Online 24-h dietary recall tools are commonly used in nationwide nutrition surveys to assess population diets. With a steep rise in the development of new and more advanced 24-h dietary recall tools, the decision of which tool to use for a national nutrition survey becomes increasingly challenging. Therefore, this short communication outlines the process of selecting a 24-h dietary recall tool for a national nutrition survey in New Zealand.

To identify suitable 24-h dietary recall tools, a review of peer-reviewed and grey literature was conducted (2019–2022). Data on functionalities, validation, usability and adaptability were extracted for eighteen pre-specified tools, which were used in the subsequent evaluation process.

Six of the eighteen tools had new relevant publications since 2019. The fourteen new publications described six validation studies and eight usability studies. Based on pre-selection criteria (e.g. availability, adaptability, previous use in national surveys), three tools were shortlisted: ASA24, Intake24 and MyFood24. These tools were further evaluated, and expert advice was sought to determine the most suitable tool for use in the New Zealand context.

A comprehensive yet time- and cost-efficient approach was undertaken to identify the potential use of online 24-h dietary recall tools for a national nutrition survey. The selection process included key evaluation criteria to determine the tools’ suitability for adaptation within the New Zealand context and ultimately to select a preferred tool. A similar approach may be useful for other countries when having to select 24-h dietary recall tools for use in national nutrition surveys.

To assess the prevalence of promotions on foods and non-alcoholic drinks purchased by New Zealand households and to determine if they vary according to healthiness of products.

We undertook a cross-sectional analysis of Nielsen New Zealand Homescan® 2018/19 panel data. We conducted multivariate analyses to examine the variability in quantities of healthy v. unhealthy food and beverage products purchased on promotion. Promotion was self-reported by the panellist. Healthiness of products was measured by the Health Star Rating (HSR) system. We also carried out a subgroup analysis for beverages according to the threshold of < 5 g v. ≥ 5 g sugar per 100 ml content of products.

The Nielsen New Zealand Homescan® data were linked with two New Zealand Food Composition Databases (Nutritrack and the FOODfiles).

Food and beverage purchases data by 1800 panel households were used.

Overall, 46 % (1 803 601/3 940 458) of all purchases made were on promotion. Compared with purchases of food and beverage products with HSR < 3·5 (unhealthy), food and beverage products with HSR ≥ 3·5 (healthy) were significantly less likely to be on promotion (OR = 0·78, 95 % CI 0·77, 0·79). The subgroup analysis for beverages shows that products with < 5 g sugar per 100 ml were significantly less likely to be on promotion than those with ≥ 5 g sugar per 100 ml (OR = 0·77, 95 % CI 0·75, 0·79).

Policies to improve healthy food retailing should focus on increasing the promotion of healthier food and drink options in stores and supermarkets.

To evaluate the impact of the 2017 update to the voluntary Advertising Standards Authority (ASA) code for advertising food on children and young people’s exposure to unhealthy food advertisements on New Zealand television.

Audience ratings data were analysed for New Zealand children and young people’s television viewing for eight random days prior to (June to August 2015) and following (October to December 2018) the code update, from 06.00 to midnight (864 h). Food advertisements were coded using three nutrient profiling models. The number of children and young people watching television each year was compared.

Three free-to-air New Zealand television channels.

New Zealand children aged 5–18 years.

Television viewer numbers decreased over the 3 years (P < 0·0001). The mean rate of unhealthy food advertising on weekdays was 10·4 advertisements/h (2015) and 9·5 advertisements/h (2018). Corresponding rates for weekend days were 8·1 and 7·3 advertisements/h, respectively. The percentage of food advertisements which were for unhealthy foods remained high (63·7 % on weekdays and 65·9 % on weekends) in 2018. The ASA definition of children’s ‘peak viewing time’ (when 25 % of the audience are children) did not correspond to any broadcast times across weekdays and weekend days.

