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Abstract Historically, the NHS did not routinely collect cost data, unlike many countries with private insurance markets. In 1998, for the first time the government mandated NHS trusts to submit estimates of their costs of service, known as reference costs. These have informed a wide range of health economic evaluations and important functions in the health service, such as setting prices. Reference costs are collected by progressively disaggregating budgets top-down into disease and treatment groups. Despite ongoing improvements to methods and guidance, these submissions continued to suffer a lack of accuracy and comparability, fundamentally undermining their credibility for critical functions. To overcome these issues, there was a long-held ambition to collect “patient-level” cost data. Patient-level costs are estimated with a combination of disaggregating budgets but also capturing the patient-level “causality of costs” bottom-up in the allocation of resources to patient episodes. These not only aim to capture more of the drivers of costs, but also improve consistency of reporting between providers. The change in methods may confer improvements to data quality, though judgement is still required and achieving consistency between trusts will take further work. Estimated costs may also change in important ways that may take many years to fully understand. We end on a cautionary note that patient-level cost methods may unlock potential, they alone contribute little to our understanding of the complexities involved with service quality or need, while that potential will require substantial investment to realise. Many healthcare resources cannot be attributed to individual patients so the very notion of “patient-level” costs may be misplaced. High hopes have been put in these new data, though much more work is now necessary to understand their quality, what they show and how their use will impact the system.

BackgroundThe soft drinks industry levy (SDIL) in the United Kingdom has led to a significant reduction in household purchasing of sugar in drinks. In this study, we examined the potential medium- and long-term implications for health and health inequalities among children and adolescents in England.Methods and findingsWe conducted a controlled interrupted time series analysis to measure the effects of the SDIL on the amount of sugar per household per week from soft drinks purchased, 19 months post implementation and by index of multiple deprivation (IMD) quintile in England. We modelled the effect of observed sugar reduction on body mass index (BMI), dental caries, and quality-adjusted life years (QALYs) in children and adolescents (0 to 17 years) by IMD quintile over the first 10 years following announcement (March 2016) and implementation (April 2018) of the SDIL. Using a lifetable model, we simulated the potential long-term impact of these changes on life expectancy for the current birth cohort and, using regression models with results from the IMD-specific lifetable models, we calculated the impact of the SDIL on the slope index of inequality (SII) in life expectancy. The SDIL was found to have reduced sugar from purchased drinks in England by 15 g/household/week (95% confidence interval: -10.3 to -19.7). The model predicts these reductions in sugar will lead to 3,600 (95% uncertainty interval: 946 to 6,330) fewer dental caries and 64,100 (54,400 to 73,400) fewer children and adolescents classified as overweight or obese, in the first 10 years after implementation. The changes in sugar purchasing and predicted impacts on health are largest for children and adolescents in the most deprived areas (Q1: 11,000 QALYs [8,370 to 14,100] and Q2: 7,760 QALYs [5,730 to 9,970]), while children and adolescents in less deprived areas will likely experience much smaller simulated effects (Q3: -1,830 QALYs [-3,260 to -501], Q4: 652 QALYs [-336 to 1,680], Q5: 1,860 QALYs [929 to 2,890]). If the simulated effects of the SDIL are sustained over the life course, it is predicted there will be a small but significant reduction in slope index of inequality: 0.76% (95% uncertainty interval: -0.9 to -0.62) for females and 0.94% (-1.1 to -0.76) for males.ConclusionsWe predict that the SDIL will lead to medium-term reductions in dental caries and overweight/obesity, and long-term improvements in life expectancy, with the greatest benefits projected for children and adolescents from more deprived areas. This study provides evidence that the SDIL could narrow health inequalities for children and adolescents in England.

Objective To determine changes in household purchases of drinks 1 year after implementation of the UK soft drinks industry levy (SDIL).Design Controlled interrupted time series.Participants Households reporting their purchasing to a market research company (average weekly n=22 091), March 2014 to March 2019.Intervention A two-tiered tax levied on soft drinks manufacturers, announced in March 2016 and implemented in April 2018. Drinks with ≥8 g sugar/100 mL (high tier) are taxed at £0.24/L, drinks with ≥5 to

BackgroundTaxes on sugar-sweetened beverages (SSBs) have been implemented globally to reduce the burden of cardiometabolic diseases by disincentivizing consumption through increased prices (e.g., 1 peso/litre tax in Mexico) or incentivizing industry reformulation to reduce SSB sugar content (e.g., tiered structure of the United Kingdom [UK] Soft Drinks Industry Levy [SDIL]). In Germany, where no tax on SSBs is enacted, the health and economic impact of SSB taxation using the experience from internationally implemented tax designs has not been evaluated. The objective of this study was to estimate the health and economic impact of national SSBs taxation scenarios in Germany.Methods and findingsIn this modelling study, we evaluated a 20% ad valorem SSB tax with/without taxation of fruit juice (based on implemented SSB taxes and recommendations) and a tiered tax (based on the UK SDIL) in the German adult population aged 30 to 90 years from 2023 to 2043. We developed a microsimulation model (IMPACTNCD Germany) that captures the demographics, risk factor profile and epidemiology of type 2 diabetes, coronary heart disease (CHD) and stroke in the German population using the best available evidence and national data. For each scenario, we estimated changes in sugar consumption and associated weight change. Resulting cases of cardiometabolic disease prevented/postponed and related quality-adjusted life years (QALYs) and economic impacts from healthcare (medical costs) and societal (medical, patient time, and productivity costs) perspectives were estimated using national cost and health utility data. Additionally, we assessed structural uncertainty regarding direct, body mass index (BMI)-independent cardiometabolic effects of SSBs and cross-validated results with an independently developed cohort model (PRIMEtime). We found that SSB taxation could reduce sugar intake in the German adult population by 1 g/day (95%-uncertainty interval [0.05, 1.65]) for a 20% ad valorem tax on SSBs leading to reduced consumption through increased prices (pass-through of 82%) and 2.34 g/day (95%-UI [2.32, 2.36]) for a tiered tax on SSBs leading to 30% reduction in SSB sugar content via reformulation. Through reductions in obesity, type 2 diabetes, and cardiovascular disease (CVD), 106,000 (95%-UI [57,200, 153,200]) QALYs could be gained with a 20% ad valorem tax and 192,300 (95%-UI [130,100, 254,200]) QALYs with a tiered tax. Respectively, €9.6 billion (95%-UI [4.7, 15.3]) and €16.0 billion (95%-UI [8.1, 25.5]) costs could be saved from a societal perspective over 20 years. Impacts of the 20% ad valorem tax were larger when additionally taxing fruit juice (252,400 QALYs gained, 95%-UI [176,700, 325,800]; €11.8 billion costs saved, 95%-UI [€6.7, €17.9]), but impacts of all scenarios were reduced when excluding direct health effects of SSBs. Cross-validation with PRIMEtime showed similar results. Limitations include remaining uncertainties in the economic and epidemiological evidence and a lack of product-level data.ConclusionsIn this study, we found that SSB taxation in Germany could help to reduce the national burden of noncommunicable diseases and save a substantial amount of societal costs. A tiered tax designed to incentivize reformulation of SSBs towards less sugar might have a larger population-level health and economic impact than an ad valorem tax that incentivizes consumer behaviour change only through increased prices.

Abstract Background Low childhood physical activity levels constitute an important modifiable risk for adult non-communicable disease incidence and subsequent socio-economic burden, but few publications have explored age and sex related patterns within the UK population. The aims were to profile child physical activity data from the Health Survey for England from 2012 (1,732 respondents) and 2015 (5,346 respondents). Methods Reported physical activity episodes were converted to metabolic equivalents with reference to child-specific compendiums. Physical activity levels were aggregated for each domain, and again to produce total physical activity estimates. Contributions from each domain to total physical activity were explored, stratifying for age, sex, socio-economic deprivation, ethnicity, and weight status. Further analyses were run stratifying for physical activity levels. Few differences were detected between the survey iterations. Results Boys reported higher absolute levels of physical activity at all ages and across all domains. For boys and girls, informal activity reduces with age. For boys this reduction is largely mitigated by increased formal sport, but this is not the case for girls. Absolute levels of school activity and active travel remained consistent regardless of total physical activity, thereby comprising an increasingly important proportion of total physical activity for less active children. Conclusions We recommend a specific focus on establishing and maintaining girl’s participation in formal sport thorough their teenage years, and a recognition and consolidation of the important role played by active travel and school-based physical activity for the least active children.

