Time-varying exposure to food retailers and cardiovascular disease hospitalization and mortality in the netherlands: a nationwide prospective cohort study.

BACKGROUND: Very few studies to date investigated the prospective association of changes in exposure to the food environment with cardiovascular disease (CVD) risk. We aim to explore if time-varying exposure to the food environment was associated with hospitalization and mortality due to total and specific types of CVD in The Netherlands. METHODS: In this prospective cohort study, 4,641,435 Dutch adults aged 35 + years who did not change residence in 2002-2018 were identified through registry data. Exposure to the food environment was defined as time-varying Food Environment Healthiness Index (FEHI) scores (range: - 5 to 5) and time-varying kernel density of specific food retailers (e.g., fast food outlets, supermarkets) around the home location between 2004 and 2018. The main outcome measures were hospitalization and mortality due to overall CVD, stroke, HF, and CHD occurring between 2004 and 2020, based on hospital and death registries. RESULTS: In Cox regression models, each unit increase in the FEHI was associated with a lower hospitalization and mortality of CVD (hospitalization hazard ratio (HRh) = 0.90 (0.89 to 0.91), mortality hazard ratio (HRm) = 0.85 (0.82 to 0.89)), CHD (HRh = 0.88 (0.85 to 0.91), HRm = 0.80 (0.75 to 0.86)), stroke (HRh = 0.89 (0.84 to 0.93)), HRm = 0.89 (0.82 to 0.98)), and HF (HRh = 0.90 (0.84-0.96), HRm = 0.84 (0.76 to 0.92)). Increased density of local food shops, fast food outlets, supermarkets, and convenience stores and decreased density of food delivery outlets and restaurants were associated with a higher risk of CVD, CHD, stroke, and HF hospitalization and mortality. CONCLUSIONS: In this observational longitudinal study, changes in exposure to a healthier food environment over 14 years were associated with a risk reduction in CVD hospitalization and mortality, in particular in urbanized areas and for younger adults and those with higher incomes.

Are Dutch adults equally susceptible to nudging and pricing strategies? Secondary analyses of the Supreme Nudge parallel cluster-randomised controlled supermarket trial.

BACKGROUND: Supermarket interventions are promising to promote healthier dietary patterns, but not all individuals may be equally susceptible. We explored whether the effectiveness of nudging and pricing strategies on diet quality differs by psychological and grocery shopping characteristics. METHODS: We used data of the 12-month Supreme Nudge parallel cluster-randomised controlled supermarket trial, testing nudging and pricing strategies to promote healthier diets. Participants were Dutch speaking adults aged 30-80 years and regular shoppers of participating supermarkets (n = 12) in socially disadvantaged neighbourhoods. Data on psychological characteristics (food-related behaviours; price sensitivity; food decision styles; social cognitive factors; self-control) and grocery shopping characteristics (time spent in the supermarket; moment of the day; average supermarket visits; shopping at other retailers; supermarket proximity) were self-reported at baseline. These characteristics were tested for their moderating effects of the intervention on diet quality (scored 0-150) in linear mixed models. RESULTS: We included 162 participants from intervention supermarkets and 199 from control supermarkets (73% female, 58 (± 10.8) years old, 42% highly educated). The interventions had no overall effect on diet quality. Only five out of 23 potential moderators were statistically significant. Yet, stratified analyses of these significant moderators showed no significant effects on diet quality for one of the subgroups and statistically non-significant negative effects for the other. Negative effects were suggested for individuals with lower baseline levels of meal planning (ß - 2.6, 95% CI - 5.9; 0.8), healthy shopping convenience (ß - 3.0, 95% CI - 7.2; 1.3), and healthy food attractiveness (ß - 3.5, 95% CI - 8.3; 1.3), and with higher levels of price consciousness (ß - 2.6, 95% CI - 6.2; 1.0) and weekly supermarket visits (ß - 2.4, 95% CI - 6.8; 1.9). CONCLUSIONS: Adults with varying psychological and grocery shopping characteristics largely seem equally (un)susceptible to nudging and pricing strategies. It might be that certain characteristics lead to adverse effects, but this is not plausible, and the observed negative effects were small and statistically non-significant and may be explained by chance findings. Verification of these findings is needed in real-world trials based on larger sample sizes and with the use of more comprehensive interventions. TRIAL REGISTRATION: Dutch Trial Register ID NL7064, 30th of May, 2018, https://onderzoekmetmensen.nl/en/trial/20990.

Real-world nudging, pricing, and mobile physical activity coaching was insufficient to improve lifestyle behaviours and cardiometabolic health: the Supreme Nudge parallel cluster-randomised controlled supermarket trial.

