Table 2 Overview of the nine selected peer-reviewed articles
Authors (year) | Study objectives | Spatial analysis method(s) | Geodata | Scale of geodata/level of analysis | Retro- or prospective (time span for analysis) | Geographic region |
|---|---|---|---|---|---|---|
Balk et al.[23] | Capture the effects of geographic and environmental variables on child hunger. Looking for causal relationships using micro-level data on a continental scale. | - Spatial Statistics: Simple ordinary least squares (OLS) regression analysis | - Agriculture | Local and regional data/Micro- and meso-level analysis | Retrospective (1995–2004) | African, Asian and Latin American countries |
- Climate | ||||||
- Health (+DHS*) | ||||||
- Infrastructure | ||||||
- Physiography | ||||||
- Politics | ||||||
- Population | ||||||
Grace et al.[19] | Evaluate the relationship between climate variables and child malnutrition using a food security framework | - Spatial Statistics: Multi-level linear regression model | - Climate | Household and local data/Micro-level analysis | Retrospective and Prospective (1990–2039) | Kenya |
- DHS* | ||||||
- Livelihood | ||||||
- Zones | ||||||
- Population | ||||||
- Spatial Interpolation: Geostatistical interpolation using a moving window regression | ||||||
Jankowska et al.[20] | Examine and project climate and health trends in the African Sahel through the spatial coupling of climate data and health data in Mali. | - Spatial Statistics: Multivariate linear regression analysis | - Climate | Local and regional data/Meso-level analysis | Prospective (1960–2039) | Mali |
- DHS* | ||||||
- Livelihood | ||||||
- Zones | ||||||
- Physiography | ||||||
- Population | ||||||
- Spatial Interpolation: Geostatistical interpolation using a moving window regression | ||||||
Kandala et al.[25] | Investigate the geographical and socioeconomic determinants of childhood undernutrition. Explore regional patterns of undernutrition. | - Spatial Statistics: Bayesian geo-additive regression model based on Markov priors | - DHS* | Local data/Meso-level analysis | Retrospective (1992) | Malawi, Tanzania and Zambia |
- Socioeconomics | ||||||
Liu et al.[21] | Spatially explicit assessment of current and future hotspots of food insecurity in SSA. Analyzing the impact of climate change on crop production. | - Spatial Modeling: Simulate dynamics of agricultural production | - Climate | Local and regional data/Meso-level analysis | Prospective (1990–2030) | Sub-Saharan Africa |
- DHS* | ||||||
- Economic | ||||||
- Population | ||||||
- Spatial Analysis: Hotspot analysis | ||||||
Margai[22] | Discuss the multi-dimensional causes of food insecurity conditions, analyze the relation- ships between food insufficiency and nutritional health outcomes among children, and identify the demographic, socio-economic and environmental correlates of these conditions. | - Spatial Analysis: Road network distance analysis | - Agriculture | Household and regional data/Meso-level analysis | Retrospective (1999) | Burkina Faso |
- Spatial Interpolation: Kriging algorithm | - DHS* | |||||
- Spatial Statistics/Statistical Methods: Chi-square test, Logistic regression analysis | - Infrastructure | |||||
Pawloski et al.[26] | Examine geographic relationships of nutritional status, including underweight, overweight and obesity among Kenyan mothers and children. | - Spatial Statistics: Getis–Ord General G Statistics, Gi* Statistic | - DHS* | Local data/Meso-level analysis | Retrospective (2003/2006) | Kenya |
Rowhani et al.[18] | Present the influence of the climate-induced changes of ecosystem resources on malnutrition and armed conflict. | - Spatial Statistics: Logistic regression models | - Agriculture | Local and regional data/Micro- and meso-level analysis | Retrospective (1946–2006) | Sudan, Ethiopia and Somalia |
- Economics | ||||||
- Health | ||||||
- Infrastructure | ||||||
- Politics | ||||||
Sherbinin[24] | Determine if, when controlling for income and the health conditions, biophysical and geographical variables help to explain variation in the rates of child malnutrition. | - Spatial Statistics: OLS Regression, Spatial Autocorrelation, Spatial Error (SE) model | - Agriculture | Regional data/Meso-level analysis | Retrospective | Africa |
- Climate | ||||||
- Economics | ||||||
- Health (+DHS*) | ||||||
- Infrastructure | ||||||
- Physiography | ||||||
- Population |