Distribuição espacial da insegurança alimentar e nutricional e seus determinantes nos municípios do Estado de Goiás

Abstract

The objective of this study is to analyze the spatial distribution and the determinants of food and nutritional insecurity (FNI) in the municipalities of the state of Goiás. FNI is defined as the lack of necessary conditions for a healthy and sufficient diet to maintain the individual’s long-term well-being, considering their biological, social, psychological, and economic needs, among others. It is a multifactorial phenomenon involving factors related to availability, access, consumption, and utilization. Existing analyses reveal spatial patterns of FNI with a tendency for spatial clustering. However, this aspect has still been little explored in the analysis of FNI determinants. To investigate these issues, the study focuses on the State of Goiás, where largescale food production coexists with food insecurity. To achieve the proposed objective, FNI in the municipalities of Goiás was measured by calculating a food and nutritional security index, generated through a scoring protocol of 25 indicators. Based on this index, an exploratory spatial data analysis was conducted to identify spatial patterns in FNI prevalence. Additionally, a SAR-probit model was estimated to analyze the determinants of FNI, incorporating spatial dependence between municipalities. Results show that in Goiás, only 5.28% of municipalities are food and nutritional secure (FS), while the remaining 94.31% were classified as FNI. There is a predominance of mild FNI, with a higher prevalence of moderate and severe FNI in municipalities of the Northern Goiás mesoregion. The findings indicate that the Gini index of household income and unemployment are positively associated with the likelihood of FNI. Household per capita income, access to treated water, coverage of the Family Health Strategy (FHS) program, and exclusive breastfeeding up to four months are negatively associated. The exploratory data analysis reveals positive spatial autocorrelation, meaning neighboring municipalities tend to show similar FNS/FNI conditions. The SAR-probit model reinforces the existence of spatial dependence in the prevalence of FNI among municipalities, indicating similarity-based clustering. Exclusive breastfeeding up to four months, ESF coverage, and access to treated water were identified as the main determinants of FNI probability in Goiás, after spatial effects were controlled. Thus, these variables are the most strategic for locally focused FS intervention programs.