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Nutrient profiling systems (NPS) are used to classify foods according to their nutritional composition. However, investigating their prospective associations with health is key to their validation. The study investigated the associations of the original Food Standards Agency (FSA)-NPS and three variants (Food Standards Australia New Zealand Nutrient Profiling Scoring Criterion (NPSC), Health Star Rating NPS and the French High Council of Public Health NPS (HCSP-NPS)), with weight status. Individual dietary indices based on each NPS at the food level were computed to characterise the dietary quality of 71 403 French individuals from the NutriNet-Santé cohort. Associations of these indices with weight gain were assessed using mixed models and with overweight and obesity risks using Cox models. Participants with a higher dietary index (reflecting lower diet nutritional quality) were more likely to have a significant increase in BMI over time (β-coefficients positive) and an increased risk of overweight (hazard ratio (HR) T3 v. T1 = 1·27 (95 % CI 1·17, 1·37)) for the HCSP-Dietary Index, followed by the original FSA-Dietary Index (HR T3 v. T1 = 1·18 (95 % CI 1·09, 1·28)), the NPSC-Dietary Index (HR T3 v. T1 = 1·14 (95 % CI 1·06, 1·24)) and the Health Star Rating-Dietary Index (HR T3 v. T1 = 1·12 (95 % CI 1·04, 1·21)). Whilst differences were small, the HCSP-Dietary Index appeared to show significantly greater association with overweight risk. Overall, these results show the validity of NPS derived from the FSA-NPS, supporting their use in public policies for chronic disease prevention.

Background Reducing sugar in packaged foods and beverages could help protect children's future health. Clear methods for the development of feasible yet impactful sugar reduction program targets are needed. Objectives To outline methods for the development of program targets that would reduce, by 20%, the total sugar content of packaged foods and beverages commonly consumed by children. New Zealand (NZ) is used as a case study. Methods Sugar content and pack size targets were developed using a 6-step process informed by the UK sugar and salt reduction programs. Food groups contributing ≥2% to children's total sugar intake were identified using national dietary survey data. Consumption volume, sugar content, and pack size were obtained from household panel data linked with a packaged food composition database. Category-specific targets were set as 20% reductions in sales-weighted means adjusted for feasibility, i.e., ∼1/3 of products already meeting the target, and alignment with existing, relevant targets. Results Twenty-two food groups were identified as major contributors to NZ children's total sugar intake. Mean reductions required in sugar content and pack size to meet the targets were 5.2 g per 100 g/mL (26%) and 61.2 g/mL/pack (23%), respectively. The percentage of products already meeting the sugar targets ranged from 14% for electrolyte drinks and flavored dairy milk to 50% for cereal bars, and for pack size targets compliance ranged from 32% for chocolate confectionary to 62% for fruit juices and drinks. Estimated reductions in annual household sugar purchases if the sugar and pack size targets were met were 1459 g (23%) and 286 g (6%), respectively. Conclusions Methods for the development of sugar and pack size reduction targets are presented, providing a robust, step-by-step process for countries to follow. The results of the case study provide a suggested benchmark for a potential national sugar reduction program in NZ.

Objective To examine the effects of health-related food taxes on substitution and complementary purchases within food groups, including from unhealthier to healthier alternatives and between brands. Methods We used data from a virtual supermarket experiment with data from 4,259 shopping events linked to varying price sets. Substitution or complementary effects within six frequently purchased food categories were analyzed. Products’ own- and cross-price elasticities were analyzed using Almost Ideal Demand System models. Results Overall, 37.5% of cross-price elasticities were significant (p Conclusions/policy implications Given the relatively low own-price elasticities and the limited substitution and complementary effects, relatively high taxes are needed to substantively increase healthy food purchases at the population level. Trial registration This study included secondary analyses; the original trial was registered in the Australian New Zealand Clinical Trials Registry ACTRN12616000122459.

Background Suboptimal diets are a leading risk factor for death and disability. Nutrition labelling is a potential method to encourage consumers to improve dietary behaviour. This systematic review and network meta-analysis (NMA) summarises evidence on the impact of colour-coded interpretive labels and warning labels on changing consumers’ purchasing behaviour. Methods and findings We conducted a literature review of peer-reviewed articles published between 1 January 1990 and 24 May 2021 in PubMed, Embase via Ovid, Cochrane Central Register of Controlled Trials, and SCOPUS. Randomised controlled trials (RCTs) and quasi-experimental studies were included for the primary outcomes (measures of changes in consumers’ purchasing and consuming behaviour). A frequentist NMA method was applied to pool the results. A total of 156 studies (including 101 RCTs and 55 non-RCTs) nested in 138 articles were incorporated into the systematic review, of which 134 studies in 120 articles were eligible for meta-analysis. We found that the traffic light labelling system (TLS), nutrient warning (NW), and health warning (HW) were associated with an increased probability of selecting more healthful products (odds ratios [ORs] and 95% confidence intervals [CIs]: TLS, 1.5 [1.2, 1.87]; NW, 3.61 [2.82, 4.63]; HW, 1.65 [1.32, 2.06]). Nutri-Score (NS) and warning labels appeared effective in reducing consumers’ probability of selecting less healthful products (NS, 0.66 [0.53, 0.82]; NW,0.65 [0.54, 0.77]; HW,0.64 [0.53, 0.76]). NS and NW were associated with an increased overall healthfulness (healthfulness ratings of products purchased using models such as FSAm-NPS/HCSP) by 7.9% and 26%, respectively. TLS, NS, and NW were associated with a reduced energy (total energy: TLS, −6.5%; NS, −6%; NW, −12.9%; energy per 100 g/ml: TLS, −3%; NS, −3.5%; NW, −3.8%), sodium (total sodium/salt: TLS, −6.4%; sodium/salt per 100 g/ml: NS: −7.8%), fat (total fat: NS, −15.7%; fat per 100 g/ml: TLS: −2.6%; NS: −3.2%), and total saturated fat (TLS, −12.9%; NS: −17.1%; NW: −16.3%) content of purchases. The impact of TLS, NS, and NW on purchasing behaviour could be explained by improved understanding of the nutrition information, which further elicits negative perception towards unhealthful products or positive attitudes towards healthful foods. Comparisons across label types suggested that colour-coded labels performed better in nudging consumers towards the purchase of more healthful products (NS versus NW: 1.51 [1.08, 2.11]), while warning labels have the advantage in discouraging unhealthful purchasing behaviour (NW versus TLS: 0.81 [0.67, 0.98]; HW versus TLS: 0.8 [0.63, 1]). Study limitations included high heterogeneity and inconsistency in the comparisons across different label types, limited number of real-world studies (95% were laboratory studies), and lack of long-term impact assessments. Conclusions Our systematic review provided comprehensive evidence for the impact of colour-coded labels and warnings in nudging consumers’ purchasing behaviour towards more healthful products and the underlying psychological mechanism of behavioural change. Each type of label had different attributes, which should be taken into consideration when making front-of-package nutrition labelling (FOPL) policies according to local contexts. Our study supported mandatory front-of-pack labelling policies in directing consumers’ choice and encouraging the food industry to reformulate their products. Protocol registry PROSPERO (CRD42020161877)., Jing Song and co-workers report a systematic review and network meta-analysis assessing evidence on food labeling and purchasing decisions., Author summary Why was this study done? Interpretive front-of-package labelling is considered a cost-effective strategy to promote a more healthful diet and mitigate the burden of non communicable diseases (NCDs), and colour-coded labels and warning labels are the most adopted interpretive front-of-package labelling schemes worldwide. Prior to this study, evidence on the impact of each type of colour-coded labels and warning labels on modifying consumers purchasing behaviour was mixed. The feasibility and likely effectiveness of each label type applied in different contexts was unclear. What did the researchers do and find? This network meta-analysis summarised the currently available 118 peer-reviewed studies to update knowledge of the most mainstream interpretive front-of-package nutrition labelling (FOPL) schemes. We found that the traffic light labelling system (TLS), Nutri-Score (NS), nutrient warning (NW), and health warning (HW) were all able to direct consumers towards more healthful purchasing behaviour. Colour-coded labels (TLS and NS) performed better in promoting the purchase of more healthful products, while warning labels (NW and HW) had the advantage in discouraging unhealthful purchasing behaviour. The difference in consumers’ behaviour could be explained by different underlying psychological mechanisms for each label. What do these findings mean? We provide more comprehensive evidence to guide policy-makers in choosing the optimal front-of-package labelling policies. This evidence synthesis may inform further generalisation of mandatory front-of-package labelling schemes and help to mitigate the burden of NCDs. Future studies should focus on the impact of FOPLs on dietary consumption in individuals, and industrial reformulation at the population level, especially in real-world settings and over a longer time frame. This will provide crucial, robust, and comprehensive evidence to guide policy making.

