Objective: To devise a measure of diet quality from a short-form FFQ (SFFFQ) for population surveys. To validate the SFFFQ against an extensive FFQ and a 24 h diet recall.Design: Population-based cross-sectional survey.Setting: East Leeds and Bolton in Northern England.Subjects: Adults (n1999) were randomly selected from lists of those registered with a general practitioner in the study areas, contacted by mail and asked to complete the SFFFQ. Responders were sent a longer FFQ to complete and asked if they would take part in a telephone-based 24 h diet recall.Results: Results from 826 people completing the SFFFQ, 705 completing the FFQ and forty-seven completing the diet recall were included in the analyses. The dietary quality score (DQS), based on fruit, vegetable, oily fish, non-milk extrinsic sugar and fat intakes, showed significant agreement between the SFFFQ and the FFQ (κ=0·38,P<0·001). The DQS for the SFFFQ and the diet recall did not show significant agreement (κ=0·04,P=0·312). A number of single items on the SFFFQ predicted a ‘healthy’ DQS when calculated from the FFQ. The odds of having a healthy diet were increased by 27 % (95 % CI 9, 49 %,P<0·001) for an increase in fruit of 1 portion/d and decreased by 67 % (95 % CI 47, 79 %,P<0·001) for an increase in crisps of 1 portion/d.Conclusions: The SFFFQ has been shown to be an effective method of assessing diet quality. It provides an important method for determining variations in diet quality within and across different populations.

Background: High blood pressure is a strong risk factor for cardiovascular disease.

Background: Obesity is an important risk factor for many chronic diseases. Mobile health interventions such as smartphone apps can potentially provide a convenient low-cost addition to other obesity reduction strategies. Objective: This study aimed to estimate the impacts on quality-adjusted life-years (QALYs) gained and health system costs over the remainder of the life span of the New Zealand population (N=4.4 million) for a smartphone app promotion intervention in 1 calendar year (2011) using currently available apps for weight loss. Methods: The intervention was a national mass media promotion of selected smartphone apps for weight loss compared with no dedicated promotion. A multistate life table model including 14 body mass index–related diseases was used to estimate QALYs gained and health systems costs. A lifetime horizon, 3% discount rate, and health system perspective were used. The proportion of the target population receiving the intervention (1.36%) was calculated using the best evidence for the proportion who have access to smartphones, are likely to see the mass media campaign promoting the app, are likely to download a weight loss app, and are likely to continue using this app. Results: In the base-case model, the smartphone app promotion intervention generated 29 QALYs (95% uncertainty interval, UI: 14-52) and cost the health system US $1.6 million (95% UI: 1.1-2.0 million) with the standard download rate. Under plausible assumptions, QALYs increased to 59 (95% UI: 27-107) and costs decreased to US $1.2 million (95% UI: 0.5-1.8) when standard download rates were doubled. Costs per QALY gained were US $53,600 for the standard download rate and US $20,100 when download rates were doubled. On the basis of a threshold of US $30,000 per QALY, this intervention was cost-effective for Māori when the standard download rates were increased by 50% and also for the total population when download rates were doubled. Conclusions: In this modeling study, the mass media promotion of a smartphone app for weight loss produced relatively small health gains on a population level and was of borderline cost-effectiveness for the total population. Nevertheless, the scope for this type of intervention may expand with increasing smartphone use, more easy-to-use and effective apps becoming available, and with recommendations to use such apps being integrated into dietary counseling by health workers.

