011. In individuals younger than the average life expectancy, the mortality of the lowest economic status was 2.48 times higher in men and 2.02 times higher in women than that in the highest economic status. Economic status-mortality association in males older than the average life expectancy was attenuated but not eliminated. However, there is no significant relationship between economic status and mortality for females above the average life expectancy., (© 2012 APJPH.)

Today, despite the decrease in agricultural areas, problems such as the continuous increase in population, poverty, pandemic, wars and global warming made food insecurity and access to clean water resources even more important. Thus, the effect of not having enough food on the average life expectancy was investigated. In the study, panel data analysis method was used and 58 countries in low and low-middle income groups were analyzed. In the study, panel data analysis method was used and 58 countries in low and low-middle income groups were analyzed. In this direction, it is aimed to determine what kind and in what direction indicators related to access to insufficient food have on the average life expectancy. As a result of the research, it is predicted that a 1% increase in the rate of malnourished population may cause a 0.04% decrease in the average life expectancy, a 1% increase in depth of food deficit may cause in a 0.09% decrease in average life expectancy, a 1% increase in extreme poverty may cause in a 0.18% decrease in average life expectancy. Finally, no significant relationship was found between the number of unsafe water-related deaths and the average life expectancy among the total deaths. [ABSTRACT FROM AUTHOR]

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