The widely recognized association between high sugar intakes and adverse health outcomes has increased consumer demand for products lower in sugar. This may lead to increased use of other sweeteners by the food industry. The current study investigated the prevalence and types of non-nutritive sweeteners over time (2013–2019) in New Zealand’s packaged food and beverages, overall and between categories. A New Zealand database of packaged foods and beverages was used to investigate the presence of Food Standards Australia New Zealand Code-approved non-nutritive sweeteners (n = 12). Products available in 2013 (n = 12,153) and 2019 (n = 14,645) were compared. Between 2013 and 2019, the prevalence of non-nutritive sweeteners in products increased from 3% to 5%. The most common non-nutritive sweeteners in both years were acesulphame-potassium, sucralose, aspartame, and stevia, which were predominantly found in special foods (breakfast beverages and nutritional supplements), non-alcoholic beverages, dairy products, and confectionery. The prevalence of non-nutritive sweeteners is increasing over time in New Zealand’s packaged foods and beverages and is likely a consequence of consumer demand for lower-sugar products. Ongoing monitoring of the prevalence and type of NNS is important to detect further increases.

Introduction: Food environments shape food behaviours and are implicated in rising rates of obesity worldwide. Measurement of people’s interactions with food stores is important to advance understanding of the associations between the food environment and in-store behaviour. This paper describes a new method, Food Store Environment Examination (FoodSee) to measure people’s interaction with the food store environment in a feasibility study focused on convenience stores and children. Methods: One hundred and sixty-eight randomly selected children (aged 11–13 years) recruited from 16 randomly selected schools in Wellington, New Zealand, used wearable cameras for 4 days that recorded images every 7 s. The study was conducted from July 2014 to June 2015. All images of convenience stores and service stations, and a sample of images from supermarkets, were evaluated to determine the feasibility of assessing food availability and marketing. The outcomes of interest assessed were: food product availability, placement, packaging, branding, price promotion, purchases and consumption. Results: Thirty-seven children (22%) visited a convenience store or service station at least once during the study period. In total, there were 65 visits to 34 different stores. Seven hundred and nineteen images revealed the in-store environment. Of those, 86.1% were usable and able to be analysed for the outcomes of interest. Conclusions: The FoodSee methodology provides a promising new method to study people’s interaction with the in-store food environment. The evidence generated will be valuable in understanding and improving the food store environment within which people shop, and will contribute to efforts to address obesity globally.

Objective: The Health Star Rating (HSR) is a front‐of‐pack nutrition labelling system, implemented voluntarily in Australia and New Zealand since 2014. Our aim was to evaluate HSR's performance. Method: We used data from peer‐reviewed publications and government‐commissioned monitoring and evaluation, websites and communiqués to evaluate HSR's performance between June 2014 and October 2018 using the RE‐AIM (Reach, Efficacy, Adoption, Implementation and Maintenance) framework. Results: Thirty‐three peer‐reviewed publications, 21 government and three independent reports informed the assessment. Awareness and trust in HSR was increasing, though campaign reach remained low. Consumers liked, could understand and use the HSR logo, though effects on purchasing were largely unknown. The algorithm was the focus of a formal review. HSR was present on 20–28% of products but biased to those that scored better (HSR≥3.0). Necessary stakeholders were mostly engaged. Conclusions: A substantial body of work supports continuation and strengthening of HSR. Reasonable refinements to HSR's star graphic and algorithm, action to initiate mandatory implementation, and strengthened HSR governance present the clearest opportunities for improving public health impact. Implications for public health: Development and implementation of government‐led front‐of‐pack nutrition labelling systems have the potential to improve public health, while engaging a diverse set of stakeholders.

