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The Eating Assessment in Toddlers FFQ (EAT FFQ) has been shown to have good reliability and comparative validity for ranking nutrient intakes in young children. With the addition of food items (n 4), we aimed to re-assess the validity of the EAT FFQ and estimate calibration factors in a sub-sample of children (n 97) participating in the Growing Up Milk - Lite (GUMLi) randomised control trial (2015-2017). Participants completed the ninety-nine-item GUMLi EAT FFQ and record-assisted 24-h recalls (24HR) on two occasions. Energy and nutrient intakes were assessed at months 9 and 12 post-randomisation and calibration factors calculated to determine predicted estimates from the GUMLi EAT FFQ. Validity was assessed using Pearson correlation coefficients, weighted kappa (κ) and exact quartile categorisation. Calibration was calculated using linear regression models on 24HR, adjusted for sex and treatment group. Nutrient intakes were significantly correlated between the GUMLi EAT FFQ and 24HR at both time points. Energy-adjusted, de-attenuated Pearson correlations ranged from 0·3 (fibre) to 0·8 (Fe) at 9 months and from 0·3 (Ca) to 0·7 (Fe) at 12 months. Weighted κ for the quartiles ranged from 0·2 (Zn) to 0·6 (Fe) at 9 months and from 0·1 (total fat) to 0·5 (Fe) at 12 months. Exact agreement ranged from 30 to 74 %. Calibration factors predicted up to 56 % of the variation in the 24HR at 9 months and 44 % at 12 months. The GUMLi EAT FFQ remained a useful tool for ranking nutrient intakes with similar estimated validity compared with other FFQ used in children under 2 years.

The second year of life is a period of nutritional vulnerability. We aimed to investigate the dietary patterns and nutrient intakes from 1 to 2 years of age during the 12-month follow-up period of the Growing Up Milk - Lite (GUMLi) trial. The GUMLi trial was a multi-centre, double-blinded, randomised controlled trial of 160 healthy 1-year-old children in Auckland, New Zealand and Brisbane, Australia. Dietary intakes were collected at baseline, 3, 6, 9 and 12 months post-randomisation, using a validated FFQ. Dietary patterns were identified using principal component analysis of the frequency of food item consumption per d. The effect of the intervention on dietary patterns and intake of eleven nutrients over the duration of the trial were investigated using random effects mixed models. A total of three dietary patterns were identified at baseline: 'junk/snack foods', 'healthy/guideline foods' and 'breast milk/formula'. A significant group difference was observed in 'breast milk/formula' dietary pattern z scores at 12 months post-randomisation, where those in the GUMLi group loaded more positively on this pattern, suggesting more frequent consumption of breast milk. No difference was seen in the other two dietary patterns. Significant intervention effects were seen on nutrient intake between the GUMLi (intervention) and cows' milk (control) groups, with lower protein and vitamin B12, and higher Fe, vitamin D, vitamin C and Zn intake in the GUMLi (intervention) group. The consumption of GUMLi did not affect dietary patterns, however, GUMLi participants had lower protein intake and higher Fe, vitamins D and C and Zn intake at 2 years of age.

scores provide an alternative approach to measuring dietary quality. The Growing Up Milk-Lite (GUMLi) Trial was a multi-centre, double-blinded, randomised controlled trial of children randomised to receive a reduced protein GUM (GUMLi) or unfortified cow's milk (CM). In a secondary analysis of the GUMLi Trial, we used the Probability of Adequate Nutrient Intake (PANDiet) to determine the nutritional adequacy of the diets of participating children living in Auckland. The PANDiet was adapted to the New Zealand Nutrient Reference Values and data from four 24 h Recalls (24HR) collected at months 7, 8, 10, and 11 post-randomisation were used. Differences between randomised groups (GUMLi vs. CM) of the PANDiet and its components were made. Eighty-three Auckland participants were included in the study (GUMLi n = 41 vs. CM n = 42). Total PANDiet scores were significantly higher in the GUMLi group ( p < 0.001), indicating better overall nutrient adequacy and diet quality. Dietary intakes of children in both groups met the recommendations for fat, total carbohydrates and most micronutrients; however, protein intakes exceeded recommendations. Consumption of GUMLi was associated with higher nutritional adequacy, with an increased likelihood of meeting nutrient requirements; however, the impact of the family diet and GUMLi on dietary diversity requires further evaluation.

