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Climate variability and health in extremely vulnerable communities: investigating variations in surface water conditions and food security in the West African Sahel

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A Correction to this article was published on 07 April 2021

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Abstract

In this project we consider the ways that different livelihood strategies impact the climate-health linkage. Specifically, we build on knowledge of livestock mobility in the Sahel and use remotely sensed-based measures of waterholes with health survey data to investigate the linkages between child health outcomes related to food security. We focus on the landscape characteristics relevant to limitedly studied, but highly climate-vulnerable populations, pastoralists and agro-pastoralists in the Sahel. We combine remotely sensed-based data on surface waterholes and spatially referenced health survey data and use flexible regression modeling techniques to uncover the quantitative relationship between waterhole depth and a child’s height-for-age z-score (HAZ). The results suggest that the water depth level of nearby waterholes does indeed impact a child’s HAZ, even after accounting for other environmental factors. This relationship is impacted, however, by the livelihood practices of the area as well as by the source of household drinking water.

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Notes

  1. Developed recently by USGS scientists in collaboration with Climate Hazards Center at the University of California, Santa Barbara.

  2. e.g. Global Precipitation Climatology Centre, Climate Prediction Center’s Unified precipitation data set, and University of Delaware’s precipitation data.

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Acknowledgements

We are thankful for the valuable feedback provided by Jim Rowland, Gabriel Senay, and Shrad Shukla. This project was supported, in part by SERVIR Applied Science Team (AST) project NASA grant # 80NSSC20K0163.

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Authors and Affiliations

  1. Department of Geography, Environment and Society University of Minnesota, MN, Minneapolis, USA

    Kathryn Grace

  2. Climate Hazards Center, University of California, Santa Barbara, CA, USA

    Frank Davenport

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  1. Kathryn Grace
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Correspondence to Kathryn Grace.

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Appendix

Appendix

Table 3 Linear regression model results with HAZ as continuous outcome variable
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Table 4 Model Quality Comparison
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Fig. 6
figure 6

Predicted HAZ values averaged over models [1–4], excluding environmental variables. Shaded area shows 95% prediction intervals averaged across models

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Grace, K., Davenport, F. Climate variability and health in extremely vulnerable communities: investigating variations in surface water conditions and food security in the West African Sahel. Popul Environ 42, 553–577 (2021). https://doi.org/10.1007/s11111-021-00375-9

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