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Predicting the impacts of land management for sustainable development on depression risk in a Ugandan case study
by
Milner-Gulland, E. J.
, Asiimwe, Caroline
, Pienkowski, Thomas
, Keane, Aidan
, Kinyanda, Eugene
in
631/158/2458
/ 631/158/672
/ 692/699/476
/ 692/699/476/1414
/ 704/844/1759
/ 704/844/685
/ Agricultural economics
/ Agriculture
/ Bayes Theorem
/ Bayesian analysis
/ Conservation of Natural Resources
/ Contract farming
/ Depression - epidemiology
/ Food
/ Food security
/ Forest conservation
/ Forests
/ Households
/ Humanities and Social Sciences
/ Humans
/ Intensive farming
/ Land management
/ Land use
/ Land use planning
/ Mental depression
/ Mental health
/ multidisciplinary
/ Poverty
/ Protected areas
/ Science
/ Science (multidisciplinary)
/ Small farms
/ Small-scale farming
/ Sugarcane
/ Sustainability
/ Sustainable Development
/ Sustainable use
/ Uganda - epidemiology
2022
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Predicting the impacts of land management for sustainable development on depression risk in a Ugandan case study
by
Milner-Gulland, E. J.
, Asiimwe, Caroline
, Pienkowski, Thomas
, Keane, Aidan
, Kinyanda, Eugene
in
631/158/2458
/ 631/158/672
/ 692/699/476
/ 692/699/476/1414
/ 704/844/1759
/ 704/844/685
/ Agricultural economics
/ Agriculture
/ Bayes Theorem
/ Bayesian analysis
/ Conservation of Natural Resources
/ Contract farming
/ Depression - epidemiology
/ Food
/ Food security
/ Forest conservation
/ Forests
/ Households
/ Humanities and Social Sciences
/ Humans
/ Intensive farming
/ Land management
/ Land use
/ Land use planning
/ Mental depression
/ Mental health
/ multidisciplinary
/ Poverty
/ Protected areas
/ Science
/ Science (multidisciplinary)
/ Small farms
/ Small-scale farming
/ Sugarcane
/ Sustainability
/ Sustainable Development
/ Sustainable use
/ Uganda - epidemiology
2022
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Do you wish to request the book?
Predicting the impacts of land management for sustainable development on depression risk in a Ugandan case study
by
Milner-Gulland, E. J.
, Asiimwe, Caroline
, Pienkowski, Thomas
, Keane, Aidan
, Kinyanda, Eugene
in
631/158/2458
/ 631/158/672
/ 692/699/476
/ 692/699/476/1414
/ 704/844/1759
/ 704/844/685
/ Agricultural economics
/ Agriculture
/ Bayes Theorem
/ Bayesian analysis
/ Conservation of Natural Resources
/ Contract farming
/ Depression - epidemiology
/ Food
/ Food security
/ Forest conservation
/ Forests
/ Households
/ Humanities and Social Sciences
/ Humans
/ Intensive farming
/ Land management
/ Land use
/ Land use planning
/ Mental depression
/ Mental health
/ multidisciplinary
/ Poverty
/ Protected areas
/ Science
/ Science (multidisciplinary)
/ Small farms
/ Small-scale farming
/ Sugarcane
/ Sustainability
/ Sustainable Development
/ Sustainable use
/ Uganda - epidemiology
2022
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Predicting the impacts of land management for sustainable development on depression risk in a Ugandan case study
Journal Article
Predicting the impacts of land management for sustainable development on depression risk in a Ugandan case study
2022
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Overview
Agricultural intensification and expanding protected areas are proposed sustainable development approaches. But, their consequences for mental health are poorly understood. This study aims to predict how forest conservation and contract farming may alter resource access and depression risk in rural Uganda. Residents (
N
= 695) in 11 communities in Masindi District were asked about their expectations under land management scenarios using scenario-based interviews, household characteristics and depression symptoms. Over 80% of respondents presented with a ‘business-as-usual forest access’ scenario expected reduced access to forest income and food over the next decade; this number climbed above 90% among ‘restricted forest access’ scenario respondents. Over 99% of those presented with two land access scenarios (‘business-as-usual land access’ and ‘sugarcane expansion land access’) expected wealthy households to gain land but poorer families to lose it, threatening to increase poverty and food insecurity among small-scale farmers. Bayesian structural equation modelling suggested that depression severity was positively associated with food insecurity (0.20, 95% CI = 0.12–0.28) and economic poverty (0.11, 95% CI 0.02–0.19). Decision-makers should evaluate the mental health impacts of conservation and agricultural approaches that restrict access to livelihood resources. Future research could explore opportunities to support mental health through sustainable use of nature.
Publisher
Nature Publishing Group UK,Nature Publishing Group,Nature Portfolio
Subject
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