Search

Background: High dietary sodium intake is a leading cause of hypertension. A major source of dietary sodium is salt added to processed food products available in retail food environments. The fast-growing online grocery shopping setting provides new opportunities for salt reduction interventions that support consumers in choosing healthier options. Methods: The SaltSwitch Online Grocery Shopping randomized controlled trial is investigating the feasibility, acceptability, and effectiveness of a novel intervention for lowering salt consumption and blood pressure amongst people with hypertension who shop for groceries online. The intervention is based on a bespoke web browser extension that interfaces with a major retailer's online store to highlight and interpret product sodium content and suggest similar but lower-sodium alternatives. The primary outcome of interest is change in mean systolic blood pressure between individuals randomized (1:1) to the intervention and control (usual online shopping) arms at 12 weeks. Secondary outcomes are diastolic blood pressure, spot urinary sodium and sodium:potassium ratio, sodium purchases, and dietary intake. Intervention implementation and lessons for future uptake will be assessed using a mixed methods process evaluation. Participants with hypertension who shop online for groceries and exhibit high sodium purchasing behavior are being recruited across Australia. A target sample size of 1,966 provides 80% power (2-sided alpha = 0.05) to detect a 2 mm Hg difference in systolic blood pressure between groups, assuming a 15 mm Hg standard deviation, after allowing for a 10% dropout rate. Discussion: This trial will provide evidence on an innovative intervention to potentially reduce salt intake and blood pressure in people with hypertension. The intervention caters to individual preferences by encouraging sustainable switches to similar but lower-salt products. If effective, the intervention will be readily scalable at low cost by

Front-of-pack labelling (FoPL) aims to promote healthier diets by altering consumer food purchasing behaviour. We quantify the impact of the voluntary Health Star Rating (HSR) FoPL adopted by New Zealand (NZ) in 2014, on (i) the quantity of foods purchased by HSR scores and food groups and (ii) the quantities of different nutrients purchased. We used Nielsen HomeScan household purchasing panel data over 2013-2019, linked to Nutritrack packaged food composition data. Fixed effects analyses were used to estimate the association of HSR with product and nutrient purchasing. We controlled for NZ-wide purchasing trends and potential confounding at the household and product level. In 2019, HSR-labelled products accounted for 24% (2890) of 12 040 products in the dataset and 32% of purchasing volume. Of HSR-labelled products, 1339 (46%) displayed a rating of 4.0-5.0 stars and 556 (19%) displayed a rating of 0.5-2.0 stars. We found little or no association between HSR labelling and the quantities of different foods purchased. Introduction of HSR was, however, associated with lower sodium (-9%, 95% CI -13% to -5%), lower protein (-3%, 95% CI -5% to 0%) and higher fibre (5%, 95% CI 2% to 7%) purchases when purchased products carrying an HSR were compared with the same products prior to introduction of the programme. Robust evidence of HSR labelling changing consumer purchasing behaviour was not observed. The positive effect on nutrient purchasing of HSR-labelled foods likely arises from reformulation of products to achieve a better HSR label.

Background: The Australian Government will soon be releasing a series of sugar reformulation targets for packaged foods. Objective: To estimate the amount of added sugar purchased from packaged food and beverages and the relative contribution that food categories and food companies made to these purchases in 2018. The secondary objective was to examine differences in purchases of added sugar across income levels. Design: Cross-sectional study. Participants/setting: We used 1 year of grocery purchase data from a nationally representative panel of Australian households (the NielsenIQ Homescan panel), combined with a packaged food and beverage database (FoodSwitch). Main outcome measures: Added sugar purchases (grams per day per capita), purchase-weighted added sugar content (grams per 100 g) and total weight of products (with added sugar) purchased (grams per day per capita). Statistical analyses performed: Food categories and food companies were ranked according to their contribution to added sugar purchases. Differences in added sugar purchases by income levels were assessed by 1-factor analysis of variance. Results: Added sugar information was available from 7188 households and across 26,291 unique foods and beverages. On average, the amount of added sugar acquired from packaged foods and beverages was (mean ± SE) 35.9 ± 0.01 g/d per capita. Low-income households purchased 11.0 g/d (95% CI: 10.9-11.0 g/d, P < .001) more added sugar from packaged products than high-income households per capita. The top 10 food categories accounted for 82.2% of added sugar purchased, largely due to purchases of chocolate and sweets, soft drinks, and ice cream and edible ices. Out of 994 food companies, the top 10 companies contributed to 62.1% of added sugar purchases. Conclusions: The Australian Government can strengthen their proposed sugar reduction program by adding further category-specific targets, prioritizing engagement with key food companies and considering a broader range

