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Objectives: Life course influences on later life depression may include parenting trajectories. We investigate associations between number and timing of births and use of antidepressant medication in late mid-life using data on the whole Norwegian population. Methods: We estimated logistic regression models to analyse variations in the purchase of antidepressants between 2004 and 2008 by timing of births and number of children among women and men aged 45 73, using Norwegian population register data. We controlled for age, education, marital and partnership status, and (in some models) family background shared among siblings. Results: Mothers and fathers of two or more children were generally less likely to purchase antidepressants than the childless. Mothers who started childbearing before age 22 were an exception, although according to sibling models they were not more likely to purchase antidepressants. All models showed that women who became mothers before age 26 and had only one child had higher odds of medication purchase than the childless. Older age at first birth was generally associated with lower risks of antidepressant purchase. Conclusion: This analysis of high-quality data for a national population indicates that early motherhood, childlessness and low parity are associated with higher usage of antidepressants in late mid-life. Our data did not allow identification of mediating pathways, and we lacked information on early mental and physical health and some other potentially important confounders not shared between siblings. Furthermore purchase of antidepressants is not a perfect indicator of depression. Those concerns aside, the results suggest complex effects of fertility on depression that merit further investigation.

AbstractChoice architecture describes the environment in which choices are presented to decision-makers. In recent years, public and private actors have looked at choice architecture with great interest as they seek to influence human behaviour. These actors are typically called choice architects. Increasingly, however, this role of architecting choice is not performed by a human choice architect, but an algorithm or artificial intelligence, powered by a stream of Big Data and infused with an objective it has been programmed to maximise. We call this entity the autonomous choice architect. In this paper, we present an account of why artificial intelligence can fulfil the role of a choice architect and why this creates problems of transparency, responsibility and accountability for nudges. We argue that choice architects, be them autonomous computational systems or human-beings, at a most basic level select, from a range of designs, the design which is most likely to maximise a pre-determined objective. We then proceed to argue that, given the growing demand for targeted, personalised choice architecture and for faster, dynamic reconfigurations of choice architecture, as well as the ever-expanding pool of data from which feedback can be drawn, the role of the human choice architect is increasingly obscured behind algorithmic, artificially intelligent systems. We provide a discussion of the implications of autonomous choice architects, focusing on the importance of the humans who programme these systems, ultimately arguing that despite technological advances, the responsibility of choice architecture and influence remains firmly one human beings must bear.

This paper explores and compares health system responses to the COVID-19 pandemic in Denmark, Finland, Iceland, Norway and Sweden, in the context of existing governance features. Content compiled in the Covid-19 Health System Response Monitor combined with other publicly available country information serve as the foundation for this analysis. The analysis mainly covers early response until August 2020, but includes some key policy and epidemiological developments up until December 2020. Our findings suggest that despite the many similarities in adopted policy measures, the five countries display differences in implementation as well as outcomes. Declaration of state of emergency has differed in the Nordic region, whereas the emphasis on specialist advisory agencies in the decision-making process is a common feature. There may be differences in how respective populations complied with the recommended measures, and we suggest that other structural and circumstantial factors may have an important role in variations in outcomes across the Nordic countries. The high incidence rates among migrant populations and temporary migrant workers, as well as differences in working conditions are important factors to explore further. An important question for future research is how the COVID-19 epidemic will influence legislation and key principles of governance in the Nordic countries. publishedVersion Peer reviewed

While many herald globalization - the increasing interconnectedness of national economies - to be associated with rising standards of living across the globe, others fear its effects on sustainability. Anti-globalization forces and environmentalists view these developments as a threat to the welfare of future generations because of profligate and excessive current consumption. This study is the first to estimate the effects of dependence on trade, foreign direct investment (FDI), and an index of economic freedom on the World Bank's measure of sustainability (the genuine savings rate), which measures the rate at which investment in the total stock of manufactured, human, and natural capital exceeds its depreciation. Contrary to pessimists' fears, our indicators of economic openness show positive effects on sustainability, results that are robust to sample size, testing procedure, and several alternative specifications. The results support those who suggest that distorted economies tend to be both inefficient and damaging to future generations. If increasing trade, foreign direct investment, and economic freedom are hallmarks of globalization, then worries about its effects on future well-being are misplaced.