BACKGROUND: Context-specific interventions may contribute to sustained behaviour change and improved health outcomes. We evaluated the real-world effects of supermarket nudging and pricing strategies and mobile physical activity coaching on diet quality, food-purchasing behaviour, walking behaviour, and cardiometabolic risk markers. METHODS: This parallel cluster-randomised controlled trial included supermarkets in socially disadvantaged neighbourhoods across the Netherlands with regular shoppers aged 30-80 years. Supermarkets were randomised to receive co-created nudging and pricing strategies promoting healthier purchasing (N = 6) or not (N = 6). Nudges targeted 9% of supermarket products and pricing strategies 3%. Subsequently, participants were individually randomised to a control (step counter app) or intervention arm (step counter and mobile coaching app) to promote walking. The primary outcome was the average change in diet quality (low (0) to high (150)) over all follow-up time points measured with a validated 40-item food frequency questionnaire at baseline and 3, 6, and 12 months. Secondary outcomes included healthier food purchasing (loyalty card-derived), daily step count (step counter app), cardiometabolic risk markers (lipid profile and HbA1c via finger prick, and waist circumference via measuring tape), and supermarket customer satisfaction (questionnaire-based: very unsatisfied (1) to very satisfied (7)), evaluated using linear mixed-models. Healthy supermarket sales (an exploratory outcome) were analysed via controlled interrupted time series analyses. RESULTS: Of 361 participants (162 intervention, 199 control), 73% were female, the average age was 58 (SD 11) years, and 42% were highly educated. Compared to the control arm, the intervention arm showed no statistically significant average changes over time in diet quality (ߠ- 1.1 (95% CI - 3.8 to 1.7)), percentage healthy purchasing (ß 0.7 ( - 2.7 to 4.0)), step count (ߠ- 124.0 (- 723.1 to 475.1), or any of the cardiometabolic risk markers. Participants in the intervention arm scored 0.3 points (0.1 to 0.5) higher on customer satisfaction on average over time. Supermarket-level sales were unaffected (ß - 0.0 (- 0.0 to 0.0)). CONCLUSIONS: Co-created nudging and pricing strategies that predominantly targeted healthy products via nudges were unable to increase healthier food purchases and intake nor improve cardiometabolic health. The mobile coaching intervention did not affect step count. Governmental policy measures are needed to ensure more impactful supermarket modifications that promote healthier purchases. TRIAL REGISTRATION: Dutch Trial Register ID NL7064, 30 May 2018, https://www.onderzoekmetmensen.nl/en/trial/20990.

Social cohesion and associations with sedentary time, physical activity and dietary quality in The Maastricht Study.

INTRO: We aim to investigate the relationship between social cohesion and sedentary behavior (SB), total physical activity (PA), moderate-to-vigorous PA (MVPA), and dietary quality. Additionally, we assess whether these associations are independent of neighborhood walkability and the food environment. METHODS: A total of 7641 participants from The Maastricht Study in the Netherlands between the ages of 40 and 75 years were analyzed. Neighborhood social cohesion was obtained by participant questionnaire completed at baseline and measured by the Dutch Livability meter. Home addresses were linked to geographic information system (GIS) data from the Geoscience and Health Cohort Consortium (GECCO) to create neighborhood exposures of walkability and food environment. A thigh worn accelerometer collected data to measure sedentary time, total daily PA, and MVPA. Dietary quality was measured with a food frequency questionnaire. Multivariate linear regression analyses were adjusted for age, sex, socioeconomic position, neighborhood walkability, and food environment. RESULTS: Those living in the highest quartile area of perceived social cohesion had statistically significant lower levels of SB (Q4 B: -13.04; 95% CI = -20.23, -5.85), higher total PA (Q4 B: 4.39; 95% CI = 1.69, 7.10), and higher MVPA (Q4 B: 2.57; 95% CI = 0.83, 4.31) and better diet quality (Q4 B: 1.12; 95% CI = 0.24, 2.01) compared to the lowest quartile independent of walkability and food environment. Similar results were found using the Livability meter. CONCLUSION: We discovered neighborhood social cohesion as an important obesogenic determinant that should be considered in policymaking to encourage higher levels of PA and higher diet quality.

The neighourhood obesogenic built environment characteristics (OBCT) index: Practice versus theory.