[This corrects the article DOI: 10.1371/journal.pmed.1003269.].

Abstract Background As the World Health Organization urges countries to strengthen their noncommunicable disease monitoring and surveillance activities, setting-specific innovations are emerging. Diet – a key, modifiable risk factor for chronic diseases – is particularly challenging to capture reliably. By socially validating self-report dietary survey tools, we may be able to increase the accuracy and representativeness of data for improved population health outcomes. The purpose of this study was to explore the factors that impact Sri Lankan Brief Dietary Survey (a newly developed tool) and 24-h Dietary Recall participation, engagement, and social validity among Sri Lankan adults. Methods We conducted semi-structured interviews with 93 participants (61 women and 32 men) in three Sri Lankan districts (Colombo, Kalutara, and Trincomalee). Interview data were analysed thematically and are presented as non-hierarchical thematic networks. Results Participants identified a number of factors that influenced their survey participation and engagement. These included the time of day interviews occur, recall ease, level of commitment required, perceived survey value, emotional response to surveys, and interviewer positionality. Many of these factors were gendered, however, both female and male participants expressed a preference for engaging with socially valid research that they felt justified their personal investment in data collection. When explicitly asked to share ideas about how to improve the surveys, many participants opted not to provide suggestions as they felt they lacked the appropriate expertise. Conclusions Our findings have implications for the accuracy and equity of dietary surveillance activities, and ultimately the appropriateness and effectiveness of programmes and policies informed by these data. Only through understanding how and why the target population engages with dietary research can we develop socially valid methods that assess and address the dietary risks of individuals and groups that are underrepresented by current conventions.

BackgroundExcess consumption of salt is linked to an increased risk of hypertension and cardiovascular disease. The United Kingdom has had a comprehensive salt reduction programme since 2003, setting a series of progressively lower, product-specific reformulation targets for the food industry, combined with advice to consumers to reduce salt. The aim of this study was to assess the changes in the sales-weighted mean salt content of grocery foods sold through retail between 2015 and 2020 by category and company.Methods and findingsInformation for products, including salt content (g/100 g), was collected online from retailer websites for 6 consecutive years (2015 to 2020) and was matched with brand-level retail sales data from Euromonitor for 395 brands. The sales-weighted mean salt content and total volume of salt sold were calculated by category and company. The mean salt content of included foods fell by 0.05 g/100 g, from 1.04 g/100 g in 2015 to 0.90 g/100 g in 2020, equivalent to -4.2% (p = 0.13). The categories with the highest salt content in 2020 were savoury snacks (1.6 g/100 g) and cheese (1.6 g/100 g), and the categories that saw the greatest reductions in mean salt content over time were breakfast cereals (-16.0%, p = 0.65); processed beans, potatoes, and vegetables (-10.6%, p = 0.11); and meat, seafood, and alternatives (-9.2%, p = 0.56). The total volume of salt sold fell from 2.41 g per person per day to 2.25 g per person per day, a reduction of 0.16 g or 6.7% (p = 0.54). The majority (63%) of this decrease was attributable to changes in mean salt content, with the remaining 37% accounted for by reductions in sales. Across the top 5 companies in each of 9 categories, the volume of salt sold decreased in 26 and increased in 19 cases. This study is limited by its exclusion of foods purchased out of the home, including at restaurants, cafes, and takeaways. It also does not include salt added at the table, or that naturally occurring in foods, meaning the findings underrepresent the population's total salt intake. The assumption was also made that the products matched with the sales data were entirely representative of the brand, which may not be the case if products are sold exclusively in convenience stores or markets, which are not included in this database.ConclusionsThere has been a small decline in the salt content of foods and total volume of salt sold between 2015 and 2020, but observed changes were not statistically significant so could be due to random variations over time. We suggest that mandatory reporting of salt sales by large food companies would increase the transparency of how individual businesses are progressing towards the salt reduction targets.

BackgroundModels that forecast non-communicable disease rates are poorly designed to predict future changes in trend because they are based on exogenous measures of disease rates. We introduce microPRIME, which forecasts myocardial infarction (MI) incidence, events and prevalence in England to 2035. microPRIME can forecast changes in trend as all MI rates emerge from competing trends in risk factors and treatment.Materials and methodsmicroPRIME is a microsimulation of MI events within a sample of 114,000 agents representative of England. We simulate 37 annual time points from 1998 to 2035, where agents can have an MI event, die from an MI, or die from an unrelated cause. The probability of each event is a function of age, sex, BMI, blood pressure, cholesterol, smoking, diabetes and previous MI. This function does not change over time. Instead population-level changes in MI rates are due to competing trends in risk factors and treatment. Uncertainty estimates are based on 450 model runs that use parameters calibrated against external measures of MI rates between 1999 and 2011.FindingsForecasted MI incidence rates fall for men and women of different age groups before plateauing in the mid 2020s. Age-standardised event rates show a similar pattern, with a non-significant upturn by 2035, larger for men than women. Prevalence in men decreases for the oldest age groups, with peaks of prevalence rates in 2019 for 85 and older at 25.8% (23.3-28.3). For women, prevalence rates are more stable. Prevalence in over 85s is estimated as 14.5% (12.6-16.5) in 2019, and then plateaus thereafter.ConclusionWe may see an increase in event rates from MI in England for men before 2035 but increases for women are unlikely. Prevalence rates may fall in older men, and are likely to remain stable in women over the next decade and a half.

Abstract Background Non-communicable diseases are the leading cause of death in England, and poor diet and physical inactivity are two of the principle behavioural risk factors. In the context of increasingly constrained financial resources, decision makers in England need to be able to compare the potential costs and health outcomes of different public health policies aimed at improving these risk factors in order to know where to invest so that they can maximise population health. This paper describes PRIMEtime CE, a multistate life table cost-effectiveness model that can directly compare interventions affecting multiple disease outcomes. Methods The multistate life table model, PRIMEtime Cost Effectiveness (PRIMEtime CE), is developed from the Preventable Risk Integrated ModEl (PRIME) and the PRIMEtime model. PRIMEtime CE uses routinely available data to estimate how changing diet and physical activity in England affects morbidity and mortality from heart disease, stroke, diabetes, liver disease, and cancers either directly or via raised blood pressure, cholesterol, and body weight. Results Model outcomes are change in quality adjusted life years, and change in English National Health Service and social care costs. Conclusion This paper describes PRIMEtime CE and highlights its main strengths and limitations. The model can be used to compare any number of public policies affecting diet and physical activity, allowing decision makers to understand how they can maximise population health with limited financial resources.

