<p>Food security achievements and household vulnerability are the most significant concerns in national and international development. Therefore, this study measured the food security and vulnerability of farming households in the southern region of Bakhtegan Lake, Iran, by utilizing the Household Food Insecurity Access Scale (HFIAS) and the Livelihood Vulnerability Index (LVI). Furthermore, the study employed a data mining framework to identify both the food security and vulnerability patterns of farmers’ households simultaneously. Following Cochran’s formula, 350 rural households were selected for sampling purposes, and data was gathered through questionnaires and interviews conducted in person during 2022. The results showed that 45% of the surveyed rural households had sufficient food, while 11% faced mild food insecurity and 32% dealt with moderate food insecurity. Additionally, 12% of the families experienced extreme food insecurity. The results of the LVI showed that only 6.8% of farming families in southern Bakhtegan Lake were classified as not at risk, with 22.85% and 23.42% categorized as moderately and highly vulnerable, respectively. The data mining results led to the selection of a K-Means clustering model with four clusters. The findings also indicated that the “water resource status” element was the most important factor in creating clusters. The empirical results demonstrated that farmers in patterns two and one had the highest vulnerability and food security, respectively.</p>

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Food security and vulnerability of farmers household in the South of Bakhtegan Lake, Iran: uncovering patterns through data mining perspective

  • Fatemeh Ardali,
  • Mohammad Hassan Tarazkar,
  • Fatemeh Nasrnia

摘要

Food security achievements and household vulnerability are the most significant concerns in national and international development. Therefore, this study measured the food security and vulnerability of farming households in the southern region of Bakhtegan Lake, Iran, by utilizing the Household Food Insecurity Access Scale (HFIAS) and the Livelihood Vulnerability Index (LVI). Furthermore, the study employed a data mining framework to identify both the food security and vulnerability patterns of farmers’ households simultaneously. Following Cochran’s formula, 350 rural households were selected for sampling purposes, and data was gathered through questionnaires and interviews conducted in person during 2022. The results showed that 45% of the surveyed rural households had sufficient food, while 11% faced mild food insecurity and 32% dealt with moderate food insecurity. Additionally, 12% of the families experienced extreme food insecurity. The results of the LVI showed that only 6.8% of farming families in southern Bakhtegan Lake were classified as not at risk, with 22.85% and 23.42% categorized as moderately and highly vulnerable, respectively. The data mining results led to the selection of a K-Means clustering model with four clusters. The findings also indicated that the “water resource status” element was the most important factor in creating clusters. The empirical results demonstrated that farmers in patterns two and one had the highest vulnerability and food security, respectively.