BACKGROUND: Obesity is a key risk factor for major chronic diseases such as type 2 diabetes and cardiovascular diseases. To extensively characterise the obesogenic built environment, we recently developed a novel Obesogenic Built environment CharacterisTics (OBCT) index, consisting of 17 components that capture both food and physical activity (PA) environments. OBJECTIVES: We aimed to assess the association between the OBCT index and body mass index (BMI) in a nationwide health monitor. Furthermore, we explored possible ways to improve the index using unsupervised and supervised methods. METHODS: The OBCT index was constructed for 12,821 Dutch administrative neighbourhoods and linked to residential addresses of eligible adult participants in the 2016 Public Health Monitor. We split the data randomly into a training (two-thirds; n = 255,187) and a testing subset (one-third; n = 127,428). In the training set, we used non-parametric restricted cubic regression spline to assess index's association with BMI, adjusted for individual demographic characteristics. Effect modification by age, sex, socioeconomic status (SES) and urbanicity was examined. As improvement, we (1) adjusted the food environment for address density, (2) added housing price to the index and (3) adopted three weighting strategies, two methods were supervised by BMI (variable selection and random forest) in the training set. We compared these methods in the testing set by examining their model fit with BMI as outcome. RESULTS: The OBCT index had a significant non-linear association with BMI in a fully-adjusted model (p<0.05), which was modified by age, sex, SES and urbanicity. However, variance in BMI explained by the index was low (<0.05%). Supervised methods increased this explained variance more than non-supervised methods, though overall improvements were limited as highest explained variance remained <0.5%. DISCUSSION: The index, despite its potential to highlight disparity in obesogenic environments, had limited association with BMI. Complex improvements are not necessarily beneficial, and the components should be re-operationalised.

The association of obesogenic environments with weight status, blood pressure, and blood lipids: A cross-sectional pooled analysis across five cohorts.

In this observational cross-sectional study, we investigated the relationship between combined obesogenic neighbourhood characteristics and various cardiovascular disease risk factors in adults, including BMI, systolic blood pressure, and blood lipids, as well as the prevalence of overweight/obesity, hypertension, and dyslipidaemia. We conducted a large-scale pooled analysis, comprising data from five Dutch cohort studies (n = 183,871). Neighbourhood obesogenicity was defined according to the Obesogenic Built-environmental CharacterisTics (OBCT) index. The index was calculated for 1000m circular buffers around participants' home addresses. For each cohort, the association between the OBCT index and prevalence of overweight/obesity, hypertension and dyslipidaemia was analysed using robust Poisson regression models. Associations with continuous measures of BMI, systolic blood pressure, LDL-cholesterol, HDL-cholesterol, and triglycerides were analysed using linear regression. All models were adjusted for age, sex, education level and area-level socio-economic status. Cohort-specific estimates were pooled using random-effects meta-analyses. The pooled results show that a 10 point higher OBCT index score was significantly associated with a 0.17 higher BMI (95%CI: 0.10 to 0.24), a 0.01 higher LDL-cholesterol (95% CI: 0.01 to 0.02), a 0.01 lower HDL cholesterol (95% CI: -0.02 to -0.01), and non-significantly associated with a 0.36 mmHg higher systolic blood pressure (95%CI: -0.14 to 0.65). A 10 point higher OBCT index score was also associated with a higher prevalence of overweight/obesity (PR = 1.03; 95% CI: 1.02 to 1.05), obesity (PR = 1.04; 95% CI: 1.01 to 1.08) and hypertension (PR = 1.02; 95% CI: 1.00 to 1.04), but not with dyslipidaemia. This large-scale pooled analysis of five Dutch cohort studies shows that higher neighbourhood obesogenicity, as measured by the OBCT index, was associated with higher BMI, higher prevalence of overweight/obesity, obesity, and hypertension. These findings highlight the importance of considering the obesogenic environment as a potential determinant of cardiovascular health.

Greater exposure to PM2.5 and PM10 was associated with lower corneal nerve measures: the Maastricht study - a cross-sectional study.