Policies to mitigate climate change are essential. The objective of this paper was to estimate the impact of greenhouse gas (GHG) food taxes and assess whether such a tax could also have health benefits in Aotearoa NZ. We undertook a systemised review on GHG food taxes to inform four tax scenarios, including one combined with a subsidy. These scenarios were modelled to estimate lifetime impacts on quality-adjusted health years (QALY), health inequities by ethnicity, GHG emissions, health system costs and food costs to the individual. Twenty-eight modelling studies on food tax policies were identified. Taxes resulted in decreased consumption of the targeted foods (e.g., -15.4% in beef/ruminant consumption, N = 12 studies) and an average decrease of 8.3% in GHG emissions (N = 19 studies). The "GHG weighted tax on all foods" scenario had the largest health gains and costs savings (455,800 QALYs and NZD 8.8 billion), followed by the tax-fruit and vegetable subsidy scenario (410,400 QALYs and NZD 6.4 billion). All scenarios were associated with reduced GHG emissions and higher age standardised per capita QALYs for Māori. Applying taxes that target foods with high GHG emissions has the potential to be effective for reducing GHG emissions and to result in co-benefits for population health.

Poor diet is a major risk factor for excess weight gain and obesity-related diseases, including cardiovascular diseases, type 2 diabetes mellitus, osteoarthritis and several cancers. This paper aims to assess the potential impacts of real-world food and beverage taxes on change in dietary risk factors, health gains (in quality-adjusted life years (QALYs)), health system costs and greenhouse gas (GHG) emissions as if they had all been implemented in New Zealand (NZ). Ten taxes or tax packages were modelled. A proportional multistate life table model was used to predict resultant QALYs and costs over the remaining lifespan of the NZ population alive in 2011, as well as GHG emissions. QALYs ranged from 12.5 (95% uncertainty interval (UI) 10.2 to 15.0; 3% discount rate) per 1000 population for the import tax on sugar-sweetened beverages (SSB) in Palau to 143 (95% UI 118 to 171) per 1000 population for the excise duties on saturated fat, chocolate and sweets in Denmark, while health expenditure savings ranged from 2011 NZ$245 (95% UI 188 to 310; 2020 US$185) per capita to NZ$2770 (95% UI 2140 to 3480; US$2100) per capita, respectively. The modelled taxes resulted in decreases in GHG emissions from baseline diets, ranging from -0.2% for the tax on SSB in Barbados to -2.8% for Denmark's tax package. There is strong evidence for the implementation of food and beverage tax packages in NZ or similar high-income settings.

Background: Vulnerable populations are the most prone to diet-related disease. The availability, healthiness, and price of foods have established associations with diet-related disease in communities. However, data describing this in India are sparse, particularly in urban slums and rural areas. Aim: To quantify and compare availability, healthiness, and price of packaged and unpackaged foods and beverages in India, and to identify opportunities to improve diets and health of vulnerable populations. Methods: Nutrition data and price were collected on foods and beverages available at 44 stores in urban, urban slum, and rural areas in four states in India between May and August 2018. Healthiness was assessed using the Australasian Health Star Rating system and product retail prices were examined. Comparisons in the findings were made across state, community area type, and adherence to current and draft Indian food labeling regulations. Results: Packaged foods and beverages (n = 1443, 89%) were more prevalent than unpackaged (n = 172, 11%). Unpackaged products were healthier than packaged (mean Health Star Rating = 3.5 vs 2.0; p < 0.001) and lower in price (median price per 100 g/ml: 13.42 Indian rupees vs 25.70 Indian rupees; p < 0.001), a pattern observed across most community area types and states. 96% of packaged products were compliant with current Indian labeling regulations but only 23% were compliant with proposed labeling regulations. Conclusions: Unpackaged products were on average much healthier and lower in price than packaged foods and beverages. Food policies that support greater availability, accessibility and consumption of unpackaged foods, while limiting consumption of packaged foods, have enormous potential for sustaining the health of the Indian population.

