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The Spanish Flu 1918–1920 saw a high degree of excess mortality among young and healthy adults. The purpose of this paper is a further exploration of the hypothesis that high mortality risk during The Spanish Flu in Copenhagen was associated with early life exposure to The Russian Flu 1889–1892.

Based on 37,000 individual-level death records in a new unique database from The Copenhagen City Archives combined with approximate cohort-specific population totals interpolated from official censuses of population, the author compiles monthly time series on all-cause mortality rates 1916–1922 in Copenhagen by gender and one-year birth cohorts. The author then analyses birth cohort effects on mortality risk during The Spanish Flu using regression analysis.

The author finds support for hypotheses relating early life exposure to The Russian Flu to mortality risk during The Spanish Flu. Some indications of possible gender heterogeneity during the first wave of The Spanish Flu – not found in previous studies – should be a topic for future research based on data from other countries.

Due to lack of individual-level death records with exact dates of birth and death, previous studies on The Spanish Flu in Denmark and many other countries have relied on data with lower birth cohort resolutions than the one-year birth cohorts used in this study. The analysis in this paper illustrates how archival Big Data can be used to gain new insights in studies on historical pandemics.

Hepatitis A is a prevalent disease that is largely preventable by vaccine usage. The vaccine for this illness is highly underused in most regions. In an attempt to find the strategies that are most beneficial in regard to quality-adjusted life years (QALYs) and cost in current environments, the purpose of this paper is to conduct cost-effectiveness analyses to investigate vaccination strategies in a more economically developed country (MEDC), generally known as a “developed” area: the USA, and a less economically developed country (LEDC), generally known as a “developing” area: the state of Rio de Janeiro, Brazil.

This study used a dynamic transmission model for comparative effectiveness analyses. The model ran two different scenarios. The two regions studied have different policies and strategies for Hepatitis A vaccination currently, and also used different strategies in 2009. In the USA, a universal vaccination policy was modeled, along with a scenario in which it was removed. In Rio de Janeiro, a no vaccination policy was modeled, along with a scenario in which a universal vaccination policy was effected.

The comparison of resulting incremental cost-effectiveness ratio values to accepted threshold values showed universal vaccination to be cost-effective in both the USA and Rio de Janeiro as compared to no vaccination. When episode and vaccination costs and vaccination efficacy were varied, this still remained true. Universal vaccination was found to result in lower incidence of Hepatitis A in both the USA and Rio de Janeiro. Over the twenty-year time horizon, universal vaccination is projected to prevent 506,945 cases of symptomatic Hepatitis A in the USA and 42,318 cases of Hepatitis A in Rio de Janeiro. Other benefits include a projected increase in cumulative QALYs through the use of universal vaccination.

This analysis showed universal vaccination to be cost-effective as compared to no vaccination, and portions of the study’s approach had not previously been applied in tandem to investigate Hepatitis A interventions. The results may help foster higher compliance rates for Hepatitis A vaccination and even greater per-person economic benefits of universal vaccination, particularly in the USA. The purpose of this study is also to encourage elevated levels of surveillance on age of infection in developing regions and consistent reevaluation utilizing dynamic transmission models in both the USA and Brazil, as well as other rapidly developing regions, in order to prevent future epidemics and costs associated with the disease.

Social participation (SP) has been shown to have a favorable impact on health status, particularly among elders in developed countries. However, empirical study is scarce for China. This study explores the relation between social participation (SP) and health status among middle-aged adults and elders in China when controlled socioeconomic characteristics of individuals.

This paper employs an empirical study based on the data from a three-wave national longitudinal survey: the Chinese Health and Retirement Longitudinal Study (CHARLS) from 2011, 2013 to 2015. It collects data from 28,895 individuals aged 45–84. It uses lagged variable method (LV) to address the reverse causality problem, and the random-effects model or fixed-effect model to address the heterogeneity problem.

The paper finds the social participation positively affect self-reported health statistically. The influence of social participation on self-reported health flows through two channels: the improved mental health effect (SP-MH-SRH channel) and the increased income effect (SP-income-SRH channel). In comparison with the SAP-income-SRH channel, the influence of the SP-MH-SRH channel l is greater.

First, the absence of other measures of volunteering, such as hours of social participation that are not available in the employed dataset. Second, even though the LV model and FE model are used in the paper, there may remain the endogeneity problem in the results. Third, the influences of formal and informal social participation should be distinguished in the future research.

