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Spatial clustering of food insecurity and its association with depression: a geospatial analysis of nationally representative South African data, 2008–2015
While food insecurity is a persistent public health challenge, its long-term association with depression at a national level is unknown. We investigated the spatial heterogeneity of food insecurity and its association with depression in South Africa (SA), using nationally-representative panel data f...
Autores principales: | , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group UK
2020
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7426853/ https://www.ncbi.nlm.nih.gov/pubmed/32792498 http://dx.doi.org/10.1038/s41598-020-70647-1 |
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author | Tomita, Andrew Cuadros, Diego F. Mabhaudhi, Tafadzwanashe Sartorius, Benn Ncama, Busisiwe P. Dangour, Alan D. Tanser, Frank Modi, Albert T. Slotow, Rob Burns, Jonathan K. |
author_facet | Tomita, Andrew Cuadros, Diego F. Mabhaudhi, Tafadzwanashe Sartorius, Benn Ncama, Busisiwe P. Dangour, Alan D. Tanser, Frank Modi, Albert T. Slotow, Rob Burns, Jonathan K. |
author_sort | Tomita, Andrew |
collection | PubMed |
description | While food insecurity is a persistent public health challenge, its long-term association with depression at a national level is unknown. We investigated the spatial heterogeneity of food insecurity and its association with depression in South Africa (SA), using nationally-representative panel data from the South African National Income Dynamics Study (years 2008–2015). Geographical clusters (“hotpots”) of food insecurity were identified using Kulldorff spatial scan statistic in SaTScan. Regression models were fitted to assess association between residing in food insecure hotspot communities and depression. Surprisingly, we found food insecurity hotspots (p < 0.001) in high-suitability agricultural crop and livestock production areas with reliable rainfall and fertile soils. At baseline (N = 15,630), we found greater likelihood of depression in individuals residing in food insecure hotspot communities [adjusted relative risk (aRR) = 1.13, 95% CI:1.01–1.27] using a generalized linear regression model. When the panel analysis was limited to 8,801 participants who were depression free at baseline, residing in a food insecure hotspot community was significantly associated with higher subsequent incidence of depression (aRR = 1.11, 95% CI:1.01–1.22) using a generalized estimating equation regression model. The association persisted even after controlling for multiple socioeconomic factors and household food insecurity. We identified spatial heterogeneity of food insecurity at a national scale in SA, with a demonstrated greater risk of incident depression in hotspots. More importantly, our finding points to the “Food Security Paradox”, food insecurity in areas with high food-producing potential. There is a need for place-based policy interventions that target communities vulnerable to food insecurity, to reduce the burden of depression. |
format | Online Article Text |
id | pubmed-7426853 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | Nature Publishing Group UK |
record_format | MEDLINE/PubMed |
spelling | pubmed-74268532020-08-14 Spatial clustering of food insecurity and its association with depression: a geospatial analysis of nationally representative South African data, 2008–2015 Tomita, Andrew Cuadros, Diego F. Mabhaudhi, Tafadzwanashe Sartorius, Benn Ncama, Busisiwe P. Dangour, Alan D. Tanser, Frank Modi, Albert T. Slotow, Rob Burns, Jonathan K. Sci Rep Article While food insecurity is a persistent public health challenge, its long-term association with depression at a national level is unknown. We investigated the spatial heterogeneity of food insecurity and its association with depression in South Africa (SA), using nationally-representative panel data from the South African National Income Dynamics Study (years 2008–2015). Geographical clusters (“hotpots”) of food insecurity were identified using Kulldorff spatial scan statistic in SaTScan. Regression models were fitted to assess association between residing in food insecure hotspot communities and depression. Surprisingly, we found food insecurity hotspots (p < 0.001) in high-suitability agricultural crop and livestock production areas with reliable rainfall and fertile soils. At baseline (N = 15,630), we found greater likelihood of depression in individuals residing in food insecure hotspot communities [adjusted relative risk (aRR) = 1.13, 95% CI:1.01–1.27] using a generalized linear regression model. When the panel analysis was limited to 8,801 participants who were depression free at baseline, residing in a food insecure hotspot community was significantly associated with higher subsequent incidence of depression (aRR = 1.11, 95% CI:1.01–1.22) using a generalized estimating equation regression model. The association persisted even after controlling for multiple socioeconomic factors and household food insecurity. We identified spatial heterogeneity of food insecurity at a national scale in SA, with a demonstrated greater risk of incident depression in hotspots. More importantly, our finding points to the “Food Security Paradox”, food insecurity in areas with high food-producing potential. There is a need for place-based policy interventions that target communities vulnerable to food insecurity, to reduce the burden of depression. Nature Publishing Group UK 2020-08-13 /pmc/articles/PMC7426853/ /pubmed/32792498 http://dx.doi.org/10.1038/s41598-020-70647-1 Text en © The Author(s) 2020 Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/. |
spellingShingle | Article Tomita, Andrew Cuadros, Diego F. Mabhaudhi, Tafadzwanashe Sartorius, Benn Ncama, Busisiwe P. Dangour, Alan D. Tanser, Frank Modi, Albert T. Slotow, Rob Burns, Jonathan K. Spatial clustering of food insecurity and its association with depression: a geospatial analysis of nationally representative South African data, 2008–2015 |
title | Spatial clustering of food insecurity and its association with depression: a geospatial analysis of nationally representative South African data, 2008–2015 |
title_full | Spatial clustering of food insecurity and its association with depression: a geospatial analysis of nationally representative South African data, 2008–2015 |
title_fullStr | Spatial clustering of food insecurity and its association with depression: a geospatial analysis of nationally representative South African data, 2008–2015 |
title_full_unstemmed | Spatial clustering of food insecurity and its association with depression: a geospatial analysis of nationally representative South African data, 2008–2015 |
title_short | Spatial clustering of food insecurity and its association with depression: a geospatial analysis of nationally representative South African data, 2008–2015 |
title_sort | spatial clustering of food insecurity and its association with depression: a geospatial analysis of nationally representative south african data, 2008–2015 |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7426853/ https://www.ncbi.nlm.nih.gov/pubmed/32792498 http://dx.doi.org/10.1038/s41598-020-70647-1 |
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