Abstract Background Successful implementation and long-term maintenance of healthy supermarkets initiatives are crucial to achieving potential population health benefits. Understanding barriers and enablers of implementation of real-world trials will enhance wide-scale implementation. This process evaluation of a healthy supermarket intervention sought to describe (i) customer, retailer and stakeholder perspectives on the intervention; (ii) intervention implementation; and (iii) implementation barriers and enablers. Methods Eat Well @ IGA was a 12-month randomised controlled trial conducted in 11 Independent Grocers of Australia (IGA) chain supermarkets in regional Victoria, Australia (5 intervention and 6 wait-listed control stores). Intervention components included trolley and basket signage, local area and in-store promotion, and shelf tags highlighting the healthiest packaged foods. A sequential mixed-methods process evaluation was undertaken. Customer exit surveys investigated demographics, and intervention recall and perceptions. Logistic mixed-models estimated associations between customer responses and demographics, with store as random effect. Supermarket staff surveys investigated staff demographics, interactions with customers, and intervention component feedback. Semi-structured stakeholder interviews with local government, retail and academic partners explored intervention perceptions, and factors which enabled or inhibited implementation, maintenance and scalability. Interviews were inductively coded to identify key themes. Results Of 500 customers surveyed, 33%[95%CI:23,44] recalled the Eat Well @ IGA brand and 97%[95%CI:93,99] agreed that IGA should continue its efforts to encourage healthy eating. The 82

Background Nutrient Profiling Systems (NPSs), including the UK Food Standards Agency NPS and its variants are used to classify foods according to their nutritional composition for nutrition policies. The prospective validity of these NPSs requires however further investigation. The study investigates the associations of the original Food Standards Agency (FSA)-NPS and three variants - the Food Standards Australia New Zealand Nutrient Profiling Scoring Criterion (NPSC), the Health Star Rating (HSR) system NPS and the French NPS (HCSP-NPS) -, which are used as a basis for nutrition policies, with weight status. Methods Dietary indices based on each of the four investigated NPSs applied at the food level were computed at the individual level to characterize the diet quality of 71,178 French individuals from the NutriNet-Santé cohort. Associations of these Dietary Indices (DIs) (as tertiles) with weight gain were assessed using multivariable mixed models, and with overweight and obesity risks using multivariable Cox models. Results For the four NPSs, participants with a lower diet nutritional quality were more likely to have an increase in body mass index over time (median follow-up of 3.14 ± 2.76 years, beta coefficients positive, all p ≤ 0.0001), and an increased risk of overweight (HRT3vs.T1=1.27 [1.17-1.37] for the HCSP-DI, followed by the original FSA-DI with HRT3vs.T1=1.18 [1.09-1.28], the NPSC-DI with HRT3vs.T1=1.14 [1.06-1.24] and the HSR-DI, HRT3vs.T1=1.12 [1.04-1.21]). Whilst differences were small, the HCSP-DI appeared to show significantly greater association with risk of overweight compared to other NPS. Conclusions Less healthy diets defined using the Food Standards Agency-NPS and related systems were all associated with weight gain and overweight risk. Demonstrating this association with health outcomes is an important indicator of one validity dimension of NPSs and supports their use in public policies for the prevention of diet-related chronic diseases.

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

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

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 <15% of products that achieved 2 stars or less. Products that adopted HSR were 6.5% and 10.7% more likely to increase their rating by ≥0.5 stars in Australia and NZ, respectively. Labelled products showed a −4.0% [95% confidence interval (CI): −6.4% to −1.7%, p = 0.001] relative decline in sodium content in NZ, and there was a −1.4% [95% CI: −2.7% to −0.0%, p = 0.045] sodium change in Australia. HSR adoption was associated with a −2.3% [−3.7% to −0.9%, p = 0.001] change in sugar content in NZ and a statistically insignificant −1.1% [−2.3% to 0.1%, p = 0.061] difference in Australia. Initially unhealthy products showed larger reformulation effects when adopting HSR than healthier products. No evidence of a change in protein or saturated fat content was observed. A limitation of our study is that results are not sales weighted. Thus, it is not able to assess changes in overall nutrient consumption that occur because of HSR-caused reformulation. Also, participation into labelling and reformulation is jointly determined by producers in this observational study, impacting its generalisability to settings with

© 2019 The Authors 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.

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.

