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Background: Air pollution contributes to a large disease burden and some populations are disproportionately exposed. We aimed to evaluate ethnic and socioeconomic differences in exposure to air pollution in the Netherlands. Methods: We did a nationwide, cross-sectional analysis of all residents of the Netherlands on Jan 1, 2019. Sociodemographic information was centralised by Statistics Netherlands and mainly originated from the National Population Register, the tax register, and education registers. Concentrations of NO2, PM2·5, PM10, and elemental carbon, modelled by the National Institute for Public Health and the Environment, were linked to the individual-level demographic data. We assessed differences in air pollution exposures across the 40 largest minority ethnic groups. Evaluation of how ethnicity intersected with socioeconomic position in relation to exposures was done for the ten largest ethnic groups, plus Chinese and Indian groups, in both urban and rural areas using multivariable linear regression analyses. Findings: The total study population consisted of 17 251 511 individuals. Minority ethnic groups were consistently exposed to higher levels of air pollution than the ethnic Dutch population. The magnitude of inequalities varied between the minority ethnic groups, with 3–44% higher exposures to NO2 and 1–9% higher exposures to PM2·5 compared with the ethnic Dutch group. Average exposures were highest for the lowest socioeconomic group. Ethnic inequalities in exposure remained after adjustment for socioeconomic position and were of similar magnitude in urban and rural areas. Interpretation: The variability in air pollution exposure across ethnic and socioeconomic subgroups in the Netherlands indicates environmental injustice at the intersection of social characteristics. The health consequences of the observed inequalities and the underlying processes driving them warrant further investigation.

Background: National food environment policies can contribute to the reduction of diet-related non-communicable diseases. Yet, their implementation in the Netherlands remains low. It has been hypothesized that the media can play a pivotal role in inducing spikes in policy attention, thereby shaping political action. The aim of this study was to examine the discourse on food policies in Dutch newspaper articles between 2000–2022, by analyzing arguments used by various actors. Methods: A systematic search in Nexis Uni was used to identify newspaper articles that covered national-level Dutch food environment policies published in seven Dutch national newspapers between 2000–2022. Covered policies were classified into six domains including food composition, labeling, promotion, prices, provision and retail and into the four stages of the policy cycle; policy formulation, decision-making, implementation, and evaluation. A grey literature search was used to identify food policies implemented during 2000–2022. Descriptive statistics were used to summarize coverage of policies over time, policy type and policy stage. An interpretive content analysis was performed on a random subsample of the newspaper articles to determine the actors, viewpoints and arguments of the food policies. Results: We identified 896 relevant newspaper articles. The coverage of food policies in newspapers was initially low but peaked in 2018/2021/2022. Through grey literature search we identified 6 food policies which were implemented or adjusted between 2000–2022. The majority of the newspaper articles reported on food pricing policies and were discussed in the policy formulation stage. Academics (mainly supportive) were the most and food industry (mostly opposing) the least cited actors. Supportive arguments highlighted health consequences, health inequalities and collective responsibility, whereas opposing arguments focused on unwanted governmental interference and ineffectiveness of policies. Con

The aim of this study is to describe how individuals use different food retailers and how food retail usage varies according to socio-demographic and diet-related characteristics. A cross-sectional survey among Dutch adults (N = 1784) was used. Results from the Two-step cluster analysis indicated that there were five clusters of food retail users. Use of discount supermarkets, organic supermarkets, fast-food outlets, and restaurants contributed to clustering, but use of regular supermarkets, local food shops and whether food retailers were close to home or further from home did not. The clusters included mixed food outlet users, discount supermarket and restaurant users, fast-food and restaurant users, predominant discount supermarket users and supermarkets, fast-food and restaurant users. Participants in each cluster had their own characteristics especially in terms of socio-economic position and diet quality. Future studies need to consider further how food retail selection links physical exposure to the food environment and diet.

This area-level cross-sectional study examined online food outlet availability through the most popular online food delivery service platforms (OFDS) across seven European countries, and explored how this online food outlet availability was socioeconomically distributed. Data collection of online food outlet availability was automated in England, Italy, Luxembourg, the Netherlands, Portugal, Spain and Switzerland. We used a geographic information system to join online food outlet availability to socio-demographic information. Median number of food outlets delivering through OFDS was highest in England and lowest in Italy, Portugal and Spain. We also found that high-income areas have the greatest online food outlet availability in most countries. In England, areas with a middle income had the least online food outlets available and no income data was available for Switzerland. Further work is needed to understand drivers of disparities in online food outlet availability, as well as possible implications for public health.

