To nutritionally analyse lunches provided for 3–4-year-old children attending school nurseries. Energy and nutrient content are compared with nutrient frameworks underpinning voluntary guidelines for early years settings (EYS) and mandatory standards for infant schools (4–7-year-olds).

A cross-sectional study, recording all main meals, vegetarian meals, jacket potato options, sandwich options and all desserts and accompaniments provided over 5 consecutive days in each school. Two portions of each meal were collected each day and weighed. Recipe and portion weight data were entered into nutrient analysis software.

School nurseries where lunch was provided by the school.

Nine schools, providing a total of 161 meals.

Lunches contained more energy (1881 kJ/450 kcal), fat (15·5 g), free sugars (10·5 g) and Na (424 mg) than suggested by the nutrient framework for EYS. Carbohydrate (60·6 g), protein (16·8 g), fibre (6·7 g), Fe (2·4 mg), Zn (2·0 mg), Ca (202 mg), vitamin A (304 µg) and vitamin C (19 mg) also exceeded minimum recommendations. Compared with a revised nutrient framework for infant schools, energy was within range, whilst saturated fat, free sugars and Na were above maximum recommendations for this age group, and Zn was below. Sandwich meals were lower in vitamin C (P < 0·001–P = 0·05) and Fe (P = 0·012–P = 0·017) and higher in Na (P < 0·001–P = 0·003) and Ca (P < 0·001–P = 0·05).

Lunches provided for children attending school nurseries are more in line with the framework for 4–7-year-olds. Free sugars, saturated fat and Na are areas of concern consistent with previous studies. Protein is three times more than recommended. Large portions of cakes and biscuits contribute to excess energy provision.

The current paper describes Diet In Nutrients Out (DINO), an integrated dietary assessment system incorporating dietary data entry and nutritional analysis within one platform for use in dietary assessment in small-scale intervention studies to national surveys.

DINO contains >6000 food items, mostly aggregated composites of branded foods, across thirty-one main food groups divided into 151 subsidiary groups for detailed reporting requirements, with fifty-three core nutrient fields.

MRC Human Nutrition Research (HNR), Cambridge, UK and MRC Keneba, Gambia.

DINO is used across dietary assessment projects at HNR and MRC Keneba.

DINO contains macro- and micronutrients as well as additional variables of current research and policy interest, such as caffeine, whole grains, vitamin K and added sugars. Disaggregated data are available for fruit, vegetables, meat, fish and cheese in composite foods, enabling greater accuracy when reporting food consumption or assessing adherence to dietary recommendations. Portion sizes are categorised in metric and imperial weights, with standardised portion sizes for each age group. Regular reviews are undertaken for portion sizes and food composition to ensure contemporary relevance. A training programme and a checking schedule are adhered to for quality assurance purposes, covering users and data. Eating context questions are integrated to record where and with whom the respondent is eating, allowing examination between these factors and the foods consumed.

An up-to-date quality-assured system for dietary assessment is crucial for nutritional surveillance and research, but needs to have the flexibility to be tailored to address specific research questions.

A novel system for nutrient analysis has been developed and tested over 5 years. Its key features are a nutrient database of 600 commonly eaten foods (95% of foods eaten in 7-day surveys); a booklet identifying each food with a bar code, bar codes for gram weight and for portion sizes (small, medium, large) and a bar-code reader with dietary analysis software for PCs. In the present study the bar-code system has been evaluated by comparison with a commonly used manual entry nutrient analysis software for dietitians' use.

Cross-sectional.

Glasgow city district.

One hundred and sixty adults aged 18–65 years old.

Comparing mean intakes for macro- and micronutrients, using the Bland and Altman method1, the bias between the two methods was small, ranging from 0.93 to 1.03. The bar-code system took significantly less professional time in data entry and nutrient analysis than the widely used manual system (29 min per 7-day diary vs. 47 min per 7-day diary, P < 0.001).

It is suggested that the bar-code system offers greater speed with a saving of professional time needed for nutrient analysis of dietary surveys. This system is commended for maintaining accuracy while promoting economy.