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The purpose of this paper is to investigate the impact of critical macroeconomic drivers like economic growth (gross domestic product (GDP)/capita), inflation and population size on the mortality rate of Nigeria. The general lockdown imposed by the government to curb the spread of coronavirus disease 2019 (COVID-19) has had so many effects like loss of jobs, insecurity, businesses collapsing, salary cuts, unemployment and increased prices of commodities in the market.

The paper focused on secondary data for the period 1991–2019 for GDP/capita, inflation, population size and mortality rate which were obtained from World Development Indicators (WDI). Time series analysis tests like augmented Dickey–Fuller (ADF), Bounds co-integration and autoregressive distributed lag (ARDL) were used to determine the stationarity conditions of the variables, co-integration presence among the variables and to determine the short-run and long-run relationships between the endogenous and exogenous variables.

The study shows that the variables are stationary at different orders i.e. I (0) and I (1) and the presence of co-integration among the variables. There exists a positive relationship between GDP/capita and mortality rate on the short-run which means increase in GDP/capita does not reduce the mortality rate in the country, there is also a positive short-run relationship between inflation and mortality rate but there are no long-run relationships among the variables.

The paper clearly examines the impact of GDP/capita, inflation and population growth on mortality rate in Nigeria.

The 30 MOCHA (Models of Child Health Appraised) countries are diverse socially, culturally and economically, and differences exist in their healthcare systems and in the scope and role of primary care. An economic analysis was undertaken that sought to explain differences in child health outcomes between countries. The conceptual framework was that of a production function for health, whereby health outputs (or outcomes) are assumed affected by several ‘inputs’. In the case of health, inputs include personal (genes, health behaviours) and socio-economic (income, living standards) factors and the structure, organisation and workforce of the healthcare system. Random effects regression modelling was used, based on countries as the unit of analysis, with data from 2004 to 2016 from international sources and published categorisations of healthcare system. The chapter describes the data deficiencies and measurement conundrums faced, and how these were addressed. In the absence of consistent indicators of child health outcomes across countries, five mortality measures were used: neonatal, infant, under five years, diabetes (0–19 years) and epilepsy (0–19 years). Factors found associated with reductions in mortality were as follows: gross domestic product per capita growth (neonatal, infant, under five years), higher density of paediatricians (neonatal, infant, under five years), less out-of-pocket expenditure (neonatal, diabetes 0–19), state-based service provision (epilepsy 0–19) and lower proportions of children in the population, a proxy for family size (all outcomes). Findings should be interpreted with caution due to the ecological nature of the analysis and the limitations presented by the data and measures employed.

In recent years, a number of historians have examined the reasons for differences in the height and health of men and women in nineteenth-century Britain, often drawing on economic studies which link excess female mortality in the developing world to restrictions in women's employment opportunities. This paper re-examines this literature and summarises the existing literature on sex-specific differences in height, weight and mortality in England and Wales before 1850. It then uses two electronic datasets to examine changes in cause-specific mortality rates between 1851 and 1995. Although there is little evidence to support the view that the systematic neglect of female children was responsible for high rates of female mortality in childhood, there is rather more evidence to show that gender inequalities contributed to excess female mortality in adulthood.

The study of war has generally been neglected in sociology, with much of the discussion focusing around military spending or the organization of the military rather than war per se. Sociologists have critiqued and investigated the military-industrial complex (Mills, 1959), investigated morale in military units (Durkheim, 1951; Stouffer & DeVinney, 1955), and studied the socialization of soldiers (Cockerham & Cohen, 1980). However, the direct examination of war has been relatively rare. When war has been examined, sociological research has focused on the causes of war, often discussing the preconditions of revolutions (Goldstone, Gurr & Moshiri, 1991; Skopol, 1979), or the reasons for military interventions by core countries in the peripheral countries of the world system (Kowalewski, 1991). Examinations of the sociological impact of war on civilian populations have been even rarer.