BACKGROUND: Epidemiological and toxicological studies indicate that increased exposure to air pollutants can lead to neurodegenerative diseases. To further confirm this relationship, we evaluated the association between exposure to ambient air pollutants and corneal nerve measures as a surrogate for neurodegeneration, using corneal confocal microscopy. METHODS: We used population-based observational cross-sectional data from The Maastricht Study including N = 3635 participants (mean age 59.3 years, 51.6% were women, and 19.9% had type 2 diabetes) living in the Maastricht area. Using the Geoscience and hEalth Cohort COnsortium (GECCO) data we linked the yearly average exposure levels of ambient air pollutants at home address-level [particulate matter with diameters of ≤ 2.5 µm (PM2.5), and ≤ 10.0 µm (PM10), nitrogen dioxide (NO2), and elemental carbon (EC)]. We used linear regression analysis to study the associations between Z-score for ambient air pollutants concentrations (PM2.5, PM10, NO2, and EC) and Z-score for individual corneal nerve measures (corneal nerve bifurcation density, corneal nerve density, corneal nerve length, and fractal dimension). RESULTS: After adjustment for potential confounders (age, sex, level of education, glucose metabolism status, corneal confocal microscopy lag time, inclusion year of participants, smoking status, and alcohol consumption), higher Z-scores for PM2.5 and PM10 were associated with lower Z-scores for corneal nerve bifurcation density, nerve density, nerve length, and nerve fractal dimension [stß (95% CI): PM2.5 -0.10 (-0.14; -0.05), -0.04 (-0.09; 0.01), -0.11 (-0.16; -0.06), -0.20 (-0.24; -0.15); and PM10 -0.08 (-0.13; -0.03), -0.04 (-0.09; 0.01), -0.08 (-0.13; -0.04), -0.17 (-0.21; -0.12)], respectively. No associations were found between NO2 and EC and corneal nerve measures. CONCLUSIONS: Our population-based study demonstrated that exposure to higher levels of PM2.5 and PM10 are associated with higher levels of corneal neurodegeneration, estimated from lower corneal nerve measures. Our results suggest that air pollution may be a determinant for neurodegeneration assessed in the cornea and may impact the ocular surface health as well.

Associations of neighborhood social cohesion and changes in BMI-The Maastricht Study.

The role of the social environment can facilitate positive health outcomes through active community engagement, normalization of healthy behaviors, and stress buffering. We aim to examine the associations of neighborhood social cohesion with changes in BMI over time. A total of 7641 participants from The Maastricht Study between the ages of 40 and 75 years were analyzed. Weight and height were measured at baseline, and weight was self-reported annually up to 10 years of follow-up (median = 4.7 years). Perceived social cohesion was obtained by questionnaire. Home addresses for each participant were linked to geographic information system data from the Geoscience and Health Cohort Consortium to create neighborhood exposure variables including area level social cohesion, neighborhood walkability, and food environment within a 1000 m Euclidian buffer. Linear regression analyses were performed with BMI adjusted for socioeconomic variables. A mixed model analysis was carried out to examine changes in BMI. Living in the highest quartile area of individually perceived social cohesion was associated with lower BMI (Q4 B: -.53; 95% CI = -.79, -.28) compared to the lowest quartile. Similar findings were discovered using the area level measure (Q4 B: -.97; 95% CI = -1.29, -.65). There was no longitudinal association between social cohesion and BMI. Neighborhood social cohesion was associated with lower BMI classifying it as an obesogenic area characteristic that influences weight, independent of conventional built environment features.

A positive neighborhood walkability is associated with a higher magnitude of leisure walking in adults upon COVID-19 restrictions: a longitudinal cohort study.

BACKGROUND: Previous cross-sectional and longitudinal observational studies revealed positive relationships between contextual built environment components and walking behavior. Due to severe restrictions during COVID-19 pandemic lockdowns, physical activity was primarily performed within the immediate living area. Using this unique opportunity, we evaluated whether built environment components were associated with the magnitude of change in walking activity in adults during COVID-19 restrictions. METHODS: Data on self-reported demographic characteristics and walking behaviour were extracted from the prospective longitudinal Lifelines Cohort Study in the Netherlands of participants ≥ 18 years. For our analyses, we made use of the data acquired between 2014-2017 (n = 100,285). A fifth of the participants completed the questionnaires during COVID-19 restrictive policies in July 2021 (n = 20,806). Seven spatial components were calculated for a 500m and 1650m Euclidean buffer per postal code area in GIS: population density, retail and service destination density, land use mix, street connectivity, green space density, sidewalk density, and public transport stops. Additionally, the walkability index (WI) of these seven components was calculated. Using multivariable linear regression analyses, we analyzed the association between the WI (and separate components) and the change in leisure walking minutes/week. Included demographic variables were age, gender, BMI, education, net income, occupation status, household composition and the season in which the questionnaire was filled in. RESULTS: The average leisure walking time strongly increased by 127 min/week upon COVID-19 restrictions. All seven spatial components of the WI were significantly associated with an increase in leisure walking time; a 10% higher score in the individual spatial component was associated with 5 to 8 more minutes of leisure walking/week. Green space density at the 500m Euclidean buffer and side-walk density at the 1650m Euclidean buffer were associated with the highest increase in leisure walking time/week. Subgroup analysis revealed that the built environment showed its strongest impact on leisure walking time in participants not engaging in leisure walking before the COVID-19 pandemic, compared to participants who already engaged in leisure walking before the COVID-19 pandemic. CONCLUSIONS: These results provide strong evidence that the built environment, corrected for individual-level characteristics, directly links to changes observed in leisure walking time during COVID-19 restrictions. Since this relation was strongest in those who did not engage in leisure walking before the COVID-19 pandemic, our results encourage new perspectives in health promotion and urban planning.