Abstract Background PRIMEtime CE is a multistate life table model that can directly compare the cost effectiveness of public health interventions affecting diet and physical activity levels, helping to inform decisions about how to spend finite resources. This paper estimates the costs and health outcomes in England of two scenarios: reformulating salt and expanding subsidised access to leisure centres. The results are used to help validate PRIMEtime CE, following the steps outlined in the Assessment of the Validation Status of Health-Economic decision models (AdViSHE) tool. Methods The PRIMEtime CE model estimates the difference in quality adjusted life years (QALYs) and difference in NHS and social care costs of modelled interventions compared with doing nothing. The salt reformulation scenario models how salt consumption would change if food producers met the 2017 UK Food Standards Agency salt reformulation targets. The leisure centre scenario models change in physical activity levels if the Birmingham Be Active scheme (where swimming pools and gym access is free to residents during defined periods) was rolled out across England. The AdViSHE tool was developed by health economic modellers and divides model validation into five parts: validation of the conceptual model, input data validation, validation of computerised model, operational validation, and other validation techniques. PRIMEtime CE is discussed in relation to each part. Results Salt reformulation was dominant compared with doing nothing, and had a 10-year return on investment of £1.44 (£0.50 to £2.94) for every £1 spent. By contrast, over 10 years the Be Active expansion would cost £727,000 (£514,000 to £1,064,000) per QALY. PRIMEtime CE has good face validity of its conceptual model and has robust input data. Cross-validation produces mixed results and shows the impact of model scope, input parameters, and model structure on cost-per-QALY estimates. Conclusions This paper illustrates how PRIMEtime CE can be used to compare the cost-effectiveness of two different public health measures affecting diet and physical activity levels. The AdViSHE tool helps to validate PRIMEtime CE, identifies some of the key drivers of model estimates, and highlights the challenges of externally validating public health economic models against independent data.

Abstract Background Health-related claims (HRCs) are statements found on food packets that convey the nutritional quality of a food (nutrition claims) and/or its impact on a health outcome (health claims). The EU stated that HRCs should be regulated such that they can only appear on foods that meet a specified nutrient profile (NP). A NP model has been proposed, but not agreed by the European Commission. Methods To model the impact of HRCs on health impacts in the UK, we built a front-end model to a pre-established non-communicable-disease (NCD) scenario model, the Preventable Risk Integrated ModEl (PRIME) by combining data from a meta-analysis examining the impact of HRCs on dietary choices and a survey of pre-packaged foods examining the prevalence of HRCs and the nutritional quality of foods that carry them. These data are used to model the impact of regulating HRCs on the nutritional quality of the diet and PRIME is used to model the health outcomes associated with these changes. Two scenarios are modelled: regulating HRCs with a NP model (the FSANZ NPSC and a draft EU model) so that only foods that pass the model are eligible to carry HRCs, and reformulating HRC-carrying foods that fail the model. Results Regulating the use of HRCs with a NP model (the FSANZ NPSC) would have unclear impacts on population health and could potentially lead to less healthy diets. This is because HRCs are currently more likely to be found on products with a better nutritional profile and restricting their use could shift consumers to less healthy diets. Two hundred fifty-eight additional deaths (95% Uncertainty Intervals [UI] -6509, 8706) were predicted if foods did not change in their nutrient composition. If all foods that currently carry HRCs were reformulated to meet the NP model criteria then there would be a positive impact of using the model: (4374 deaths averted (95%UI -2569, 14,009)). The largest contributor to the uncertainty is the underpowered estimates of nutritional quality of foods with and without claims. Conclusions Regulating HRCs could result in negative health impacts, however the wide uncertainty intervals from this analysis demonstrate that a larger health impact assessment is necessary.

BackgroundReducing meat consumption could bring health and environmental benefits, but there is little research to date on effective interventions to achieve this. A non-randomised controlled intervention study was used to evaluate whether prominent positioning of meat-free products in the meat aisle was associated with a change in weekly mean sales of meat and meat-free products.Methods and findingsWeekly sales data were obtained from 108 stores: 20 intervention stores that moved a selection of 26 meat-free products into a newly created meat-free bay within the meat aisle and 88 matched control stores. The primary outcome analysis used a hierarchical negative binomial model to compare changes in weekly sales (units) of meat products sold in intervention versus control stores during the main intervention period (Phase I: February 2019 to April 2019). Interrupted time series analysis was also used to evaluate the effects of the Phase I intervention. Moreover, 8 of the 20 stores enhanced the intervention from August 2019 onwards (Phase II intervention) by adding a second bay of meat-free products into the meat aisle, which was evaluated following the same analytical methods. During the Phase I intervention, sales of meat products (units/store/week) decreased in intervention (approximately -6%) and control stores (-5%) without significant differences (incidence rate ratio [IRR] 1.01 [95% CI 0.95-1.07]. Sales of meat-free products increased significantly more in the intervention (+31%) compared to the control stores (+6%; IRR 1.43 [95% CI 1.30-1.57]), mostly due to increased sales of meat-free burgers, mince, and sausages. Consistent results were observed in interrupted time series analyses where the effect of the Phase II intervention was significant in intervention versus control stores.ConclusionsProminent positioning of meat-free products into the meat aisle in a supermarket was not effective in reducing sales of meat products, but successfully increased sales of meat-free alternatives in the longer term. A preregistered protocol (https://osf.io/qmz3a/) was completed and fully available before data analysis.

BackgroundConsumption of free sugars in the UK greatly exceeds dietary recommendations. Public Health England (PHE) has set voluntary targets for industry to reduce the sales-weighted mean sugar content of key food categories contributing to sugar intake by 5% by 2018 and 20% by 2020. The aim of this study was to assess changes in the sales-weighted mean sugar content and total volume sales of sugar in selected food categories among UK companies between 2015 and 2018.Methods and findingsWe used sales data from Euromonitor, which estimates total annual retail sales of packaged foods, for 5 categories-biscuits and cereal bars, breakfast cereals, chocolate confectionery, sugar confectionery, and yoghurts-for 4 consecutive years (2015-2018). This analysis includes 353 brands (groups of products with the same name) sold by 99 different companies. These data were linked with nutrient composition data collected online from supermarket websites over 2015-2018 by Edge by Ascential. The main outcome measures were sales volume, sales-weighted mean sugar content, and total volume of sugar sold by category and company. Our results show that between 2015 and 2018 the sales-weighted mean sugar content of all included foods fell by 5.2% (95% CI -9.4%, -1.4%), from 28.7 g/100 g (95% CI 27.2, 30.4) to 27.2 g/100 g (95% CI 25.8, 28.4). The greatest change seen was in yoghurts (-17.0% [95% CI -26.8%, -7.1%]) and breakfast cereals (-13.3% [95% CI -19.2%, -7.4%]), with only small reductions in sugar confectionery (-2.4% [95% CI -4.2%, -0.6%]) and chocolate confectionery (-1.0% [95% CI -3.1, 1.2]). Our results show that total volume of sugars sold per capita fell from 21.4 g/d (95% CI 20.3, 22.7) to 19.7 g/d (95% CI 18.8, 20.7), a reduction of 7.5% (95% CI -13.1%, -2.8%). Of the 50 companies representing the top 10 companies in each category, 24 met the 5% reduction target set by PHE for 2018. The key limitations of this study are that it does not encompass the whole food market and is limited by its use of brand-level sales data, rather than individual product sales data.ConclusionsOur findings show there has been a small reduction in total volume sales of sugar in the included categories, primarily due to reductions in the sugar content of yoghurts and breakfast cereals. Additional policy measures may be needed to accelerate progress in categories such as sugar confectionery and chocolate confectionery if the 2020 PHE voluntary sugar reduction targets are to be met.

Background The provision and over-consumption of foods high in energy, saturated fat, free sugars or salt are important risk factors for poor diet and ill-health. In the UK, policies seek to drive improvement through voluntary reformulation of single nutrients in key food groups. There has been little consideration of the overall progress by individual companies. This study assesses recent changes in the nutrient profile of brands and products sold by the top 10 food and beverage companies in the UK. Methods The FSA/Ofcom nutrient profile model was applied to the nutrient composition data for all products manufactured by the top 10 food and beverage companies and weighted by volume sales. The mean nutrient profiling score, on a scale of 1–100 with thresholds for healthy products being 62 for foods and 68 for drinks, was used to rank companies and food categories between 2015 and 2018, and to calculate the proportion of individual products and sales that are considered by the UK Government to be healthy. Results Between 2015 and 2018 there was little change in the sales-weighted nutrient profiling score of the top 10 companies (49 to 51; p = 0.28) or the proportion of products classified as healthy (46% to 48%; p = 0.23). Of the top five brands sold by each of the ten companies, only six brands among ten companies improved their nutrient profiling score by 20% or more. The proportion of total volume sales classified as healthy increased from 44% to 51% (p = 0.07) driven by an increase in the volume sales of bottled water, low/no calorie carbonates and juices, but after removing soft drinks, the proportion of foods classified as healthy decreased from 7% to 6% (p = 33). Conclusions The UK voluntary reformulation policies, setting targets for reductions in calories, sugar and salt, do not appear to have led to significant changes in the nutritional quality of foods, though there has been progress in soft drinks where the soft drink industry levy also applies. Further policy action is needed to incentivise companies to make more substantive changes in product composition to support consumers to achieve a healthier diet.