Between 2015 and 2018, children and young people’s television exposure to unhealthy food advertising decreased. However, almost two-thirds of all food advertisements were still unhealthy, and the updated ASA code excluded the times when the greatest number of children was watching television. Consequently, government regulation and regular monitoring should reflect the evolving food marketing environment.

To assess trends in relative availability, sugar content and serve size of ready-to-drink non-alcoholic beverages available for sale in supermarkets from 2013 to 2019.

Repeat cross-sectional surveys. Data on single-serve beverages to be consumed in one sitting were obtained from an updated brand-specific food composition database. Trends in beverages availability and proportions with serve size ≤ 250 ml were assessed by χ2 tests. Sugar content trends were examined using linear regressions. The proportion of beverages exceeding the sugar threshold of the United Kingdom Soft Drinks Industry Levy (SDIL) was assessed.

New Zealand.

From 2013 to 2019, there was (i) an increase in the availability of sugar-free/low-sugar beverages (n 25 (8·4 %) to n 75 (19·1 %); P < 0·001) and craft sugar-sweetened soft drinks (n 11 (3·7 %) to n 36 (9·2 %); P < 0·001), and a decrease in availability of fruit/vegetable juices/drinks (n 94 (31·8 %) to n 75 (19·4 %); P < 0·001); (ii) small decreases in sugar content (mean g/100 ml) of sugar-sweetened soft drinks (3·03; 95 % CI 3·77, 2·29); fruit/vegetable juices/drinks (1·08; 95 % CI 2·14, 0·01) and energy drinks (0·98; 95 % CI 1·63, 0·32) and (iii) slight reduction in the proportion of beverages with serve size ≤ 250 ml (21·6 to 18·9 %; P < 0·001). In 2019, most beverages were sugar-sweetened or had naturally occurring sugars (79·1 %) and serve size > 250 ml (81·1 %) and most sugar-sweetened beverages exceeded the SDIL lower benchmark (72·9 %).

Most single-serve beverages available for sale in 2019 were sugary drinks with high sugar content and large serve sizes; therefore, changes made across the years were not meaningful for population’s health.

To quantify sales trends for key energy-dense, nutrient-poor (EDNP) foods and beverages over 5 years in Australia.

The Euromonitor Global Market Information Database and linear regression models were used to estimate average annual change in sales per capita of thirteen EDNP food categories and two EDNP beverage categories (defined using Australian Dietary Guidelines) over 5 years (2012–2017 for foods and 2011–2016 for beverages). The average annual change in sales was divided by the observed sales in 2012 (foods) or 2011 (beverages) to estimate the average percentage-change in sales per capita per annum.

All major retail outlets in Australia.

Euromonitor Global Market Information Database sales data.

Between 2012 and 2017, sales per capita per annum of frozen pizza (6 %), pastries (5 %), potato chips (crisps) (5 %), tortilla chips (3 %), chocolate confectionery (2 %), frozen processed potatoes (2 %), ice cream (2 %) and sugar confectionery (0·2 %) increased. There were no changes in sales of sweet biscuits, chocolate spreads and cakes, and sales of savoury biscuits and processed meat decreased (–2 and –1 %, respectively). Between 2011 and 2016, sales per capita per annum of sports and energy drinks increased (4 %), sales of regular (sugar-sweetened) cola (–6 %) and all non-cola soft drinks (–1 %) decreased and sales of diet cola did not change.

Sales of EDNP foods and beverages generally increased or remained stable relative to population growth. Our results demonstrate the need for public health policies to reduce sales of EDNP foods and beverages.

Emerging evidence suggests that free sugars intake in many countries exceeds that recommended by the WHO. However, information regarding real-world dietary patterns associated with meeting the WHO free sugars guidelines is lacking. The current study aimed to determine dietary patterns associated with meeting the guidelines to inform effective free sugars reduction interventions in New Zealand (NZ) and similar high-income countries.

Dietary patterns were derived using principal component analysis on repeat 24-h NZ Adult Nutrition Survey dietary recall data. Associations between dietary patterns and the WHO guidelines (<5 and <10 % total energy intake) were determined using logistic regression analyses.