Unhealthy diets are a leading cause of death and disability globally. The WHO recommends Member States implement front-of-pack (FOP) nutrition labels to guide consumers towards healthier food choices, as part of comprehensive strategies to prevent diet-related non-communicable diseases. Interest in FOP nutrition labelling is increasing, but there is limited guidance for policymakers developing regulations necessary for effective implementation. A rapidly evolving evidence base, limited regulatory capacity and possibility of legal challenge by affected food industry stakeholders can create ' regulatory chill', whereby governments are dissuaded from progressive public health policymaking. We use a framework for analysing public health law and available best-practice guidance to evaluate key components of 31 FOP nutrition labelling regulations endorsed by governments up to June 2019. Analysis of regulatory form shows recent rapid uptake of label formats that are easier for consumers to understand and increasing use of mandatory legislation. However, policymakers must decide much more than whether to apply ' stars', ' traffic lights' or ' stop signs'. The substance of effective regulation must contain strategic regulatory objectives, clear specifications for displaying the label on pack, a valid scoring mechanism and a justified scope for including foods. While there are limited data on current practice, good governance of FOP nutrition labelling regulation also requires transparency and accountability in processes of label development, implementation, evaluation and enforcement to promote continuous improvement and withstand undue commercial interference. Whether developing new FOP nutrition labels or reforming existing ones, our findings support policymakers to design and implement best-practice, evidence-informed regulation.

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 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 clus

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 < 0.05). One food group (Asian) and one chain (St Pierre's) displayed large, desirable changes for two or more outcomes. The only significant reformulation change was a drop in sodium density (- 22 (- 36, - 8) mg/100 g, - 7%). Conclusions: The serve size and energy density of NZ fast food products has increased significantly over the past 5 years. Lower sodium concentration in new and reformulated products has been offset by overall increases in serve size. Continued monitoring and development and implementation of Government-led targets for serve size and nutrient content of new and existing fast food products are required.

In Australia, manufacturers can use two government-endorsed approaches to advertise product healthiness: the Health Star Rating (HSR) front-of-pack nutrition labelling system, and health claims. Related, but different, algorithms determine the star rating of a product (the HSR algorithm) and eligibility to display claims (the Nutrient Profiling Scoring Criterion (NPSC) algorithm). The objective of this study was to examine the agreement between the HSR and NPSC algorithms. Food composition information for 41,297 packaged products was extracted from The George Institute’s FoodSwitch database. HSR and the NPSC scores were calculated, and the proportion of products in each HSR category that were eligible to display a health claim under the NPSC was examined. The highest agreement between the HSR scoring algorithm and the NPSC threshold to determine eligibility to display a health claim was at the HSR cut-off of 3.5 stars (k = 0.83). Overall, 97.3% (n = 40,167) of products with star ratings of 3.5 or higher were also eligible to display a health claim, and 94.3% (n = 38,939) of products with star ratings less than 3.5 were ineligible to display a health claim. The food group with greatest divergence was “edible oils”, with 45% products (n = 342) with HSR >3.5, but 64% (n = 495) eligible to display a claim. Categories with large absolute numbers of products with HSR <3.5, but eligible to display a claim, were “yoghurts and yoghurt drinks” (335 products, 25.4%) and “soft drinks” (299 products, 29.7%). Categories with a large number of products with HSR ≥3.5, but ineligible to display a claim, were “milk” (260 products, 21.2%) and “nuts and seeds” (173 products, 19.7%). We conclude that there is good agreement between the HSR and the NPSC systems overall, but divergence in some food groups is likely to result in confusion for consumers, particularly where foods with low HSRs are eligible to display a health claim. The alignment of the NPSC and HSR scoring algorithms should

© European Society of Cardiology. 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

Reducing salt intake is a cost-effective public health intervention to reduce the global burden of non-communicable disease (NCDs). Ultra-processed foods contribute ~80% of dietary salt in high income countries, and are becoming prominent in low-middle income countries. Instant noodle consumption is particularly high in the Asia Pacific region. The aim of this study was to compare the sodium content of instant noodles sold worldwide to identify potential for reformulation. Analysis was undertaken for 765 instant noodle products from 10 countries using packaged food composition databases of ultra-processed foods compiled by the Global Food Monitoring Group (GFMG) and national shop survey data. Sodium levels were high and variable, within and between countries. Instant noodles in China had the highest mean sodium content (1944 mg/100 g, range: 397-3678/100 g) compared to New Zealand (798 mg/100 g, range: 249-2380 mg/100 g). Average pack size ranged from 57 g (Costa Rica) to 98 g (China). The average packet contributed 35% to 95% of the World Health Organization recommended daily salt intake of <5 g. Forty-one percent of products met the Pacific Island (PICs) regional sodium targets, 37% met the South Africa 2016 targets, and 62% met the UK 2017 targets. This study emphasises a need for stronger regulation and closer monitoring to drive rigorous reformulation of salt in ultra-processed foods.