Objectives: Delivery of interventions via smartphone is a relatively new initiative in public health, and limited evidence exists regarding optimal strategies for recruitment. We describe the effectiveness of approaches used to recruit participants to a smartphone-enabled nutrition intervention trial., Methods: Internet and social media advertising, mainstream media advertising and research team networks were used to recruit New Zealand adults to a fully automated smartphone-delivered nutrition labelling trial (no face-to-face visits were required). Recruitment of Māori and Pacific participants was a key focus and ethically relevant recruitment materials and approaches were used where possible. The effectiveness of recruitment strategies was evaluated using Google Analytics, monitoring of study website registrations and randomisations, and self-reported participant data. The cost of the various strategies and associations with participant demographics were assessed., Results: Over a period of 13 months, there were 2448 registrations on the study website, and 1357 eligible individuals were randomised into the study (55%). Facebook campaigns were the most successful recruitment strategy overall (43% of all randomised participants) and for all ethnic groups (Māori 44%, Pacific 44% and other 43%). Significant associations were observed between recruitment strategy and age (p<0.001), household size (p<0.001), ethnicity (p<0.001), gender (p=0.005) and interest in healthy eating (p=0.022). Facebook campaigns resulted in the highest absolute numbers of study registrations and randomisations (966 and 584, respectively). Network strategies and Facebook campaigns cost least per randomised participant (NZ$4 and NZ$5, respectively), whereas radio advertising costs most (NZ$179 per participant)., Conclusion: Internet and social media advertising were the most effective and least costly approaches to recruiting participants to a smartphone-delivered trial. These approaches also reached diverse ethnic groups. However, more culturally appropriate recruitment strategies are likely to be necessary in studies where large numbers of participants from specific ethnic groups are sought., Trial Registration: ACTRN12614000644662; Post-results., Competing Interests: Competing interests: None declared., (© Article author(s) (or their employer(s) unless otherwise stated in the text of the article) 2017. All rights reserved. No commercial use is permitted unless otherwise expressly granted.)

Population exposure to food and nutrients can be estimated from household food purchases, but store surveys of foods and their composition are more available, less costly and might provide similar information. Our aim was to compare estimates of nutrient exposure from a store survey of packaged food with those from household panel food purchases. A cross-sectional store survey of all packaged foods for sale in two major supermarkets was undertaken in Auckland, New Zealand, between February and May 2012. Longitudinal household food purchase data (November 2011 to October 2012) were obtained from the nationally representative, population-weighted New Zealand Nielsen HomeScan® panel. Data on 8440 packaged food and non-alcoholic beverage products were collected in the store survey. Food purchase data were available for 1229 households and 16 812 products. Store survey data alone produced higher estimates of exposure to Na and sugar compared with estimates from household panel food purchases. The estimated mean difference in exposure to Na was 94 (95 % CI 72, 115) mg/100 g (20 % relative difference; P<0·01), to sugar 1·6 (95 % CI 0·8, 2·5) g/100 g (11 %; P<0·01), to SFA -0·3 (95 % CI -0·8, 0·3) g/100 g (6 %; P=0·3) and to energy -18 (-71, 35) kJ/100 g (2 %; P=0·51). Compared with household panel food purchases, store survey data provided a reasonable estimate of average population exposure to key nutrients from packaged foods. However, caution should be exercised in using such data to estimate population exposure to Na and sugar and in generalising these findings to other countries, as well as over time.

Electronic supermarket sales data provide a promising, novel way of estimating nutrient intakes. However, little is known about how these data reflect the nutrients consumed by an individual household member. A cross-sectional survey of 49 primary household shoppers (age [mean+/-standard deviation age]=48+/-14 years; 84% female) from Wellington, New Zealand, was undertaken. Three months of baseline electronic supermarket sales data were compared with individual dietary intakes estimated from four random 24-hour dietary recalls collected during the same 3-month period. Spearman rank correlations between household purchases and individual intakes ranged from 0.54 for percentage of energy from saturated fat (P<0.001) to 0.06 for sodium (P=0.68). Other correlation coefficients were: percentage of energy from carbohydrate, 0.48; and protein, 0.44; energy density of nonbeverages, 0.37 (kcal/oz); percentage of energy from total fat, 0.34; sugar, 0.33 (oz/kcal); and energy density of beverages, 0.09 (oz/kcal; all P values <0.05). This research suggests that household electronic supermarket sales data may be a useful surrogate measure of some nutrient intakes of individuals, particularly percentage of energy from saturated and total fat. In the case of a supermarket intervention, an effect on household sales of percentage energy from saturated and total fat is also likely to impact the saturated and total fat intake of individual household members., (Copyright 2010 American Dietetic Association. Published by Elsevier Inc. All rights reserved.)