The use of lifelogging device in dietary assessments can reduce misreporting and underreporting, which are common in the previous studies conventional methods. We performed the first study in Chinese children (primary school Grade 4) that applied the wearable cameras in assisting dietary recall. Children (n = 52) wore the wearable cameras (Narrative Clip 2) for seven consecutive days, during which they completed a 3-day 24-h dietary recall at home. Then children modified their dietary recalls at school by reviewing the photos taken by the wearable camera at school, with the assistance of the investigator, and generated the camera-assisted 24-h dietary recalls. Compared with camera-assisted dietary recalls, 8% (n = 160) and 1% (n = 11) of food items were underreported (i.e. not reported at all) and misreported (i.e. reported in an incorrect amount) by dietary recalls without camera-assistance, respectively. Dietary recalls without camera assistance underestimated daily energy intake by 149 ± 182 kcal/d (8%) in comparison to the camera-assisted dietary recalls. Foods consumed on the snacking occasions (40%) were more likely to be underreported than those consumed at main meals (P

We compared the healthiness of packaged foods and beverages between selected countries using the Health Star Rating (HSR) nutrient profiling system. Packaged food and beverage data collected 2013-2018 were obtained for Australia, Canada, Chile, China, India, Hong Kong, Mexico, New Zealand, Slovenia, South Africa, the UK, and USA. Each product was assigned to a food or beverage category and mean HSR was calculated overall by category and by country. Median energy density (kJ/100 g), saturated fat (g/100 g), total sugars (g/100 g) and sodium (mg/100 g) contents were calculated. Countries were ranked by mean HSR and median nutrient levels. Mean HSR for all products (n = 394,815) was 2.73 (SD 1.38) out of 5.0 (healthiest profile). The UK, USA, Australia and Canada ranked highest for overall nutrient profile (HSR 2.74-2.83) and India, Hong Kong, China and Chile ranked lowest (HSR 2.27-2.44). Countries with higher overall HSR generally ranked better with respect to nutrient levels. India ranked consistently in the least healthy third for all measures. There is considerable variability in the healthiness of packaged foods and beverages in different countries. The finding that packaged foods and beverages are less healthy in middle-income countries such as China and India suggests that nutrient profiling is an important tool to enable policymakers and industry actors to reformulate products available in the marketplace to reduce the risk of obesity and NCDs among populations.

Background Obesity and diet-related noncommunicable diseases (NCDs) account for the largest proportion of disease burden worldwide, and an unhealthy food environment is a key driver. Food retailers play an important role in food environments through the availability and purchases of healthy food products at various stores. Objectives To assess whether the healthiness of food and non-alcoholic drink product purchases vary according to retail store type. Methods We undertook a cross-sectional analysis of Nielsen New Zealand Homescan® panel data, which is a nationally representative sample of 2500 households in terms of certain key household demographic and socioeconomic characteristics. Panel members were asked to record all food and beverage products that were purchased and brought back to the home between October 2018 and October 2019. Household food and non-alcoholic drink purchases were linked with two food composition databases (Nutritrack, a New Zealand packaged food composition database, and the FOODfiles New Zealand Food Composition Database) to extract data on the nutrient profile of products purchased. We developed a store classification tool, and classified stores as supermarkets, grocery stores, convenience stores, fruit and vegetable stores, meat and fish stores, or bakeries. We estimated the Health Star Rating (HSR) for all products and defined a product with HSR ≥ 3.5 as ‘healthy’. We computed estimated mean HSR and conducted multivariate regression analyses. Results In total, 3,940,458 product purchases were included in the analyses, consisting of 20,491 unique products purchased at different stores over the one-year period by 1800 panellist households. Supermarket products made up the majority of household food and drink purchases (3,545,141 of 3,940,458; 90%). Overall, the estimated mean HSR was 3.5 stars. In comparison to the reference group of supermarkets, the odds ratio for healthy products purchased at fruit and vegetable stores was 4.62, at grocery stores it was 2.36, and at meat and fish stores it was 1.99. In contrast, the odds ratios from convenience stores and bakeries were 0.58 and 0.03. Except for convenience stores, these differences were statistically significant (p Discussion We found significant differences in household purchases of healthy food and beverages according to food retail store type, with healthier food much more likely to be purchased from fruit and vegetable stores, meat and fish stores and grocery stores, and much less likely to be purchased from bakeries and convenience stores as compared with supermarkets. Conclusion Policies to improve healthy food retailing should consider all retail store types and focus particularly on increasing the availability of healthy food options at convenience stores and bakeries. Given that supermarkets are the source of most household food purchases (both healthy and unhealthy), strategies are also warranted to increase the relative availability and purchases of healthy foods from supermarkets.

Young adults are the highest consumers of food prepared outside home (FOH) and gain most weight among Australian adults. One strategy to address the obesogenic food environment is menu labelling legislation whereby outlets with &gt, 20 stores in one state and &gt, 50 Australia-wide must display energy content in kJ. The aim of this study was to assess the contribution of FOH to the energy and macronutrients, saturated fat, total sugars and sodium intakes of young Australians. One thousand and one 18 to 30-year-olds (57% female) residing in Australia’s most populous state recorded all foods and beverages consumed and the location of preparation for three consecutive days using a purpose-designed smartphone application. Group means for the daily consumption of energy, percentage energy (%E) for protein, carbohydrate, total sugars, total and saturated fats, and sodium density (mg/1000 kJ) and proportions of nutrients from FOH from menu labelling and independent outlets were compared. Overall, participants consumed 42.4% of their energy intake from FOH with other nutrients ranging from 39.8% (sugars) to 47.3% (sodium). Independent outlets not required to label menus, contributed a greater percentage of energy (23.6%) than menu labelling outlets (18.7%, p &lt, 0.001). Public health policy responses such as public education campaigns, extended menu labelling, more detailed nutrition information and reformulation targets are suggested to facilitate healthier choices.

Supermarkets are the principal source of grocery food in many high-income countries. Choice architecture strategies show promise to improve the healthiness of food choices. A retailer-academic collaboration was formed to co-design and pilot selected commercially sustainable strategies to increase sales of healthier foods relative to less healthy foods in supermarkets. Two co-design workshops, involving supermarket corporate staff and public health nutrition academics, identified potential interventions. One intervention, more prominent shelf placement of healthier products within one category (breakfast cereals), was selected for testing. A pilot study (baseline, intervention and follow-up, 12-weeks each) was undertaken in six supermarkets (three intervention and three control) in Auckland, New Zealand. Products were ranked by nutrient levels and profile, and after accounting for the supermarkets' space management principles, healthier products were placed at adult eye level. The primary outcome was change in sales of healthier products relative to total category sales. Secondary outcomes were nutrient profile of category sales, in-store product promotions, customer perceptions, and retailer feedback. There was no difference in proportional sales of more prominently positioned healthier products between intervention (56%) and control (56%) stores during the intervention. There were no differences in the nutrient profile of category sales. A higher proportion of less healthy breakfast cereals were displayed in intervention versus control stores (57% vs 43%). Most customers surveyed supported shelf placement as a strategy (265, 88%) but noted brand preferences and price were more salient determinants of purchases. Retailers were similarly supportive but balancing profit, health/nutrition and customer satisfaction was challenging. Shelf placement alone was not an effective strategy to increase purchases of healthier breakfast cereals. This study showed co-design of a healthy eating intervention with a commercial retailer is feasible, but concurrent retail environment factors likely limited the public health impact of the intervention.

