Country-Level Investment in Cultural Opportunity Structures. A Potential Source of Health Differences Between 21 European Countries

Individual’s participation in cultural activities may positively affect health through a pathway mediated by social capital. We examine whether country-level investment in cultural opportunity structures was associated with between-country differences in self-rated health and, if so, whether these associations were mediated by citizens’ confidence in societal institutions, i.e., by institutional trust, regarded as a dimension of social capital. For 24,887 respondents in the European Social Survey, 2006, data on self-rated health, institutional trust (individual-level and country-level), and sociodemographic variables were linked with statistics-based country-level data on 10 indicators of cultural opportunity structures and mediator variables (gross domestic product (GDP), Gini index, and welfare state regime). Over and above the sociodemographics, six cultural indicators contributed to between-country health differences in logistic multilevel regression analysis: the percentage of arts students, the RC index, the percentage of writers and creative artists of total employment, exports of cultural goods, imports of cultural goods, and the number of feature films produced per capita. Controlling, furthermore, for trust, and country-level mediators, only imports of cultural goods contributed to between-country differences in health. No associations with other cultural indicators remained after controlling for GDP or welfare state regime. Institutional trust may partially mediate the significance of cultural investments for self-rated health. However, both cultural investment and trust may be concomitants of general prosperity and welfare policies. Future studies should investigate whether the countries’ welfare policies influence the transformation of cultural investment into institutional trust and which types of indicators best depict associations between investments and health.     

SNAP Benefits and Pregnancy-Related Emergency Room Visits

Pregnant women are likely to be sensitive to daily fluctuations in nutritional intake. To see if income constraints at the end of the month limit food consumption and trigger health problems, we examine how the date that benefits are issued for the Supplemental Nutrition Assistance Program (SNAP) changes the probability that a woman will go to the Emergency Room (ER) for pregnancy-related conditions using administrative data from SNAP and Medicaid from Missouri for 2010–2013. SNAP benefits in Missouri are distributed from the 1st through the 22nd day of the month based on the birth month and the first letter of the last name of the head of the household, making timing of SNAP issuance exogenous. We estimate probit models of the calendar month and SNAP benefit month on the probability of a pregnancy-related ER visit for women age 17–45, or the sample at risk of being pregnant. We also examine the relationship between SNAP benefit levels and ER visits. We found that women who received SNAP benefits in the second or third week of the calendar month were less likely to receive pregnancy-related care through the ER in the week following benefit receipt. Results suggest that SNAP benefits might be related to patterns of pregnancy-related medical care accessed through the ER. Since SNAP issuance date is within state control in the United States, states may want to consider the health effects of their choice.     

Towards the Use of Crowdsourced GIS Data to Georeference Child Well-Being Globally

Child well-being is described as a social problem, such that in most cases social indicators defined by experts are used, without much input from local and heterogeneous communities. This article makes the case for an innovative way to monitor and explore child well-being globally, while also critiquing currently used indices. Based on Nussbaum’s Capabilities approach, we propose to formulate indices by using GIS and a comprehensive list of relevant geospatial datasets, using uniquely designed meta-layers and feature catalogues. Moreover, we argue that these geospatial data can be collected and mapped by the local communities, through participatory approaches, thus not relying on authoritative engagement and data. This will contribute to the empowerment of communities, making them relevant stakeholders with valued contribution to the process. This paper outlines preliminary work related to concepts and ideas, whereas future work is planned to develop an elaborate and comprehensive GIS model, and conduct further spatial analysis in the framework of a small scale campaign.     

The effects of school desegregation on mixed-race births

We find a strong positive raw correlation between black exposure to whites in their school district and the prevalence of later mixed-race (black-white) births, consistent with the literature on residential segregation and endogamy. However, that relationship is significantly attenuated by the addition of a few control variables, suggesting that individuals with higher propensities to have mixed-race births are more likely to live in desegregated school districts. We exploit quasi-random variation from court-ordered school desegregation to estimate causal effects of school desegregation on mixed-race childbearing, finding small to moderate effects that are largely statistically insignificant. Because the upward trend across cohorts in mixed-race childbearing was substantial, separating the effects of desegregation plans from secular cohort trends is difficult; results are sensitive to how we specify the cohort trends and to the inclusion of Chicago/Cook County in the sample. The fact that the addition of a few control variables substantially weakens the cross-sectional relationship between lower levels of school segregation and higher rates of mixed-race childbearing suggests that a substantial portion of the observed correlation is likely due to who chooses to live in places with desegregated schools. Researchers should be cautious about interpreting raw correlations between segregation—whether residential or school—and other outcomes as causal. Our results also point to the need to carefully explore specification of cohort effects in quasi-experimental designs for treatments where cumulative exposure is important.     

