Food and nutrition security trends and challenges in the Ganges Brahmaputra Meghna (GBM) delta

• Main Authors: Arnout van Soesbergen, Kristine Nilsen, Neil D. Burgess, Sylvia Szabo, Zoë Matthews
• Format: Article
• Language: English
• Published: BioOne 2017-09-01
• Series: Elementa: Science of the Anthropocene
• Subjects: GBM Delta; nutrition; climate change; NDVI; stunting; wasting
• Online Access: https://www.elementascience.org/articles/153

The population of the Ganges Brahmaputra Meghna (GBM) delta is highly vulnerable to food insecurity and malnutrition due to the specific environmental, climatic and human development factors affecting agricultural production and fisheries. To better understand the impacts of climate and environmental change on food security and nutrition in this delta, this study combines spatially explicit data from the 2007 and 2011 Bangladesh Demographic and Health Survey (BDHS) with a standard satellite remotely sensed vegetation greenness index (Normalised Difference Vegetation Index, NDVI), used as a proxy for rice production. The strength of association between NDVI and child nutrition in this tropical mega-delta were tested, showing correlations between two widely used indicators of child malnutrition; stunting and wasting, and deviations from a 10 year mean NDVI (anomalies) for rice crop growing seasons – regarded as critical to individual children’s early lives. For children surveyed in 2007 we found that the likelihood of being stunted decreased with increased NDVI as a measure of food production. Similarly, for children surveyed in 2011, the likelihood of being wasted reduced with increased NDVI. However, regression results for stunting in 2011 and wasting in 2007 were not statistically significant. Our findings suggest that NDVI can be regarded as indicative of climatic variability and periods of low food production but is only partly successful as an indicator of climate related impacts on child nutrition in the GBM delta. Furthermore, our study highlights some of the uncertainties and challenges with linking environmental indicators such as the NDVI with household survey data across spatial and temporal scales.