Snacking is a common eating behaviour, but there is little objective data about children&rsquo, s snacking. We aimed to determine the frequency and context of children&rsquo, s snacking (n = 158, mean age = 12.6 years) by ethnicity, gender, socioeconomic deprivation and body mass index (BMI) children. Participants wore wearable cameras that passively captured images of their surroundings every seven seconds. Images (n = 739,162) were coded for snacking episodes, defined as eating occasions in between main meals. Contextual factors analysed included: snacking location, food source, timing, social contact and screen use. Rates of total, discretionary (not recommended for consumption) and healthful (recommended for consumption) snacking were calculated using negative binomial regression. On average, children consumed 8.2 (95%CI 7.4, 9.1) snacks per day, of which 5.2 (95%CI 4.6, 5.9) were discretionary foods/beverages. Children consumed more discretionary snacks than healthful snacks in each setting and at all times, including 15.0&times, more discretionary snacks in public spaces and 2.4&times, more discretionary snacks in schools. Most snacks (68.9%) were sourced from home. Girls consumed more total, discretionary and healthful snacks than boys, and Māori and Pacific consumed fewer healthful snacks than New Zealand (NZ) Europeans. Results show that children snack frequently, and that most snacking involves discretionary food items. Our findings suggest targeting home buying behaviour and environmental changes to support healthy snacking choices.

Background The Health Star Rating (HSR) is the government-endorsed front-of-pack labeling system in Australia and New Zealand. Objectives We aimed to examine prospective associations of a dietary index (DI) based on the HSR, as an indicator of overall diet quality, with all-cause and cardiovascular disease (CVD) mortality. Methods We utilized data from the national population-based Australian Diabetes, Obesity and Lifestyle Study. The HSR-DI at baseline (1999–2000) was constructed by 1) calculation of the HSR points for individual foods in the baseline FFQ, and 2) calculation of the HSR-DI for each participant based on pooled HSR points across foods, weighted by the proportion of energy contributed by each food. Vital status was ascertained by linkage to the Australian National Death Index. Associations of HSR-DI with mortality risk were assessed by Cox proportional hazards regression. Results Among 10,025 eligible participants [baseline age: 51.6 ± 14.3 y (mean ± standard deviation)] at entry, higher HSR-DI (healthier) was associated with higher consumption of healthy foods such as fruits, vegetables, and nuts, and lower consumption of discretionary foods such as processed meats and confectionery (P-trend, Better diet quality as defined by an Australian government–endorsed nutrient profiling system was associated with lower risk of all-cause and CVD mortality among Australian adults.

Background Front-of-pack nutrition labelling (FoPL) of packaged foods can promote healthier diets. Australia and New Zealand (NZ) adopted the voluntary Health Star Rating (HSR) scheme in 2014. We studied the impact of voluntary adoption of HSR on food reformulation relative to unlabelled foods and examined differential impacts for more-versus-less healthy foods. Methods and findings Annual nutrition information panel data were collected for nonseasonal packaged foods sold in major supermarkets in Auckland from 2013 to 2019 and in Sydney from 2014 to 2018. The analysis sample covered 58,905 unique products over 14 major food groups. We used a difference-in-differences design to estimate reformulation associated with HSR adoption. Healthier products adopted HSR more than unhealthy products: >35% of products that achieved 4 or more stars displayed the label compared to, Laxman Bablani and colleagues investigate whether voluntary adoption of the Health Star Rating on food packaging was associated with healthier reformulation., Author summary Why was this study done? Front-of-pack nutrition labelling (FoPL) systems may lead to reformulation of food to healthier compositions. In December 2014, Australia and New Zealand (NZ) adopted the voluntary Health Star Rating (HSR) scheme on packaged food products. We studied whether the HSR was associated with industry-led reformulation. We also determined whether reformulation differed between products that were initially more healthy or unhealthy. What did the researchers do and find? Healthier products are more likely to show HSR scores than unhealthy ones: >35% of products that should have achieved 4 or more stars displayed the label compared to

Increasing rates of childhood obesity worldwide has focused attention on the obesogenic food environment. This paper reports an analysis of children&rsquo, s interactions with food in convenience stores. Kids&rsquo, Cam was a cross-sectional study conducted from July 2014 to June 2015 in New Zealand in which 168 randomly selected children aged 11&ndash, 14 years old wore a wearable camera for a 4&ndash, day period. In this ancillary study, images from children who visited a convenience store were manually coded for food and drink availability. Twenty-two percent of children (n = 37) visited convenience stores on 62 occasions during the 4-day data collection period. Noncore items dominated the food and drinks available to children at a rate of 8.3 to 1 (means were 300 noncore and 36 core, respectively). The food and drinks marketed in-store were overwhelmingly noncore and promoted using accessible placement, price offers, product packaging, and signage. Most of the 70 items purchased by children were noncore foods or drinks (94.6%), and all of the purchased food or drink subsequently consumed was noncore. This research highlights convenience stores as a key source of unhealthy food and drink for children, and policies are needed to reduce the role of convenience stores in the obesogenic food environment.

