184 research outputs found
The sociology of ecologically unequal exchange, foreign investment dependence and environmental load displacement: summary of the literature and implications for sustainability
The article begins by summarizing sociological approaches to (1) ecologically unequal exchange, and (2) foreign investment dependence and environmental load displacement. These areas of sociological inquiry consist of structural theories and cross-national statistical analyses that test hypotheses derived from both approaches. It concludes by briefly describing sociological research on global civil society and the environment, with a focus on the world society approach to environmental change. This area of theory and research provides some insights on ways in which global and transnational civil society groups, such as environmental international nongovernmental organizations, can partially mitigate the environmental harms caused by ecologically unequal exchanges and environmental load displacements.
Key words: ecologically unequal exchange, environmental load displacement, foreign investment dependenc
Power, Proximity, and Physiology: Does Income Inequality and Racial Composition Amplify the Impacts of Air Pollution on Life Expectancy in the United States?
This study advances research at the intersection of environmental degradation, social stratification, and population health in the United States. Expanding the theoretical principles of power, proximity, and physiology, we hypothesize that the harmful effect of fine particulate matter on life expectancy is greater in states with higher levels of income inequality and larger black populations. To test our hypothesis, we use two-way fixed effects regression analysis to estimate the effect of a three-way interaction between fine particulate matter, income share of the top ten percent, and the percent of the population that is black on state-level average life expectancy for all US states and the District of Columbia (2000–2014). The findings support our hypothesis: the estimated effect of the three-way interaction on average life expectancy is negative and statistically significant, net of various socioeconomic and demographic controls. Using post-estimation techniques, we visually illustrate that the harmful effect of fine particulate matter on life expectancy is especially pronounced in states with both very high levels of income inequality and very large black populations. We conclude by summarizing the theoretical and substantive implications of our findings, the limitations of the study, and potential next steps in this evolving area of interdisciplinary research
Social science perspectives on drivers of and responses to global
This article provides a review of recent anthropological, archeological, geographical, and sociological research on anthropogenic drivers of climate change, with a particular focus on drivers of carbon emissions, mitigation and adaptation. The four disciplines emphasize cultural, economic, geographic, historical, political, and social‐structural factors to be important drivers of and responses to climate change. Each of these disciplines has unique perspectives and makes noteworthy contributions to our shared understanding of anthropogenic drivers, but they also complement one another and contribute to integrated, multidisciplinary frameworks. The article begins with discussions of research on temporal dimensions of human drivers of carbon emissions, highlighting interactions between long‐term and near‐term drivers. Next, descriptions of the disciplines\u27 contributions to the understanding of mitigation and adaptation are provided. It concludes with a summary of key lessons offered by the four disciplines as well as suggestions for future research
The relationship between international trade and non-nutritional health outcomes : A systematic review of quantitative studies
Markets throughout the world have been reducing barriers to international trade and investment in recent years. The resulting increases in levels of international trade and investment have subsequently generated research interest into the potential population health impact. We present a systematic review of quantitative studies investigating the relationship between international trade, foreign direct investment and non-nutritional health outcomes. Articles were systematically collected from the SCOPUS, PubMed, EconLit and Web of Science databases. Due to the heterogeneous nature of the evidence considered, the 16 included articles were subdivided into individual level data analyses, selected country analyses and international panel analyses. Articles were then quality assessed using a tool developed as part of the project. Nine of the studies were assessed to be high quality, six as medium quality, and one as low quality. The evidence from the quantitative literature suggests that overall, there appears to be a beneficial association between international trade and population health. There was also evidence of the importance of foreign direct investment, yet a lack of research considering the direction of causality. Taken together, quantitative research into the relationship between trade and non-nutritional health indicates trade to be beneficial, yet this body of research is still in its infancy. Future quantitative studies based on this foundation will provide a stronger basis on which to inform relevant national and international institutions about the health consequences of trade policies
A meta-analysis of the investment-uncertainty relationship
In this article we use meta-analysis to investigate the investment-uncertainty relationship. We focus on the direction and statistical significance of empirical estimates. Specifically, we estimate an ordered probit model and transform the estimated coefficients into marginal effects to reflect the changes in the probability of finding a significantly negative estimate, an insignificant estimate, or a significantly positive estimate. Exploratory data analysis shows that there is little empirical evidence for a positive relationship. The regression results suggest that the source of uncertainty, the level of data aggregation, the underlying model specification, and differences between short- and long-run effects are important sources of variation in study outcomes. These findings are, by and large, robust to the introduction of a trend variable to capture publication trends in the literature. The probability of finding a significantly negative relationship is higher in more recently published studies. JEL Classification: D21, D80, E22 1
The Polygenic and Monogenic Basis of Blood Traits and Diseases
