The effects of a supermarket-based intervention on the nutritional quality of private-label foods: a prospective study

Private-label products, products owned by supermarkets, are a growing area of the food supply. The aim of this study was to assess the effect of an intervention that provided an Australian supermarket ('intervention supermarket') with comparative nutrition data to improve the healthiness of their private-label range. Between 2015 and 2016, the intervention supermarket received reports that ranked the nutritional quality of their products against competitors. Changes in the nutrient content (sodium, sugar, saturated fat, energy and Health Star Rating) of products from the intervention supermarket between 2015 and 2018 were compared against changes achieved for three comparators (private-label products from two other supermarkets and branded products). The intervention supermarket achieved a significantly greater reduction in the sodium content of their products relative to all three comparators, which ranged between -104 and -52 mg/100 g (all p 0.05). Providing comparative nutrition information to a supermarket may be ineffective in improving the healthiness of their private-label products, likely due to competing factors that play a role in the decision-making process behind product reformulation and product discontinuation/innovation

Estimating the potential impact of the Australian government's reformulation targets on household sugar purchases

BACKGROUND: Countries around the world are putting in place sugar reformulation targets for packaged foods to reduce excess sugar consumption. The Australian government released its voluntary sugar reformulation targets for nine food categories in 2020. We estimated the potential impact of these targets on household sugar purchases and examined differences by income. For comparison, we also modelled the potential impact of the UK sugar reduction targets on per capita sugar purchases as the UK has one of the most comprehensive sugar reduction strategies in the world. METHODS: Grocery purchase data from a nationally representative consumer panel (n=7,188) in Australia was linked with a large database (FoodSwitch) with product-specific sugar content information for packaged foods (n=25,261); both datasets were collected in 2018. Potential reductions in per capita sugar purchases were calculated overall and by food category. Differences in sugar reduction across income level were assessed by analysis of variance. RESULTS: In 2018, the total sugar acquired from packaged food and beverage purchases consumed at-home was 56.1 g/day per capita. Australia's voluntary reformulation targets for sugar covered 2,471/25,261 (9.8%) unique products in the FoodSwitch dataset. Under the scenario that all food companies adhered to the voluntary targets, sugar purchases were estimated to be reduced by 0.9 g/day per capita, which represents a 1.5% reduction in sugar purchased from packaged foods. However, if Australia adopted the UK targets, over twice as many products would be covered (n=4,667), and this would result in a more than four times greater reduction in sugar purchases (4.1 g/day per capita). It was also estimated that if all food companies complied with Australia's voluntary sugar targets, reductions to sugar would be slightly greater in low-income households compared with high-income households by 0.3 g/day (95%CI 0.2 - 0.4 g/day, p<0.001). CONCLUSIONS: Sugar-reduction policies have the potential to substantially reduce population sugar consumption and may help to reduce health inequalities related to excess sugar consumption. However, the current reformulation targets in Australia are estimated to achieve only a small reduction to sugar intakes, particularly in comparison to the UK's sugar reduction program

Socio-economic difference in purchases of ultra-processed foods in Australia: an analysis of a nationally representative household grocery purchasing panel

Background: Consumption of ultra-processed foods is associated with increased risk of obesity and non-communicable diseases. Little is known about current patterns of ultra-processed foods intake in Australia. The aim of this study was to examine the amount and type of ultra-processed foods purchased by Australian households in 2019 and determine whether purchases differed by socio-economic status (SES). We also assessed whether purchases of ultra-processed foods changed between 2015 and 2019. Methods: We used grocery purchase data from a nationally representative consumer panel in Australia to assess packaged and unpackaged grocery purchases that were brought home between 2015 to 2019. Ultra-processed foods were identified according to the NOVA system, which classifies foods according to the nature, extent and purpose of industrial food processing. Purchases of ultra-processed foods were calculated per capita, using two outcomes: grams/day and percent of total energy. The top food categories contributing to purchases of ultra-processed foods in 2019 were identified, and differences in ultra-processed food purchases by SES (Index of Relative Social Advantage and Disadvantage) were assessed using survey-weighted linear regression. Changes in purchases of ultra-processed foods between 2015 to 2019 were examined overall and by SES using mixed linear models. Results: In 2019, the mean ± SD total grocery purchases made by Australian households was 881.1 ± 511.9 g/d per capita. Of this, 424.2 ± 319.0 g/d per capita was attributable to purchases of ultra-processed foods, which represented 56.4% of total energy purchased. The largest food categories contributing to total energy purchased included mass-produced, packaged breads (8.2% of total energy purchased), chocolate and sweets (5.7%), biscuits and crackers (5.7%) and ice-cream and edible ices (4.3%). In 2019, purchases of ultra-processed foods were significantly higher for the lowest SES households compared to all other SES quintiles (P < 0.001). There were no major changes in purchases of ultra-processed foods overall or by SES over the five-year period. Conclusions: Between 2015 and 2019, ultra-processed foods have consistently made up the majority of groceries purchased by Australians, particularly for the lowest SES households. Policies that reduce ultra-processed food consumption may reduce diet-related health inequalities