Prioritizing a research agenda on built environments and physical activity: a twin panel Delphi consensus process with researchers and knowledge users.

BACKGROUND: The growth of urban dwelling populations globally has led to rapid increases of research and policy initiatives addressing associations between the built environment and physical activity (PA). Given this rapid proliferation, it is important to identify priority areas and research questions for moving the field forward. The objective of this study was to identify and compare research priorities on the built environment and PA among researchers and knowledge users (e.g., policy makers, practitioners). METHODS: Between September 2022 and April 2023, a three-round, modified Delphi survey was conducted among two independent panels of international researchers (n = 38) and knowledge users (n = 23) to identify similarities and differences in perceived research priorities on the built environment and PA and generate twin 'top 10' lists of the most important research needs. RESULTS: From a broad range of self-identified issues, both panels ranked in common the most pressing research priorities including stronger study designs such as natural experiments, research that examines inequalities and inequities, establishing the cost effectiveness of interventions, safety and injuries related to engagement in active transportation (AT), and considerations for climate change and climate adaptation. Additional priorities identified by researchers included: implementation science, research that incorporates Indigenous perspectives, land-use policies, built environments that support active aging, and participatory research. Additional priorities identified by knowledge users included: built environments and PA among people living with disabilities and a need for national data on trip chaining, multi-modal travel, and non-work or school-related AT. CONCLUSIONS: Five common research priorities between the two groups emerged, including (1) to better understand causality, (2) interactions with the natural environment, (3) economic evaluations, (4) social disparities, and (5) preventable AT-related injuries. The findings may help set directions for future research, interdisciplinary and intersectoral collaborations, and funding opportunities.

Longitudinal effects of environmental noise and air pollution exposure on autism spectrum disorder and attention-deficit/hyperactivity disorder during adolescence and early adulthood: The TRAILS study.

BACKGROUND: Exposure to ambient noise and air pollution may affect the manifestation and severity of Autism Spectrum Disorder (ASD) and Attention-Deficit/Hyperactivity Disorder (ADHD). However, evidence is limited, and most studies solely assessed environmental exposures during pregnancy and early childhood. OBJECTIVE: To examine the longitudinal effects of ambient noise and air pollutants on ASD and ADHD symptom severity during adolescence and early adulthood. METHODS: Using a longitudinal design, we included 2750 children between 10 and 12 years old from the TRacking Adolescents' Individual Lives Survey (TRAILS) in the Netherlands, who were assessed in 6 waves from 2001 to 2017. ASD was measured by the Children's Social Behavior Questionnaire and the Adult Social Behavior Questionnaire. ADHD was measured by Child Behavior Checklist and the Adult Behavior Checklist. Ambient noise and air pollution exposures, including Ozone (O3), soot, sulfur dioxide (SO2), nitrogen dioxide (NO2), particulate matter 2.5 (PM2.5), and PM10 were modeled at the residential level according to standardized protocols. The longitudinal associations between exposures and symptom outcomes were examined using linear mixed models. RESULTS: We found evidence that higher levels of exposure to PM were associated with more severe ASD and ADHD symptoms. This association decreased over time. We did not observe any other consistent associations of noise or other air pollutants with ASD and ADHD severity. CONCLUSION: The current study provides evidence for the negative impact of PM on ASD and ADHD symptoms. We did not find evidence of the negative health impact of other air pollutants and noise exposures on ASD or ADHD symptoms. Our study adds more evidence on the presence of associations between PM air pollution and neurodevelopmental diseases among adolescents and young adults.

Individual and environmental determinants of serum ferritin levels: A structural equation model.

BACKGROUND AND OBJECTIVES: Serum ferritin levels are increasingly being used to assess iron stores. Considerable variation in ferritin levels within and between individuals has been observed, but our current understanding of factors that explain this variation is far from complete. We aim to combine multiple potential determinants in an integrative model, and investigate their relative importance and potential interactions. METHODS: We use ferritin measurements collected by Sanquin Blood Bank on both prospective (N = 59 596) and active blood donors (N = 78 318) to fit a structural equation model with three latent constructs (individual characteristics, donation history, and environmental factors). Parameters were estimated separately by sex and donor status. RESULTS: The model explained 25% of ferritin variance in prospective donors, and 40% in active donors. Individual characteristics and donation history were the most important determinants of ferritin levels in active donors. The association between environmental factors and ferritin was smaller but still substantial; higher exposure to air pollution was associated with higher ferritin levels, and this association was considerably stronger for active blood donors than for prospective donors. DISCUSSION: In active donors, individual characteristics explain 20% (17%) of ferritin variation, donation history explains 14% (25%) and environmental factors explain 5% (4%) for women (men). Our model presents known ferritin determinants in a broader perspective, allowing for comparison with other determinants as well as between new and active donors, or between men and women.

