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      Poverty–Food Insecurity Nexus in the Post-Construction Context of a Large Hydropower Dam in the Brazilian Amazon

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          Abstract

          Within the 2030 Sustainable Development Agenda, large hydropower dams are positioned as a sustainable energy source, notwithstanding their adverse impacts on societies and ecosystems. This study contributed to ongoing discussions about the persistence of critical social issues, even after the investments of large amounts of resources in areas impacted by the construction of large hydropower dams. Our study focused on food insecurity and evaluated this issue in the city of Altamira in the Brazilian Amazon, which has been profoundly socially and economically impacted by the construction, between 2011 and 2015, of Brazil’s second-largest dam, namely, Belo Monte. A survey in Altamira city featured a 500-household random sample. Structural equation modeling showed conditioning factors of 60% of the population experiencing varying food insecurity degrees. Poverty, female-led households, lower education, youth, and unemployment were strongly linked to higher food insecurity. Crowded, officially impacted, and resettled households also faced heightened food insecurity. Our findings underscore the food insecurity conditions in the region impacted by the Belo Monte dam, emphasizing the need to take into account this crucial issue while planning and implementing hydropower dams.

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          Estimating wealth effects without expenditure data—or tears: An application to educational enrollments in states of India

          Using data from India, we estimate the relationship between household wealth and children’s school enrollment. We proxy wealth by constructing a linear index from asset ownership indicators, using principal-components analysis to derive weights. In Indian data this index is robust to the assets included, and produces internally coherent results. State-level results correspond well to independent data on per capita output and poverty. To validate the method and to show that the asset index predicts enrollments as accurately as expenditures, or more so, we use data sets from Indonesia, Pakistan, and Nepal that contain information on both expenditures and assets. The results show large, variable wealth gaps in children’s enrollment across Indian states. On average a “rich” child is 31 percentage points more likely to be enrolled than a “poor” child, but this gap varies from only 4.6 percentage points in Kerala to 38.2 in Uttar Pradesh and 42.6 in Bihar.
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            COVID-19 risks to global food security

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              The role of conceptual frameworks in epidemiological analysis: a hierarchical approach.

              This paper discusses appropriate strategies for multivariate data analysis in epidemiological studies.
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                Author and article information

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                Journal
                IJERGQ
                International Journal of Environmental Research and Public Health
                IJERPH
                MDPI AG
                1660-4601
                February 2024
                January 30 2024
                : 21
                : 2
                : 155
                Article
                10.3390/ijerph21020155
                3f788087-0ff0-4997-8fc1-781d0c7ecb40
                © 2024

                https://creativecommons.org/licenses/by/4.0/

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