© 2019 The Author(s). Published by Elsevier Ltd. This is an Open Access article under the CC BY 4.0 license Background: The OL@-OR@ mobile health programme was co-designed with Māori and Pasifika communities in New Zealand, to support healthy lifestyle behaviours. We aimed to determine whether use of the programme improved adherence to health-related guidelines among Māori and Pasifika communities in New Zealand compared with a control group on a waiting list for the programme. Methods: The OL@-OR@ trial was a 12-week, two-arm, cluster-randomised controlled trial. A cluster was defined as any distinct location or setting in New Zealand where people with shared interests or contexts congregated, such as churches, sports clubs, and community groups. Members of a cluster were eligible to participate if they were aged 18 years or older, had regular access to a mobile device or computer, and had regular internet access. Clusters of Māori and of Pasifika (separately) were randomly assigned (1:1) to either the intervention or control condition. The intervention group received the OL@-OR@ mHealth programme (smartphone app and website). The control group received a control version of the app that only collected baseline and outcome data. The primary outcome was self-reported adherence to health-related guidelines, which were measured with a composite health behaviour score (of physical activity, smoking, alcohol intake, and fruit and vegetable intake) at 12 weeks. The secondary outcomes were self-reported adherence to health-related behaviour guidelines at 4 weeks; self-reported bodyweight at 12 weeks; and holistic health and wellbeing status at 12 weeks, in all enrolled individuals in eligible clusters; and user engagement with the app, in individuals allocated to the intervention. Adverse events were not collected. This study is registered with the Australian New Zealand Clinical Trials Registry, ACTRN12617001484336. Findings: Between Jan 24 and Aug 14, 2018, we enrolled 337 Māori participants from 19 clusters and 389 Pasifika participants from 18 clusters (n=726 participants) in the intervention group and 320 Māori participants from 15 clusters and 405 Pasifika participants from 17 clusters (n=725 participants) in the control group. Of these participants, 227 (67%) Māori participants and 347 (89%) Pasifika participants (n=574 participants) in the intervention group and 281 (88%) Māori participants and 369 (91%) Pasifika participants (n=650 participants) in the control group completed the 12-week follow-up and were included in the final analysis. Relative to baseline, adherence to health-related behaviour guidelines increased at 12 weeks in both groups (315 [43%] of 726 participants at baseline to 329 [57%] of 574 participants in the intervention group; 331 [46%] of 725 participants to 369 [57%] of 650 participants in the control group); however, there was no significant difference between intervention and control groups in adherence at 12 weeks (odds ratio [OR] 1·13; 95% CI 0·84–1·52; p=0·42). Furthermore, the proportion of participants adhering to guidelines on physical activity (351 [61%] of 574 intervention group participants vs 407 [63%] of 650 control group participants; OR 1·03, 95% CI 0·73–1·45; p=0·88), smoking (434 [76%] participants vs 501 [77%] participants; 1·12, 0·67–1·87; p=0·66), alcohol consumption (518 [90%] participants vs 596 [92%] participants; 0·73, 0·37–1·44; p=0·36), and fruit and vegetable intake (194 [34%] participants vs 196 [30%] participants; 1·08, 0·79–1·49; p=0·64) did not differ between groups. We found no significant differences between the intervention and control groups in any secondary outcome. 147 (26%) intervention group participants engaged with the OL@-OR@ programme (ie, set at least one behaviour change goal online). Interpretation: The OL@-OR@ mobile health programme did not improve adherence to health-related behaviour guidelines amongst Māori and Pasifika individuals. Funding: Healthier Lives He Oranga Hauora National Science Challenge.

Background Institutions are a recommended setting for dietary interventions and nutrition policies as these provide an opportunity to improve health by creating healthy food environments. In Australia, state and territory governments encourage or mandate institutions in their jurisdiction to adopt nutrition policies. However, no work has analysed the policy design across settings and jurisdictions. This study aimed to compare the design and components of government-led institutional nutrition policies between Australian states and territories, determine gaps in existing policies, and assess the potential for developing stronger, more comprehensive policies. Methods Government-led institutional nutrition policies, in schools, workplaces, health facilities and other public settings, were identified by searching health and education department websites for each Australian state and territory government. This was supplemented by data from other relevant stakeholder websites and from the Food Policy Index Australia website. A framework for monitoring and evaluating nutrition policies in publicly-funded institutions was used to extract data and a qualitative analysis of the design and content of institutional nutrition policies was performed. Comparative analyses between the jurisdictions and institution types were conducted, and policies were assessed for comprehensiveness. Results Twenty-seven institutional nutrition policies were identified across eight states and territories in Australia. Most policies in health facilities and public schools were mandatory, though most workplace policies were voluntary. Twenty-four included nutrient criteria, and 22 included guidelines for catering/fundraising/advertising. While most included implementation guides or tools and additional supporting resources, less than half included tools/timelines for monitoring and evaluation. The policy design, components and nutrient criteria varied between jurisdictions and institution types, though all were based on the Australian Dietary Guidelines. Conclusions Nutrition policies in institutions present an opportunity to create healthy eating environments and improve population health in Australia. However, the design of these policies, including lack of key components such as accountability mechanisms, and jurisdictional differences, may be a barrier to implementation and prevent the policies having their intended impact.

Objective: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.Design: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 (Setting:New Zealand.Participants:NZ adults (n 4721) over 15 years old.Results:Eight dietary patterns were identified: ‘takeaway foods and alcohol’ was associated with meeting both WHO guidelines; ‘contemporary’ was associated with meeting the Conclusions: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.

Summary Background One possible policy response to the burden of diet-related disease is food taxes and subsidies, but the net health gains of these approaches are uncertain because of substitution effects between foods. We estimated the health and cost impacts of various food taxes and subsidies in one high-income country, New Zealand. Methods In this modelling study, we compared the effects in New Zealand of a 20% fruit and vegetable subsidy, of saturated fat, sugar and salt taxes (each set at a level that increased the total food price by the same magnitude of decrease from the fruit and vegetable subsidy), and of an 8% so-called junk food tax (on non-essential, energy-dense food). We modelled the effect of price changes on food purchases, the consequent changes in fruit and vegetable and sugar-sweetened beverage purchasing, nutrient risk factors, and body-mass index, and how these changes affect health status and health expenditure. The pre-intervention intake for 340 food groups was taken from the New Zealand National Nutrition Survey and the post-intervention intake was estimated using price and expenditure elasticities. The resultant changes in dietary risk factors were then propagated through a proportional multistate lifetable (with 17 diet-related diseases) to estimate the changes in health-adjusted life years (HALYs) and health system expenditure over the 2011 New Zealand population's remaining lifespan. Findings Health gains (expressed in HALYs per 1000 people) ranged from 127 (95% uncertainty interval 96–167; undiscounted) for the 8% junk food tax and 212 (102–297) for the fruit and vegetable subsidy, up to 361 (275–474) for the saturated fat tax, 375 (272–508) for the salt tax, and 581 (429–792) for the sugar tax. Health expenditure savings across the remaining lifespan per capita (at a 3% discount rate) ranged from US$492 (334–694) for the junk food tax to $2164 (1472–3122) for the sugar tax. Interpretation The large magnitude of the health gains and cost savings of these modelled taxes and subsidies suggests that their use warrants serious policy consideration. Funding Health Research Council of New Zealand.

