Perception is reality: qualitative insights into how consumers perceive alcohol warning labels.

AIMS: This study explores perspectives of on-pack alcohol warning labels, and how they might influence alcohol purchase and/or consumption behavior to inform culturally appropriate label design for effective behavior change. METHODS: New Zealand participants ≥18 years, who reported having purchased and consumed alcoholic beverages in the last month were recruited via a market research panel and grouped into 10 focus groups (n = 53) by ethnicity (general population, Maori, and Pacific peoples), age group, and level of alcohol consumption. Participants were shown six potential alcohol health warning labels, with design informed by relevant literature, label framework, and stakeholder feedback. Interviews were transcribed and analyzed via qualitative (directed) content analysis. RESULTS: Effective alcohol labels should be prominent, featuring large red and/or black text with a red border, combining text with visuals, and words like "WARNING" in capitals. Labels should contrast with bottle color, be easily understood, and avoid excessive text and confusing imagery. Participants preferred specific health outcomes, such as heart disease and cancer, increasing message urgency and relevance. Anticipated behavior change included reduced drinking and increased awareness of harms, but some may attempt to mitigate warnings by covering or removing labels. Contextual factors, including consistent design and targeted labels for different beverages and populations, are crucial. There was a strong emphasis on collective health impacts, particularly among Maori and Pacific participants. CONCLUSIONS: Our findings indicate that implementing alcohol warning labels, combined with comprehensive strategies like retail and social marketing campaigns, could effectively inform and influence the behavior of New Zealand's varied drinkers.

Potential effect of real-world junk food and sugar-sweetened beverage taxes on population health, health system costs and greenhouse gas emissions in New Zealand: a modelling study.

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.

Can a Greenhouse Gas Emissions Tax on Food also Be Healthy and Equitable? A Systemised Review and Modelling Study from Aotearoa New Zealand.

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 Maori. 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.

A co-designed mHealth programme to support healthy lifestyles in Maori and Pasifika peoples in New Zealand (OL@-OR@): a cluster-randomised controlled trial.

BACKGROUND: The OL@-OR@ mobile health programme was co-designed with Maori 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 Maori 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 Maori 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 Maori participants from 19 clusters and 389 Pasifika participants from 18 clusters (n=726 participants) in the intervention group and 320 Maori participants from 15 clusters and 405 Pasifika participants from 17 clusters (n=725 participants) in the control group. Of these participants, 227 (67%) Maori participants and 347 (89%) Pasifika participants (n=574 participants) in the intervention group and 281 (88%) Maori 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 Maori and Pasifika individuals. FUNDING: Healthier Lives He Oranga Hauora National Science Challenge.

A Co-Designed, Culturally-Tailored mHealth Tool to Support Healthy Lifestyles in Maori and Pasifika Communities in New Zealand: Protocol for a Cluster Randomized Controlled Trial.

