Estimating dietary intake and nutrient adequacy among adults in Saudi Arabia: a population-based assessment.

Abstract

Non‑communicable diseases (NCDs) pose a significant health challenge in Saudi Arabia, where 18.95% of adults report at least one chronic condition, including diabetes (9.1%), hypertension (7.9%), and cardiovascular diseases (1.5%). This burden highlights the need for reliable, national‑level estimation of dietary intake and nutrient adequacy to inform evidence‑based nutrition policy. Therefore, this study aimed to estimate dietary intake, nutrient exposure, and adequacy among Saudi adults using an updated, locally developed probabilistic model (NNC‑v2). This modeling study was developed a model using nationally published data from Saudi Arabia starting in 2010. The model was designed to generate probabilistic estimates that account for uncertainty and variability by linking food supply data to population-level intake and nutrient exposure. Model parameters were specified as statistical distributions rather than fixed values, allowing variability and uncertainty to propagate through the estimation process. Age-related intake adjustment and routine variation were incorporated within the model structure. Nutrient adequacy was evaluated using a Monte Carlo-based Average Requirement cut-point approach (10,000 iterations). Predictive performance was assessed indirectly by comparing model-derived food expenditure with national survey data. Grains estimated intake (mean 278 g/day), followed by protein foods (120 g/day). Median energy intake was 2399 kcal/day in males and 2366 kcal/day in females. Estimated intake levels were evaluated against the Average Requirement (AR) values of 320 µg/day for folate and 75-90 mg/day for vitamin C. Among individuals with intake below the AR, the mean intake gaps were approximately 97 µg/day for folate and 27 mg/day for vitamin C. Magnesium intake was evaluated relative to AR values of 350 mg/day for males and 255 mg/day for females. Model-estimated monthly food expenditure closely aligned with national data (7% difference in 2018; 2% in 2023). NNC-v2 offers a probabilistic framework for estimating dietary intake and nutrient adequacy at the national level in Saudi Arabia within the available data sources.