Background SaltSwitch is an innovative smartphone application (app) that enables shoppers to scan the barcode of a packaged food and receive an immediate, interpretive, traffic light nutrition label on the screen, along with suggestions for lower salt alternatives. Our aim was to determine the effectiveness of SaltSwitch to support people with cardiovascular disease to make lower salt food choices. Design Six-week, two-arm, parallel, randomised controlled trial in Auckland, New Zealand (2 weeks baseline and 4 weeks intervention). Methods Sixty-six adults with diagnosed cardiovascular disease (mean (SD) age 64 (7) years) were randomly assigned in a 1:1 ratio to either the SaltSwitch smartphone app or control (usual care). The primary outcome was the salt content of household packaged food purchases during the 4-week intervention (g/MJ). Secondary outcomes were the saturated fat content (g/MJ), energy content (kJ/kg) and expenditure (NZ$) of household food purchases; systolic blood pressure (mmHg), urinary sodium (mg) and use and acceptability of the SaltSwitch app. Results Thirty-three participants with cardiovascular disease were allocated to the SaltSwitch intervention, and 33 to the control group. A significant reduction in mean household purchases of salt was observed (mean difference (95% confidence interval), -0.30 (-0.58 to -0.03) g/MJ), equating to a reduction of ∼0.7 g of salt per person per day during the 4-week intervention phase. There were no significant between-group differences in any secondary outcomes (all P > 0.05). Conclusions The SaltSwitch smartphone app is effective in supporting people with cardiovascular disease to make lower salt food purchases. A larger trial with longer follow-up is warranted to determine the effects on blood pressure. Trial registration Australian New Zealand Clinical Trials Registry https://www.anzctr.org.au/Trial/Registration/TrialReview.aspx?id=365784&isReview=true ACTRN12614000206628.

High dietary sodium intake increases blood pressure, a major risk factor for cardiovascular disease. [...]

Background Healthy lifestyle programs that are designed specifically to appeal to and support men to improve lifestyle behaviors and lose weight are needed. The Rugby Fans in Training-New Zealand (RUFIT-NZ) program is delivered by professional rugby clubs and inspired by the successful Football Fans In Training program (FFIT), a gender sensitized weight loss program for obese middle-aged men delivered by professional football clubs in Scotland. RUFIT-NZ required development and evaluation for feasibility. Methods To develop the intervention we reviewed content from the FFIT program and evidence-based physical activity, dietary and weight management guidelines, and undertook a series of focus groups and key informant interviews. We then evaluated the feasibility of the intervention in a two-arm, parallel, pilot randomized controlled trial in New Zealand. Ninety-six participants were randomized to either the 12-week RUFIT-NZ intervention (N = 49) or a control group (N = 47). The intervention was delivered through professional rugby clubs and involved physical activity training and classroom sessions on healthy lifestyle behaviors. Pilot trial outcomes included body weight, heart rate, blood pressure, cardiorespiratory fitness, and lifestyle behaviors. Feasibility was assessed by recruitment and retention rates, and acceptability of the intervention. Results At 12 weeks the mean difference in body weight was 2.5 kg (95% CI -0.4 to 5.4), which favored the intervention. Statistically significant differences in favor of the intervention group were also observed for waist circumference, resting heart rate, diastolic blood pressure, cardiorespiratory fitness, and the proportion of participants that were adherent to 3 or more healthy lifestyle behaviors. The intervention was considered feasible to test in a full trial given the good recruitment and retention rates, and positive feedback from participants. Conclusions A pilot study of a healthy lifestyle intervention delivered via professional rugby clubs in New Zealand demonstrated positive effects on weight and physiological outcomes, as well as adherence to lifestyle behaviors. Feasibility issues in terms of recruitment, retention, and participant acceptability were assessed and findings will be used to inform the design of a definitive trial. Trial registration The trial was prospectively registered with the Australian New Zealand Clinical Trials Registry ACTRN12616000137493, 05/12/2016.

Sugar-sweetened beverage (SSB) intake is associated with tooth decay, obesity and diabetes. We aimed to model the health and cost impact of reducing the serving size of all single serve SSB to a maximum of 250 ml in New Zealand. A 250 ml serving size cap was modeled for all instances of single serves (

Improvement of national food supplies are an opportunity to improve a country’s health. Our aim was to identify the major food companies manufacturing packaged foods and non-alcoholic beverages available in New Zealand supermarkets in 2018; to assess the healthiness of products using (1) the Health Star Rating (HSR) system, (2) Australian Dietary Guidelines classification (core/discretionary), and (3) by level of processing; to compare the healthiness of products displaying and not displaying the HSR and; to assess potential for food reformulation within selected food sub-categories. Information on packaged foods was obtained from the Nutritrack supermarket database. Companies that manufactured each food and brand were identified using company websites and the New Zealand companies register. In total, 13,506 packaged products were mapped to 1,767 brands and 1,214 companies. Based on market share of products available for sale (Euromonitor data), there were 22 dominating companies producing 31% of products and 17% of brands. Fifty-nine percent of products were classified as unhealthy (HSR versus 2.5±1.4, p = 0.000). Efforts to improve the healthiness of products should be directed to the 22 food companies dominating this market share, particularly in the core foods groups which are currently less likely to meet Heart Foundation reformulation targets (bread, breakfast cereals, cheese, canned baked beans, yoghurt). The New Zealand supermarket packaged food supply included in the Nutritrack database is dominated by a small number of companies and is mostly unhealthy. Government leadership is required to improve the healthiness of the packaged food supply and provide adequate information to consumers. This includes interventions setting reformulation targets for core food groups, setting population nutrient intake targets and mandating that the HSR is displayed on all products.

Background Excess sodium intake is one of the top 2 dietary risk factors contributing to the global burden of disease. As such, many countries are now developing national sodium reduction strategies, a key component of which is a sodium reduction model that includes sodium targets for packaged foods and other sources of dietary sodium. Objective We sought to develop a sodium reduction model to determine the reductions required in the sodium content of packaged foods and other dietary sources of sodium to reduce adult population salt intake by ∼30% toward the optimal WHO target of 5 g/d. Design Nationally representative household food-purchasing data for New Zealand were linked with branded food composition information to determine the mean contribution of major packaged food categories to total population sodium consumption. Discretionary salt use and the contribution of sodium from fresh foods and foods consumed away from the home were estimated with the use of national nutrition survey data. Reductions required in the sodium content of packaged foods and other dietary sources of sodium to achieve a 30% reduction in dietary sodium intakes were estimated. Results A 36% reduction (1.6 g salt or 628 mg Na) in the sodium content of packaged foods in conjunction with a 40% reduction in discretionary salt use and the sodium content of foods consumed away from the home would reduce total population salt intake in New Zealand by 35% (from 8.4 to 5.5 g/d) and thus meet the WHO 2025 30% relative reduction target. Key reductions required include a decrease of 21% in the sodium content of white bread, 27% for hard cheese, 42% for sausages, and 54% for ready-to-eat breakfast cereals. Conclusions Achieving the WHO sodium target in New Zealand will take considerable efforts by both food manufacturers and consumers and will likely require a national government-led sodium reduction strategy.