BackgroundObesity is a leading risk for poor health outcomes in England. We examined best- and worst-case scenarios for the future trajectory of the obesity epidemic.MethodsTaking the last 27 years of Health Survey for England data, we determined both position and shape of the adult body mass index (BMI) distribution and projected these parameters 20 years forward in time. For the best-case scenario, we fitted linear models, allowing for a quadratic relationship between the outcome variable and time, to reflect a potential reversal in upwards trends. For the worst-case scenario, we fitted non-linear models that applied an exponential function to reflect a potential flattening of trends over time. Best-fitting models were identified using Monte Carlo cross-validation on 1991-2014 data, and predictions of population prevalence across five BMI categories were then validated using 2015-17 data.ResultsBoth linear and non-linear models showed a close fit to observed data (mean absolute error ConclusionsWhile obesity prediction depends on chosen modelling methods, even under optimistic assumptions it is likely that the majority of the English population will still be at increased risk of disease due to their weight until at least 2035, without greater allocation of resources to effective interventions.

BackgroundSugar-sweetened beverage (SSB) consumption is positively associated with obesity, type 2 diabetes, and cardiovascular disease. The World Health Organization recommends that member states implement effective taxes on SSBs to reduce consumption. The United Kingdom Soft Drinks Industry Levy (SDIL) is a two-tiered tax, announced in March 2016 and implemented in April 2018. Drinks with ≥8 g of sugar per 100 ml (higher levy tier) are taxed at £0.24 per litre, drinks with ≥5 to 1.2% alcohol by volume are exempt. We aimed to determine if the announcement of the SDIL was associated with anticipatory changes in purchases of soft drinks prior to implementation of the SDIL in April 2018. We explored differences in the volume of and amount of sugar in household purchases of drinks in each levy tier at 2 years post announcement.Methods and findingsWe used controlled interrupted time series to compare observed changes associated with the announcement of the SDIL to the counterfactual scenario of no announcement. We used data from Kantar Worldpanel, a commercial household purchasing panel with approximately 30,000 British members that includes linked nutritional data on purchases. We conducted separate analyses for drinks liable for the SDIL in the higher, lower, and no-levy tiers controlling with household purchase volumes of toiletries. At 2 years post announcement, there was no difference in volume of or sugar from purchases of higher-levy-tier drinks compared to the counterfactual of no announcement. In contrast, a reversal of the existing upward trend in volume (ml) of and amount of sugar (g) in purchases of lower-levy-tier drinks was seen. These changes led to a -96.1 ml (95% confidence interval [CI] -144.2 to -48.0) reduction in volume and -6.4 g (95% CI -9.8 to -3.1) reduction in sugar purchased in these drinks per household per week. There was a reversal of the existing downward trend in the amount of sugar in household purchases of the no-levy drinks but no change in volume purchased. At 2 years post announcement, these changes led to a 6.1 g (95% CI 3.9-8.2) increase in sugar purchased in these drinks per household per week. There was no evidence that volume of or amount of sugar in purchases of all drinks combined was different from the counterfactual. This is an observational study, and changes other than the SDIL may have been responsible for the results reported. Purchases consumed outside of the home were not accounted for.ConclusionsThe announcement of the UK SDIL was associated with reductions in volume and sugar purchased in lower-levy-tier drinks before implementation. These were offset by increases in sugar purchased from no-levy drinks. These findings may reflect reformulation of drinks from the lower levy to no-levy tier with removal of some but not all sugar, alongside changes in consumer attitudes and beliefs.Trial registrationISRCTN Registry ISRCTN18042742.

BackgroundDietary sugar, especially in liquid form, increases risk of dental caries, adiposity, and type 2 diabetes. The United Kingdom Soft Drinks Industry Levy (SDIL) was announced in March 2016 and implemented in April 2018 and charges manufacturers and importers at £0.24 per litre for drinks with over 8 g sugar per 100 mL (high levy category), £0.18 per litre for drinks with 5 to 8 g sugar per 100 mL (low levy category), and no charge for drinks with less than 5 g sugar per 100 mL (no levy category). Fruit juices and milk-based drinks are exempt. We measured the impact of the SDIL on price, product size, number of soft drinks on the marketplace, and the proportion of drinks over the lower levy threshold of 5 g sugar per 100 mL.Methods and findingsWe analysed data on a total of 209,637 observations of soft drinks over 85 time points between September 2015 and February 2019, collected from the websites of the leading supermarkets in the UK. The data set was structured as a repeat cross-sectional study. We used controlled interrupted time series to assess the impact of the SDIL on changes in level and slope for the 4 outcome variables. Equivalent models were run for potentially levy-eligible drink categories ('intervention' drinks) and levy-exempt fruit juices and milk-based drinks ('control' drinks). Observed results were compared with counterfactual scenarios based on extrapolation of pre-SDIL trends. We found that in February 2019, the proportion of intervention drinks over the lower levy sugar threshold had fallen by 33.8 percentage points (95% CI: 33.3-34.4, p < 0.001). The price of intervention drinks in the high levy category had risen by £0.075 (£0.037-0.115, p < 0.001) per litre-a 31% pass through rate-whilst prices of intervention drinks in the low levy category and no levy category had fallen and risen by smaller amounts, respectively. Whilst the product size of branded high levy and low levy drinks barely changed after implementation of the SDIL (-7 mL [-23 to 11 mL] and 16 mL [6-27ml], respectively), there were large changes to product size of own-brand drinks with an increase of 172 mL (133-214 mL) for high levy drinks and a decrease of 141 mL (111-170 mL) for low levy drinks. The number of available drinks that were in the high levy category when the SDIL was announced was reduced by 3 (-6 to 12) by the implementation of the SDIL. Equivalent models for control drinks provided little evidence of impact of the SDIL. These results are not sales weighted, so do not give an account of how sugar consumption from drinks may have changed over the time period.ConclusionsThe results suggest that the SDIL incentivised many manufacturers to reduce sugar in soft drinks. Some of the cost of the levy to manufacturers and importers was passed on to consumers as higher prices but not always on targeted drinks. These changes could reduce population exposure to liquid sugars and associated health risks.

Abstract Objective: To estimate the impact of integrating the price of greenhouse gas emissions into the price of food commodities on dietary and weight‐related risk factors and associated disease burden in Australia, as well as on national emissions reductions and public revenues. Methods: We used country‐specific data for Australia to build a coupled modelling framework that includes economic, environmental and health analyses. Data sources included the 2011‐12 Australian food and nutrition survey, meta‐analysis of food‐related lifecycle emissions, and price and income elasticities. Consumption‐related changes in disease burden were calculated using a comparative risk assessment framework with 11 disease states and seven diet and weight‐related risk factors. Results: Including a price of $23 per tonne of carbon dioxide equivalent (tCO2‐eq) – the starting price of the former Australian carbon pricing mechanism – into the price of food commodities in our model simulations led to 49,500 avoided disability‐adjusted life years (DALYs) (95% confidence interval [CI] 43,200‐55,200). Food‐related greenhouse gas emissions were reduced by 6% (2.3 MtCO2‐eq), and greenhouse gas tax revenues amounted to $866 million. Conclusion: Incorporating the price of food‐related greenhouse gas emissions into the price of food commodities in Australia could be beneficial for population health, while generating public finance revenues and supporting Australia's emission‐reduction commitment. Implications for public health: Climate policies that integrate the price of greenhouse gas emissions into the price of food commodities in Australia are compatible with public health objectives to reduce diet‐related disease mortality.

