The Effects of a Supermarket-Based Intervention on the Nutritional Quality of Private-Label Foods: A Prospective Study

Epidemiological Data Mining for Assisting with Foodborne Outbreak Investigation

Diseases caused by the consumption of food are a significant but avoidable public health issue, and identifying the source of contamination is a key step in an outbreak investigation to prevent foodborne illnesses. Historical foodborne outbreaks provide rich data on critical attributes such as outbreak factors, food vehicles, and etiologies, and an improved understanding of the relationships between these attributes could provide insights for developing effective food safety interventions. The purpose of this study was to identify hidden patterns underlying the relations between the critical attributes involved in historical foodborne outbreaks through data mining approaches. A statistical analysis was used to identify the associations between outbreak factors and food sources, and the factors that were strongly significant were selected as predictive factors for food vehicles. A multinomial prediction model was built based on factors selected for predicting "simple" foods (beef, dairy, and vegetables) as sources of outbreaks. In addition, the relations between the food vehicles and common etiologies were investigated through text mining approaches (support vector machines, logistic regression, random forest, and naïve Bayes). A support vector machine model was identified as the optimal model to predict etiologies from the occurrence of food vehicles. Association rules also indicated the specific food vehicles that have strong relations to the etiologies. Meanwhile, a food ingredient network describing the relationships between foods and ingredients was constructed and used with Monte Carlo simulation to predict possible ingredients from foods that cause an outbreak. The simulated results were confirmed with foods and ingredients that are already known to cause historical foodborne outbreaks. The method could provide insights into the prediction of the possible ingredient sources of contamination when given the name of a food. The results could provide insights into the early identification of food sources of contamination and assist in future outbreak investigations. The data-driven approach will provide a new perspective and strategies for discovering hidden knowledge from massive data.

Changes in the Sodium Content in Branded Foods in the Slovenian Food Supply (2011-2020)

High sodium intake is the leading diet-related risk factor for mortality globally. Many countries have introduced policies to support the reformulation of foods and to reduce sodium intake, mainly on a voluntary basis, but there are limited data available about the long-term efficiency of such measures. Slovenia implemented salt reduction policies for the period of 2010-2020; these policies also included the voluntary reformulation of foods with the lowering of sodium content. This study's aim was to explore the nationally representative branded food datasets collected in the years 2011, 2015, 2017, and 2020 to investigate the changes in the sodium content in prepacked branded foods. The study was conducted with datasets collected from food labels using standard food monitoring studies and included all the major retailers. Differences in market shares were adjusted by sales weighting, which was conducted using the yearly sales data provided by the major retailers. The food categories with a major contribution to the overall sales of sodium in prepacked branded foods were processed meat and derivatives (19.0%), canned vegetables (7.1%), water (6.7%), bread (7.2%), and cheese (6.3%). Considering the available food products, a notable decreasing sodium content trend was observed in biscuits, breakfast cereals, pizza, and spreads. Year-to-year differences were much less expressed after the correction for market share differences, and neutral trends were most frequently highlighted. This indicates that sodium was less frequently reduced in market-leading products. The study results revealed that very limited progress in sodium food reformulation was achieved in the 10-year period, indicating the need for more efficient policy approaches. The study demonstrated the importance of the systematic monitoring of the food supply for the evaluation of food policies.

The estimated health impact of sodium reduction through food reformulation in Australia: A modeling study

BACKGROUND

The Australian Government recently established sodium targets for packaged foods to encourage voluntary reformulation to reduce population sodium consumption and related diseases. We modeled the health impact of Australia's sodium reformulation targets and additional likely health gains if more ambitious, yet feasible sodium targets had been adopted instead.

METHODS AND FINDINGS

Using comparative risk assessment models, we estimated the averted deaths, incidence, and disability-adjusted life years (DALYs) from cardiovascular disease (CVD), chronic kidney disease (CKD) and stomach cancer after implementation of (a) Australia's sodium targets (overall and by individual companies); (b) United Kingdom's targets (that covers more product categories); and (c) an optimistic scenario (sales-weighted 25th percentile sodium content for each food category included in the UK program). We used nationally representative data to estimate pre- and post-intervention sodium intake, and other key data sources from the Global Burden of Disease study. Full compliance with the Australian government's sodium targets could prevent approximately 510 deaths/year (95% UI, 335 to 757), corresponding to about 1% of CVD, CKD, and stomach cancer deaths, and prevent some 1,920 (1,274 to 2,600) new cases and 7,240 (5,138 to 10,008) DALYs/year attributable to these diseases. Over half (59%) of deaths prevented is attributed to reformulation by 5 market-dominant companies. Compliance with the UK and optimistic scenario could avert approximately an additional 660 (207 to 1,227) and 1,070 (511 to 1,856) deaths/year, respectively, compared to Australia's targets. The main limitation of this study (like other modeling studies) is that it does not prove that sodium reformulation programs will prevent deaths and disease events; rather, it provides the best quantitative estimates and the corresponding uncertainty of the potential effect of the different programs to guide the design of policies.

CONCLUSIONS

There is significant potential to strengthen Australia's sodium reformulation targets to improve its health impact. Promoting compliance by market-dominant food companies will be critical to achieving the potential health gains.

The Contribution of Major Food Categories and Companies to Household Purchases of Added Sugar in Australia

BACKGROUND

The Australian Government will soon be releasing a series of sugar reformulation targets for packaged foods.

OBJECTIVE

To estimate the amount of added sugar purchased from packaged food and beverages and the relative contribution that food categories and food companies made to these purchases in 2018. The secondary objective was to examine differences in purchases of added sugar across income levels.

DESIGN

Cross-sectional study.

PARTICIPANTS/SETTING

We used 1 year of grocery purchase data from a nationally representative panel of Australian households (the NielsenIQ Homescan panel), combined with a packaged food and beverage database (FoodSwitch).

MAIN OUTCOME MEASURES

Added sugar purchases (grams per day per capita), purchase-weighted added sugar content (grams per 100 g) and total weight of products (with added sugar) purchased (grams per day per capita).

STATISTICAL ANALYSES PERFORMED

Food categories and food companies were ranked according to their contribution to added sugar purchases. Differences in added sugar purchases by income levels were assessed by 1-factor analysis of variance.

RESULTS

Added sugar information was available from 7188 households and across 26,291 unique foods and beverages. On average, the amount of added sugar acquired from packaged foods and beverages was (mean ± SE) 35.9 ± 0.01 g/d per capita. Low-income households purchased 11.0 g/d (95% CI: 10.9-11.0 g/d, P < .001) more added sugar from packaged products than high-income households per capita. The top 10 food categories accounted for 82.2% of added sugar purchased, largely due to purchases of chocolate and sweets, soft drinks, and ice cream and edible ices. Out of 994 food companies, the top 10 companies contributed to 62.1% of added sugar purchases.

CONCLUSIONS

The Australian Government can strengthen their proposed sugar reduction program by adding further category-specific targets, prioritizing engagement with key food companies and considering a broader range of policies to reduce added sugar intakes across the Australian population.