Background: Iron deficiency (ID) and vitamin D deficiency (VDD) are significant pediatric health issues in New Zealand and Australia and remain prevalent micronutrient deficiencies in young children globally.Objective: We aimed to investigate the effect of a micronutrient-fortified, reduced-energy growing-up milk (GUMLi) compared with cow milk (CM) consumed for 1 y on dietary iron and vitamin D intakes and the status of New Zealand and Australian children at 2 y of age.Methods: The GUMLi Trial was a multicenter, double-blind, randomized controlled trial in 160 healthy 1-y-old New Zealand and Australian children conducted in 2015-2017. Participants were randomly assigned 1:1 to receive GUMLi (1.7 mg Fe/100 mL; 1.3 µg cholecalciferol/100 mL) or CM (0.02 mg Fe/100 mL; 0.06 µg cholecalciferol/100 mL) for 12 mo. Secondary outcomes, reported here, included change in dietary iron and vitamin D intakes, iron status, and 25-hydroxyvitamin D [25(OH)D] concentrations from blood samples at age 2 y. All regression models were adjusted for baseline outcome and study center.Results: GUMLi was a large contributor to dietary intakes of iron and vitamin D after 12 mo when compared with intakes from food and CM. The adjusted mean difference between groups for serum ferritin concentrations was 17.8 µg/L (95% CI: 13.6, 22.0 µg/L; P < 0.0001), and for 25(OH)D it was 16.6 nmol/L (95% CI: 9.9, 23.3 nmol/L; P < 0.0001). After 12 mo, ID was present in 16 (24%) participants in the CM group and 5 (7%) participants in the GUMLi group (P = 0.009), and the prevalence of VDD in the CM group increased to 14% (n = 10) and decreased to 3% (n = 2) (P = 0.03) in the GUMLi group.Conclusion: In comparison with CM, GUMLi significantly improved dietary iron and vitamin D intakes and the iron and vitamin D status of healthy children at 2 y of age. This trial was registered with the Australian New Zealand Clinical Trials Registry (www.anzctr.org.au) as ACTRN12614000918628. [ABSTRACT FROM AUTHOR]

Background: There are few objective data on how nutrition labels are used in real-world shopping situations, or how they affect dietary choices and patterns.Design: The Starlight study was a four-week randomised, controlled trial of the effects of three different types of nutrition labels on consumer food purchases: Traffic Light Labels, Health Star Rating labels, or Nutrition Information Panels (control). Smartphone technology allowed participants to scan barcodes of packaged foods and receive randomly allocated labels on their phone screen, and to record their food purchases. The study app therefore provided objectively recorded data on label viewing behaviour and food purchases over a four-week period. A post-hoc analysis of trial data was undertaken to assess frequency of label use, label use by food group, and association between label use and the healthiness of packaged food products purchased.Results: Over the four-week intervention, study participants (n = 1255) viewed nutrition labels for and/or purchased 66,915 barcoded packaged products. Labels were viewed for 23% of all purchased products, with decreasing frequency over time. Shoppers were most likely to view labels for convenience foods, cereals, snack foods, bread and bakery products, and oils. They were least likely to view labels for sugar and honey products, eggs, fish, fruit and vegetables, and meat. Products for which participants viewed the label and subsequently purchased the product during the same shopping episode were significantly healthier than products where labels were viewed but the product was not subsequently purchased: mean difference in nutrient profile score -0.90 (95% CI -1.54 to -0.26).Conclusions: In a secondary analysis of a nutrition labelling intervention trial, there was a significant association between label use and the healthiness of products purchased. Nutrition label use may therefore lead to healthier food purchases. [ABSTRACT FROM AUTHOR]