Bayesian regression filter and the issue of priors

We propose a Bayesian framework for regression problems, which covers areas which are usually dealt with by function approximation. An online learning algorithm is derived which solves regression problems with a Kalman filter. Its solution always improves with increasing model complexity, without the risk of over-fitting. In the infinite dimension limit it approaches the true Bayesian posterior. The issues of prior selection and over-fitting are also discussed, showing that some of the commonly held beliefs are misleading. The practical implementation is summarised. Simulations using 13 popular publicly available data sets are used to demonstrate the method and highlight important issues concerning the choice of priors

Socio-economic difference in purchases of ultra-processed foods in Australia: an analysis of a nationally representative household grocery purchasing panel

Background: Consumption of ultra-processed foods is associated with increased risk of obesity and non-communicable diseases. Little is known about current patterns of ultra-processed foods intake in Australia. The aim of this study was to examine the amount and type of ultra-processed foods purchased by Australian households in 2019 and determine whether purchases differed by socio-economic status (SES). We also assessed whether purchases of ultra-processed foods changed between 2015 and 2019. Methods: We used grocery purchase data from a nationally representative consumer panel in Australia to assess packaged and unpackaged grocery purchases that were brought home between 2015 to 2019. Ultra-processed foods were identified according to the NOVA system, which classifies foods according to the nature, extent and purpose of industrial food processing. Purchases of ultra-processed foods were calculated per capita, using two outcomes: grams/day and percent of total energy. The top food categories contributing to purchases of ultra-processed foods in 2019 were identified, and differences in ultra-processed food purchases by SES (Index of Relative Social Advantage and Disadvantage) were assessed using survey-weighted linear regression. Changes in purchases of ultra-processed foods between 2015 to 2019 were examined overall and by SES using mixed linear models. Results: In 2019, the mean ± SD total grocery purchases made by Australian households was 881.1 ± 511.9 g/d per capita. Of this, 424.2 ± 319.0 g/d per capita was attributable to purchases of ultra-processed foods, which represented 56.4% of total energy purchased. The largest food categories contributing to total energy purchased included mass-produced, packaged breads (8.2% of total energy purchased), chocolate and sweets (5.7%), biscuits and crackers (5.7%) and ice-cream and edible ices (4.3%). In 2019, purchases of ultra-processed foods were significantly higher for the lowest SES households compared to all other SES quintiles (P < 0.001). There were no major changes in purchases of ultra-processed foods overall or by SES over the five-year period. Conclusions: Between 2015 and 2019, ultra-processed foods have consistently made up the majority of groceries purchased by Australians, particularly for the lowest SES households. Policies that reduce ultra-processed food consumption may reduce diet-related health inequalities

Time from first presentation in primary care to treatment of symptomatic colorectal cancer:effect on disease stage and survival

BACKGROUND: British 5-year survival from colorectal cancer (CRC) is below the European average, but the reasons are unclear. This study explored if longer provider delays (time from presentation to treatment) were associated with more advanced stage disease at diagnosis and poorer survival. METHODS: Data on 958 people with CRC were linked with the Scottish Cancer Registry, the Scottish Death Registry and the acute hospital discharge (SMR01) dataset. Time from first presentation in primary care to first treatment, disease stage at diagnosis and survival time from date of first presentation in primary care were determined. Logistic regression and Cox survival analyses, both with a restricted cubic spline, were used to model stage and survival, respectively, following sequential adjustment of patient and tumour factors. RESULTS: On univariate analysis, those with <4 weeks from first presentation in primary care to treatment had more advanced disease at diagnosis and the poorest prognosis. Treatment delays between 4 and 34 weeks were associated with earlier stage (with the lowest odds ratio occurring at 20 weeks) and better survival (with the lowest hazard ratio occurring at 16 weeks). Provider delays beyond 34 weeks were associated with more advanced disease at diagnosis, but not increased mortality. Following adjustment for patient, tumour factors, emergency admissions and symptoms and signs, no significant relationship between provider delay and stage at diagnosis or survival from CRC was found. CONCLUSIONS: Although allowing for a nonlinear relationship and important confounders, moderately long provider delays did not impact adversely on cancer outcomes. Delays are undesirable because they cause anxiety; this may be fuelled by government targets and health campaigns stressing the importance of very prompt cancer diagnosis. Our findings should reassure patients. They suggest that a health service's primary emphasis should be on quality and outcomes rather than on time to treatment

Diagnostic routes and time intervals for patients with colorectal cancer in 10 international jurisdictions; findings from a cross-sectional study from the International Cancer Benchmarking Partnership (ICBP)