Social participation may improve the self-reported health status. The influence of SP on health may be due to the improved mental health effect (SP-MH-SRH channel). In order to improve the mental and physical health status of middle-aged adults and elders the government should consider even more promotion of social participation.

First, this paper focuses on the correlation between social participation and well-being (self-reported health) of middle-aged adults and elderly in China, the previous studies on the issue for China are scarce. Second, this paper uses the lagged variable method (LV) to address the reverse causal relation problem, and the fixed-effects model or the random-effects model to address the heterogeneity problem. Third, the two channels (the improved mental health effect and the increased income effect) are firstly investigated in this study.

The purpose of this paper is to investigate the relationship between occupational degree requirement and mortality between ethnic groups in a cohort of urban workers.

The study included 118,606 health-insured full-time workers from the New York City Health and Hospitals Corporation (HHC). Mortality rates (MR) and mortality rate ratios (MRR) were calculated for major ethnic categories. Estimates were adjusted for age, sex, and occupational degree requirement.

Prior to adjustment for degree requirement, mortality rates (MRs) by ethnic groups in the Health and Hospitals Corporation were in line with national estimates: highest for blacks, followed by whites, Hispanics, and Asian/Pacific Islander (APIs). After adjustment, the MR for blacks became comparable to whites (mortality rate ratio (MRR)=1.02). The low-Hispanic MR did not change; the Hispanic advantage persisted (MRR=0.66), as did the API advantage (MRR=0.50).

Higher education may not substantially change the MR for Hispanics, and it may only account for a portion of the survival advantage among APIs. The findings also suggest that without reducing the disparity in higher education attainment between blacks and whites, equality in other socioeconomic factors may not abolish the disparity in mortality between these groups.

This study bypassed common limitations of ethnic mortality studies, with intrinsic parity for certain socio-economic status factors (full-time employment and health care access) across cohort members and consistent ethnic classification across time-points. This includes a cohort of API workers with complete self-identification of ethnicity, which has not been accomplished by previous investigations.

To determine the mortality of drug users after release from prison in Denmark, a cohort of drug users was identified from two national registers during 1996‐2001: the drug treatment register (T) and the register of viral hepatitis (H). Incarcerations were extracted from the national penal register, vital status from the civil register, and causes of death from the death certificate register and the police register of drug‐related deaths. We identified 15,885 drug users (T: 15,735, H: 896), 62% of the estimated drug‐using population in Denmark. There were 1000 observed deaths, of which 51% were classified as overdose deaths. Mortality in the treatment cohort was 2.4/100 person years (py) (95% C.I. 2.2‐2.5/100 py) compared to the general population expectation of 0.2/100 py. Within the first 2 weeks after release from prison, 26 deaths were observed among 6019 released drug users corresponding to 13/100 py (95% CI 8‐19/100 py). Overdose deaths accounted for 24/26 deaths (92%) in the first two weeks compared to 121/179 (68%) hereafter (p <0.001). We conclude that drug users released from prison are at high risk of overdose death. We suggest that methadone treatment should be evaluated as a way to decrease mortality after release from prison.

This paper aims to measure the financial impact on social security system of a recently proposed indexation mechanism for retirement age by considering the Italian longevity experience. The analysis is motivated by the progressive increase in life expectancy at advanced age, which is rapidly bringing to the fore noticeable socio-economic consequences in most industrialized countries. Among those, the impact on National Social Security systems is particularly relevant if people live longer than expected; this will lead to greater financial exposure for pension providers.

Referring to the Italian population for illustrative purposes, the authors contemplate different scenarios for mortality projection methods and for the implementation of pension age shift while accounting for gender and cohort gaps and model risk. Synthetic indicators to measure the impact of the indexation mechanism on social security system are introduced on the basis of pension cash flows.

An indexation policy that manages gender gap while adjusting retirement age for varying life expectancy is proposed. As a result, sustainability of public retirement expenditure is improved.

The paper is a concise scenario analysis of the reduction of costs and risks that pension providers would have if the system resorted to link retirement age to life expectancy. The ideas fostered by the paper follow a recent proposal of the Authors on a flexible retirement scheme that deals with model risk for mortality projection and accounts for gender gap in mortality rates.