Abstract Background Health-related claims are statements regarding the nutritional content of a food (nutrition claims) and/or indicate that a relationship exists between a food and a health outcome (health claims). Their impact on food purchasing or consumption decisions is unclear. This systematic review measured the effect of health-related claims, on pre-packaged foods in retail settings, on adult purchasing decisions (real and perceived). Methods In September 2016, we searched MEDLINE, EMBASE, PsychINFO, CAB abstracts, Business Source Complete, and Web of Science/Science Citation Index & Social Science Citation Index for articles in English published in peer-review journals. Studies were included if they were controlled experiments where the experimental group(s) included a health-related claim and the control group involved an identical product without a health-related claim. Included studies measured (at an individual or population level); actual or intended choice, purchases, and/or consumption. The primary outcome was product choices and purchases, the secondary outcome was food consumption and preference. Results were standardised through calculating odds ratios and 95% confidence intervals (CI) for the likelihood of choosing a product when a health-related claim was present. Results were combined in a random-effects meta-analysis. Results Thirty-one papers were identified, 17 of which were included for meta-analyses. Most studies were conducted in Europe (n = 17) and the USA (n = 7). Identified studies were choice experiments that measured the likelihood of a product being chosen when a claim was present compared to when a claim was not present, (n = 16), 15 studies were experiments that measured either; intent-rating scale outcomes (n = 8), consumption (n = 6), a combination of the two (n = 1), or purchase data (n = 1). Overall, 20 studies found that claims increase purchasing and/or consumption, eight studies had mixed results, and two studies found consumption/purchasing reductions. The meta-analyses of 17 studies found that health-related claims increase consumption and/or purchasing (OR 1.75, CI 1.60–1.91). Conclusion Health-related claims have a substantial effect on dietary choices. However, this finding is based on research mostly conducted in artificial settings. Findings from natural experiments have yielded smaller effects. Further research is needed to assess effects of claims in real-world settings. Trial registration PROSPERO systematic review registration number: CRD42016044042 .

BackgroundFood taxes and subsidies are one intervention to address poor diets. Price elasticity (PE) matrices are commonly used to model the change in food purchasing. Usually a PE matrix is generated in one setting then applied to another setting with differing starting consumptions and prices of foods. This violates econometric assumptions resulting in likely mis-estimation of total food consumption. In this paper we demonstrate this problem, canvass possible options for rescaling all consumption after applying a PE matrix, and illustrate the use of a total food expenditure elasticity (TFEe; the expenditure elasticity for all food combined given the policy-induced change in the total price of food). We use case studies of: NZ$2 per 100g saturated fat (SAFA) tax, NZ$0.4 per 100g sugar tax, and a 20% fruit and vegetable (F&V) subsidy.MethodsWe estimated changes in food purchasing using a NZ PE matrix applied conventionally, and then with TFEe adjustment. Impacts were quantified for pre- to post-policy changes in total food expenditure and health adjusted life years (HALYs) for the total NZ population alive in 2011 over the rest of their lifetime using a multistate lifetable model.ResultsTwo NZ studies gave TFEe's of 0.68 and 0.83, with international estimates ranging from 0.46 to 0.90 (except a UK outlier of 0.04). Without TFEe adjustment, total food expenditure decreased with the tax policies and increased with the F&V subsidy-implausible directions of shift given economic theory and the external TFEe estimates. After TFEe adjustment, HALY gains reduced by a third to a half for the two taxes and reversed from an apparent health loss to a health gain for the F&V subsidy. With TFEe adjustment, HALY gains (in 1000's) were: 1,805 (95% uncertainty interval 1,337 to 2,340) for the SAFA tax; 1,671 (1,220 to 2,269) for the sugar tax; and 953 (453 to 1,308) for the F&V subsidy.ConclusionsIf PE matrices are applied in settings beyond where they were derived, additional scaling is likely required. We suggest that the TFEe is a useful scalar, but we also encourage other researchers to examine this issue and propose alternative options.

ObjectivesTraditional methods for creating food composition tables struggle to cope with the large number of products and the rapid pace of change in the food and drink marketplace. This paper introduces foodDB, a big data approach to the analysis of this marketplace, and presents analyses illustrating its research potential.DesignfoodDB has been used to collect data weekly on all foods and drinks available on six major UK supermarket websites since November 2017. As of June 2018, foodDB has 3 193 171 observations of 128 283 distinct food and drink products measured at multiple timepoints.MethodsWeekly extraction of nutrition and availability data of products was extracted from the webpages of the supermarket websites. This process was automated with a codebase written in Python.ResultsAnalyses using a single weekly timepoint of 97 368 total products in March 2018 identified 2699 ready meals and pizzas, and showed that lower price ready meals had significantly lower levels of fat, saturates, sugar and salt (p

Abstract Background The DisMod II model is designed to estimate epidemiological parameters on diseases where measured data are incomplete and has been used to provide estimates of disease incidence for the Global Burden of Disease study. We assessed the external validity of the DisMod II model by comparing modelled estimates of the incidence of first acute myocardial infarction (AMI) in England in 2010 with estimates derived from a linked dataset of hospital records and death certificates. Methods Inputs for DisMod II were prevalence rates of ever having had an AMI taken from a population health survey, total mortality rates and AMI mortality rates taken from death certificates. By definition, remission rates were zero. We estimated first AMI incidence in an external dataset from England in 2010 using a linked dataset including all hospital admissions and death certificates since 1998. 95 % confidence intervals were derived around estimates from the external dataset and DisMod II estimates based on sampling variance and reported uncertainty in prevalence estimates respectively. Results Estimates of the incidence rate for the whole population were higher in the DisMod II results than the external dataset (+54 % for men and +26 % for women). Age-specific results showed that the DisMod II results over-estimated incidence for all but the oldest age groups. Confidence intervals for the DisMod II and external dataset estimates did not overlap for most age groups. Conclusion By comparison with AMI incidence rates in England, DisMod II did not achieve external validity for age-specific incidence rates, but did provide global estimates of incidence that are of similar magnitude to measured estimates. The model should be used with caution when estimating age-specific incidence rates.

BACKGROUND:Traffic-light labelling (TLL) is a promising front-of-pack system to help consumers make informed dietary choices. It has been shown that adopting TLL in Canada, through an optimistic scenario of avoiding, if possible, foods with red traffic lights, could effectively reduce Canadians' intakes of energy, total fat, saturated fat, and sodium by 5%, 13%, 14% and 6%, respectively. However, the potential health impact of adopting TLL has not been determined in the North American context. OBJECTIVE:This study modelled the potential impact of adopting TLL on mortality from noncommunicable diseases (NCDs) in Canada, due to the previously predicted improved nutrient intakes. METHODS:Investigators used data from adults (n = 19,915) in the 2004 nationally representative Canadian Community Health Survey (CCHS)-Cycle 2.2. Nutrient amounts in foods consumed by CCHS respondents were profiled using the 2013 United Kingdom's TLL criteria. Whenever possible, foods assigned at least one red light (non-compliant foods) were replaced with similar, but compliant, foods identified from a Canadian brand-specific food database. Respondents' nutrient intakes were calculated under the original CCHS scenario and the counterfactual TLL scenario, and entered in the Preventable Risk Integrated ModEl (PRIME) to estimate the health impact of adopting TLL. The primary outcome was the number of deaths attributable to diet-related NCDs that could be averted or delayed based on the TLL scenario compared with the baseline scenario. RESULTS:PRIME estimated that 11,715 deaths (95% CI 10,500-12,865) per year due to diet-related NCDs, among which 72% are specifically related to cardiovascular diseases, could be prevented if Canadians avoided foods labelled with red traffic lights. The reduction in energy intakes would by itself save 10,490 deaths (9,312-11,592; 90%). CONCLUSIONS:This study, although depicting an idealistic scenario, suggests that TLL (if used to avoid red lights when possible) could be an effective population-wide intervention to improve NCD outcomes in Canada.

