Aging Population, Balanced Diet and China's Grain Demand.

Area of Science:

• Agricultural Economics
• Food Security Studies
• Population Dynamics

Background:

• Accurate grain demand forecasting is critical for global food security.
• Previous models often overlooked the simultaneous impact of multiple influencing factors.
• The need for improved short-term grain demand (GD) prediction is paramount.

Purpose of the Study:

• To develop and illustrate a multi-factor model for enhancing short-term grain demand (GD) prediction.
• To integrate key factors including dietary shifts, population demographics, urbanization, and food waste.
• To provide updated projections for China's annual GD from 2022 to 2025.

Main Methods:

• Developed a multi-factor model incorporating dietary structure, population size and age, urbanization, food waste, and COVID-19 impact.
• Calibrated model parameters using the latest available survey and statistical data.
• Projected China's annual GD under different dietary scenarios (2013-2019 trends vs. 2022 guidelines).

Main Results:

• Projected China's GD to be 629.35 million tons in 2022 and 658.16 million tons in 2025 under 2013-2019 dietary trends.
• A shift towards recommended diets could reduce annual GD by 5.9-11.1%, primarily through reduced feed grain.
• Ignoring population age structure could overestimate GD by 3.8%; reducing food waste significantly impacts GD reduction.

Conclusions:

• Simultaneous consideration of dietary structure and demographic composition is essential for accurate GD prediction.
• Policy interventions focusing on dietary shifts and food waste reduction are vital for grain security, health, and environmental sustainability.
• The model provides valuable insights for policymakers addressing complex challenges in the grain sector.