BACKGROUND: New Zealand urgently requires scalable, effective, behavior change programs to support healthy lifestyles that are tailored to the needs and lived contexts of Maori and Pasifika communities. OBJECTIVE: The primary objective of this study is to determine the effects of a co-designed, culturally tailored, lifestyle support mHealth tool (the OL@-OR@ mobile phone app and website) on key risk factors and behaviors associated with an increased risk of noncommunicable disease (diet, physical activity, smoking, and alcohol consumption) compared with a control condition. METHODS: A 12-week, community-based, two-arm, cluster-randomized controlled trial will be conducted across New Zealand from January to December 2018. Participants (target N=1280; 64 clusters: 32 Maori, 32 Pasifika; 32 clusters per arm; 20 participants per cluster) will be individuals aged ≥18 years who identify with either Maori or Pasifika ethnicity, live in New Zealand, are interested in improving their health and wellbeing or making lifestyle changes, and have regular access to a mobile phone, tablet, laptop, or computer and to the internet. Clusters will be identified by community coordinators and randomly assigned (1:1 ratio) to either the full OL@-OR@ tool or a control version of the app (data collection only plus a weekly notification), stratified by geographic location (Auckland or Waikato) for Pasifika clusters and by region (rural, urban, or provincial) for Maori clusters. All participants will provide self-reported data at baseline and at 4- and 12-weeks postrandomization. The primary outcome is adherence to healthy lifestyle behaviors measured using a self-reported composite health behavior score at 12 weeks that assesses smoking behavior, fruit and vegetable intake, alcohol intake, and physical activity. Secondary outcomes include self-reported body weight, holistic health and wellbeing status, medication use, and recorded engagement with the OL@-OR@ tool. RESULTS: Trial recruitment opened in January 2018 and will close in July 2018. Trial findings are expected to be available early in 2019. CONCLUSIONS: Currently, there are no scalable, evidence-based tools to support Maori or Pasifika individuals who want to improve their eating habits, lose weight, or be more active. This wait-list controlled, cluster-randomized trial will assess the effectiveness of a co-designed, culturally tailored mHealth tool in supporting healthy lifestyles. TRIAL REGISTRATION: Australia New Zealand Clinical Trials Register ACTRN12617001484336; http://www.ANZCTR.org.au/ACTRN12617001484336.aspx (Archived by WebCite at http://www.webcitation.org/71DX9BsJb). REGISTERED REPORT IDENTIFIER: RR1-10.2196/10789.

Do nutrition labels influence healthier food choices? Analysis of label viewing behaviour and subsequent food purchases in a labelling intervention trial.

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

Kids'Cam: An Objective Methodology to Study the World in Which Children Live.

INTRODUCTION: This paper reports on a new methodology to objectively study the world in which children live. The primary research study (Kids'Cam Food Marketing) illustrates the method; numerous ancillary studies include exploration of children's exposure to alcohol, smoking, "blue" space and gambling, and their use of "green" space, transport, and sun protection. METHODS: One hundred sixty-eight randomly selected children (aged 11-13 years) recruited from 16 randomly selected schools in Wellington, New Zealand used wearable cameras and GPS units for 4 days, recording imagery every 7 seconds and longitude/latitude locations every 5 seconds. Data were collected from July 2014 to June 2015. Analysis commenced in 2015 and is ongoing. Bespoke software was used to manually code images for variables of interest including setting, marketing media, and product category to produce variables for statistical analysis. GPS data were extracted and cleaned in ArcGIS, version 10.3 for exposure spatial analysis. RESULTS: Approximately 1.4 million images and 2.2 million GPS coordinates were generated (most were usable) from many settings including the difficult to measure aspects of exposures in the home, at school, and during leisure time. The method is ethical, legal, and acceptable to children and the wider community. CONCLUSIONS: This methodology enabled objective analysis of the world in which children live. The main arm examined the frequency and nature of children's exposure to food and beverage marketing and provided data on difficult to measure settings. The methodology will likely generate robust evidence facilitating more effective policymaking to address numerous public health concerns.

Effects of interpretive nutrition labels on consumer food purchases: the Starlight randomized controlled trial.