We assessed the quality of food-related OpenStreetMap (OSM) data in urban areas of five European countries. We calculated agreement statistics between point-of-interests (POIs) from OSM and from Google Street View (GSV) in five European regions. We furthermore assessed correlations between exposure measures (distance and counts) from OSM data and administrative data from local data sources on food environment data in three European countries. Agreement between POI data in OSM compared to GSV was poor, but correlations were moderate to high between exposures from OSM and local data sources. OSM data downloaded in 2020 seems to be an acceptable source of data for generating count-based food exposure measures for research in selected European regions.

The evidence of selective daily mobility bias distorting exposure-health associations is limited. Using 7-day smartphone-based global positioning system (GPS) tracking data for 67 Dutch adults aged 25–45, we conducted paired Wilcoxon tests to compare the absolute and relative exposure to food outlets along actual and modelled commuting routes. We fitted Tobit regressions to examine their associations with three daily snack and soft drink intake outcomes. We found significant differences in absolute food outlet exposure between two types of routes. Adjusted regression analyses yielded unexpected associations between dietary intakes and food outlet exposures. Our results suggested no evidence of a selective daily mobility bias in the association between the food environment along commuting routes and adults’ snacks and soft drink consumption in this sample.

Background Supermarkets are the primary source of food for many people yet their full potential as a setting to encourage healthy dietary-related behaviours remains underutilised. Sharing the experiences from research groups who have worked with supermarket chains to evaluate strategies that promote healthy eating could improve the efficiency of building such relationships and enhance the design quality of future research studies. Methods A collective case study approach was used to synthesise experiences of engaging and sustaining researchcollaborations with national supermarket chains to test the effectiveness of health-focused in-store interventions. The collective narrative covers studies conducted in three high-income countries: Australia, the Netherlands and theUnited Kingdom. Results We have distilled our experiences and lessons learned into six recommendations for conducting high quality public health research with commercial supermarket chains. These include: (i) using personal contacts, knowledge of supermarket activities and engaging executive management to establish a partnership and allowing time to build trust; (ii) using scientifically robust study designs with appropriate sample size calculations; (iii) formalising data exchange arrangements and allocating adequate resource for data extraction and re-categorisation; (iv) assessing effects at individual/households level where possible; (v) designing a mixed-methods process evaluation to measure intervention fidelity, dose and unintended consequences; and (vi) ensuring scientific independence through formal contract agreements. Conclusions Our collective experiences of working in non-financial partnerships with national supermarket chains could be useful for other research groups looking to develop and implement supermarket studies in an efficient manner. Further evidence from real-life supermarket interventions is necessary to identify sustainable strategies that can improve population diet and mainta

Abstract Objective: The current study aimed to explore the interplay between food insecurity, fast-food outlet exposure and dietary quality in disadvantaged neighbourhoods. Design: In this cross-sectional study, main associations between fast-food outlet density and proximity, food insecurity status and dietary quality were assessed using Generalized Estimating Equation analyses. We assessed potential moderation by fast-food outlet exposure in the association between food insecurity status and dietary quality by testing for effect modification between food insecurity status and fast-food outlet density and proximity. Setting: A deprived urban area in the Netherlands. Participants: We included 226 adult participants with at least one child below the age of 18 years living at home. Results: Fast-food outlet exposure was not associated with experiencing food insecurity (fast-food outlet density: b = -0·026, 95 % CI = -0·076; 0·024; fast-food outlet proximity: b = -0·003, 95 % CI = -0·033; 0·026). Experiencing food insecurity was associated with lower dietary quality (b = -0·48 per unit increase, 95 % CI = -0·94; -0·012). This association was moderated by fast-food outlet proximity (P interaction = 0·008), and stratified results revealed that the adverse effect of food insecurity on dietary quality was more pronounced for those with the nearest fast-food outlet located closer to the home. Conclusions: Food insecurity but not fast-food outlet density is associated with dietary quality. However, the association between food insecurity and dietary quality may be modified by the food environment. These findings could inform policymakers to promote a healthier food environment including less fast-food outlets, with particular emphasis on areas with high percentages of food insecure households.

Abstract Objective: The aim of the current study was to establish whether the neighbourhood food environment, characterised by the healthiness of food outlets, the diversity of food outlets and fast-food outlet density within a 500 m or 1000 m street network buffer around the home address, contributed to ethnic differences in diet quality. Design: Cross-sectional cohort study. Setting: Amsterdam, the Netherlands. Participants: Data on adult participants of Dutch, South-Asian Surinamese, African Surinamese, Turkish and Moroccan descent (n total 4728) in the HELIUS study were analysed. Results: The neighbourhood food environment of ethnic minority groups living in Amsterdam is less supportive of a healthy diet and of less diversity than that of participants of Dutch origin. For example, participants of Turkish, Moroccan and South-Asian Surinamese descent reside in a neighbourhood with a significantly higher fast-food outlet density (≤1000 m) than participants of Dutch descent. However, we found no evidence that neighbourhood food environment characteristics directly contributed to ethnic differences in diet quality. Conclusion: Although ethnic minority groups lived in less healthy food environments than participants of ethnic Dutch origin, this did not contribute to ethnic differences in diet quality. Future research should investigate other direct or indirect consequences of residing in less supportive food environments and gain a better understanding of how different ethnic groups make use of their neighbourhood food environment.