Rethinking the effectiveness of family planning in Africa

For the past 50 years there has been a near global consensus that the demands of development necessitate that couples reduce their fertility as a critical act which would jump start economic growth. This consensus heralded the era of the One Child policy and over 90% of least developed states continue to run programs which seek to induce lower fertility rates in their populations. However, a growing body of literature is questioning both the validity and utility of these interventions. This article seeks to contribute to the rethinking of family planning programs. Using new data on family planning scores from forty two African states this article shows that rates of fertility are unlikely to be affected by the strength of family planning programs at lower levels of development. However, at moderate levels of development, family planning programs may contribute to accelerating the decline in fertility initiated by exogenous factors. These findings offer a fresh perspective on the wide spread adoption of family planning policy that permeates the developing world.     

Paternal Incarceration and Adolescent Social Network Disadvantage

Previous research has suggested that adolescent peers influence behavior and provide social support during a critical developmental period, but few studies have addressed the antecedents of adolescent social networks. Research on the collateral consequences of incarceration has explored the implications of parental incarceration for children’s behavioral problems, academic achievement, health, and housing stability, but not their social networks. Using network data from the National Longitudinal Study of Adolescent Health, I find that adolescents with recently incarcerated fathers are in socially marginal positions in their schools and befriend more-marginal peers than other adolescents: their friends are less advantaged, less academically successful, and more delinquent than other adolescents’ friends. Differences in network outcomes are robust to a variety of specifications and are consistent across race and gender subgroups. This study advances the social networks literature by exploring how familial characteristics can shape adolescent social networks and contributes to the collateral consequences of incarceration literature by using network analysis to consider how mass incarceration may promote intergenerational social marginalization.     

On the kidney exchange problem: cardinality constrained cycle and chain problems on directed graphs: a survey of integer programming approaches

The Kidney Exchange Problem (KEP) is a combinatorial optimization problem and has attracted the attention from the community of integer programming/combinatorial optimisation in the past few years. Defined on a directed graph, the KEP has two variations: one concerns cycles only, and the other, cycles as well as chains on the same graph. We call the former a Cardinality Constrained Multi-cycle Problem (CCMcP) and the latter a Cardinality Constrained Cycles and Chains Problem (CCCCP). The cardinality for cycles is restricted in both CCMcP and CCCCP. As for chains, some studies in the literature considered cardinality restrictions, whereas others did not. The CCMcP can be viewed as an Asymmetric Travelling Salesman Problem that does allow subtours, however these subtours are constrained by cardinality, and that it is not necessary to visit all vertices. In existing literature of the KEP, the cardinality constraint for cycles is usually considered to be small (to the best of our knowledge, no more than six). In a CCCCP, each vertex on the directed graph can be included in at most one cycle or chain, but not both. The CCMcP and the CCCCP are interesting and challenging combinatorial optimization problems in their own rights, particularly due to their similarities to some travelling salesman- and vehicle routing-family of problems. In this paper, our main focus is to review the existing mathematical programming models and solution methods in the literature, analyse the performance of these models, and identify future research directions. Further, we propose a polynomial-sized and an exponential-sized mixed-integer linear programming model, discuss a number of stronger constraints for cardinality-infeasible-cycle elimination for the latter, and present some preliminary numerical results.     

The thickness of the complete multipartite graphs and the join of graphs

The thickness of a graph is the minimum number of planar spanning subgraphs into which the graph can be decomposed. It is known for relatively few classes of graphs, compared to other topological invariants, e.g., genus and crossing number. For the complete bipartite graphs, Beineke et al. (Proc Camb Philos Soc 60:1–5, 1964) gave the answer for most graphs in this family in 1964. In this paper, we derive formulas and bounds for the thickness of some complete k-partite graphs. And some properties for the thickness for the join of two graphs are also obtained.     

Family Instability and Material Hardship: Results from the 2008 Survey of Income and Program Participation

This study used longitudinal, nationally representative data from the 2008 Survey of Income and Program Participation to explore how each of six sources of instability (employment shocks, household formation shocks, residential changes, income changes, household size changes, and disability shocks) impacted the key domains of material hardship (food insecurity and medical, housing and essential expense hardship). The study found that income shocks and having a person with a disability join the household were the only consistent triggers for all types of material hardship, and that overall, sources of instability had an asymmetrical impact on material hardship; that is, sources of instability did not help households when they were removed as much as they harmed households when introduced. These results provided a nuanced understanding of the household dynamics that result in economic and family instability in the US and provided new evidence regarding why some households were unable to cover basic needs.