The food systems upon which humanity depends face multiple interdependent environmental, social and economic threats in the 21st Century. Yet, the governance of these systems, which determines to a large extent the ability to adapt and transform in response to these challenges, is underresearched. This perspective piece synthesises the findings of two recent reviews of food systems governance and transformations and proposes a comprehensive research agenda for the coming years. These reviews highlight the influence of governance on food systems, methodological obstacles to explaining the effectiveness of governance in realising food sustainability, and conditions that have historically supported food system transformations. We argue that the following steps are key to improving our knowledge of the role of governance in food systems: (1) developing more comparable research designs for building generalisable explanations of the governance elements that are most effective in realising food systems goals; (2) using the lens of polycentricity to help disentangle complex governance networks; (3) giving greater attention to the conditions and pre-conditions associated with historical food system transformations; (4) identifying adaptations that strengthen or weaken path dependency; and, (5) focusing research on how transformations can be supported by institutions that facilitate collective action and stakeholder agency.

Terrorism is an instrument for groups that cannot achieve their political goals legally. One important strategic function of terrorism is to weaken the government – either directly by attacking representatives or supporters of the government or indirectly by causing a political response that is unpopular among the population. Often, however, political stability of the home government is buttressed by foreign powers. In this case, the terrorists can have a strategic interest in attacking nationals of these foreign countries. This article analyses this logic by looking at international alliances as a proxy for international support. If the friend of my enemy is my enemy, then terror entrepreneurs, which seek to overthrow their home country's government (the enemy), may find it attractive to target nationals of the foreign allies of their country (the friends of the enemy). The theory in this article predicts that attacking nationals of a foreign ally is particularly attractive if this ally is militarily more powerful than the home country. Moreover, the combined effect of alliance and relative power differentials becomes stronger the more democratic the ally and becomes weaker the more democratic the terrorists' home country. Empirical support for the hypotheses in this article is found in an analysis of a directed country dyad sample of international terrorism.

We propose to approximate the conditional expectation of a spatial random variable given its nearest-neighbour observations by an additive function. The setting is meaningful in practice and requires no unilateral ordering. It is capable of catching nonlinear features in spatial data and exploring local dependence structures. Our approach is different from both Markov field methods and disjunctive kriging. The asymptotic properties of the additive estimators have been established for $��$-mixing spatial processes by extending the theory of the backfitting procedure to the spatial case. This facilitates the confidence intervals for the component functions, although the asymptotic biases have to be estimated via (wild) bootstrap. Simulation results are reported. Applications to real data illustrate that the improvement in describing the data over the auto-normal scheme is significant when nonlinearity or non-Gaussianity is pronounced. Published at http://dx.doi.org/10.3150/07-BEJ5093 in the Bernoulli (http://isi.cbs.nl/bernoulli/) by the International Statistical Institute/Bernoulli Society (http://isi.cbs.nl/BS/bshome.htm)

One of the most intriguing facets of the climate system is that it exhibits variability across all temporal and spatial scales; pronounced examples are temperature and precipitation. The structure of this variability, however, is not arbitrary. Over certain spatial and temporal ranges, it can be described by scaling relationships in the form of power laws in probability density distributions and autocorrelation functions. These scaling relationships can be quantified by scaling exponents which measure how the variability changes across scales and how the intensity changes with frequency of occurrence. Scaling determines the relative magnitudes and persistence of natural climate fluctuations. Here, we review various scaling mechanisms and their relevance for the climate system. We show observational evidence of scaling and discuss the application of scaling properties and methods in trend detection, climate sensitivity analyses, and climate prediction.