Background: There is limited evidence regarding socioeconomic inequalities of exposure to the food environment and its contribution to childhood obesity. Methods: We used data from 4235 children from the Generation R Study, a large birth-cohort conducted in the city of Rotterdam, The Netherlands. We included 11,277 person-observations of body mass index (BMI) and 6240 person-observations of DXA-derived fat mass index (FMI) and fat-free mass index (FFMI) when children were between 4 and 14 years. We applied linear regression models to evaluate changes in the relative and absolute exposure of fast-food outlets, and the healthiness of the food environment within 400 m from home by maternal education. Furthermore, we used individual-level fixed-effects models to study changes in the food environment to changes in BMI, FMI and FFMI. Results: Children from lower educated mothers were exposed to more fast-food outlets at any time-point between the age of 4 and 14 years. Over a median period of 7.1 years, the absolute (0.6 fast-food outlet (95% CI: 0.4–0.8)) and relative (2.0%-point (95% CI: 0.7–3.4)) amount of fast-food outlets increased more for children from lower as compared to higher educated mothers. The food environment became more unhealthy over time, but no differences in trends were seen by maternal education level. Changes in the food environment were not associated with subsequent changes in BMI, FMI and FFMI. For children from lower educated mothers not exposed to fast-food at first, we found some evidence that the introduction of fast-food was associated with small increases in BMI. Conclusions: Our findings provide evidence of widening inequalities in exposure to fast-food in an already poor food environment. Access to more fast-food outlets does not seem to have an additional impact on BMI in contemporary contexts with ubiquitous fast-food outlets.

Background: There is limited evidence regarding socioeconomic inequalities of exposure to the food environment and its contribution to childhood obesity. Methods: We used data from 4235 children from the Generation R Study, a large birth-cohort conducted in the city of Rotterdam, The Netherlands. We included 11,277 person-observations of body mass index (BMI) and 6240 person-observations of DXA-derived fat mass index (FMI) and fat-free mass index (FFMI) when children were between 4 and 14 years. We applied linear regression models to evaluate changes in the relative and absolute exposure of fast-food outlets, and the healthiness of the food environment within 400 m from home by maternal education. Furthermore, we used individual-level fixed-effects models to study changes in the food environment to changes in BMI, FMI and FFMI. Results: Children from lower educated mothers were exposed to more fast-food outlets at any time-point between the age of 4 and 14 years. Over a median period of 7.1 years, the absolute (0.6 fast-food outlet (95% CI: 0.4–0.8)) and relative (2.0%-point (95% CI: 0.7–3.4)) amount of fast-food outlets increased more for children from lower as compared to higher educated mothers. The food environment became more unhealthy over time, but no differences in trends were seen by maternal education level. Changes in the food environment were not associated with subsequent changes in BMI, FMI and FFMI. For children from lower educated mothers not exposed to fast-food at first, we found some evidence that the introduction of fast-food was associated with small increases in BMI. Conclusions: Our findings provide evidence of widening inequalities in exposure to fast-food in an already poor food environment. Access to more fast-food outlets does not seem to have an additional impact on BMI in contemporary contexts with ubiquitous fast-food outlets.

Background Obesogenic food environments may influence dietary behaviours and contribute to obesity. Few countries quantified changes in their foodscape. We explored how the availability of different types of food retailers has changed in the Netherlands across levels of neighbourhood socioeconomic status (SES) and urbanisation. Methods This longitudinal ecological study conducted in the Netherlands had as unit of analysis administrative neighbourhoods. From 2004 to 2018, the geographic location and type of each food retailer were objectively assessed by a commercial company. Food retailers were categorised as local food shops, fast food restaurants, food delivery, restaurants, supermarkets, and convenience stores. Information on neighbourhood SES and urbanisation was obtained from Central Bureau of Statistics (CBS). To test the change in the counts of food retailers we used negative binomial generalized estimating equations (GEE), with neighbourhoods as the group variable, time as the independent variable and the counts of each type of food retailer as outcome. To account for changes in population density, analyses were adjusted for the number of inhabitants per neighbourhood. We tested effect modification by adding an interaction term for neighbourhood SES and urbanisation to the models. Results In Dutch neighbourhoods between 2004 and 2018, a 120 and 35% increase was found in the count of food delivery outlets and restaurants, respectively, and a 24% decrease in count of local food shops. Stratified analyses showed an increase in the availability of supermarkets and convenience stores in the more urbanised and lower SES neighbourhoods, while a decrease was observed in the less urbanised and higher SES neighbourhoods. Conclusions We observed considerable changes in the Dutch foodscape. Over a 14 years period, the foodscape changed towards a higher availability of food retailers offering convenience and ready-to-eat foods.

