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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.

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.

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 aim of this paper is to examine biological, maternal and socioeconomic determinants of infant mortality in Sierra Leone.

It uses an analytical framework and Cox proportional hazards regression to break down the effects of factors determining infant mortality. Factors utilized in the empirical investigation include sex of the child, birth size, birth spacing, mother's working status, age of mother, antenatal care, postnatal care, mother's anemia level, religion, mother's education and wealth status.

Results suggest that birth spacing of three years and above associated with a reduced risk of infant mortality contrasted with short birth intervals. Children born to nonanemic mothers have a lower hazard (22%) of infant mortality compared to those born to anemic mothers (HR = 0.78; 95% CI: 0.64–0.96). At least one antenatal care visit by mothers lowers infant mortality rate by 41% compared to no antenatal visits at all ( HR = 0.59; 95% CI: 0.36–0.96). Similarly, infants whose mothers have received postnatal care are at lower risk (31%) of dying than those whose mothers have not received (HR = 0.69; 95% CI: 0.52, 0.93). Infant mortality is likely to decrease with the increase in the birth order.

The family health and planning programs should aim at educating men and women about the usefulness of birth spacing methods.

This paper might be the first attempt to analyze the determinants of infant mortality by utilizing a methodological framework and Cox regression.

The peer review history for this article is available at: https://publons.com/publon/10.1108/IJSE-08-2019-0478.

This article examines whether increasing the income of the poor – measured as the income of the lowest quintile – is more beneficial in reducing infant and child mortality rates compared with increases in average income. Given the global importance in reducing infant mortality, the value of this research is important to academics, policymakers and practitioners alike.

Using a sample of 86 countries from 1995–2014 inclusive, our preferred estimation strategy uses an instrumental variable fixed-effects estimator.

Our results propose that the elasticity of the income of the lowest quintile never exceeds that of average income. Therefore, if reducing infant and child mortality is a key policy goal, then boosting average income may be preferable to raising incomes at the lower end of the distribution.

Given these findings, we open a gateway for new literature to add to this unexplored area of research in the income and health relationship.

Many world regions are developing quickly and experiencing increasing levels of sanitation, causing an epidemiological shift of hepatitis A in these areas. The shift occurs when children avoid being infected with the disease until a later age due to cleaner water sources, food, and hygiene practices in their environment; but if they are infected at later age, the disease is much more severe and lost productivity costs are higher. The purpose of this paper is to examine what could occur if an epidemiological shift of the disease continues in these regions, and what type of future burden hepatitis A may have in a hypothetical rapidly developing country.

Initially, annual hepatitis A mortality was regressed on the Human Development Index (HDI) for each country classified as an emerging and growth-leading economy (EAGLE) to provide an overview of how economic development and hepatitis A mortality related. Data from the various EAGLE countries were also fit to a model of hepatitis A mortality rates in relation to HDI, which were both weighted by each country’s 1995–2010 population of available data, in order to create a model for a hypothetical emerging market country. A second regression model was fit for the weighted average annual hepatitis A mortality rate of all EAGLE countries from the years 1995 to 2010. Additionally, hepatitis A mortality rate was regressed on year.

Regression results show a constant decline of mortality as HDI increased. For each increase of one in HDI value in this hypothetical country, mortality rate declined by 2.3016 deaths per 100,000 people. The hypothetical country showed the HDI value increasing by 0.0073 each year. Also, results displayed a decrease in hepatitis A mortality rate of 0.0168 per 100,000 people per year. Finally, the mortality rate for hepatitis A in this hypothetical country is projected to be down to 0.11299 deaths per 100,000 people by 2030 and its economic status will fall just below the HDI criteria for a developed country by 2025.

The hypothetical country as a prototype model was created from the results of regressed data from EAGLE countries. It is aimed to display an example of the health and economic changes occurring in these rapidly developing regions in order to help understand potential hepatitis A trends, while underscoring the importance of informed and regular policy updates in the coming years. The author believes this regression provides insight into the patterns of hepatitis A mortality and HDI as these EAGLE countries undergo rapid development.

The Sendai Framework for Disaster Risk Reduction 2015–2030 calls for a reduction in disaster mortality, yet measuring mortality remains a challenge due to varying definitions of disaster mortality, the quality, availability and diversity of data sources, generating mortality estimates, and how mortality data are interpreted.

This paper uses five case studies to provide details around some of the complexities involved with measuring disaster mortality and to demonstrate the clear need for accurate disaster mortality data.

The findings highlight the benefits of combining multiple data sources for accurate mortality estimates, access to interoperable and readily available global, national, regional and local data sets, and creating standardized definitions for direct and indirect mortality for easier attribution of causes of death.

Countries should find a method of measuring mortality that works for them and their resources, and for the hazards they face. Combining accurate mortality data and estimates and leadership at all levels can inform policy and actions to reduce disaster mortality, and ultimately strengthen disaster risk reduction in countries for all citizens.