Better understanding determinants of dietary guideline adherence among Dutch adults with varying socio-economic backgrounds through a mixed-methods exploration.

OBJECTIVE: Low dietary guideline adherence is persistent, but there is limited understanding of how individuals with varying socio-economic backgrounds reach a certain dietary intake. We investigated how quantitative and qualitative data on dietary guidelines adherence correspond and complement each other, to what extent determinants of guideline adherence in quantitative data reflect findings on determinants derived from qualitative data and which of these determinants emerged as interdependent in the qualitative data. DESIGN: This mixed-methods study used quantitative questionnaire data (n 1492) and qualitative data collected via semi-structured telephone interviews (n 24). Quantitative data on determinants and their association with total guideline adherence (scored 0-150) were assessed through linear regression. Directed content analysis was used for qualitative data. SETTING: Dutch urban areas. PARTICIPANTS: Adults aged 18-65 years. RESULTS: A range of determinants emerged from both data sources, for example higher levels of cognitive restraint (ß 5·6, 95 % CI 4·2, 7·1), habit strength of vegetables (ß 4·0, 95 % CI 3·3, 4·7) and cooking skills (ß 4·7, 95 % CI 3·5, 5·9), were associated with higher adherence. Qualitative data additionally suggested the influence of food prices, strong dietary habits and the social aspect of eating, and for the determinants cognitive restraint, habit strength related to vegetables, food prices and home cooking, some variation between interviewees with varying socio-economic backgrounds emerged in how these determinants affected guideline adherence. CONCLUSIONS: This mixed-methods exploration provides a richer understanding of why adults with varying socio-economic backgrounds do or do not adhere to dietary guidelines. Results can guide future interventions promoting healthy diets across populations.

The association between the food environment and adherence to healthy diet quality: the Maastricht Study.

OBJECTIVE: The purpose of this study is to determine if healthier neighbourhood food environments are associated with healthier diet quality. DESIGN: This was a cross-sectional study using linear regression models to analyse data from the Maastricht Study. Diet quality was assessed using data collected with a FFQ to calculate the Dutch Healthy Diet (DHD). A buffer zone encompassing a 1000 m radius was created around each participant home address. The Food Environment Healthiness Index (FEHI) was calculated using a Kernel density analysis within the buffers of available food outlets. The association between the FEHI and the DHD score was analysed and adjusted for socio-economic variables. SETTING: The region of Maastricht including the surrounding food retailers in the Netherlands. PARTICIPANTS: 7367 subjects aged 40-75 years in the south of the Netherlands. RESULTS: No relationship was identified between either the FEHI (B = 0·62; 95 % CI = -2·54, 3·78) or individual food outlets, such as fast food (B = -0·07; 95 % CI = -0·20, 0·07) and diet quality. Similar null findings using the FEHI were identified at the 500 m (B = 0·95; 95 % CI = -0·85, 2·75) and 1500 m (B = 1·57; 95 % CI = -3·30, 6·44) buffer. There was also no association between the food environment and individual items of the DHD including fruits, vegetables and sugar-sweetened beverages. CONCLUSION: The food environment in the Maastricht area appeared marginally unhealthy, but the differences in the food environment were not related to the quality of food that participants reported as intake.

Association of perceived and objective neighborhood walkability with accelerometer-measured physical activity and sedentary time in the Maastricht Study.

BACKGROUND: We investigated the association of neighborhood walkability with accelerometer-measured physical activity (PA) and sedentary behavior (SB) and examined whether objective and subjective measures of walkability resulted in similar findings. METHODS: PA and SB from the first 7689 Maastricht Study participants ages 40-75 from 2010 to 2017 were measured using accelerometers for 7 days. Mean daily step count, light-intensity PA, moderate- to vigorous- intensity PA (MVPA), and SB were calculated. Objective walkability was measured by the 7-component Dutch Walkability Index within 500 m Euclidean buffers around residential addresses of participants. Subjective walkability was obtained from the Abbreviated Neighborhood Environment Walkability Scale. Linear regression models analyzed the associations of walkability with PA and SB, controlling for potential confounders. RESULTS: Objective walkability was negatively associated with light intensity PA in the most walkable quartile (b = -14.58, 95% CI = -20.94, -8.23). Compared to participants living in the least walkable neighborhoods, those in the most walkable quartile had statistically significantly higher SB levels (b = 11.64, 95% CI = 4.95, 18.32). For subjective walkability, mean daily step count was significantly higher in the most walkable quartile (b = 509.60, 95% CI = 243.38, 775.81). Higher subjective walkability was positively associated with MVPA (b = 4.40, 95% CI = 2.56, 6.23). CONCLUSION: Living in a neighborhood with higher objective walkability was associated with lower levels of PA and higher SB levels while higher subjective walkability was associated with higher levels of PA. These results show discordant findings and thus, the effect of walkability on participant PA and SB within our sample is to be determined.