Background: The impacts of supermarket-based nutrition promotion interventions might be overestimated if participants shift their proportionate food purchasing away from their usual stores. This study quantified whether participants who received price discounts on fruits and vegetables (FV) in the Supermarket Healthy Eating for Life (SHELf) randomized controlled trial (RCT) shifted their FV purchasing into study supermarkets during the intervention period. Methods: Participants were 642 females 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. Participants self-reported the proportion of FV purchased in study supermarkets at baseline, 3- and 6-months post-intervention. Fisher's exact and ?2 tests assessed differences among groups in the proportion of FV purchased in study supermarkets at each time point. Multinomial logistic regression assessed differences among groups in the change in proportionate FV purchasing over time. Results: Post-intervention, 49% of participants purchased =50% of their FV in study supermarkets. Compared to all other groups, the price reduction group was approximately twice as likely (RRR: 1.8-2.2) to have increased proportionate purchasing of FV in study supermarkets from baseline to post-intervention (p<0.05). Conclusions: Participants who received price reductions on FV were approximately twice as likely to shift their FV purchasing from other stores into study supermarkets during the intervention period. Unless food purchasing data are available for all sources, differential changes in purchasing patterns can make it difficult to discern the true impacts of nutrition interventions. Trial registration: The SHELf trial is registered with Current Controlled Trials Registration ISRCTN39432901, Registered 30 June 2010, Retrospectively registered (http://www.isrctn.com/ISRCTN39432901)

BACKGROUND: There is a need for accurate and precise food price elasticities (PE, change in consumer demand in response to change in price) to better inform policy on health-related food taxes and subsidies. METHODS/DESIGN: The Price Experiment and Modelling (Price ExaM) study aims to: I) derive accurate and precise food PE values; II) quantify the impact of price changes on quantity and quality of discrete food group purchases and; III) model the potential health and disease impacts of a range of food taxes and subsidies. To achieve this, we will use a novel method that includes a randomised Virtual Supermarket experiment and econometric methods. Findings will be applied in simulation models to estimate population health impact (quality-adjusted life-years [QALYs]) using a multi-state life-table model. The study will consist of four sequential steps: 1. We generate 5000 price sets with random price variation for all 1412 Virtual Supermarket food and beverage products. Then we add systematic price variation for foods to simulate five taxes and subsidies: a fruit and vegetable subsidy and taxes on sugar, saturated fat, salt, and sugar-sweetened beverages. 2. Using an experimental design, 1000 adult New Zealand shoppers complete five household grocery shops in the Virtual Supermarket where they are randomly assigned to one of the 5000 price sets each time. 3. Output data (i.e., multiple observations of price configurations and purchased amounts) are used as inputs to econometric models (using Bayesian methods) to estimate accurate PE values. 4. A disease simulation model will be run with the new PE values as inputs to estimate QALYs gained and health costs saved for the five policy interventions. DISCUSSION: The Price ExaM study has the potential to enhance public health and economic disciplines by introducing internationally novel scientific methods to estimate accurate and precise food PE values. These values will be used to model the potential health and disease im

Background: Supermarket Healthy Eating for Life (SHELf) was a randomized controlled trial that operationalized a socioecological approach to population-level dietary behaviour change in a real-world supermarket setting. SHELf tested the impact of individual (skill-building), environmental (20 % price reductions), and combined (skill-building + 20 % price reductions) interventions on women's purchasing and consumption of fruits, vegetables, low-calorie carbonated beverages and water. This process evaluation investigated the reach, effectiveness, implementation, and maintenance of the SHELf interventions. Methods: RE-AIM provided a conceptual framework to examine the processes underlying the impact of the interventions using data from participant surveys and objective sales data collected at baseline, post-intervention (3 months) and 6-months post-intervention. Fisher's exact, ? 2 and t-tests assessed differences in quantitative survey responses among groups. Adjusted linear regression examined the impact of self-reported intervention dose on food purchasing and consumption outcomes. Thematic analysis identified key themes within qualitative survey responses. Results: Reach of the SHELf interventions to disadvantaged groups, and beyond study participants themselves, was moderate. Just over one-third of intervention participants indicated that the interventions were effective in changing the way they bought, cooked or consumed food (p < 0.001 compared to control), with no differences among intervention groups. Improvements in purchasing and consumption outcomes were greatest among those who received a higher intervention dose. Most notably, participants who said they accessed price reductions on fruits and vegetables purchased (519 g/week) and consumed (0.5 servings/day) more vegetables. The majority of participants said they accessed (82 %) and appreciated discounts on fruits and vegetables, while there was limited use (40 %) and appreciation of discounts on low-ca

© 2015 American Society for Nutrition. 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 pricereduction 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 i