New Zealand.

NZ adults (n 4721) over 15 years old.

Eight dietary patterns were identified: ‘takeaway foods and alcohol’ was associated with meeting both WHO guidelines; ‘contemporary’ was associated with meeting the <10 % guideline (males only); ‘fast foods, sugar-sweetened beverages and dessert’, ‘traditional’ and ‘breakfast foods’ were negatively associated with meeting both guidelines; ‘sandwich’ and ‘snack foods’ were negatively associated with the <5 % guideline; and ‘saturated fats and sugar’ was negatively associated with the <10 % guideline.

The majority of NZ dietary patterns were not consistent with WHO free sugars guidelines. It is possible to meet the WHO guidelines while consuming a healthier (‘contemporary’) or energy-dense, nutrient-poor (‘takeaway foods and alcohol’) diet. However, the majority of energy-dense patterns were not associated with meeting the guidelines. Future nutrition interventions would benefit from focusing on establishing healthier overall diets and reducing consumption and free sugars content of key foods.

To examine the availability of packaged food products in New Zealand supermarkets by level of industrial processing, nutrient profiling score (NPSC), price (energy, unit and serving costs) and brand variety.

Secondary analysis of cross-sectional survey data on packaged supermarket food and non-alcoholic beverages. Products were classified according to level of industrial processing (minimally, culinary and ultra-processed) and their NPSC.

Packaged foods available in four major supermarkets in Auckland, New Zealand.

Packaged supermarket food products for the years 2011 and 2013.

The majority (84 % in 2011 and 83 % in 2013) of packaged foods were classified as ultra-processed. A significant positive association was found between the level of industrial processing and NPSC, i.e. ultra-processed foods had a worse nutrient profile (NPSC=11·63) than culinary processed foods (NPSC=7·95), which in turn had a worse nutrient profile than minimally processed foods (NPSC=3·27), P<0·001. No clear associations were observed between the three price measures and level of processing. The study observed many variations of virtually the same product. The ten largest food manufacturers produced 35 % of all packaged foods available.

In New Zealand supermarkets, ultra-processed foods comprise the largest proportion of packaged foods and are less healthy than less processed foods. The lack of significant price difference between ultra- and less processed foods suggests ultra-processed foods might provide time-poor consumers with more value for money. These findings highlight the need to improve the supermarket food supply by reducing numbers of ultra-processed foods and by reformulating products to improve their nutritional profile.

To assess the mean package size and manufacturer-recommended serving size of sweet beverages available in four high-income countries: Australia, Canada, the Netherlands and New Zealand.

Cross-sectional surveys.

The two largest supermarket chains of each country in 2012/2013.

Individual pack size (IPS) drinks (n 891) and bulk pack size (BPS) drinks (n 1904).

For all IPS drinks, the mean package size was larger than the mean serving size (mean (sd)=412 (157) ml and 359 (159) ml, respectively). The mean (sd) package size of IPS drinks was significantly different for all countries (range: Australia=370 (149) ml to New Zealand=484 (191) ml; P<0·01). The mean (sd) package size of Dutch BPS drinks (1313 (323) ml) was significantly smaller compared with the other countries (New Zealand=1481 (595) ml, Australia=1542 (595) ml, Canada=1550 (434) ml; P<0·01). The mean (sd) serving size of BPS drinks was significantly different across all countries (range: Netherlands=216 (30) ml to Canada=248 (31) ml; P<0·00). New Zealand had the largest package and serving sizes of the countries assessed. In all countries, a large number of different serving sizes were used to provide information on the amount appropriate to consume in one sitting.

At this point there is substantial inconsistency in package sizes and manufacturer-recommended serving sizes of sweet beverages within and between four high-income countries, especially for IPS drinks. As consumers do factor serving size into their judgements of healthiness of a product, serving size regulations, preferably set by governments and global health organisations, would provide consistency and assist individuals in making healthier food choices.

