Food security is one of the major concerns in the Philippines. Although livestock and poultry production accounts for a significant proportion of the country’s agricultural output, smallholder households are still vulnerable to food insecurity.
The current study aims to examine how livestock production and selling difficulties affect food-insecure conditions of smallholder households.
The study employed the mindsponge theory as its theoretical foundation for constructing the models. Subsequently, it applied the Bayesian mindsponge framework (BMF) analytics to analyse a dataset sourced from the Data in Emergencies Monitoring (DIEM) system of the Food and Agriculture Organization. Key variables in the dataset were transformed into indicators, enabling a detailed examination of smallholder livestock farmers’ difficulties in production or selling over the past 3 months. Production difficulties include hurdles in raising and producing livestock, covering aspects such as resource acquisition, animal health, and breeding. Selling difficulties involve obstacles in selling livestock products, including issues related to market access, pricing, and transportation.