Using data from the Survey of Income and Program Participation (SIPP) matched to administrative records, we examine mortality risk and participation in the Disability Insurance (DI) and Supplemental Security Income (SSI) disability programs from a long-term perspective. Over a period of 14 years, we analyze the effect of self-reported health and disability on the probability of death and disability program entry among individuals aged 18–48 in 1984. We also assess DI and SSI programs from a life-cycle perspective. Self-reported poor health and severe disability at baseline are strongly correlated with death over the 14-year follow-up period. These variables also are strong predictors of disability program participation over the follow-up period among non-participants at baseline or before, with increasing marginal probabilities in the out-years. Our cross-sectional models are consistent with recent studies that find that the work-prevented measure is useful in modeling DI entry. However, once self-reported health and functional limitations are accounted for, the longitudinal entry models provide conflicting DI results for the work-prevented measure, suggesting that, contrary to claims based on cross-sectional or short-time horizon application models, the work-prevented measure is an unreliable indicator of severity. The risk of SSI and DI participation is significantly greater for individuals who die, suggesting that future mortality captures the effect of case severity and deterioration of health during the follow-up period. From a life-cycle perspective, a substantially greater proportion of individuals participate in SSI or DI at some point in their lives compared to typical cross-sectional estimates of participation, especially among minorities, people with less than a high school education, and those with early onset of poor health and/or disabilities. Cross-sectional estimates for the Social Security area population indicate SSI and DI participation rates of no more than 5% combined in 2000. In contrast, for individuals aged 43–48 in 1984, we observe a cumulative lifetime SSI and/or DI participation rate of 14%. The corresponding figure is 32% for individuals in that age group who did not graduate from high school, suggesting the need for human capital investments and/or improved work incentives.

This chapter proposes that efforts to improve our understanding of factors affecting migrant health and longevity in the United States must consider migrants’ labor market incorporation and the structural conditions under which they work. I use public-use death certificate data to examine whether there is a mortality penalty for foreign-born workers in the secondary sector industries of agriculture and construction. I focus on the decade of the 1990s for two contextual and empirical reasons: (1) the decade was characterized by economic restructuring, restrictive immigration policy, increased migration, and dispersion of migrants to new geographic destinations; and (2) the 1990s is an opportunistic decade because 19 states coded the industry and occupation of the decedent during this time. These numerator mortality data and Census denominator data are used to compare all-cause mortality rates between working-age (16–64 years) US-born and foreign-born agricultural and construction workers, the overall foreign-born population, and foreign-born workers in health care – an industry where the foreign-born tend to work in well-paid occupations that are well-regulated by the state. The results show a clear mortality penalty for foreign-born workers in agriculture and construction compared to the overall foreign-born population and foreign-born healthcare workers. The results also show the mortality penalty for foreign-born secondary sector workers varies by industry. These findings support the argument that bringing work into our analyses is critical to understanding the contextual and structural factors affecting migrant health and survival.

The purpose of this paper is to evaluate socioeconomic factors related to COVID-19 mortality rates in New York City (NYC) to understand the connections between socioeconomic variables, including race and income and the disease.

Using multivariable negative binomial regression, the association between health and mortality disparities related to COVID-19 and socioeconomic conditions is evaluated. The authors obtained ZIP code-level data from the NYC Department of Health and Mental Hygiene and the US Census Bureau.

This study concludes that the mortality rate rises in areas with a higher proportion of Hispanic and Black residents, whereas areas with higher income rates had lower mortality associated with COVID-19, among over 18,000 confirmed deaths in NYC.

The paper highlights the impacts of social, racial and wealth disparities in mortality rates. It brings to focus the importance of targeted policies regarding these disparities to alleviate health inequality among marginalized communities and to reduce disease mortality.

