Estimating the contribution of overweight and obesity to ethnic inequalities in cardio-metabolic diseases in the Netherlands: a simulation study.

OBJECTIVES: Overweight and obesity (OWOB) starts in childhood, influences adult cardiovascular risk, and is not equally distributed across ethnic groups. It is unclear which effects can be expected from reductions in OWOB across the life course on inequalities in cardio-metabolic diseases in a multi-ethnic population. This study aims to estimate the effects of three scenarios of changes in OWOB (the Normal-Weight-for-All scenario, the No-Ethnic-Difference-over-the-Life-Course scenario, the and No-Ethnic-Differences-in-Childhood scenario). STUDY DESIGN: A simulation study. METHODS: We combine data from multiple data sources and use the Dynamic Modeling for Health Impact Assessment (DYNAMO-HIA) model to estimate the effects of three scenarios on the cumulative incidence of diabetes mellitus, ischaemic heart disease (IHD) and stroke between 18 and 70 years in the five largest ethnic groups in the Netherlands. RESULTS: In the scenario where all individuals have normal weight, the cumulative incidence decreased in all ethnic minority groups for all diseases, with largest decreases among South-Asian Surinamese, where the reduction of diabetes incidence exceeded 50%. In the scenario where the prevalence of OWOB in each ethnic-minority group was reduced to the current level among the Dutch-origin population, ethnic inequalities in cardio-metabolic diseases were substantially reduced, particularly when lowered prevalence of OWOB persisted across the lifespan. Reductions were the largest for diabetes and for the Asian Surinamese population. CONCLUSIONS: A substantial part of the well-known ethnic inequalities in incidence of diabetes, IHD, and stroke can be attributed to OWOB. Interventions aimed at reducing OWOB have clear potential to reduce the health inequalities in these outcomes, especially for diabetes, in particular when they have an impact across the lifespan.

The effect of on-shelf sugar labeling on beverage sales in the supermarket: a comparative interrupted time series analysis of a natural experiment.

BACKGROUND: Nutrition labels show potential in increasing healthy food and beverage purchases, but their effectiveness seems to depend on the type of label, the targeted food category and the setting, and evidence on their impact in real-world settings is limited. The aim of this study was to evaluate the effectiveness of an industry-designed on-shelf sugar label on the sales of beverages with no, low, medium and high sugar content implemented within a real-world supermarket. METHODS: In week 17 of 2019, on-shelf sugar labels were implemented by a Dutch supermarket chain. Non-alcoholic beverages were classified using a traffic-light labeling system and included the beverage categories "green" for sugar free (< 1.25 g/250 ml), "blue" for low sugar (1.25-6.24 g/250 ml), "yellow" for medium sugar (6.25-13.5 g/250 ml) and "amber" for high sugar (> 13.5 g/250 ml). Store-level data on beverage sales and revenue from 41 randomly selected supermarkets for 13 weeks pre-implementation and 21 weeks post-implementation were used for analysis. In total, 30 stores implemented the on-shelf sugar labels by week 17, and the 11 stores that had not were used as comparisons. Outcome measures were differences in the number of beverages sold in the four label categories and the total revenue from beverage sales in implementation stores relative to comparison stores. Analyses were conducted using a multiple-group Interrupted Time Series Approach. Results of individual store data were combined using random effect meta-analyses. RESULTS: At the end of the intervention period, the changes in sales of beverages with green (B 3.4, 95%CI -0.3; 7.0), blue (B 0.0, 95%CI -0.6; 0.7), yellow (B 1.3, 95%CI -0.9; 3.5), and amber (B 0.9, 95%CI -5.5; 7.3) labels were not significantly different between intervention and comparison stores. The changes in total revenues for beverages at the end of the intervention period were also not significantly different between intervention and comparison stores. CONCLUSION: The implementation of an on-shelf sugar labeling system did not significantly decrease unhealthy beverage sales or significantly increase healthier beverage sales. Nutrition labeling initiatives combined with complementary strategies, such as pricing strategies or other healthy food nudging approaches, should be considered to promote healthier beverage purchases.

Monitoring the availability of healthy and unhealthy foods and non-alcoholic beverages in community and consumer retail food environments globally.

Retail food environments are increasingly considered influential in determining dietary behaviours and health outcomes. We reviewed the available evidence on associations between community (type, availability and accessibility of food outlets) and consumer (product availability, prices, promotions and nutritional quality within stores) food environments and dietary outcomes in order to develop an evidence-based framework for monitoring the availability of healthy and unhealthy foods and non-alcoholic beverages in retail food environments. Current evidence is suggestive of an association between community and consumer food environments and dietary outcomes; however, substantial heterogeneity in study designs, methods and measurement tools makes it difficult to draw firm conclusions. The use of standardized tools to monitor local food environments within and across countries may help to validate this relationship. We propose a step-wise framework to monitor and benchmark community and consumer retail food environments that can be used to assess density of healthy and unhealthy food outlets; measure proximity of healthy and unhealthy food outlets to homes/schools; evaluate availability of healthy and unhealthy foods in-store; compare food environments over time and between regions and countries; evaluate compliance with local policies, guidelines or voluntary codes of practice; and determine the impact of changes to retail food environments on health outcomes, such as obesity.