Blood cells play essential roles in human health, underpinning physiological processes such as immunity, oxygen transport, and clotting, which when perturbed cause a significant global health burden. Here we integrate data from UK Biobank and a large-scale international collaborative effort, including data for 563,085 European ancestry participants, and discover 5,106 new genetic variants independently associated with 29 blood cell phenotypes covering a range of variation impacting hematopoiesis. We holistically characterize the genetic architecture of hematopoiesis, assess the relevance of the omnigenic model to blood cell phenotypes, delineate relevant hematopoietic cell states influenced by regulatory genetic variants and gene networks, identify novel splice-altering variants mediating the associations, and assess the polygenic prediction potential for blood traits and clinical disorders at the interface of complex and Mendelian genetics. These results show the power of large-scale blood cell trait GWAS to interrogate clinically meaningful variants across a wide allelic spectrum of human variation. Analysis of blood cell traits in the UK Biobank and other cohorts illuminates the full genetic architecture of hematopoietic phenotypes, with evidence supporting the omnigenic model for complex traits and linking polygenic burden with monogenic blood diseases
Hair Cortisol in Twins : Heritability and Genetic Overlap with Psychological Variables and Stress-System Genes
A. Palotie on työryhmän jäsen.Hair cortisol concentration (HCC) is a promising measure of long-term hypothalamus-pituitary-adrenal (HPA) axis activity. Previous research has suggested an association between HCC and psychological variables, and initial studies of inter-individual variance in HCC have implicated genetic factors. However, whether HCC and psychological variables share genetic risk factors remains unclear. The aims of the present twin study were to: (i) assess the heritability of HCC; (ii) estimate the phenotypic and genetic correlation between HPA axis activity and the psychological variables perceived stress, depressive symptoms, and neuroticism; using formal genetic twin models and molecular genetic methods, i.e. polygenic risk scores (PRS). HCC was measured in 671 adolescents and young adults. These included 115 monozygotic and 183 dizygotic twin-pairs. For 432 subjects PRS scores for plasma cortisol, major depression, and neuroticism were calculated using data from large genome wide association studies. The twin model revealed a heritability for HCC of 72%. No significant phenotypic or genetic correlation was found between HCC and the three psychological variables of interest. PRS did not explain variance in HCC. The present data suggest that HCC is highly heritable. However, the data do not support a strong biological link between HCC and any of the investigated psychological variables.Peer reviewe
Genome-wide interaction study of a proxy for stress-sensitivity and its prediction of major depressive disorder
Individual response to stress is correlated with neuroticism and is an important predictor of both neuroticism and the onset of major depressive disorder (MDD). Identification of the genetics underpinning individual differences in response to negative events (stress-sensitivity) may improve our understanding of the molecular pathways involved, and its association with stress-related illnesses. We sought to generate a proxy for stress-sensitivity through modelling the interaction between SNP allele and MDD status on neuroticism score in order to identify genetic variants that contribute to the higher neuroticism seen in individuals with a lifetime diagnosis of depression compared to unaffected individuals. Meta-analysis of genome-wide interaction studies (GWIS) in UK Biobank (N = 23,092) and Generation Scotland: Scottish Family Health Study (N = 7,155) identified no genome-wide significance SNP interactions. However, gene-based tests identified a genome-wide significant gene, ZNF366, a negative regulator of glucocorticoid receptor function implicated in alcohol dependence (p = 1.48x10-7; Bonferroni-corrected significance threshold p < 2.79x10-6). Using summary statistics from the stress-sensitivity term of the GWIS, SNP heritability for stress-sensitivity was estimated at 5.0%. In models fitting polygenic risk scores of both MDD and neuroticism derived from independent GWAS, we show that polygenic risk scores derived from the UK Biobank stress-sensitivity GWIS significantly improved the prediction of MDD in Generation Scotland. This study may improve interpretation of larger genome-wide association studies of MDD and other stress-related illnesses, and the understanding of the etiological mechanisms underpinning stress-sensitivity
Association studies of up to 1.2 million individuals yield new insights into the genetic etiology of tobacco and alcohol use
Tobacco and alcohol use are leading causes of mortality that influence risk for many complex diseases and disorders 1 . They are heritable 2,3 and etiologically related 4,5 behaviors that have been resistant to gene discovery efforts 6–11 . In sample sizes up to 1.2 million individuals, we discovered 566 genetic variants in 406 loci associated with multiple stages of tobacco use (initiation, cessation, and heaviness) as well as alcohol use, with 150 loci evidencing pleiotropic association. Smoking phenotypes were positively genetically correlated with many health conditions, whereas alcohol use was negatively correlated with these conditions, such that increased genetic risk for alcohol use is associated with lower disease risk. We report evidence for the involvement of many systems in tobacco and alcohol use, including genes involved in nicotinic, dopaminergic, and glutamatergic neurotransmission. The results provide a solid starting point to evaluate the effects of these loci in model organisms and more precise substance use measures
Genetic diversity fuels gene discovery for tobacco and alcohol use
Tobacco and alcohol use are heritable behaviours associated with 15% and 5.3% of worldwide deaths, respectively, due largely to broad increased risk for disease and injury(1-4). These substances are used across the globe, yet genome-wide association studies have focused largely on individuals of European ancestries(5). Here we leveraged global genetic diversity across 3.4 million individuals from four major clines of global ancestry (approximately 21% non-European) to power the discovery and fine-mapping of genomic loci associated with tobacco and alcohol use, to inform function of these loci via ancestry-aware transcriptome-wide association studies, and to evaluate the genetic architecture and predictive power of polygenic risk within and across populations. We found that increases in sample size and genetic diversity improved locus identification and fine-mapping resolution, and that a large majority of the 3,823 associated variants (from 2,143 loci) showed consistent effect sizes across ancestry dimensions. However, polygenic risk scores developed in one ancestry performed poorly in others, highlighting the continued need to increase sample sizes of diverse ancestries to realize any potential benefit of polygenic prediction.Peer reviewe
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