People in prison are at a higher risk of preventable mortality from infectious disease such as human immunodeficiency virus (HIV)/acquired immunodeficiency syndrome (AIDS), hepatitis B (HBV), hepatitis C (HCV) and tuberculosis (TB) than those in the community. The extent of infectious disease-related mortality within the prison setting remains unclear. The purpose of this paper was to collate available information on infectious disease-related mortality, including the number of deaths and calculate the person-time death rate.

The authors searched databases between 1 January 2000 and 18 November 2020 for studies reporting HIV, HBV, HCV, TB and/or HIV/TB-related deaths among people in prison.

The authors identified 78 publications drawn from seven Joint United Nations Programme on HIV/AIDS’ regions encompassing 33 countries and reporting on 6,568 deaths in prison over a 20-year period. HIV/AIDS (n = 3,305) was associated with the highest number of deaths, followed by TB (n = 2,892), HCV (n = 189), HIV/TB (n = 173) and HBV (n = 9). Due to the limitations of the available published data, it was not possible to meta-analyse or in any other way synthesise the available evidence.

To inform targeted efforts to reduce mortality, there is a need for more, better quality data to understand infectious disease-related mortality in custodial settings. Increased investment in the prevention and management of infectious diseases in custodial settings, and in documenting infectious disease-related deaths in prison, is warranted and will yield public health benefits.

To the authors’ best knowledge, this is the first scoping review focussed on deaths due to these infections among people in prison internationally. The gaps identified form recommendations to improve the future collection and reporting of prison mortality data.

This paper aims to examine how mortality-related sadness, as compared to other emotions such as fear, anger and happiness, can leverage the effectiveness of fresh start appeals.

Drawing upon the consumption-based affect regulation principle, this paper investigates how sadness associated with mortality can elicit the appraisal of irretrievable loss, which subsequently increases the effectiveness of fresh start appeals. These predictions are tested across three experimental studies.

Findings demonstrate that mortality-related sadness enhances donation allocations (Study 1), willingness to pay (Study 2) and favorable attitudes (Study 3) toward an advertisement promoted with a fresh start appeal. This effect is mediated by an appraisal of irretrievable loss (Studies 1–3). Moreover, the emotion’s effect only emerges among consumers who believe that their emotional experiences are stable (vs malleable) (Study 3).

This paper investigates the effects of negative (vs positive emotions). It would thus be of interest to explore whether different discrete positive emotions may also enhance favorable evaluations of fresh start appeals.

While fresh start appeals have been widely used by marketers and organizations, the extant literature in this area has yet to identify how marketers can leverage the effectiveness of such appeals. This paper highlights how a specific negative emotion can be beneficial to marketers in leveraging the effectiveness of fresh start appeals.

The findings of this research suggest a novel potential strategy for the regulation of sadness. Specifically, consumers experiencing mortality-related sadness show favorable evaluations of fresh start appeals, indicating they are seeking to dissociate themselves from the past.

The purpose of the paper is to investigate the potential relationships between emergency-care flow, patient mortality and healthcare costs using a patient-flow model.

The researchers used performance data from one UK NHS trust collected over three years to identify periods where patient flow was compromised. The delays’ root causes in the entire emergency care system were investigated. Event time-lines that disrupted patient flow and patient mortality statistics were compared.

Data showed that patient mortality increases at times when accident and emergency (A&E) department staff were struggling to admit patients. Four delays influenced mortality: first, volume increase and mixed admissions; second, process delays; third, unplanned hospital capacity adjustments and finally, long-term capacity restructuring downstream.

This is an observational study that uses process control data to find times when mortality increases coincide with other events. It captures contextual background to whole system issues that affect patient mortality.

Managers must consider cost-decisions and flow in the whole system. Localised, cost-focused decisions can have a detrimental effect on patient care. Attention must also be paid to mortality reports as existing data-presentation methods do not allow correlation analysis.

Previous studies correlate A&E overcrowding and mortality. This method allows the whole system to be studied and increased mortality root causes to be understood.