Background: Nutrition labeling is a prominent policy to promote healthy eating.Objective: We aimed to evaluate the effects of 2 interpretive nutrition labels compared with a noninterpretive label on consumer food purchases.Design: In this parallel-group randomized controlled trial, we enrolled household shoppers across New Zealand who owned smartphones and were aged ≥18 y. Eligible participants were randomly assigned (1:1:1) to receive either traffic light labels (TLLs), Health Star Rating labels (HSRs), or a control [nutrition information panel (NIP)]. Smartphone technology allowed participants to scan barcodes of packaged foods and to receive allocated labels on their smartphone screens. The primary outcome was the mean healthiness of all packaged food purchases over the 4-wk intervention period, which was measured by using the Food Standards Australia New Zealand Nutrient Profiling Scoring Criterion (NPSC).Results: Between October 2014 and November 2015, 1357 eligible shoppers were randomly assigned to TLL (n = 459), HSR (n = 443), or NIP (n = 455) labels. Overall difference in the mean transformed NPSC score for the TLL group compared with the NIP group was -0.20 (95% CI: -0.94, 0.54; P = 0.60). The corresponding difference for HSR compared with NIP was -0.60 (95% CI: -1.35, 0.15; P = 0.12). In an exploratory per-protocol analysis of participants who used the labeling intervention more often than average (n = 423, 31%), those who were assigned to TLL and HSR had significantly better NPSC scores [TLL compared with NIP: -1.33 (95% CI: -2.63, -0.04; P = 0.04); HSR compared with NIP: -1.70 (95% CI: -2.97, -0.43; P = 0.01)]. Shoppers who were randomly assigned to HSR and TLL also found the labels significantly more useful and easy to understand than the NIP (all P values <0.001).Conclusions: At the relatively low level of use observed in this trial, interpretive nutrition labels had no significant effect on food purchases. However, shoppers who used interpretive labels found them to be significantly more useful and easy to understand, and compared with frequent NIP users, frequent TLL and HSR users had significantly healthier food purchases. This trial was registered at the Australian New Zealand Clinical Trials Registry (https://www.anzctr.org.au/Trial/Registration/TrialReview.aspx?id=366446&isReview=true) as ACTRN12614000644662.

A process evaluation of the Supermarket Healthy Eating for Life (SHELf) randomized controlled trial.

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, χ (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-calorie carbonated beverages and water. Overall reported satisfaction with, use, and impact of the skill-building resources was moderate. Maintenance of newly acquired behaviours was limited, with less than half of participants making changes or using study-provided resources during the 6-month post-intervention period. CONCLUSIONS: SHELf's reach and perceived effectiveness were moderate. The interventions were more effective among those reporting greater engagement with them (an implementation-related construct). Maintenance of newly acquired behaviours proved challenging. TRIAL REGISTRATION: Current controlled trials ISRCTN39432901 .

The Influence of Nutrition Labeling and Point-of-Purchase Information on Food Behaviours.

Point-of-purchase information on packaged food has been a highly debated topic. Various types of nutrition labels and point-of-purchase information have been studied to determine their ability to attract consumers' attention, be well understood and promote healthy food choices. Country-specific regulatory and monitoring frameworks have been implemented to ensure reliability and accuracy of such information. However, the impact of such information on consumers' behaviour remains contentious. This review summarizes recent evidence on the real-world effectiveness of nutrition labels and point-of-purchase information.

Effects of Health-Related Food Taxes and Subsidies on Mortality from Diet-Related Disease in New Zealand: An Econometric-Epidemiologic Modelling Study.

BACKGROUND: Health-related food taxes and subsidies may promote healthier diets and reduce mortality. Our aim was to estimate the effects of health-related food taxes and subsidies on deaths prevented or postponed (DPP) in New Zealand. METHODS: A macrosimulation model based on household expenditure data, demand elasticities and population impact fractions for 18 diet-related diseases was used to estimate effects of five tax and subsidy regimens. We used price elasticity values for 24 major commonly consumed food groups in New Zealand, and food expenditure data from national Household Economic Surveys. Changes in mortality from cardiovascular disease, cancer, diabetes and other diet-related diseases were estimated. FINDINGS: A 20% subsidy on fruit and vegetables would result in 560 (95% uncertainty interval, 400 to 700) DPP each year (1.9% annual all-cause mortality). A 20% tax on major dietary sources of saturated fat would result in 1,500 (950 to 2,100) DPP (5.0%), and a 20% tax on major dietary sources of sodium would result in 2,000 (1300 to 2,700) DPP (6.8%). Combining taxes on saturated fat and sodium with a fruit and vegetable subsidy would result in 2,400 (1,800 to 3,000) DPP (8.1% mortality annually). A tax on major dietary sources of greenhouse gas emissions would generate 1,200 (750 to 1,700) DPP annually (4.0%). Effects were similar or greater for Maori and low-income households in relative terms. CONCLUSIONS: Health-related food taxes and subsidies could improve diets and reduce mortality from diet-related disease in New Zealand. Our study adds to the growing evidence base suggesting food pricing policies should improve population health and reduce inequalities, but there is still much work to be done to improve estimation of health impacts.

