New Zealand and Australian governments rely heavily on voluntary industry initiatives to improve population nutrition, such as voluntary front-of-pack nutrition labelling (Health Star Rating [HSR]), industry-led food advertising standards, and optional food reformulation programmes. Research in both countries has shown that food companies vary considerably in their policies and practices on nutrition(1). We aimed to determine if a tailored nutrition support programme for food companies improved their nutrition policies and practices compared with control companies who were not offered the programme. REFORM was a 24-month, two-country, cluster-randomised controlled trial. 132 major packaged food/drink manufacturers (n=96) and fast-food companies (n=36) were randomly assigned (2:1 ratio) to receive a 12-month tailored support programme or to the control group (no intervention). The intervention group was offered a programme designed and delivered by public health academics comprising regular meetings, tailored company reports, and recommendations and resources to improve product composition (e.g., reducing nutrients of concern through reformulation), nutrition labelling (e.g., adoption of HSR labels), marketing to children (reducing the exposure of children to unhealthy products and brands) and improved nutrition policy and corporate sustainability reporting. The primary outcome was the nutrient profile (measured using HSR) of company food and drink products at 24 months. Secondary outcomes were the nutrient content (energy, sodium, total sugar, and saturated fat) of company products, display of HSR labels on packaged products, company nutrition-related policies and commitments, and engagement with the intervention. Eighty-eight eligible intervention companies (9,235 products at baseline) were invited to participate, of whom 21 accepted and were enrolled in the REFORM programme (delivered between September 2021 and December 2022). Forty-four companies (3,551 products at baseline) were randomised to the control arm. At 24 months, the model-adjusted mean HSR of intervention company products was 2.58 compared to 2.68 for control companies, with no significant difference between groups (mean difference -0.10, 95% CI -0.40 to 0.21, p-value 0.53). A per protocol analysis of intervention companies who enrolled in the programme compared to control companies with no major protocol violation also found no significant difference (2.93 vs 2.64, mean difference 0.29, 95% CI -0.13 to 0.72, p-value 0.18). We found no significant differences between the intervention and control groups in any secondary outcome, except in total sugar (g/100g) where the sugar content of intervention company products was higher than that of control companies (12.32 vs 6.98, mean difference 5.34, 95% CI 1.73 to 8.96, p-value 0.004). The per-protocol analysis for sugar did not show a significant difference (10.47 vs 7.44, mean difference 3.03, 95% CI -0.48 to 6.53, p-value 0.09).In conclusion, a 12-month tailored nutrition support for food companies did not improve the nutrient profile of company products.

Depth-averaged systems of equations describing the motion of fluid–sediment mixtures have been widely adopted by scientists in pursuit of models that can predict the paths of dangerous overland flows of debris. As models have become increasingly sophisticated, many have been developed from a multi-phase perspective in which separate, but mutually coupled sets of equations govern the evolution of different components of the mixture. However, this creates the opportunity for the existence of pathological instabilities stemming from resonant interactions between the phases. With reference to the most popular approaches, analyses of two- and three-phase models are performed, which demonstrate that they are more often than not ill posed as initial-value problems over physically relevant parameter regimes – an issue which renders them unsuitable for scientific applications. Additionally, a general framework for detecting ill posedness in models with any number of phases is developed. This is used to show that small diffusive terms in the equations for momentum transport, which are sometimes neglected, can reliably eliminate this issue. Conditions are derived for the regularisation of models in this way, but they are typically not met by multi-phase models that feature diffusive terms.