1. Predicting the impacts of land management for sustainable development on depression risk in a Ugandan case study.
- Author
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Pienkowski T, Keane A, Kinyanda E, Asiimwe C, and Milner-Gulland EJ
- Subjects
- Agriculture, Bayes Theorem, Depression epidemiology, Humans, Uganda epidemiology, Conservation of Natural Resources, Sustainable Development
- Abstract
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., (© 2022. The Author(s).)
- Published
- 2022
- Full Text
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