OBJECTIVE: International differences in colorectal cancer (CRC) survival and stage at diagnosis have been reported previously. They may be linked to differences in time intervals and routes to diagnosis. The International Cancer Benchmarking Partnership Module 4 (ICBP M4) reports the first international comparison of routes to diagnosis for patients with CRC and the time intervals from symptom onset until the start of treatment. Data came from patients in 10 jurisdictions across six countries (Canada, the UK, Norway, Sweden, Denmark and Australia). DESIGN: Patients with CRC were identified via cancer registries. Data on symptomatic and screened patients were collected; questionnaire data from patients\u27 primary care physicians and specialists, as well as information from treatment records or databases, supplemented patient data from the questionnaires. Routes to diagnosis and the key time intervals were described, as were between-jurisdiction differences in time intervals, using quantile regression. PARTICIPANTS: A total of 14&thinsp;664 eligible patients with CRC diagnosed between 2013 and 2015 were identified, of which 2866 were included in the analyses. PRIMARY AND SECONDARY OUTCOME MEASURES: Interval lengths in days (primary), reported patient symptoms (secondary). RESULTS: The main route to diagnosis for patients was symptomatic presentation and the most commonly reported symptom was \u27bleeding/blood in stool\u27. The median intervals between jurisdictions ranged from: 21 to 49 days (patient); 0 to 12 days (primary care); 27 to 76 days (diagnostic); and 77 to 168 days (total, from first symptom to treatment start). Including screen-detected cases did not significantly alter the overall results. CONCLUSION: ICBP M4 demonstrates important differences in time intervals between 10 jurisdictions internationally. The differences may justify efforts to reduce intervals in some jurisdictions

Changing presentation of prostate cancer in a UK population--10 year trends in prostate cancer risk profiles in the East of England.

BACKGROUND: Prostate cancer incidence is rising in the United Kingdom but there is little data on whether the disease profile is changing. To address this, we interrogated a regional cancer registry for temporal changes in presenting disease characteristics. METHODS: Prostate cancers diagnosed from 2000 to 2010 in the Anglian Cancer Network (n=21,044) were analysed. Risk groups (localised disease) were assigned based on NICE criteria. Age standardised incidence rates (IRs) were compared between 2000-2005 and 2006-2010 and plotted for yearly trends. RESULTS: Over the decade, overall IR increased significantly (P<0.00001), whereas metastasis rates fell (P<0.0007). For localised disease, IR across all risk groups also increased but at different rates (P<0.00001). The most striking change was a three-fold increase in intermediate-risk cancers. Increased IR was evident across all PSA and stage ranges but with no upward PSA or stage shift. In contrast, IR of histological diagnosis of low-grade cancers fell over the decade, whereas intermediate and high-grade diagnosis increased significantly (P<0.00001). CONCLUSION: This study suggests evidence of a significant upward migration in intermediate and high-grade histological diagnosis over the decade. This is most likely to be due to a change in histological reporting of diagnostic prostate biopsies. On the basis of this data, increasing proportions of newly diagnosed cancers will be considered eligible for radical treatment, which will have an impact on health resource planning and provision

Photodynamic therapy augments the efficacy of oncolytic vaccinia virus against primary and metastatic tumours in mice

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Effectiveness of Provider and Community Interventions to Improve Treatment of Uncomplicated Malaria in Nigeria: A Cluster Randomized Controlled Trial

The World Health Organization recommends that malaria be confirmed by parasitological diagnosis before treatment using Artemisinin-based Combination Therapy (ACT). Despite this, many health workers in malaria endemic countries continue to diagnose malaria based on symptoms alone. This study evaluates interventions to help bridge this gap between guidelines and provider practice. A stratified cluster-randomized trial in 42 communities in Enugu state compared 3 scenarios: Rapid Diagnostic Tests (RDTs) with basic instruction (control); RDTs with provider training (provider arm); and RDTs with provider training plus a school-based community intervention (provider-school arm). The primary outcome was the proportion of patients treated according to guidelines, a composite indicator requiring patients to be tested for malaria and given treatment consistent with the test result. The primary outcome was evaluated among 4946 (93%) of the 5311 patients invited to participate. A total of 40 communities (12 in control, 14 per intervention arm) were included in the analysis. There was no evidence of differences between the three arms in terms of our composite indicator (p = 0.36): stratified risk difference was 14% (95% CI -8.3%, 35.8%; p = 0.26) in the provider arm and 1% (95% CI -21.1%, 22.9%; p = 0.19) in the provider-school arm, compared with control. The level of testing was low across all arms (34% in control; 48% provider arm; 37% provider-school arm; p = 0.47). Presumptive treatment of uncomplicated malaria remains an ingrained behaviour that is difficult to change. With or without extensive supporting interventions, levels of testing in this study remained critically low. Governments and researchers must continue to explore alternative ways of encouraging providers to deliver appropriate treatment and avoid the misuse of valuable medicines