An important hypothesis put forth by Amartya Sen is that a given level of per capita real income in a population can generate quite different levels of socio‐economic well‐being depending on the economic infrastructure of that population and the distribution of income. Sen's hypothesis is refined in this paper to reflect the manner in which income is spent and labor is allocated and utilized within a household specific to particular groups within society and how this impacts upon both the level of well‐being and economic efficiency. The evidence on living conditions and mortality presented here from early twentieth century New York City, underlies the potential significance of the household economy as a key determinant of economic well‐being. Focusing simply on per capita income estimates, even corrected for the distribution of income, misses fundamentally important determinants of human capabilities and economic well‐being with potentially important implications for public policy.

The improvements of longevity are intensifying the need for capital markets to be used to manage and transfer the risk through longevity-linked securities. Nevertheless, the difference between the reference population of the hedging instrument and the population of members of a pension plan, or the beneficiaries of an annuity portfolio, determines a significant heterogeneity causing the so-called basis risk. In particular, it is shown that if insurers use financial instruments based on national indices to hedge longevity risk, this hedge can become imperfect. For this reason, it is fundamental to arrange a model allowing to quantify the basis risk for minimising it through a correct calibration of the hedging instrument.

The paper provides a framework for measuring the basis risk impact on the. To this aim, we propose a model that measures the population basis risk involved in a longevity hedge, in the functional data model setting. hedging strategies.

The innovative contribution of the paper occurs in two key points: the modelling of mortality and the hedging strategy. Regarding the first point, the paper proposes a functional demographic model framework (FDMF) for capturing the basis risk. The FDMF model generally designed for single population combines functional data analysis, nonparametric smoothing and robust statistics. It allows to capture the variability of the mortality trend, by separating out the effects of several orthogonal components. The novelty is to set the FDMF for modelling the mortality of the two populations, the hedging and the exposed one. Regarding the second point, the basic idea is to calibrate the hedging strategy determining a suitable mixture of q-forwards linked to mortality rates to maximise the degree of longevity risk reduction. This calibration is based on the key q-duration intended as a measure allowing to estimate the price sensitivity of the annuity portfolio to the changes in the underlying mortality curve.

The novelty lies in linking the shift in the mortality curve to the standard deviation of the historical mortality rates of the exposed population. This choice has been determined by the observation that the shock in a mortality rate is age dependent. The main advantage of the presented framework is its strong versatility, being the functional demographic setting a generalisation of the Lee-Carter model commonly used in mortality forecasting, it allows to adapt to different demographic scenarios. In the next developments, we set out to compare other common factor models to assess the most effective longevity hedge. Moreover, the parsimony for considering together two trajectories of the populations under consideration and the convergence of long-term forecast are important aspects of our approach.

This study is a mortality assessment on police officers (68-years, 1950–2018) and includes all causes of death.

The authors investigated 1,853 police deaths (1950–2018) using sources of mortality that included the National Death Index, NY State, and available records from the Buffalo NY police department. Standardized Mortality Ratios were calculated. Death codes were obtained from 8th and 9th International Classification of Disease revisions in accordance with the year of death.

Compared to the US general population, white male police officers from 1950–2018 had elevated mortality rates for some causes of death, including diseases of the circulatory system, malignant neoplasms, cirrhosis of the liver, and mental disorders. Black and female officers had lower mortality rates for all causes of death compared to the general population.

The findings of elevated risk for chronic disease among police need to be studied in relation to stress, lifestyle, and exposure to chemical and physical agents. There is a special need to further study officers from minority populations as larger samples become available.

The results of this study will provide police and occupational health practitioners with objective evidence to determine the health impact of work on law enforcement officers.

This study is longest running mortality assessment on police officers ever conducted (1950–2018) and includes white, black, and female officers.

There is increasing evidence that participation in various art forms can be beneficial for health and well-being. The purpose of this paper is to examine the impact of participating in a poetry reading group on a group of older residents of an assisted living facility.

Six poetry sessions, each on a different theme, were conducted with a group of volunteer participants. These sessions, those of pre- and post-study focus groups and interviews with the group facilitator and staff contact were audio-recorded. The transcripts of the recordings were then subjected to a thematic analysis.

Overall the participants were enthused by the opportunity to participate in the project and the benefits were confirmed by the support staff. In addition, reading poetry on particular themes promoted different types of discussion.

The number of participants in this study was small and the study was conducted over a short period of time.

This paper confirms the impact of poetry reading for older people. The challenge is to explore this impact in more detail and over community as well as residential settings.

This paper is the first empirical report on the value of poetry reading for older people.