Using a 3D virtual supermarket to measure food purchase behavior: a validation study.

BACKGROUND: There is increasing recognition that supermarkets are an important environment for health-promoting interventions such as fiscal food policies or front-of-pack nutrition labeling. However, due to the complexities of undertaking such research in the real world, well-designed randomized controlled trials on these kinds of interventions are lacking. The Virtual Supermarket is a 3-dimensional computerized research environment designed to enable experimental studies in a supermarket setting without the complexity or costs normally associated with undertaking such research. OBJECTIVE: The primary objective was to validate the Virtual Supermarket by comparing virtual and real-life food purchasing behavior. A secondary objective was to obtain participant feedback on perceived sense of "presence" (the subjective experience of being in one place or environment even if physically located in another) in the Virtual Supermarket. METHODS: Eligible main household shoppers (New Zealand adults aged ≥18 years) were asked to conduct 3 shopping occasions in the Virtual Supermarket over 3 consecutive weeks, complete the validated Presence Questionnaire Items Stems, and collect their real supermarket grocery till receipts for that same period. Proportional expenditure (NZ$) and the proportion of products purchased over 18 major food groups were compared between the virtual and real supermarkets. Data were analyzed using repeated measures mixed models. RESULTS: A total of 123 participants consented to take part in the study. In total, 69.9% (86/123) completed 1 shop in the Virtual Supermarket, 64.2% (79/123) completed 2 shops, 60.2% (74/123) completed 3 shops, and 48.8% (60/123) returned their real supermarket till receipts. The 4 food groups with the highest relative expenditures were the same for the virtual and real supermarkets: fresh fruit and vegetables (virtual estimate: 14.3%; real: 17.4%), bread and bakery (virtual: 10.0%; real: 8.2%), dairy (virtual: 19.1%; real: 12.6%), and meat and fish (virtual: 16.5%; real: 16.8%). Significant differences in proportional expenditures were observed for 6 food groups, with largest differences (virtual - real) for dairy (in expenditure 6.5%, P<.001; in items 2.2%, P=.04) and fresh fruit and vegetables (in expenditure: -3.1%, P=.04; in items: 5.9%, P=.002). There was no trend of overspending in the Virtual Supermarket and participants experienced a medium-to-high presence (88%, 73/83 scored medium; 8%, 7/83 scored high). CONCLUSIONS: Shopping patterns in the Virtual Supermarket were comparable to those in real life. Overall, the Virtual Supermarket is a valid tool to measure food purchasing behavior. Nevertheless, it is important to improve the functionality of some food categories, in particular fruit and vegetables and dairy. The results of this validation will assist in making further improvements to the software and with optimization of the internal and external validity of this innovative methodology.

Effects of interpretive front-of-pack nutrition labels on food purchases: protocol for the Starlight randomised controlled trial.