Summary: Background: Sustainable diets are intended to address the increasing health and environmental concerns related to food production and consumption. Although many candidates for sustainable diets have emerged, a consistent and joint environmental and health analysis of these diets has not been done at a regional level. Using an integrated health and environmental modelling framework for more than 150 countries, we examined three different approaches to sustainable diets motivated by environmental, food security, and public health objectives. Methods: In this global modelling analysis, we combined analyses of nutrient levels, diet-related and weight-related chronic disease mortality, and environmental impacts for more than 150 countries in three sets of diet scenarios. The first set, based on environmental objectives, replaced 25–100% of animal-source foods with plant-based foods. The second set, based on food security objectives, reduced levels of underweight, overweight, and obesity by 25–100%. The third set, based on public health objectives, consisted of four energy-balanced dietary patterns: flexitarian, pescatarian, vegetarian, and vegan. In the nutrient analysis, we calculated nutrient intake and changes in adequacy based on international recommendations and a global dataset of nutrient content and supply. In the health analysis, we estimated changes in mortality using a comparative risk assessment with nine diet and weight-related risk factors. In the environmental analysis, we combined country-specific and food group-specific footprints for greenhouse gas emissions, cropland use, freshwater use, nitrogen application, and phosphorus application to analyse the relationship between the health and environmental impacts of dietary change. Findings: Following environmental objectives by replacing animal-source foods with plant-based ones was particularly effective in high-income countries for improving nutrient levels, lowering premature mortality (reduction of up to 12% [95% CI 10–13] with complete replacement), and reducing some environmental impacts, in particular greenhouse gas emissions (reductions of up to 84%). However, it also increased freshwater use (increases of up to 16%) and had little effectiveness in countries with low or moderate consumption of animal-source foods. Following food-security objectives by reducing underweight and overweight led to similar reductions in premature mortality (reduction of up to 10% [95% CI 9–11]), and moderately improved nutrient levels. However, it led to only small reductions in environmental impacts at the global level (all impacts changed by

BackgroundIn the United Kingdom, the Food Standards Agency-Ofcom nutrient profiling model (FSA-Ofcom model) is used to define less-healthy foods that cannot be advertised to children. However, there has been limited investigation of whether less-healthy foods defined by this model are associated with prospective health outcomes. The objective of this study was to test whether consumption of less-healthy food as defined by the FSA-Ofcom model is associated with cardiovascular disease (CVD).Methods and findingsWe used data from the European Prospective Investigation of Cancer (EPIC)-Norfolk cohort study in adults (n = 25,639) aged 40-79 years who completed a 7-day diet diary between 1993 and 1997. Incident CVD (primary outcome), cardiovascular mortality, and all-cause mortality (secondary outcomes) were identified using record linkage to hospital admissions data and death certificates up to 31 March 2015. Each food and beverage item reported was coded and given a continuous score, using the FSA-Ofcom model, based on the consumption of energy; saturated fat; total sugar; sodium; nonsoluble fibre; protein; and fruits, vegetables, and nuts. Items were classified as less-healthy using Ofcom regulation thresholds. We used Cox proportional hazards regression to test for an association between consumption of less-healthy food and incident CVD. Sensitivity analyses explored whether the results differed based on the definition of the exposure. Analyses were adjusted for age, sex, behavioural risk factors, clinical risk factors, and socioeconomic status. Participants were followed up for a mean of 16.4 years. During follow-up, there were 4,965 incident cases of CVD (1,524 fatal within 30 days). In the unadjusted analyses, we observed an association between consumption of less-healthy food and incident CVD (test for linear trend over quintile groups, p < 0.01). After adjustment for covariates (sociodemographic, behavioural, and indices of cardiovascular risk), we found no association between consumption of less-healthy food and incident CVD (p = 0.84) or cardiovascular mortality (p = 0.90), but there was an association between consumption of less-healthy food and all-cause mortality (test for linear trend, p = 0.006; quintile group 5, highest consumption of less-healthy food, versus quintile group 1, HR = 1.11, 95% CI 1.02-1.20). Sensitivity analyses produced similar results. The study is observational and relies on self-report of dietary consumption. Despite adjustment for known and reported confounders, residual confounding is possible.ConclusionsAfter adjustment for potential confounding factors, no significant association between consumption of less-healthy food (as classified by the FSA-Ofcom model) and CVD was observed in this study. This suggests, in the UK setting, that the FSA-Ofcom model is not consistently discriminating among foods with respect to their association with CVD. More studies are needed to understand better the relationship between consumption of less-healthy food, defined by the FSA-Ofcom model, and indices of health.

OBJECTIVES:Healthcare interventions, and particularly those in public health may affect multiple diseases and significantly prolong life. No consensus currently exists for how to estimate comparable healthcare costs across multiple diseases for use in health and public health cost-effectiveness models. We aim to describe a method for estimating comparable disease specific English healthcare costs as well as future healthcare costs from diseases unrelated to those modelled. METHODS:We use routine national datasets including programme budgeting data and cost curves from NHS England to estimate annual per person costs for diseases included in the PRIMEtime model as well as age and sex specific costs due to unrelated diseases. RESULTS:The 2013/14 annual cost to NHS England per prevalent case varied between £3,074 for pancreatic cancer and £314 for liver disease. Costs due to unrelated diseases increase with age except for a secondary peak at 30-34 years for women reflecting maternity resource use. CONCLUSIONS:The methodology described allows health and public health economic modellers to estimate comparable English healthcare costs for multiple diseases. This facilitates the direct comparison of different health and public health interventions enabling better decision making.

BACKGROUND:The consumption of red and processed meat has been associated with increased mortality from chronic diseases, and as a result, it has been classified by the World Health Organization as carcinogenic (processed meat) and probably carcinogenic (red meat) to humans. One policy response is to regulate red and processed meat consumption similar to other carcinogens and foods of public health concerns. Here we describe a market-based approach of taxing red and processed meat according to its health impacts. METHODS:We calculated economically optimal tax levels for 149 world regions that would account for (internalize) the health costs associated with ill-health from red and processed meat consumption, and we used a coupled modelling framework to estimate the impacts of optimal taxation on consumption, health costs, and non-communicable disease mortality. Health impacts were estimated using a global comparative risk assessment framework, and economic responses were estimated using international data on health costs, prices, and price elasticities. FINDINGS:The health-related costs to society attributable to red and processed meat consumption in 2020 amounted to USD 285 billion (sensitivity intervals based on epidemiological uncertainty (SI), 93-431), three quarters of which were due to processed meat consumption. Under optimal taxation, prices for processed meat increased by 25% on average, ranging from 1% in low-income countries to over 100% in high-income countries, and prices for red meat increased by 4%, ranging from 0.2% to over 20%. Consumption of processed meat decreased by 16% on average, ranging from 1% to 25%, whilst red meat consumption remained stable as substitution for processed meat compensated price-related reductions. The number of deaths attributable to red and processed meat consumption decreased by 9% (222,000; SI, 38,000-357,000), and attributable health costs decreased by 14% (USD 41 billion; SI, 10-57) globally, in each case with greatest reductions in high and middle-income countries. INTERPRETATION:Including the social health cost of red and processed meat consumption in the price of red and processed meat could lead to significant health and environmental benefits, in particular in high and middle-income countries. The optimal tax levels estimated in this study are context-specific and can complement the simple rules of thumb currently used for setting health-motivated tax levels.

