Semi-quantitative dietary assessment methods are frequently used in low income countries, and the use of photographic series for portion size estimation is gaining popularity. However, when adequate data on commonly consumed foods and portion sizes are not available to design these tools, alternative data sources are needed. This study aimed to develop and test methods to: (i) identify foods likely to be consumed in a study population in rural Uganda, and; (ii) to derive distributions of portion sizes for common foods and dishes. A process was designed to derive detailed food and recipe lists using guided group interviews with women from the survey population, including a score for the likelihood of foods being consumed. A rapid recall method for portion size distribution estimation (PSDE) using direct weight by a representative sample of the survey population was designed and implemented. Results were compared to data from a 24 hour dietary recall (24HR). Of the 82 food items reported in the 24HR survey, 87% were among those scored with a high or medium likelihood of being consumed and accounted for 95% of kilocalories. Of the most frequently reported foods in the 24HR, portion sizes for many (15/25), but not all foods did not differ significantly (p<0.05) from those in the portion size estimation method. The percent of portion sizes reported in the 24 hour recall falling between the 5th and 95th percentiles as determined by the PSDE method ranged from 18% up to 100%. In conclusion, a simple food listing and scoring method effectively identified foods most likely to occur in a dietary survey. A novel PSDE method produced similar estimates as for the 24HR, while the approach for others should be further considered and validated. These methods are an improvement on those in current use.

Semi-quantitative dietary assessment methods are frequently used in low income countries, and the use of photographic series for portion size estimation is gaining popularity. However, when adequate data on commonly consumed foods and portion sizes are not available to design these tools, alternative data sources are needed. This study aimed to develop and test methods to: (i) identify foods likely to be consumed in a study population in rural Uganda, and; (ii) to derive distributions of portion sizes for common foods and dishes. A process was designed to derive detailed food and recipe lists using guided group interviews with women from the survey population, including a ranking for the likelihood of foods being consumed. A rapid recall method to estimate portion sizes using direct weight by a representative sample of the survey population was designed and implemented. Results were compared to data from a 24 hour dietary recall. Of the 82 food items reported in the 24 hour recall survey, 87% were among those ranked with a high or medium likelihood of being consumed and accounted for 95% of kilocalories. Of the most frequently reported foods in the 24 hour recall, portion sizes for many (15/25), but not all foods did not differ significantly (p<0.05) from those in the portion size estimation method. The percent of portion sizes reported in the 24 hour recall between the 5th and 95th percentiles determined by the portion size distribution estimation method ranged from a low of 18% up to 100%. In conclusion, a simple food listing and ranking method effectively identified foods most likely to occur in a dietary survey. A simple method to obtain reliable portion size distributions was effective for many foods, while the approach for others should be modified. These methods are an improvement on those in current use.