Dietary salt reduction is included in the top five priority actions for non-communicable disease control internationally. We therefore aimed to identify health gain and cost impacts of achieving a national target for sodium reduction, along with component targets in different food groups. We used an established dietary sodium intervention model to study 10 interventions to achieve sodium reduction targets. The 2011 New Zealand (NZ) adult population (2.3 million aged 35+ years) was simulated over the remainder of their lifetime in a Markov model with a 3 % discount rate. Achieving an overall 35 % reduction in dietary salt intake via implementation of mandatory maximum levels of sodium in packaged foods along with reduced sodium from fast foods/restaurant food and discretionary intake (the “full target”), was estimated to gain 235,000 QALYs over the lifetime of the cohort (95 % uncertainty interval [UI]: 176,000 to 298,000). For specific target components the range was from 122,000 QALYs gained (for the packaged foods target) down to the snack foods target (6100 QALYs; and representing a 34–48 % sodium reduction in such products). All ten target interventions studied were cost-saving, with the greatest costs saved for the mandatory “full target” at NZ$1260 million (US$820 million). There were relatively greater health gains per adult for men and for Māori (indigenous population). This work provides modeling-level evidence that achieving dietary sodium reduction targets (including specific food category targets) could generate large health gains and cost savings for a national health sector. Demographic groups with the highest cardiovascular disease rates stand to gain most, assisting in reducing health inequalities between sex and ethnic groups.

What we eat is fundamental to human and planetary health, with the current global dietary transition towards increased red meat intakes and ultra-processed foods likely detrimental. We modelled five red and processed meat replacement scenarios to consider health, equity, greenhouse gas emissions (GHGe), and cost outcomes using an established multistate life table model using data from New Zealand as a case study of a developed, westernised country. Current red and processed meat intakes were replaced with: minimally or ultra-processed plant based meat alternatives, cellular meat, or diets in line with EAT-Lancet or Heart Foundation recommendations on red meat intake. We then conducted a systematic review of literature from database inception to 14 November 2022 to identify implemented population-level meat replacement strategies which could inform evidence-based recommendations to achieve any benefits observed in modelling. PROSPERO CRD42020200023. When compared with current red and processed meat intakes, all red and processed meat replacement scenarios were nutritionally adequate and improved overall Quality Adjusted Life Years (159–297 per 1000 people over life course for the five scenarios modelled). Age standardised per capita health gain for Māori was 1.6–2.3 times that of non-Māori. Health system cost savings were $2530–$5096 per adult, and GHGe reduced 19–35%. Finally, grocery cost varied (↓7%–↑2%) per modelled scenario when compared with baseline costs. The greatest benefits for all outcomes were achieved by meat replacement with minimally-processed plant-based foods, such as legumes. The systematic review identified only two implemented population-level strategies to reduce meat intakes within the academic literature. All meat replacement scenarios considered indicated appreciable health gains and GHGe reductions. Replacement with minimally-processed plant-based foods appeared consistently superior than other scenarios. Evidence of real-world population strategies to achieve these benefits however is currently lacking. Healthier Lives National Science Challenge (Grant UOOX1902).

Smartphones are increasingly available and some high quality apps are available for smoking cessation. However, the cost-effectiveness of promoting such apps has never been studied. We therefore aimed to estimate the health gain, inequality impacts and cost-utility from a five-year promotion campaign of a smoking cessation smartphone app compared to business-as-usual (no app use for quitting). A well-established Markov macro-simulation model utilising a multi-state life-table was adapted to the intervention (lifetime horizon, 3% discount rate). The setting was the New Zealand (NZ) population (N = 4.4 million). The intervention effect size was from a multi-country randomised trial: relative risk for quitting at 6 months = 2.23 (95%CI: 1.08 to 4.77), albeit subsequently adjusted to consider long-term relapse. Intervention costs were based on NZ mass media promotion data and the NZ cost of attracting a smoker to smoking cessation services (NZ$64 per person). The five-year intervention was estimated to generate 6760 QALYs (95%UI: 5420 to 8420) over the remaining lifetime of the population. For Māori (Indigenous population) there was 2.8 times the per capita age-standardised QALY gain relative to non-Māori. The intervention was also estimated to be cost-saving to the health system (saving NZ$115 million [m], 95%UI: 72.5m to 171m; US$81.8m). The cost-saving aspect of the intervention was maintained in scenario and sensitivity analyses where the discount rate was doubled to 6%, the effect size halved, and the intervention run for just 1 year. This study provides modelling-level evidence that mass-media promotion of a smartphone app for smoking cessation could generate health gain, reduce ethnic inequalities in health and save health system costs. Nevertheless, there are other tobacco control measures which generate considerably larger health gains and cost-savings such as raising tobacco taxes.