Background: Unhealthy lifestyle behaviours such as unhealthy dietary intake and insufficient physical activity (PA) tend to cluster in adults with a low socioeconomic position (SEP), putting them at high cardiometabolic disease risk. Educational approaches aiming to improve lifestyle behaviours show limited effect in this population. Using environmental and context-specific interventions may create opportunities for sustainable behaviour change. In this study protocol, we describe the design of a real-life supermarket trial combining nudging, pricing and a mobile PA app with the aim to improve lifestyle behaviours and lower cardiometabolic disease risk in adults with a low SEP. Methods: The Supreme Nudge trial includes nudging and pricing strategies cluster-randomised on the supermarket level, with: i) control group receiving no intervention; ii) group 1 receiving healthy food nudges (e.g., product placement or promotion); iii) group 2 receiving nudges and pricing strategies (taxing of unhealthy foods and subsidizing healthy foods). In collaboration with a Dutch supermarket chain we will select nine stores located in low SEP neighbourhoods, with the nearest competitor store at > 1 km distance and managed by a committed store manager. Across the clusters, a personalized mobile coaching app targeting walking behaviour will be randomised at the individual level, with: i) control group; ii) a group receiving the mobile PA app. All participants (target n = 1485) should be Dutch-speaking, aged 45-75 years with a low SEP and purchase more than half of their household grocery shopping at the selected supermarkets. Participants will be recruited via advertisements and mail-invitations followed by community-outreach methods. Primary outcomes are changes in systolic blood pressure, LDL-cholesterol, HbA1c and dietary intake after 12 months follow-up. Secondary outcomes are changes in diastolic blood pressure, blood lipid markers, waist circumference, steps per day, and be

The definition of neighborhoods as areas of exposure to the food environment is a challenge in food environment research. We aimed to test the association of density of restaurants with home cooking using four different definitions of residential neighborhoods. We also tested effect modification by age, length of residency, education, and income. This innovative cross-sectional study was conducted in the Netherlands (N = 1245 adults). We calculated geographic information system-based measures of restaurant density using residential administrative neighborhood boundaries, 800 m and 1600 m buffers around the home and respondents’ self-defined boundaries (drawn by the respondents on a map of their residential area). We used adjusted Poisson regression to test associations of restaurant density (tertiles) and the outcome ”weekly consumption of home-cooked meals” (six to seven as compared to five days per week (day/week) or fewer). Most respondents reported eating home-cooked meals for at least 6 day/week (74.2%). Regardless of the neighborhood definition used, no association between food environment and home cooking was observed. No effect modification was found. Although exposure in terms of density of restaurants was different according to the four different neighborhood definitions, we found no evidence that the area under study influences the association between density of restaurants and home cooking among Dutch adults.

Little is known about socioeconomic differences in the association between the food environment and dietary behavior. We systematically reviewed four databases for original studies conducted in adolescents and adults. Food environments were defined as all objective and perceived aspects of the physical and economic food environment outside the home. The 43 included studies were diverse in the measures used to define the food environment, socioeconomic position (SEP) and dietary behavior, as well as in their results. Based on studies investigating the economic (n = 6) and school food environment (n = 4), somewhat consistent evidence suggests that low SEP individuals are more responsive to changes in food prices and benefit more from healthy options in the school food environment. Evidence for different effects of availability of foods and objectively measured access, proximity and quality of food stores on dietary behavior across SEP groups was inconsistent. In conclusion, there was no clear evidence for socioeconomic differences in the association between food environments and dietary behavior, although a limited number of studies focusing on economic and school food environments generally observed stronger associations in low SEP populations. (Prospero registration: CRD42017073587)

Low self-control and financial strain may limit individuals’ capacity to resist temptations in the local food environment. We investigated the moderating role of self-control and financial strain in the relation between the food environment and higher body weight. We used data from 2812 Dutch adults who participated in the population-based GLOBE study in 2014. Participants’ home addresses and the location of food retailers in 2013 were mapped using GIS. The density of fast food retailers and the totality of food retailers in Euclidean buffers of 250, 400 and 800 m around the home were linked to body mass index and overweight status. A higher density of fast food outlets (B (95% confidence interval (CI)) =−0.04 (−0.07;−0.01)) and the totality of food outlets (B (95% CI) =−0.01 (−0.01; −0.00)) were associated with a lower body mass index. Stratification showed that associations were strongest for those experiencing low self-control or great financial strain. For example, every additional fast food outlet was associated with a 0.17 point lower BMI in thosewithgreatfinancialstrain,whilenotsignificantlyassociatedwithBMIinthosewithnofinancial strain. In conclusion, we did find support for a moderating role of self-control and financial strain, but associations between the food environment and weight status were not in the expected direction.