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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.

Summary: 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.

Summary: Background: Most evidence on health-related food taxes and subsidies relies on observational data and effects on single nutrients or foods instead of total diet. The aim of this study was to measure the effect of randomly assigned food price variations on consumer purchasing, where sets of prices emulated commonly discussed food tax and subsidy policies, including a subsidy on fruit and vegetables, a sweetened beverage tax, and taxes on foods according to sugar, sodium, and saturated fat content. Methods: In this study, adult participants (≥18 years) in New Zealand completed up to five weekly shops in a virtual supermarket. Each shopping occasion was randomly allocated to control (no change in prices) or one or more pricing options simulating the following: a fruit and vegetable subsidy (20%), a sweetened beverage tax (20% or 40%), a saturated fat tax (NZ$2 per 100 g or $4 per 100 g saturated fat), a salt tax ($0·02 per 100 mg or $0·04 per 100 mg sodium), or sugar tax ($0·40 per 100 g or $0·80 per 100 g sugar). The primary outcome was the healthiness of the total shopping basket for each weekly shop (% of total unit food items defined as healthy). Low and high price change options were combined in analyses (eg, results for a saturated fat tax are an average of $2 per 100 g or $4 per 100 g). Findings: Between Feb 1, and Dec 1, 2016, we randomly assigned 1132 shoppers, of whom 1038 (91·7%) completed at least one shop and 743 (71·6%) completed all five shops. Overall, data from 4258 shops were included in the analysis, including 645 control shops, 2545 shops where one policy was activated, and 1068 shops with two (or more) policies activated. In the control condition, 67·90% (SD 13·01) of food purchases were classified as healthy. Three of the five policies increased this proportion by a small, but significant amount (saturated fat tax mean absolute difference 1·77%, 95% CI 1·03 to 2·52, p