We examined whether specific input data and assumptions explain outcome differences in otherwise comparable health impact assessment models. Seven population health models estimating the impact of salt reduction on morbidity and mortality in western populations were compared on four sets of key features, their underlying assumptions and input data. Next, assumptions and input data were varied one by one in a default approach (the DYNAMO-HIA model) to examine how it influences the estimated health impact. Major differences in outcome were related to the size and shape of the dose-response relation between salt and blood pressure and blood pressure and disease. Modifying the effect sizes in the salt to health association resulted in the largest change in health impact estimates (33% lower), whereas other changes had less influence. Differences in health impact assessment model structure and input data may affect the health impact estimate. Therefore, clearly defined assumptions and transparent reporting for different models is crucial. However, the estimated impact of salt reduction was substantial in all of the models used, emphasizing the need for public health actions.

Background: In March, 2016, the UK Government proposed a tiered levy on sugar-sweetened beverages (SSBs; high tax for drinks with >8 g of sugar per 100 mL, moderate tax for 5–8 g, and no tax for

Background The relationships between physical activity (PA) and both cardiovascular disease (CVD) and type 2 diabetes mellitus (T2DM) have predominantly been estimated using categorical measures of PA, masking the shape of the dose‐response relationship. In this systematic review and meta‐analysis, for the very first time we are able to derive a single continuous PA metric to compare the association between PA and CVD/T2DM, both before and after adjustment for a measure of body weight. Methods and Results The search was applied to MEDLINE and EMBASE electronic databases for all studies published from January 1981 to March 2014. A total of 36 studies (3 439 874 participants and 179 393 events, during an average follow‐up period of 12.3 years) were included in the analysis (33 pertaining to CVD and 3 to T2DM). An increase from being inactive to achieving recommended PA levels (150 minutes of moderate‐intensity aerobic activity per week) was associated with lower risk of CVD mortality by 23%, CVD incidence by 17%, and T2DM incidence by 26% (relative risk [RR], 0.77 [0.71–0.84]), (RR, 0.83 [0.77–0.89]), and (RR, 0.74 [0.72–0.77]), respectively, after adjustment for body weight. Conclusions By using a single continuous metric for PA levels, we were able to make a comparison of the effect of PA on CVD incidence and mortality including myocardial infarct (MI), stroke, and heart failure, as well as T2DM. Effect sizes were generally similar for CVD and T2DM, and suggested that the greatest gain in health is associated with moving from inactivity to small amounts of PA.

OBJECTIVE: To investigate the poorly understood relationship between the process of urbanization and noncommunicable diseases (NCDs) through the application of a quantitative measure of urbanicity. METHODS: We constructed a measure of the urban environment for seven areas using a seven-item scale based on data from the Census of India 2001 to develop an "urbanicity" scale. The scale was used in conjunction with data collected from 3705 participants in the World Health Organization's 2003 STEPwise risk factor surveillance survey in Tamil Nadu, India, to analyse the relationship between the urban environment and major NCD risk factors. Linear and logistic regression models were constructed examining the relationship between urbanicity and chronic disease risk. FINDINGS: Among men, urbanicity was positively associated with smoking (odds ratio, OR: 3.54; 95% confidence interval, Cl: 2.4-5.1), body mass index (OR: 7.32; 95% Cl: 4.0-13.6), blood pressure (OR: 1.92; 95% Cl: 1.4-2.7) and low physical activity (OR: 3.26; 95% Cl: 2.5-4.3). Among women, urbanicity was positively associated with low physical activity (OR: 4.13; 95% Cl: 3.0-5.7) and high body mass index (OR: 6.48; 95% Cl: 4.6-9.2). In both sexes urbanicity was positively associated with the mean number of servings of fruit and vegetables consumed per day (P< 0.05). CONCLUSION: Urbanicity is associated with the prevalence of several NCD risk factors in Tamil Nadu, India.

OBJECTIVE:To model population health impacts of dietary changes associated with the redevelopment of the UK food-based dietary guidelines (the 'Eatwell Guide'). METHOD:Using multi-state lifetable methods, we modelled the impact of dietary changes on cardiovascular disease, diabetes and cancers over the lifetime of the current UK population. From this model, we determined change in life expectancy and disability-adjusted life years (DALYs) that could be averted. RESULTS:Changing the average diet to that recommended in the new Eatwell Guide, without increasing total energy intake, could increase average life expectancy by 5.4 months (95% uncertainty interval: 4.7 to 6.2) for men and 4.0 months (3.4 to 4.6) for women; and avert 17.9 million (17.6 to 18.2) DALYs over the lifetime of the current population. A large proportion of the health benefits are from prevention of type 2 diabetes, with 440,000 (400,000 to 480,000) new cases prevented in men and 340,000 (310,000 to 370,000) new cases prevented in women, over the next ten years. Prevention of cardiovascular diseases and colorectal cancer is also large. However, if the diet recommended in the new Eatwell Guide is achieved with an accompanying increase in energy intake (and thus an increase in body mass index), around half the potential improvements in population health will not be realised. CONCLUSIONS:The dietary changes required to meet recommendations in the Eatwell Guide, which include eating more fruits and vegetables and less red and processed meats and dairy products, are large. However, the potential population health benefits are substantial.

INTRODUCTION:Researchers and policy-makers are interested in the influence that food retailing around schools may have on child obesity risk. Most previous research comes from North America, uses data aggregated at the school-level and focuses on associations between fast food outlets and school obesity rates. This study examines associations between food retailing and BMI among a large sample of primary school students in Berkshire, England. By controlling for individual, school and home characteristics and stratifying results across the primary school years, we aimed to identify if the food environment around schools had an effect on BMI, independent of socio-economic variables. METHODS:We measured the densities of fast food outlets and food stores found within schoolchildren's home and school environments using Geographic Information Systems (GIS) and data from local councils. We linked these data to measures from the 2010/11 National Child Measurement Programme and used a cross-classified multi-level approach to examine associations between food retailing and BMI z-scores. Analyses were stratified among Reception (aged 4-5) and Year 6 (aged 10-11) students to measure associations across the primary school years. RESULTS:Our multilevel model had three levels to account for individual (n = 16,956), home neighbourhood (n = 664) and school (n = 268) factors. After controlling for confounders, there were no significant associations between retailing near schools and student BMI, but significant positive associations between fast food outlets in home neighbourhood and BMI z-scores. Year 6 students living in areas with the highest density of fast food outlets had an average BMI z-score that was 0.12 (95% CI: 0.04, 0.20) higher than those living in areas with none. DISCUSSION:We found little evidence to suggest that food retailing around schools influences student BMI. There is some evidence to suggest that fast food outlet densities in a child's home neighbourhood may have an effect on BMI, particularly among girls, but more research is needed to inform effective policies targeting the effects of the retail environment on child obesity.

Increased physical activity (PA) has been associated with a reduction in non-communicable disease risk factors and outcomes. However, interventions to increase childhood PA typically produce small to negligible effects. Recent reviews are limited due to lack of post-intervention follow-up measurement. This review aimed to examine measured effects at least six months post-intervention.We searched PubMed, MEDLINE, EMBASE, PsychINFO, ScienceDirect, SportDiscus and Google Scholar between 1st January 1991 and 1st November 2014 for controlled studies reporting six-month post-intervention measurement for children aged 5 to 18 years. 14 studies met inclusion criteria; 12 reported moderate-to-vigorous PA (MVPA) (n = 5790) and 10 reported total PA (TPA) (n = 4855). We calculated overall effect estimates and 95% CI's using random effects modelling with inverse variance weighting. Mean difference was calculated for MVPA, with standardised mean difference calculated to TPA due to measurement variation. Meta-regression assessed heterogeneity by continuous level variables. Negligible mean difference in MVPA existed in favour of the intervention group, amounting to 1.47 (95% CI -1.88, 4.82) mins/day compared to controls, while no difference was recorded on TPA. Sub-group analyses revealed males (2.65 mins/day: 95% CI 2.03, 3.27) reported higher levels of MVPA than females (-0.42 mins/day: 95% CI -7.77, 6.94), community settings (2.67 mins/day: 95% CI 2.05, 3.28) were more effective than school settings (1.70 mins/day: 95% CI -4.84, 8.25), and that treatment (4.47 mins/day: 95% CI -0.81, 9.76) demonstrated greater effects than population approaches (1.03 mins/day: 95% CI -2.54, 4.60). Meta-regression revealed no significant differences by factor on pooled effects. Significant heterogeneity existed between studies and potential for small study effects was present.Improved PA levels subsequent to intervention were not maintained six month post-intervention. A potentially useful avenue of future research is to specifically explore community treatment of high risk individuals.PROSPERO CRD42014007545.

