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Background: Cost-effectiveness is a tool to maximize health benefits and to improve efficiency in healthcare. However, efficient outcomes are not always the most equitable ones. Distributional cost-effectiveness analysis (DCEA) offers a framework for incorporating equity concerns into cost-effectiveness analysis., Objective: This systematic review aims to outline the challenges and limitations in applying DCEA in healthcare settings., Methods: We searched Medline, Scopus, BASE, APA Psych, and JSTOR databases. We also included Google Scholar. We searched for English-language peer-reviewed academic publications, while books, editorials and commentary papers were excluded. Titles and abstract screening, full-text screening, reference list reviews, and data extraction were performed by the main researcher. Another researcher checked every paper for eligibility. Details, such as study population, disease area, intervention and comparators, costs and health effects, cost-effectiveness findings, equity analysis and effects, and modelling technique, were extracted. Thematic analysis was applied, focusing on challenges, obstacles, and gaps in DCEA., Results: In total, 615 references were identified, of which 18 studies met the inclusion criteria. Most of these studies were published after 2017. DCEA studies were mainly conducted in Europe and Africa and used quality health-adjusted measurements. In the included studies, absolute inequality indices were used more frequently than relative inequality indices. Every stage of the DCEA presented challenges and/or limitations., Conclusion: This review provides an overview of the literature on the DCEA in healthcare as well as the challenges and limitations related to the different steps needed to conduct the analysis. In particular, we found problems with data availability, the relative unfamiliarity of this analysis among policymakers, and challenges in estimating differences among socioeconomic groups.

Under the influence of economic globalization, the internationalization trend of energy security issues has become increasingly prominent. This paper adopts the natural discontinuity grading method to classify the energy security status of 102 countries into five categories: Best, Better, Good, Poor and Worse types; reveals the dynamic evolution characteristics and main formation mechanisms of world energy security; and puts forward the game focus of future energy geopolitics. The results show that: (1) during 1995-2019, global energy security presents local turbulence and an overall "J" shaped trend; (2) the global energy security pattern coincides with the international geopolitical order. The countries with the "Best" energy security are found in Western Europe and North America while the countries with "Poor" or "Worse" energy security are located in Asia and the less developed regions of Africa; (3) the main reason why developed economies have better energy security is due to their high energy use efficiency, while developing countries lag behind mainly because of their lower innovation capacity, lower productivity and lower disposable income; and (4) the global energy security landscape is expected to be affected by the changing US-China relationship, coercive energy transition and the uncertainty of the political environment.

Globally, traditional food security fears have been supplemented by concerns about food system sustainability that link current agricultural production practices to damages of environmental ecosystems and the world's climate, thus threatening the natural resource base of future generations. This paper aims at creating a better understanding of the evolution of diet sustainability from 1961 to 2013. Data from the Food and Agriculture Organization of the United Nations were used to investigate the situation for the world as a whole as well as for its macro-regions Africa, Asia, the Americas, Europe and Oceania. We define diet sustainability by (a) the share of daily per capita calorie intake derived from vegetable/plant products and (b) the variety of vegetable/plant products consumed, measured by the Simpson diversity index. Moreover, total calorie consumption is considered. Then the correlations between diet sustainability and (a) macro-regional life expectancy rates and (b) food system greenhouse gas emissions are calculated. The results show that diet sustainability has not changed much during the last 50 years. Moreover, the nexus between diets and health and climate outcomes is not fully evident at the macro-regional level. Therefore, Malthus 2.0, i.e., scientific food pessimism, should be avoided. In particular, the limitations of dietary contributions to human and planetary health ought to be more widely acknowledged., Competing Interests: The authors declare no conflict of interest.

Modern global cropland products have been widely used to assess the impact of land use and cover change (LUCC) on carbon budgets, climate change, terrestrial ecosystems, etc. However, each product has its own uncertainty, and inconsistencies exist among different products. Understanding the reliability of these datasets is essential for knowing the uncertainties that exist in the study of global change impact forced by cropland reclamation. In this paper, we propose a set of coincidence assessments to identify where reliable cropland distribution is by overlaying ten widely used global land cover/cropland datasets around 2000 AD. A quantitative assessment for different spatial units is also performed. We further discuss the spatial distribution characteristics of different coincidence degrees and explain the reasons. The results show that the high-coincidence proportion is only 40.5% around the world, and the moderate-coincidence and low-coincidence proportion is 18.4% and 41.1%, respectively. The coincidence degrees among different continents and countries have large discrepancies. The coincidence is relatively higher in Europe, South Asia and North America, while it is very poor in Latin America and Africa. The spatial distribution of high and moderate coincidence roughly corresponds to the regions with suitable agricultural conditions and intensive reclamation. In addition to the random factors such as the product's quality and the year it represented, the low coincidence is mainly caused by the inconsistent land cover classification systems and the recognition capability of cropland pixels with low fractions in different products., Competing Interests: The authors declare no conflict of interest.