BACKGROUND: Interpretive front-of-pack nutrition labels are better understood than non-interpretive labels. However, robust evidence on the effects of such labels on consumer food purchases in the real-world is lacking. Our aim is to assess the effects of two interpretive front-of-pack nutrition labels, compared with a non-interpretive label, on the healthiness of consumer food purchases. METHODS/DESIGN: A five-week (1-week baseline and 4-week intervention) three-arm parallel randomised controlled trial will be conducted using a bespoke smartphone application, which will administer study questionnaires and deliver intervention (Multiple Traffic Light and Health Star Rating) and control (Nutrition Information Panel) labels. To view their allocated nutrition label, participants scan the barcode of packaged food products using their smartphone camera. The assigned label is displayed instantly on the smartphone screen.1500 eligible participants (New Zealand adult smartphone owners who shop in a supermarket at least once a week and are main household shoppers) will be randomised in a 1:1:1 ratio to one of the three nutrition label formats, using computer-generated randomisation sequences. Randomisation will be stratified by ethnicity and interest in healthy eating. Food and beverage purchase data will be collected continuously throughout the study via hard copy till receipts and electronic grocery purchase lists recorded and transmitted using the smartphone application. The primary outcome will be healthiness of food purchases in each trial arm, assessed as mean Food Standards Australia New Zealand nutrient profiling score criterion score for all food and beverages purchased over the intervention period. Secondary outcomes will include saturated fat, sugar, sodium and energy content of food purchases; food expenditure; labelling profile of food purchases (i.e. mean number of Health Star Rating stars and proportion of red, green and amber traffic lights); nutrient profiling score over time and by food categories; purchases of unpackaged foods; self-reported nutrition knowledge and recorded use of assigned labelling system. DISCUSSION: The Starlight randomised, controlled trial will determine the effects of interpretive front-of-pack nutrition labels on the healthiness of consumer food purchases in the real world. TRIAL REGISTRATION: Australian New Zealand Clinical Trials Registry ACTRN12614000644662 (registered 18 June 2014).

The effect of active video games by ethnicity, sex and fitness: subgroup analysis from a randomised controlled trial.

BACKGROUND: The prevention and treatment of childhood obesity is a key public health challenge. However, certain groups within populations have markedly different risk profiles for obesity and related health behaviours. Well-designed subgroup analysis can identify potential differential effects of obesity interventions, which may be important for reducing health inequalities. The study aim was to evaluate the consistency of the effects of active video games across important subgroups in a randomised controlled trial (RCT). FINDINGS: A two-arm, parallel RCT was conducted in overweight or obese children (n=322; aged 10-14 years) to determine the effect of active video games on body composition. Statistically significant overall treatment effects favouring the intervention group were found for body mass index, body mass index z-score and percentage body fat at 24 weeks. For these outcomes, pre-specified subgroup analyses were conducted among important baseline demographic (ethnicity, sex) and prognostic (cardiovascular fitness) groups. No statistically significant interaction effects were found between the treatment and subgroup terms in the main regression model (p=0.36 to 0.93), indicating a consistent treatment effect across these groups. CONCLUSIONS: Preliminary evidence suggests an active video games intervention had a consistent positive effect on body composition among important subgroups. This may support the use of these games as a pragmatic public health intervention to displace sedentary behaviour with physical activity in young people.

Stores Healthy Options Project in Remote Indigenous Communities (SHOP@RIC): a protocol of a randomised trial promoting healthy food and beverage purchases through price discounts and in-store nutrition education.

BACKGROUND: Indigenous Australians suffer a disproportionate burden of preventable chronic disease compared to their non-Indigenous counterparts--much of it diet-related. Increasing fruit and vegetable intakes and reducing sugar-sweetened soft-drink consumption can reduce the risk of preventable chronic disease. There is evidence from some general population studies that subsidising healthier foods can modify dietary behaviour. There is little such evidence relating specifically to socio-economically disadvantaged populations, even though dietary behaviour in such populations is arguably more likely to be susceptible to such interventions.This study aims to assess the impact and cost-effectiveness of a price discount intervention with or without an in-store nutrition education intervention on purchases of fruit, vegetables, water and diet soft-drinks among remote Indigenous communities. METHODS/DESIGN: We will utilise a randomised multiple baseline (stepped wedge) design involving 20 communities in remote Indigenous Australia. The study will be conducted in partnership with two store associations and twenty Indigenous store boards. Communities will be randomised to either i) a 20% price discount on fruit, vegetables, water and diet soft-drinks; or ii) a combined price discount and in-store nutrition education strategy. These interventions will be initiated, at one of five possible time-points, spaced two-months apart. Weekly point-of-sale data will be collected from each community store before, during, and for six months after the six-month intervention period to measure impact on purchasing of discounted food and drinks. Data on physical, social and economic factors influencing weekly store sales will be collected in order to identify important covariates. Intervention fidelity and mediators of behaviour change will also be assessed. DISCUSSION: This study will provide original evidence on the effectiveness and cost-effectiveness of price discounts with or without an in-store nutrition education intervention on food and drink purchasing among a socio-economically disadvantaged population in a real-life setting. TRIAL REGISTRATION: Australian New Zealand Clinical Trials Registry: ACTRN12613000694718.