To compare the nutrient profile of packaged supermarket food products available in Australia and New Zealand. Eligibility to carry health claims and relationship between nutrient profile score and nutritional content were also evaluated.

Nutritional composition data were collected in six major Australian and New Zealand supermarkets in 2012. Mean Food Standards Australia New Zealand Nutrient Profiling Scoring Criterion (NPSC) scores were calculated and the proportion of products eligible to display health claims was estimated. Regression analyses quantified associations between NPSC scores and energy density, saturated fat, sugar and sodium contents.

NPSC scores were derived for 23 596 packaged food products (mean score 7·0, range −17 to 53). Scores were lower (better nutrient profile) for foods in Australia compared with New Zealand (mean 6·6 v. 7·8). Overall, 45 % of foods were eligible to carry health claims based on NPSC thresholds: 47 % in Australia and 41 % in New Zealand. However, less than one-third of dairy (32 %), meat and meat products (28 %) and bread and bakery products (27·5 %) were eligible to carry health claims. Conversely, >75 % of convenience food products were eligible to carry health claims (82·5 %). Each two-unit higher NPSC score was associated with higher energy density (78 kJ/100 g), saturated fat (0·95 g/100 g), total sugar (1·5 g/100 g) and sodium (66 mg/100 g; all P values<0·001).

Fewer than half of all packaged foods available in Australia and New Zealand in 2012 met nutritional criteria to carry health claims. The few healthy choices available in key staple food categories is a concern. Improvements in nutritional quality of foods through product reformulation have significant potential to improve population diets.

There has been a growing interest in tailored nutrition education over the previous decade, with a number of literature reviews suggesting this intervention strategy holds considerable potential. Nevertheless, the majority of intervention trials undertaken to date have employed subjective self-report outcome measures (such as dietary recalls). The aim of the present review is to further consider the likely true effect of tailored nutrition education by assessing the findings of tailored nutrition education intervention trials where objective outcome measures (such as sales data) have been employed.

Four trials of tailored nutrition education employing objective outcome measures were identified: one was undertaken in eight low-cost supermarkets in New Zealand (2010; n 1104); one was an online intervention trial in Australia (2006; n 497); and two were undertaken in US supermarkets (1997 and 2001; n 105 and 296, respectively). Findings from the high-quality New Zealand trial were negative. Findings from the US trials were also generally negative, although reporting was poor making it difficult to assess quality. Findings from the high-quality online trial were positive, although have limited generalisability for public health.

Trials employing objective outcome measures strongly suggest tailored nutrition education is not effective as a stand-alone strategy. However, further large, high-quality trials employing objective outcome measures are needed to determine the true effectiveness of this popular nutrition intervention strategy. Regardless, education plays an important role in generating social understanding and acceptance of broader interventions to improve nutrition.

Effective nutrition labels are part of a supportive environment that encourages healthier food choices. The present study examined the use, understanding and preferences regarding nutrition labels among ethnically diverse shoppers in New Zealand.

A survey was carried out at twenty-five supermarkets in Auckland, New Zealand, between February and April 2007. Recruitment was stratified by ethnicity. Questions assessed nutrition label use, understanding of the mandatory Nutrition Information Panel (NIP), and preference for and understanding of four nutrition label formats: multiple traffic light (MTL), simple traffic light (STL), NIP and percentage of daily intake (%DI).

In total 1525 shoppers completed the survey: 401 Maori, 347 Pacific, 372 Asian and 395 New Zealand European and Other ethnicities (ten did not state ethnicity).

Reported use of nutrition labels (always, regularly, sometimes) ranged from 66 % to 87 % by ethnicity. There was little difference in ability to obtain information from the NIP according to ethnicity or income. However, there were marked ethnic differences in ability to use the NIP to determine if a food was healthy, with lesser differences by income. Of the four label formats tested, STL and MTL labels were best understood across all ethnic and income groups, and MTL labels were most frequently preferred.

