Nations' income inequality predicts ambivalence in stereotype content: How societies mind the gap

Income inequality undermines societies: The more inequality, the more health problems, social tensions, and the lower social mobility, trust, life expectancy. Given people's tendency to legitimate existing social arrangements, the stereotype content model (SCM) argues that ambivalence-perceiving many groups as either warm or competent, but not both-may help maintain socio-economic disparities. The association between stereotype ambivalence and income inequality in 37 cross-national samples from Europe, the Americas, Oceania, Asia, and Africa investigates how groups' overall warmth-competence, status-competence, and competition-warmth correlations vary across societies, and whether these variations associate with income inequality (Gini index). More unequal societies report more ambivalent stereotypes, whereas more equal ones dislike competitive groups and do not necessarily respect them as competent. Unequal societies may need ambivalence for system stability: Income inequality compensates groups with partially positive social images. © 2012 The British Psychological Society.

Violence Exposure and Welfare over Time: Evidence from the Burundi Civil War

We investigate the relationship between exposure to conflict and poverty dynamics over time, using original three-waves panel data for Burundi which tracked individuals and reported local-level violence exposure from 1998 to 2012. Firstly, the data reveal that headcount poverty has not changed since 1998 while we observe multiple transitions into and out of poverty. Moreover, households exposed to the war exhibit a lower level of welfare than non-exposed households, with the difference between the two groups predicted to remain significant at least until 2017, i.e. twelve years after the conflict termination. The correlation between violence exposure and deprivation over time is confirmed in a household-level panel setting. Secondly, our empirical investigation shows how violence exposure over different time spans interacts with households' subsequent welfare. Our analysis of the determinants of households' likelihood to switch poverty status (i.e. to fall into poverty or escape poverty) combined with quantile regressions suggest that, (i) exposure during the first phase of the conflict has affected the entire distribution, and (ii) exposure during the second phase of the conflict has mostly affected the upper tail of the distribution: initially non-poor households have a higher propensity to fall into poverty while initially poor households see their propensity to pull through only slightly decrease with recent exposure to violence. Although not directly testable with the data at hand, these results are consistent with the changing nature of violence in the course of the Burundi civil war, from relatively more labour-destructive to relatively more capital-destructive.

Epidemiological and nutrition transition in developing countries: impact on human health and development

Whereas common infectious and parasitic diseases such as malaria and the HIV/AIDS pandemic remain major unresolved health problems in many developing countries, emerging non-communicable diseases relating to diet and lifestyle have been increasing over the last two decades, thus creating a double burden of disease and impacting negatively on already over-stretched health services in these countries. Prevalence rates for type 2 diabetes mellitus and CVD in sub-Saharan Africa have seen a 10-fold increase in the last 20 years. In the Arab Gulf current prevalence rates are between 25 and 35% for the adult population, whilst evidence of the metabolic syndrome is emerging in children and adolescents. The present review focuses on the concept of the epidemiological and nutritional transition. It looks at historical trends in socio-economic status and lifestyle and trends in nutrition-related non-communicable diseases over the last two decades, particularly in developing countries with rising income levels, as well as the other extreme of poverty, chronic hunger and coping strategies and metabolic adaptations in fetal life that predispose to non-communicable disease risk in later life. The role of preventable environmental risk factors for obesity and the metabolic syndrome in developing countries is emphasized and also these challenges are related to meeting the millennium development goals. The possible implications of these changing trends for human and economic development in poorly-resourced healthcare settings and the implications for nutrition training are also discussed.

Impacts of wildlife on household food security and income in northeastern Tanzania

We evaluated the impacts of wildlife on household food security and income in three semi-arid villages adjacent to Lake Manyara National Park (LMNP) and Mkomazi Game Reserve (MGR) in Northeastern Tanzania. Survey data were collected using both household interviews and human-wildlife conflict related archive information from the village government offices. Crop destruction by wildlife influenced both household food security and cash income. Crop damage to households was, on average, 0.08 ton/annum, equivalent to two months household loss of food and reduced household cash income by 1.3%. A combination of measures is proposed as incentives for conservation. These include provision of economic incentives, soft loans to initiate non-farm (e.g., ecotourism, business enterprises) projects to ease dependency on natural resources, increasing of reserves buffer zones and fencing of reserves.

Risk adjustment for hospital use using social security data: cross sectional small area analysis

Objectives: To identify demographic and socioeconomic determinants of need for acute hospital treatment at small area level. To establish whether there is a relation between poverty and use of inpatient services. To devise a risk adjustment formula for distributing public funds for hospital services using, as far as possible, variables that can be updated between censuses. Design: Cross sectional analysis. Spatial interactive modelling was used to quantify the proximity of the population to health service facilities. Two stage weighted least squares regression was used to model use against supply of hospital and community services and a wide range of potential needs drivers including health, socioeconomic census variables, uptake of income support and family credit, and religious denomination. Setting: Northern Ireland. Main outcome measure: Intensity of use of inpatient services. Results: After endogeneity of supply and use was taken into account, a statistical model was produced that predicted use based on five variables: income support, family credit, elderly people living alone, all ages standardised mortality ratio, and low birth weight. The main effect of the formula produced is to move resources from urban to rural areas. Conclusions: This work has produced a population risk adjustment formula for acute hospital treatment in which four of the five variables can be updated annually rather than relying on census derived data. Inclusion of the social security data makes a substantial difference to the model and to the results produced by the formula.