Foods and dietary patterns that are healthy, low-cost, and environmentally sustainable: a case study of optimization modeling for New Zealand.

OBJECTIVE: Global health challenges include non-communicable disease burdens, ensuring food security in the context of rising food prices, and environmental constraints around food production, e.g., greenhouse gas [GHG] emissions. We therefore aimed to consider optimized solutions to the mix of food items in daily diets for a developed country population: New Zealand (NZ). METHODS: We conducted scenario development and linear programming to model 16 diets (some with uncertainty). Data inputs included nutrients in foods, food prices, food wastage and food-specific GHG emissions. FINDINGS: This study identified daily dietary patterns that met key nutrient requirements for as little as a median of NZ$ 3.17 per day (US$ 2.41/d) (95% simulation interval [SI] = NZ$ 2.86 to 3.50/d). Diets that included "more familiar meals" for New Zealanders, increased the cost. The optimized diets also had low GHG emission profiles compared with the estimate for the 'typical NZ diet' e.g., 1.62 kg CO2e/d for one scenario (95%SI = 1.39 to 1.85 kg CO2e) compared with 10.1 kg CO2e/d, respectively. All of the optimized low-cost and low-GHG dietary patterns had likely health advantages over the current NZ dietary pattern, i.e., lower cardiovascular disease and cancer risk. CONCLUSIONS: We identified optimal foods and dietary patterns that would lower the risk of non-communicable diseases at low cost and with low greenhouse gas emission profiles. These results could help guide central and local government decisions around which foods to focus policies on. That is which foods are most suitable for: food taxes (additions and exemptions); healthy food vouchers and subsidies; and for increased use by public institutions involved in food preparation.

Tackling 'wicked' health promotion problems: a New Zealand case study.

This paper reports on a complex environmental approach to addressing 'wicked' health promotion problems devised to inform policy for enhancing food security and physical activity among Maori, Pacific and low-income people in New Zealand. This multi-phase research utilized literature reviews, focus groups, stakeholder workshops and key informant interviews. Participants included members of affected communities, policy-makers and academics. Results suggest that food security and physical activity 'emerge' from complex systems. Key areas for intervention include availability of money within households; the cost of food; improvements in urban design and culturally specific physical activity programmes. Seventeen prioritized intervention areas were explored in-depth and recommendations for action identified. These include healthy food subsidies, increasing the statutory minimum wage rate and enhancing open space and connectivity in communities. This approach has moved away from seeking individual solutions to complex social problems. In doing so, it has enabled the mapping of the relevant systems and the identification of a range of interventions while taking account of the views of affected communities and the concerns of policy-makers. The complex environmental approach used in this research provides a method to identify how to intervene in complex systems that may be relevant to other 'wicked' health promotion problems.

Patterns and trends of beverage consumption among children and adults in Great Britain, 1986-2009.