Most mobile health (mHealth) programmes are designed with minimal input from target end users and are not truly personalised or adaptive to their specific and evolving needs. This review describes the methods and processes used in the co-design of mHealth interventions. Nine relevant studies of varying design were identified following searches of six academic databases. All employed co-design or participatory methods for the development of a health intervention delivered via a mobile device, with three focusing on health behaviour change (one on nutrition) and six on management of a health condition. Overall, six key phases of design and 17 different methods were used. Sufficiency of reporting was poor, and no study undertook a robust assessment of efficacy; these factors should be a focus for future studies. An opportunity exists to use co-design methods to develop acceptable and feasible mHealth interventions, especially to support improved nutrition and for minority and indigenous groups.

Objective: The primary aim of the current study was to synthesize evidence of the effect of social media use compared with no social media use as part of interventions to reduce risk factors for noncommunicable diseases. Data Sources: Databases were searched up to June 10, 2014, using medical subject headings. A secondary aim of this study was to assess the effectiveness of social media use compared with no social media use in reducing the risk factors for noncommunicable diseases, stratifying the results by the extent of bias on outcomes, by social media use alone, and by the levels of social presence and media richness. Study Selection: Sixteen trials (n=10 711 participants) met the inclusion criteria, but interventions mostly used social media with low levels of media richness and presence (e.g., discussion boards, bulletin boards). Data Synthesis: Meta-analysis of all trials showed no significant differences (standardized mean difference [SMD] −0.14; 95%CI −0.28 to 0.01), with similar findings for physical activity (SMD 0.07; 95%CI −0.25 to 0.38), body weight (SMD 0.07; 95%CI −0.17 to 0.20), and fruit and vegetable intake (SMD 0.39; 95%CI −0.11 to 0.89). Trials assessing social media interventions aimed at modifying risk factors for noncommunicable diseases showed that social media use improved the primary outcomes, but the overall quality of the included studies limits the generalizability of these findings. Conclusion: Further trials are warranted, especially to isolate the effect of social media use and to fully evaluate the effect of the social presence and media richness of social media platforms.

Background:Food taxes and subsidies are one intervention to address poor diets. Price elasticity (PE) matrices are commonly used to model the change in food purchasing. Usually a PE matrix is generated in one setting then applied to another setting with differing starting consumptions and prices of foods. This violates econometric assumptions resulting in likely mis-estimation of total food consumption. In this paper we demonstrate this problem, canvass possible options for rescaling all consumption after applying a PE matrix, and illustrate the use of a total food expenditure elasticity (TFEe; the expenditure elasticity for all food combined given the policy-induced change in the total price of food). We use case studies of: NZD2 per 100g saturated fat (SAFA) tax, NZD0.4 per 100g sugar tax, and a 20% fruit and vegetable (F&V) subsidy. Methods:We estimated changes in food purchasing using a NZ PE matrix applied conventionally, and then with TFEe adjustment. Impacts were quantified for pre- to post-policy changes in total food expenditure and health adjusted life years (HALYs) for the total NZ population alive in 2011 over the rest of their lifetime using a multistate lifetable model. Results:Two NZ studies gave TFEe’s of 0.68 and 0.83, with international estimates ranging from 0.46 to 0.90 (except a UK outlier of 0.04). Without TFEe adjustment, total food expenditure decreased with the tax policies and increased with the F&V subsidy–implausible directions of shift given economic theory and the external TFEe estimates. After TFEe adjustment, HALY gains reduced by a third to a half for the two taxes and reversed from an apparent health loss to a health gain for the F&V subsidy. With TFEe adjustment, HALY gains (in 1000’s) were: 1,805 (95% uncertainty interval 1,337 to 2,340) for the SAFA tax; 1,671 (1,220 to 2,269) for the sugar tax; and 953 (453 to 1,308) for the F&V subsidy. Conclusions:If PE matrices are applied in settings beyond where they were derived, additional scaling is likely required. We suggest that the TFEe is a useful scalar, but we also encourage other researchers to examine this issue and propose alternative options.

A comprehensive approach involving both environmental and individual strategies offers opportunities to strengthen school-based interventions for childhood obesity.To evaluate a theory-based comprehensive intervention implemented within primary schools for childhood obesity in China.A 1-year, cluster randomized controlled trial was conducted in twelve primary schools (7-11 years old) in Beijing, China. Environmental and individual factors were improved in the intervention group (6 schools, 930 children) to promote knowledge and behaviors related to energy balance. The control group (6 schools, 959 children) did not receive any intervention. The primary outcome was body mass index (BMI) and its Z-score at 12 months. Generalized linear mixed models were used controlling for the cluster effect of school.No significant differences were found between groups on BMI (0.07 kg/mThe intervention did not mitigate excess weight gain, but did improve children's knowledge and several behaviors related to energy balance.

Background The nutritional composition of foods and beverages consumed away from the home has important implications for population health. Our objective was to determine if the serve size, energy, and sodium contents of fast foods sold at chain restaurants in New Zealand (NZ) changed between 2012 and 2016. Methods Serve size and nutrient data were collected in annual cross-sectional surveys of all products sold at 10 major fast food chains. Changes over time may occur due to alterations in product availability or individual product reformulation. Linear regression adjusting for food group and chain was used to estimate overall changes in serve size and nutrients. Random effects mixed models were used to estimate reformulation changes on same products available for two or more years. Results Across all products (n = 5468) increases were observed in mean serve size (+ 9 (3, 15) g, + 5%), energy density (+ 54 (27, 81) kJ/100 g, + 6%), energy per serve (+ 178 (125, 231) kJ, + 14%), and sodium per serve (+ 55 (24, 87) mg, + 12%). Sodium density did not change significantly. Four of 12 food groups (Desserts, Pizza, Sandwiches, and Salads) and four of 10 fast food chains (Domino’s, Hell Pizza, Pizza Hut, and Subway) displayed large, undesirable changes for three or more (of five) outcomes (≥10%; p

