نوع مقاله : مقالات پژوهشی
نویسندگان
1 استادیار اقتصاد کشاورزی، دانشگاه پیام نور، تهران، ایران.
2 استادیار گروه اقتصاد کشاورزی دانشگاه پیام نور ،تهران ، ایران
کلیدواژهها
عنوان مقاله English
نویسندگان English
Introduction
Food security and nutritional welfare are among the most important dimensions of social well-being and sustainable development. In recent years, inflation, fluctuations in food prices, and increasing income inequality have significantly influenced household food consumption patterns in Iran. Among different food groups, protein products such as red meat, poultry, fish, and eggs are considered key indicators of dietary quality because they provide essential nutrients necessary for human health. Therefore, examining protein consumption patterns can provide valuable insights into food welfare and nutritional inequality across regions. Regional disparities in income, purchasing power, and food accessibility have created considerable differences in dietary behavior among Iranian provinces. While some provinces benefit from better economic conditions and diversified food markets, others face higher food expenditure burdens and limited access to quality protein sources. In this context, identifying the structural dimensions of food welfare is essential for designing effective nutrition and food security policies. Accordingly, this study aims to analyze the structure of protein consumption and evaluate food welfare across Iranian provinces using multivariate statistical methods.
Materials and Methods
This study used data from the 2024 Iranian Urban Household Income and Expenditure Survey conducted by the Statistical Center of Iran. The analysis was initially performed at the household level using data from more than 19,000 urban households and subsequently aggregated to the provincial level for the 31 provinces of Iran. Four variables were selected as indicators of protein consumption: per capita consumption of red meat, poultry meat, fish, and eggs. In the first stage, household-level variables were standardized and analyzed using Principal Component Analysis (PCA) to reduce dimensionality and identify dominant dietary patterns. The first principal component (PC1), which explained the largest share of variance, was interpreted as a composite “Food Welfare Index.” Provincial averages of this index were then calculated. To examine spatial dependence, Moran’s I statistic was applied using a contiguity-based spatial weight matrix. Since the results indicated no significant spatial autocorrelation, multivariate cluster analysis based on the K-means algorithm was employed to classify provinces according to similarities in food welfare and selected socioeconomic variables, including household income, unemployment, Gini coefficient, food expenditure share, and inflation rate.
Results and Discussion
The results showed that the first principal component explained approximately 41.8 percent of the total variance in protein consumption variables and could therefore be interpreted as a reliable indicator of food welfare. Factor loadings indicated that red meat, poultry, and egg consumption contributed most strongly to the index. Moran’s I statistic was negative and statistically insignificant, suggesting that food welfare patterns across provinces do not follow a meaningful spatial clustering process. This finding implies that differences in food welfare are influenced more by structural and socioeconomic factors than by geographical proximity. Cluster analysis identified three distinct groups of provinces with different combinations of dietary quality, income conditions, and inequality levels. Some provinces exhibited relatively favorable food welfare despite moderate income levels, indicating the importance of local production systems and traditional dietary patterns. Other provinces showed lower food welfare associated with higher inequality and food expenditure burdens. In more urbanized provinces, greater dependence on food markets and changing consumption behavior appeared to reduce dietary quality despite relatively higher nominal incomes.
Conclusion
The findings demonstrate that food welfare in Iran is a multidimensional phenomenon shaped by income distribution, inflation, household expenditure structures, and market dependence rather than by simple geographical proximity. The study highlights substantial regional disparities in protein consumption and dietary quality across provinces. From a policy perspective, the results emphasize the importance of targeted and region-specific nutritional policies. Improving access to affordable protein products, reducing income inequality, supporting vulnerable households, and strengthening local food systems can contribute significantly to improving food security and nutritional welfare in Iran. Furthermore, the integrated analytical framework used in this study can provide a useful model for future research on food security and regional inequality in developing countries.
Introduction
Food security and nutritional welfare are among the most important dimensions of social well-being and sustainable development. In recent years, inflation, fluctuations in food prices, and increasing income inequality have significantly influenced household food consumption patterns in Iran. Among different food groups, protein products such as red meat, poultry, fish, and eggs are considered key indicators of dietary quality because they provide essential nutrients necessary for human health. Therefore, examining protein consumption patterns can provide valuable insights into food welfare and nutritional inequality across regions. Regional disparities in income, purchasing power, and food accessibility have created considerable differences in dietary behavior among Iranian provinces. While some provinces benefit from better economic conditions and diversified food markets, others face higher food expenditure burdens and limited access to quality protein sources. In this context, identifying the structural dimensions of food welfare is essential for designing effective nutrition and food security policies. Accordingly, this study aims to analyze the structure of protein consumption and evaluate food welfare across Iranian provinces using multivariate statistical methods.
کلیدواژهها English