Many dietary recommendations include reduction of excessive intake of sugar-sweetened beverages (SSB) and other energy-rich beverages such as juices and alcohol. The present study examines surveys of both individual dietary intake data and household food expenditure surveys to provide a picture of patterns and trends in beverage intake and purchases in Great Britain from 1986 to 2009, and estimates the potential for pricing policy to promote more healthful beverage purchase patterns. In 2008-9, beverages accounted for 21, 14 and 18 % of daily energy intake for children aged 1·5-18 and 4-18 years, and adults (19-64 years), respectively. Since the 1990s, the most important shifts have been a reduction in consumption of high-fat dairy products and an increased consumption of fruit juices and reduced-fat milk among preschoolers, children and adolescents. Among adults, consumption of high-fat milk beverages, sweetened tea and coffee and other energy-containing drinks fell, but reduced-fat milk, alcohol (particularly beer) and fruit juice rose. In testing taxation as an option for shifting beverage purchase patterns, we calculate that a 10 % increase in the price of SSB could potentially result in a decrease of 7·5 ml/capita per d. A similar 10 % tax on high-fat milk is associated with a reduction of high-fat milk purchases by 5 ml/capita per d and increased reduced-fat milk purchase by 7 ml/capita per d. This analysis implies that taxation or other methods of shifting relative costs of these beverages could be a way to improve beverage choices in Great Britain.

Tailored nutrition education: is it really effective?

OBJECTIVE: There has been a growing interest in tailored nutrition education over the previous decade, with a number of literature reviews suggesting this intervention strategy holds considerable potential. Nevertheless, the majority of intervention trials undertaken to date have employed subjective self-report outcome measures (such as dietary recalls). The aim of the present review is to further consider the likely true effect of tailored nutrition education by assessing the findings of tailored nutrition education intervention trials where objective outcome measures (such as sales data) have been employed. RESULTS: Four trials of tailored nutrition education employing objective outcome measures were identified: one was undertaken in eight low-cost supermarkets in New Zealand (2010; n 1104); one was an online intervention trial in Australia (2006; n 497); and two were undertaken in US supermarkets (1997 and 2001; n 105 and 296, respectively). Findings from the high-quality New Zealand trial were negative. Findings from the US trials were also generally negative, although reporting was poor making it difficult to assess quality. Findings from the high-quality online trial were positive, although have limited generalisability for public health. CONCLUSIONS: Trials employing objective outcome measures strongly suggest tailored nutrition education is not effective as a stand-alone strategy. However, further large, high-quality trials employing objective outcome measures are needed to determine the true effectiveness of this popular nutrition intervention strategy. Regardless, education plays an important role in generating social understanding and acceptance of broader interventions to improve nutrition.

Do effects of price discounts and nutrition education on food purchases vary by ethnicity, income and education? Results from a randomised, controlled trial.

BACKGROUND: Reducing health inequalities requires interventions that work as well, if not better, among disadvantaged populations. The aim of this study was to determine if the effects of price discounts and tailored nutrition education on supermarket food purchases (percentage energy from saturated fat and healthy foods purchased) vary by ethnicity, household income and education. METHOD: A 2×2 factorial trial of 1104 New Zealand shoppers randomised to receive a 12.5% discount on healthier foods and/or tailored nutrition education (or no intervention) for 6 months. RESULTS: There was no overall association of price discounts or nutrition education with percentage energy from saturated fat, or nutrition education with healthy food purchasing. There was an association of price discounts with healthy food purchasing (0.79 kg/week increase; 95% CI 0.43 to 1.16) that varied by ethnicity (p=0.04): European/other 1.02 kg/week (n=755; 95% CI 0.60 to 1.43); Pacific 1.20 kg/week (n=101; 95% CI 0.06 to 2.34); Maori -0.15 kg/week (n=248; 95% CI -1.10 to 0.80). This association of price discounts with healthy food purchasing did not vary by household income or education. CONCLUSIONS: While a statistically significant variation by ethnicity in the effect of price discounts on food purchasing was found, the authors caution against a causal interpretation due to likely biases (eg, attrition) that differentially affected Maori and Pacific people. The study highlights the challenges in generating valid evidence by social groups for public health interventions. The null findings for tailored nutritional education across all social groups suggest that structural interventions (such as price) may be more effective.