Nudging customers towards healthier food and beverage purchases in a real-life online supermarket: a multi-arm randomized controlled trial.

BACKGROUND: Nudging is increasingly used to promote healthy food choices in supermarkets. Ordering groceries online is gaining in popularity and nudging seems efficacious there as well, but is never comprehensively tested in real-life. We evaluated the real-life effectiveness of nudging in an online supermarket on healthy food purchases. METHODS: We conducted a multi-arm, parallel-group, individually randomized controlled trial in an online supermarket. During 1 month, all customers were randomized to (1) control condition, (2) information nudges, (3) position nudges, and (4) information and position nudges combined. Allocation was concealed and customers were not blinded, but unaware of the intervention. Mean differences between the control condition and the intervention arms in the total percentage of healthy purchases were assessed with a linear mixed model. We tested for effect modification by area-level deprivation. RESULTS: Based on sales data from 11,775 shoppers, no overall significant effects were detected. Yet, effects were modified by area-level deprivation (pArm 2 < 0.001). Among shoppers from deprived areas, those allocated to information nudges purchased a 2.4% (95%CI 0.8, 4.0) higher percentage of healthy products compared to controls. No significant differences were observed for position (- 1.3%; 95%CI - 2.8, 0.3) and combined nudges (- 0.1%; 95%CI - 1.7, 1.5). Shoppers from non-deprived areas exposed to information nudges (- 1.6%; 95%CI - 3.2, - 0.1) and the combined nudges (- 2.1%; 95%CI - 3.6, - 0.6), but not position nudges (- 0.9%; 95%CI - 2.4, 0.7), purchased a lower percentage of healthy products. CONCLUSION: Information nudges in an online supermarket can increase healthy product purchases, but only for those living in deprived areas. The adverse effects found on purchasing behaviors for those from non-deprived areas call for further research. Further research should also focus on real-life effects of online healthy food nudging as part of a broader nutrition intervention strategy, and on the equitability of the online nudging intervention within populations. TRIAL REGISTRATION: Retrospectively registered in the ISRCTN registry at May 21, 2021 ( ISRCTN10491616 ).

Development of an objectively measured walkability index for the Netherlands.

BACKGROUND: Walkability indices have been developed and linked to behavioural and health outcomes elsewhere in the world, but not comprehensively for Europe. We aimed to 1) develop a theory-based and evidence-informed Dutch walkability index, 2) examine its cross-sectional associations with total and purpose-specific walking behaviours of adults across socioeconomic (SES) and urbanisation strata, 3) explore which walkability components drive these associations. METHODS: Components of the index included: population density, retail and service density, land use mix, street connectivity, green space, sidewalk density and public transport density. Each of the seven components was calculated for three Euclidean buffers: 150 m, 500 m and 1000 m around every 6-digit postal code location and for every administrative neighbourhood in GIS. Componential z-scores were averaged, and final indices normalized between 0 and 100. Data on self-reported demographic characteristics and walking behaviours of 16,055 adult respondents (aged 18-65) were extracted from the Dutch National Travel Survey 2017. Using Tobit regression modelling adjusted for individual- and household-level confounders, we assessed the associations between walkability and minutes walking in total, for non-discretionary and discretionary purposes. By assessing the attenuation in associations between partial indices and walking outcomes, we identified which of the seven components drive these associations. We also tested for effect modification by urbanization degree, SES, age and sex. RESULTS: In fully adjusted models, a 10% increase in walkability was associated with a maximum increase of 8.5 min of total walking per day (95%CI: 7.1-9.9). This association was consistent across buffer sizes and purposes of walking. Public transport density was driving the index's association with walking outcomes. Stratified results showed that associations with minutes of non-discretionary walking were stronger in rural compared to very urban areas, in neighbourhoods with low SES compared to high SES, and in middle-aged (36-49 years) compared to young (18-35 years old) and older adults (50-65 years old). CONCLUSIONS: The walkability index was cross-sectionally associated with Dutch adult's walking behaviours, indicating its validity for further use in research.