Fiscal interventions to improve population diet have been recommended for consideration by many organisations including the World Health Organisation and the United Nations and policies such as sugar-sweetened beverage taxes have been implemented at national and sub-national levels. However, concerns have been raised with respect to the differential impact of fiscal interventions on population sub-groups and this remains a barrier to implementation.To examine how personal characteristics (such as socioeconomic status, sex, impulsivity, and income) moderate changes in purchases of targeted foods in response to food and beverage price changes in experimental settings.Systematic review.Online databases (PubMed, EMBASE, Web of Science, EconLit and PsycInfo), reference lists of previous reviews, and additional data from study authors.We included randomised controlled trials where food and beverage prices were manipulated and reported differential effects of the intervention on participant sub-groups defined according to personal characteristics.Where possible, we extracted data to enable the calculation of price elasticities for the target foods by personal characteristic.8 studies were included in the review. Across studies, the difference in price elasticity varied from 0.02 to 2.43 between groups within the same study. 11 out of the total of 18 comparisons of own-price elasticity estimates by personal characteristic differed by more than 0.2 between groups. Income related factors were the most commonly considered and there was an indication that own-price elasticity estimates do vary by income but the direction of this effect was not clear.Experimental studies provide an opportunity to examine the differential effects of fiscal measures to improve population diets. Patterns in price sensitivity by personal characteristics are complex. General conclusions pertaining to the effects of personal characteristics on price sensitivity are not supported by the evidence, which shows heterogeneity between studies and populations.PROSPERO CRD42014009705.

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.

Noncommunicable disease (NCD) scenario models are an essential part of the public health toolkit, allowing for an estimate of the health impact of population-level interventions that are not amenable to assessment by standard epidemiological study designs (e.g., health-related food taxes and physical infrastructure projects) and extrapolating results from small samples to the whole population. The PRIME (Preventable Risk Integrated ModEl) is an openly available NCD scenario model that estimates the effect of population-level changes in diet, physical activity, and alcohol and tobacco consumption on NCD mortality. The structure and methods employed in the PRIME are described here in detail, including the development of open source code that will support a PRIME web application to be launched in 2015. This paper reviews scenario results from eleven papers that have used the PRIME, including estimates of the impact of achieving government recommendations for healthy diets, health-related food taxes and subsidies, and low-carbon diets. Future challenges for NCD scenario modelling, including the need for more comparisons between models and the improvement of future prediction of NCD rates, are also discussed.

There are substantial geographic variations in coronary heart disease (CHD) mortality rates in England that may in part be due to differences in climate and air pollution. An ecological cross-sectional multi-level analysis of male and female CHD mortality rates in all wards in England (1999-2004) was conducted to estimate the relative strength of the association between CHD mortality rates and three aspects of the physical environment--temperature, hours of sunshine and air quality. Models were adjusted for deprivation, an index measuring the healthiness of the lifestyle of populations, and urbanicity. In the fully adjusted model, air quality was not significantly associated with CHD mortality rates, but temperature and sunshine were both significantly negatively associated (p

Introduction It is unclear how much of the geographical variation in coronary heart disease (CHD), stroke and cancer mortality rates within the UK is associated with diet. The aim of this study is to estimate how many deaths from CHD, stroke and cancer would be delayed or averted if Wales, Scotland and Northern Ireland adopted a diet equivalent in nutritional quality to the English diet.Methods Mortality data for CHD, stroke and 10 diet-related cancers for 2007–2009 were used to calculate the mortality gap (the difference between actual mortality and English mortality rates) for Wales, Scotland and Northern Ireland. Estimates of mean national consumption of 10 dietary factors were used as baseline and counterfactual inputs in a macrosimulation model (DIETRON). An uncertainty analysis was conducted using a Monte Carlo simulation with 5000 iterations.Results The mortality gap in the modelled scenario (achieving the English diet) was reduced by 81% (95% credible intervals: 62% to 108%) for Wales, 40% (33% to 51%) for Scotland and 81% (67% to 99%) for Northern Ireland, equating to approximately 3700 deaths delayed or averted annually. For CHD only, the mortality gap was reduced by 88% (69% to 118%) for Wales, 58% (47% to 72%) for Scotland, and 88% (70% to 111%) for Northern Ireland.Conclusion Improving the average diet in Wales, Scotland and Northern Ireland to a level already achieved in England could have a substantial impact on reducing geographical variations in chronic disease mortality rates in the UK. Much of the mortality gap between Scotland and England is explained by non-dietary risk factors.

Arab-American (AA) populations in the US are exposed to discrimination and acculturative stress-two factors that have been associated with higher suicide risk. However, prior work suggests that socially oriented norms and behaviors, which characterize recent immigrant ethnic groups, may be protective against suicide risk. Here we explored suicide rates and their determinants among AAs in Michigan, the state with the largest proportion of AAs in the US.ICD-9/10 underlying cause of death codes were used to identify suicide deaths from among all deaths in Michigan between 1990 and 2007. Data from the 2000 U.S. Census were collected for population denominators. Age-adjusted suicide rates among AAs and non-ethnic whites were calculated by gender using the direct method of standardization. We also stratified by residence inside or outside of Wayne County (WC), the county with the largest AA population in the state. Suicide rates were 25.10 per 100,000 per year among men and 6.40 per 100,000 per year among women in Michigan from 1990 to 2007. AA men had a 51% lower suicide rate and AA women had a 33% lower rate than non-ethnic white men and women, respectively. The suicide rate among AA men in WC was 29% lower than in all other counties, while the rate among AA women in WC was 20% lower than in all other counties. Among non-ethnic whites, the suicide rate in WC was higher compared to all other counties among both men (12%) and women (16%).Suicide rates were higher among non-ethnic white men and women compared to AA men and women in both contexts. Arab ethnicity may protect against suicide in both sexes, but more so among men. Additionally, ethnic density may protect against suicide among Arab-Americans.

Although nearly 112 million residents of the United States belong to a non-white ethnic group, the literature about differences in health indicators across ethnic groups is limited almost exclusively to Hispanics. Features of the social experience of many ethnic groups including immigration, discrimination, and acculturation may plausibly influence mortality risk. We explored life expectancy and age-adjusted mortality risk of Arab-Americans (AAs), relative to non-Arab and non-Hispanic Whites in Michigan, the state with the largest per capita population of AAs in the US.Data were collected about all deaths to AAs and non-Arab and non-Hispanic Whites in Michigan between 1990 and 2007, and year 2000 census data were collected for population denominators. We calculated life expectancy, age-adjusted all-cause, cause-specific, and age-specific mortality rates stratified by ethnicity and gender among AAs and non-Arab and non-Hispanic Whites. Among AAs, life expectancies among men and women were 2.0 and 1.4 years lower than among non-Arab and non-Hispanic White men and women, respectively. AA men had higher mortality than non-Arab and non-Hispanic White men due to infectious diseases, chronic diseases, and homicide. AA women had higher mortality than non-Arab and non-Hispanic White women due to chronic diseases.Despite better education and higher income, AAs have higher age-adjusted mortality risk than non-Arab and non-Hispanic Whites, particularly due to chronic diseases. Features specific to AA culture may explain some of these findings.