Objective 842 million people worldwide are undernourished, while simultaneously the number of overweight and obese individuals increased to 2.1 billion in 2013. There is growing opinion that addressing the global burden of diet-related disease requires a much more comprehensive and multidisciplinary approach than stand-alone public health nutrition interventions such as nutrition education or food labelling. Instead, we need to develop whole of systems interventions to address the core problem and consider the way we grow, process, distribute and commercialize our food. However, there is little evidence or guidance on how to best achieve this goal. This research aims to develop a whole of food systems approach for public health nutrition research by building on systems methods from other fields of science. Specific objectives are to: 1) identify systems methods that are applicable to public health nutrition research; 2) identify how these systems methods and public health research can best be integrated. Methods/results We explored a range of systems methods which could potentially be applied to public health nutrition research. Based on these, we developed a framework for using and combining different systems methods in public health nutrition research. The framework consists of three main phases: A) availability and affordability of (un)healthy food; B) determinants of (un)healthy food availability and affordability; and C) food system intervention development. Phase A forms the platform of this research combining a series of smaller projects examining food availability, affordability and healthiness. Phase B uses global value chain analysis (GVCA) to identify different attributes of value, including both health and monetary values. Phase C aims to identify sustainable food system public health interventions using Group Model Building (GMB) and logistic modelling approaches. Conclusion This paper presents why and how systems methods can be used in public health nutrition research. The food system is highly complex and this complexity needs to be acknowledged to find solutions for the current nutrition challenges (obesity, under nutrition), which cannot be solved in isolation. We envision that the methods presented in this paper can form the basis for future research in this area where it can be applied to other public health nutrition research (for example other food products, in relation to specific diseases, different countries) as well as other domains of a sustainable food system not specifically focused on here e.g. economic, social and specific environmental outcomes.

Research investigating the influence of the environmental and social factors on eating behaviours in free-living settings is limited. This study investigates the utility of using wearable camera images to assess the context of eating episodes. Adult participants (N = 40) wore a SenseCam wearable camera for 4 days (including 1 familiarisation day) over a 15-day period in free-living conditions, and had their diet assessed using three image-assisted multiple-pass 24-hour dietary recalls. The images of participants' eating episodes were analysed and annotated according to their environmental and social contexts; including eating location, external environment (indoor/outdoor), physical position, social interaction, and viewing media screens. Data for 107 days were used, with a total of 742 eating episodes considered for annotation. Twenty nine per cent (214/742) of the episodes could not be categorised due to absent images (12%, n = 85), dark/blurry images (8%, n = 58), camera not worn (7%, n = 54) and for mixed reasons (2%, n = 17). Most eating episodes were at home (59%) and indoors (91%). Meals at food retailers were 24.8 minutes longer (95% CI: 13.4 to 36.2) and were higher in energy (mean difference = 1196 kJ 95% CI: 242, 2149) than at home. Most episodes were seated at tables (27%) or sofas (26%), but eating standing (19%) or at desks (18%) were common. Social interaction was evident for 45% of episodes and media screens were viewed during 55% of episodes. Meals at home watching television were 3.1 minutes longer (95% CI: -0.6 to 6.7) and higher in energy intake than when no screen was viewed (543 kJ 95% CI: -32 to 1120). The environmental and social context that surrounds eating and dietary behaviours can be assessed using wearable camera images.

A letter to Nutrients from the Chief Executive of the New Zealand Food and Grocery Council [1] questioned the validity of methods and findings reported in our recent paper, “Changes in the Sodium Content of New Zealand Processed Foods: 2003–2013” [2]. [...]

BACKGROUND: Fiscal strategies are increasingly considered upstream nutrition promotion measures. However, few trials have investigated the effectiveness or cost effectiveness of pricing manipulations on diet in real-world settings. OBJECTIVE: We assessed the effects on fruit, vegetable, and beverage purchasing and consumption of a 20% price-reduction intervention, a tailored skills-based behavior-change intervention, and a combined intervention compared with a control condition. DESIGN: The Supermarket Healthy Eating for Life trial was a randomized controlled trial conducted over 3 mo [baseline (time 1) to postintervention (time 2) with a 6-mo follow-up (time 3)]. Female primary household shoppers in Melbourne, Australia, were randomly assigned to a 1) skill-building (n = 160), 2) price-reduction (n = 161), 3) combined skill-building and price-reduction (n = 160), or 4) control (n = 161) group. Supermarket transaction data and surveys were used to measure the following study outcomes: fruit, vegetable, and beverage purchases and self-reported fruit and vegetable consumption at each time point. RESULTS: At 3 mo (time 2), price reduction-alone participants purchased more total vegetables and frozen vegetables than did controls. Price reduction-alone and price reduction-plus-skill-building participants purchased more fruit than did controls. Relative to controls, in the price-reduction group, total vegetable consumption increased by 233 g/wk (3.1 servings or 15% more than at baseline), and fruit purchases increased by 364 g/wk (2.4 servings; 35% more than at baseline). Increases were not maintained 6 mo postintervention (time 3). Price reduction-alone participants showed a tendency for a slight increase in fruit consumption at time 2 (P = 0.09) that was maintained at time 3 (P = 0.014). No intervention improved purchases of bottled water or low-calorie beverages. CONCLUSIONS: A 20% price reduction in fruit and vegetables resulted in increased purchasing per household of 35% for fruit and 15% for vegetables over the price-reduction period. These findings show that price modifications can directly increase produce purchases. The Supermarket Healthy Eating for Life trial was registered at Current Controlled Trials Registration as ISRCTN39432901.

Images captured during eating episodes provide objective information to assist in the assessment of dietary intake. Images are captured using handheld devices or wearable cameras, and can support traditional self-report or provide the primary record of dietary intake. A diverse range of image-assisted methods have been developed and evaluated but have not been previously examined together. Therefore, a review was undertaken to examine all studies that have evaluated or validated image-assisted methods of dietary assessment for assessing dietary energy intake. Identified image-assisted methods that employ similar methodologies were grouped for comparison. English-language full-text research articles published between January 1998 and November 2013 were searched using five electronic databases. A search of reference lists and associated websites was also conducted. Thirteen studies that evaluated 10 unique image-assisted methods among adults aged 18 to 70 years were included. Ten studies used handheld devices and three studies used wearable cameras. Eight studies evaluated image-based food records, two studies explored the use of images to enhance written food records, and three studies evaluated image-assisted 24-hour dietary recalls. Results indicate images enhance self-report by revealing unreported foods and identify misreporting errors not captured by traditional methods alone. Moreover, when used as the primary record of dietary intake, images can provide valid estimates of energy intake. However, image-assisted methods that rely on image analysis can be prone to underestimation if users do not capture images of satisfactory quality before all foods are consumed. Further validation studies using criterion measures are warranted. The validity among children, adolescents, and elderly persons as well as the feasibility of using image-assisted methods in large samples needs to be examined. Additional research is also needed to better understand the potential applications and pitfalls of wearable cameras.