Vitamin D food fortification in European countries: the underused potential to prevent cancer deaths.

BACKGROUND: Meta-analyses of randomized controlled trials have shown that vitamin D supplementation reduces cancer mortality by 13%. Vitamin D fortification of foods may increase vitamin D levels in a similar manner as vitamin D supplementation and could achieve similar reductions in cancer mortality. Whereas some European countries already implemented widespread fortification of foods with vitamin D, in other countries only few or no foods are fortified. In this study, we estimated the reduction in cancer mortality presumably already achieved by current fortification policies in 2017 and the potential for further reductions if all countries had effective fortification. METHODS: We reviewed scientific literature, publicly available information, and contacted health authorities to obtain information on current vitamin D food fortification policies in 34 European countries. Together with country-specific cancer death statistics from Eurostat, information on life expectancy, and country-specific fortification policies, we used data from studies on supplementation and serum 25(OH)D increases and cancer mortality to estimate numbers of probably already prevented cancer deaths and numbers of potentially further preventable deaths and years of life lost. RESULTS: Current vitamin D fortification is estimated to prevent approximately 11,000 in the European Union and 27,000 cancer deaths in all European countries considered per year. If all countries considered here would implement adequate vitamin D fortification of foods, an estimated additional 129,000 cancer deaths (113,000 in the European Union) could be prevented, corresponding to almost 1.2 million prevented years of life lost (1.0 million in the EU) or approximately 9% of cancer deaths (10% in the EU). INTERPRETATION: Systematic fortification of foods might considerably reduce the burden of cancer deaths in Europe.

The Physical Activity Environment Policy Index for monitoring government policies and actions to improve physical activity.

BACKGROUND: A multifaceted response, including government action, is essential to improve population levels of physical activity (PA). This article describes the development process of the 'Physical Activity Environment Policy Index' (PA-EPI) monitoring framework, a tool to assess government policies and actions for creating a healthy PA environment. METHODS: An iterative process was undertaken. This involved a review of policy documents from authoritative organizations, a PA policy audit of four European countries, and a systematic review of scientific literature. This was followed by an online consultation with academic experts (N = 101; 20 countries, 72% response rate), and policymakers (N = 40, 4 EU countries). During this process, consensus workshops were conducted, where quantitative and qualitative data, alongside theoretical and pragmatic considerations, were used to inform PA-EPI development. RESULTS: The PA-EPI is conceptualized as a two-component 'policy' and 'infrastructure support' framework. The two-components comprise eight policy and seven infrastructure support domains. The policy domains are education, transport, urban design, healthcare, public education (including mass media), sport-for-all, workplaces and community. The infrastructure support domains are leadership, governance, monitoring and intelligence, funding and resources, platforms for interaction, workforce development and health-in-all-policies. Forty-five 'good practice statements' or indicators of ideal good practice within each domain conclude the PA-EPI. A potential eight-step process for conducting the PA-EPI is described. CONCLUSIONS: Once pre-tested and piloted in several countries of various sizes and income levels, the PA-EPI good practice statements will evolve into benchmarks established by governments at the forefront of creating and implementing policies to address inactivity.

Dietary behaviour and physical activity policies in Europe: learnings from the Policy Evaluation Network (PEN).

The European Policy Evaluation Network (PEN), initiated in autumn 2018, aimed at advancing the evidence base for public policies impacting dietary behaviour, physical activity and sedentary behaviours in Europe. This is needed because non-communicable diseases-the leading cause of global mortality-are substantially caused by physical inactivity and unhealthy dietary behaviours, which in turn are driven by upstream factors that have not yet been addressed effectively by prevention approaches. Thus, successful policy interventions are required that target entire populations and tackle the 'causes of the causes'. To advance our knowledge on the effective implementation of policies and their impact in terms of improving health behaviours, PEN focused on five research tasks: (i) Adaptation and implementation of a Food Environment Policy Index (Food-EPI) and development of a Physical Activity Environment Policy Index (PA-EPI); (ii) Mapping of health-related indicators needed for policy evaluation and facilitating a harmonized pan-European approach for surveillance to assess the impact of policy interventions; (iii) Refining quantitative methods to evaluate the impact of public policies; (iv) Identifying key barriers and facilitators of implementation of policies; and (v) Advance understanding the equity impact of the development, implementation and evaluation of policies aimed at promoting physical activity and a healthy diet. Finally, and in order to provide concrete evidence for policymaking, existing exemplary policies, namely sugar-sweetened beverages taxation, active transport policies and school policies on nutrition and physical activity were assessed in consideration of these five tasks. At the end of the PEN project's formal runtime, considerable advancements have been made. Here, we present an overview of the most important learnings and outputs.