Validation of a computer-based analysis tool for real-time dietary assessment within a Ghanaian region

Potentials and limitations of a food group-based algorithm to assess dietary nutrient intake of women in rural areas in Tanzania

The aim of this study was to evaluate the accuracy of nutrient intake assessment with the food group-based algorithm "Calculator of Inadequate Micronutrient Intake" (CIMI) in comparison to the established nutrition software NutriSurvey. Using Food Frequency Questionnaires and 24-h dietary recalls of 1010 women from two rural districts in Tanzania, 23 relevant typical Tanzanian food groups were identified and subsequently the dietary protocols assessed via CIMI algorithm were compared by bivariate correlations and Bland-Altman analysis with the results of the NutriSurvey software (reference) and were set in relation to blood biomarkers of 666 participants. CIMI and NutriSurvey calculations regarding macro- and micronutrient intakes were similar. The Bland-Altman analyses and correlation coefficients of energy (0.931), protein (0.898), iron (0.775) and zinc (0.838) confirm the agreement of both calculations. The food group based CIMI algorithm is a practical tool to identify the inadequacy of macro- and micronutrient intake at population level.

Calculator for inadequate micronutrient intake for Ethiopia (CIMI‐Ethiopia): Validation of the software for lactating mothers and their children under 2 years

Early identification of inadequate intake of nutrients from a person's diet is usually crucial to prevent the development of micronutrient malnutrition. However, there is no single dietary assessment tool for Ethiopia that can assess the nutrient intake of a person from the type of food she or he consumed with a given amount. Therefore, the Calculator for Inadequate Micronutrient Intake (CIMI) application was adapted in consideration of food and nutrition contexts in Ethiopia and validated for its suitability to compute nutrient intake and identify nutrient intake inadequacy. For this, a 24‐h recall quantitative dietary data of children aged 12–23 months (n = 781) and lactating mothers (n = 1086) were collected between February 15 and 30, 2017, from rural Genta Afeshum district, Tigray region, Ethiopia. An individual nutrient intake was estimated by calculating using CIMI‐Ethiopia and also by NutriSurvey (NS) software for comparison. The average (mean and median) intake of energy and most nutrients and the prevalence of inadequacy calculated by the two software for the children aged 12–23 months and lactating mothers were comparable, except that of the vitamin A. The correlation coefficients for the intake results calculated by CIMI‐Ethiopia and NS were between 0.85 and 0.97 for the children and between 0.5 and 0.96 for the lactating mothers' group. Most of the mean intake differences calculated by the two methods were within the acceptable limits, except for the vitamins A, D, and B12 in the Bland–Altman plots. CIMI‐Ethiopia is very sensitive to identifying energy, protein, and selected micronutrients inadequacy included in this study, both for the lactating mothers (84.1%–100%) and 12–23‐month‐old children (77.6%–100%) group. Our results showed that CIMI‐Ethiopia estimates the energy and nutrient intake, and can be also used as a screening tool to identify energy, protein, and selected micronutrients inadequacy from an individual woman's and child's diet in rural Tigray, Ethiopia.

The forgotten agriculture-nutrition link: farm technologies and human energy requirements

In the quest to reduce global under- and malnutrition, which are particularly high among smallholder farmers, agriculture-nutrition linkages are receiving increasing attention. Researchers have analyzed the link between the quantity and diversity of food that farmers produce and nutritional outcomes but paid limited attention to a third agriculture-nutrition link: the link between how food is produced and nutritional outcomes. This neglect persists despite the majority of smallholder farmers relying on hand tools for farming, which implies heavy physical work and, thus, high energy requirements. To address this research gap, this study compares the energy requirements of farm households in rural Zambia that are characterized by three different levels of mechanization: hand tools, animal drought power, and tractors. 1638 days of detailed time-use and nutrition data were collected from 186 male and female adults and boys and girls during different seasons (land preparation, weeding, and harvesting/processing) using an innovative picture-based smartphone app called “Timetracker”. This data served to calculate different proxies for physical activity and energy requirements using “Ainsworth’s Compendium of Physical Activities”. The results suggest that detailed time-use data offers great potentials to study physical activity and energy requirements. The findings show strong linkages between farm technologies, physical activity levels, and energy requirements, suggesting that this agriculture-nutrition link deserves more scientific and political attention to reduce under- and malnutrition among smallholder farmers.

Validation of the CIMI-Ethiopia Program and Seasonal Variation in Maternal Nutrient Intake in Enset (False Banana) Growing Areas of Southern Ethiopia

BACKGROUND

Tools for the rapid and accurate analysis of nutrient intakes from diets of individuals in Southern Ethiopia are lacking. The Calculator of Inadequate Micronutrient Intake program for Ethiopia (CIMI-Ethiopia) has been developed to overcome this problem. CIMI-Ethiopia also computes protein and energy intakes from the diet. The objectives of the current study were to validate CIMI-Ethiopia for the dietary pattern of Southern Ethiopia, and assess the nutrient intakes in postharvest dry and lean wet seasons.

METHODS

24-h dietary recall (24HR) data was collected from 578 women of a reproductive age in postharvest dry and lean wet seasons in 2017. For analysis, 24HR data was entered into NutriSurvey (NS), which was the reference nutrition software, and then into CIMI-Ethiopia. For validation, the mean and standard deviation (SD) of the difference between CIMI-Ethiopia and NS were computed. The percentage of participants with an inadequate intake was calculated. The correlation between CIMI-Ethiopia and NS results was determined. The nutrient intakes in postharvest dry and lean seasons were compared.

RESULTS

Among the nutrients, pantothenic acid, vitamin B1, and protein showed a very high accuracy in CIMI-Ethiopia calculation (|difference (D)| < 5.0% of the NS result). Nutrients with a good accuracy (|D| = 5%-15%) were iron, zinc, magnesium, vitamin B12, vitamin B6, and energy. The accuracy for calcium, niacin, and vitamin A was moderate (|D| = 15%-30%). The intakes calculated by CIMI-Ethiopia and NS of iron, zinc, magnesium, calcium, B-complex vitamins, vitamin A, protein, and energy were highly correlated (r = 0.85-0.97, p < 0.001). NS analysis identified a significant reduction in the mean intake of iron; zinc; magnesium; pantothenic acid; vitamin B1, B12, and D; protein; and energy in the lean wet season; however, calcium and vitamin A intake increased.

CONCLUSIONS

It has been found that CIMI-Ethiopia is a valid tool for estimating nutrient intakes at an individual level in Southern Ethiopia. The study demonstrated a decline in intakes of iron; zinc; magnesium; pantothenic acid; vitamin B1, B12, and D; protein; and energy in the lean wet season. This result provides some hint for fortification and supplementation programs that aim to combat maternal malnutrition in rural Southern Ethiopia.