There are clear ethnic and income disparities in ability to use the current mandatory food labels in New Zealand (NIP) to determine if foods are healthy. Conversely, MTL and STL label formats demonstrated high levels of understanding and acceptance across ethnic and income groups.

In New Zealand the burden of nutrition-related disease is greatest among Māori, Pacific and low-income peoples. Nutrition labels have the potential to promote healthy food choices and eating behaviours. To date, there has been a noticeable lack of research among indigenous peoples, ethnic minorities and low-income populations regarding their perceptions, use and understanding of nutrition labels. Our aim was to evaluate perceptions of New Zealand nutrition labels by Māori, Pacific and low-income peoples and to explore improvements or alternatives to current labelling systems.

Māori, Samoan and Tongan researchers recruited participants who were regular food shoppers. Six focus groups were conducted which involved 158 people in total: one Māori group, one Samoan, one Tongan, and three low-income groups.

Māori, Pacific and low-income New Zealanders rarely use nutrition labels to assist them with their food purchases for a number of reasons, including lack of time to read labels, lack of understanding, shopping habits and relative absence of simple nutrition labels on the low-cost foods they purchase.

Current New Zealand nutrition labels are not meeting the needs of those who need them most. Possible improvements include targeted social marketing and education campaigns, increasing the number of low-cost foods with voluntary nutrition labels, a reduction in the price of ‘healthy’ food, and consideration of an alternative mandatory nutrition labelling system that uses simple imagery like traffic lights.

To examine food and nutrient availability in New Zealand using supermarket sales data in conjunction with a brand-specific supermarket food composition database (SFD).

The SFD was developed by selecting the top-selling supermarket food products and linking them to food composition data from a variety of sources, before merging with individualised sales data. Supermarket food and nutrient data were then compared with data from national nutrition and household budget/economic surveys.

A supermarket in Wellington, New Zealand.

Eight hundred and eighty-two customers (73% female; mean age 38 years) who shopped regularly at the participating supermarket store and for whom electronic sales data were available for the period February 2004–January 2005.

Top-selling supermarket food products included full-fat milk, white bread, sugary soft drinks and butter. Key food sources of macronutrients were similar between the supermarket sales database and national nutrition surveys. For example, bread was the major source of energy and contributed 12–13% of energy in all three data sources. Proportional expenditure on fruit, vegetables, meat, poultry, fish, farm products and oils, and cereal products recorded in the Household Economic Survey and supermarket sales data were within 2% of each other.

Electronic supermarket sales data can be used to evaluate a number of important aspects of food and nutrient availability. Many of our findings were broadly comparable with national nutrition and food expenditure survey data, and supermarket sales have the advantage of being an objective, convenient, up-to-date and cost-effective measure of household food purchases.

To pilot the design and methodology for a large randomised controlled trial (RCT) of two interventions to promote healthier food purchasing: culturally appropriate nutrition education and price discounts.

A 12-week, single-blind, pilot RCT. Effects on food purchases were measured using individualised electronic shopping data (‘Shop ’N Go’ system). Partial data were also collected on food expenditure at other (non-supermarket) retail outlets.

A supermarket in Wellington, New Zealand.

Eligible customers were those who were the main household shoppers, shopped mainly at the participating store, and were registered to use the Shop ’N Go system. Ninety-seven supermarket customers (72% women; age 40 ± 9.6 years, mean ± standard deviation) were randomised to one of four intervention groups: price discounts, nutrition education, a combination of price discounts and nutrition education, or control (no intervention).

There was a 98% follow-up rate of participants, with 85% of all reported supermarket purchases being captured via the electronic data collection system. The pilot did, however, demonstrate difficulty recruiting Maori, Pacific and low-income shoppers using the electronic register and mail-out.

This pilot study showed that electronic sales data capture is a viable way to measure effects of study interventions on food purchases in supermarkets, and points to the feasibility of conducting a large-scale RCT to evaluate the effectiveness of price discounts and nutrition education. Recruitment strategies will, however, need to be modified for the main trial in order to ensure inclusion of all ethnic and socio-economic groups.