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.

Exposome-Wide Association Study of Body Mass Index Using a Novel Meta-Analytical Approach for Random Forest Models.

BACKGROUND: Overweight and obesity impose a considerable individual and social burden, and the urban environments might encompass factors that contribute to obesity. Nevertheless, there is a scarcity of research that takes into account the simultaneous interaction of multiple environmental factors. OBJECTIVES: Our objective was to perform an exposome-wide association study of body mass index (BMI) in a multicohort setting of 15 studies. METHODS: Studies were affiliated with the Dutch Geoscience and Health Cohort Consortium (GECCO), had different population sizes (688-141,825), and covered the entire Netherlands. Ten studies contained general population samples, others focused on specific populations including people with diabetes or impaired hearing. BMI was calculated from self-reported or measured height and weight. Associations with 69 residential neighborhood environmental factors (air pollution, noise, temperature, neighborhood socioeconomic and demographic factors, food environment, drivability, and walkability) were explored. Random forest (RF) regression addressed potential nonlinear and nonadditive associations. In the absence of formal methods for multimodel inference for RF, a rank aggregation-based meta-analytic strategy was used to summarize the results across the studies. RESULTS: Six exposures were associated with BMI: five indicating neighborhood economic or social environments (average home values, percentage of high-income residents, average income, livability score, share of single residents) and one indicating the physical activity environment (walkability in 5-km buffer area). Living in high-income neighborhoods and neighborhoods with higher livability scores was associated with lower BMI. Nonlinear associations were observed with neighborhood home values in all studies. Lower neighborhood home values were associated with higher BMI scores but only for values up to €300,000. The directions of associations were less consistent for walkability and share of single residents. DISCUSSION: Rank aggregation made it possible to flexibly combine the results from various studies, although between-study heterogeneity could not be estimated quantitatively based on RF models. Neighborhood social, economic, and physical environments had the strongest associations with BMI. https://doi.org/10.1289/EHP13393.

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.

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.

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.

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.

Ethnic and socioeconomic inequalities in air pollution exposure: a cross-sectional analysis of nationwide individual-level data from the Netherlands.

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. FUNDING: The Gravitation programme of the Dutch Ministry of Education, Culture, and Science, the Netherlands Organization for Scientific Research, the Netherlands Organisation for Health Research and Development, and Amsterdam University Medical Center.

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.

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.

The built environment and cardiovascular disease: an umbrella review and meta-meta-analysis.

AIMS: To provide a comprehensive overview of the current evidence on objectively measured neighbourhood built environment exposures in relation to cardiovascular disease (CVD) events in adults. METHODS AND RESULTS: We searched seven databases for systematic reviews on associations between objectively measured long-term built environmental exposures, covering at least one domain (i.e. outdoor air pollution, food environment, physical activity environment like greenspace and walkability, urbanization, light pollution, residential noise, and ambient temperature), and CVD events in adults. Two authors extracted summary data and assessed the risk of bias independently. Robustness of evidence was rated based on statistical heterogeneity, small-study effect, and excess significance bias. Meta-meta-analyses were conducted to combine the meta-analysis results from reviews with comparable exposure and outcome within each domain. From the 3304 initial hits, 51 systematic reviews were included, covering 5 domains and including 179 pooled estimates. There was strong evidence of the associations between increased air pollutants (especially PM2.5 exposure) and increased residential noise with greater risk of CVD. Highly suggestive evidence was found for an association between increased ambient temperature and greater risk of CVD. Systematic reviews on physical activity environment, food environment, light pollution, and urbanization in relation to CVD were scarce or lacking. CONCLUSION: Air pollutants, increased noise levels, temperature, and greenspace were associated with CVD outcomes. Standardizing design and exposure assessments may foster the synthesis of evidence. Other crucial research gaps concern the lack of prospective study designs and lack of evidence from low-to-middle-income countries (LMICs). REGISTRATION: PROSPERO: CRD42021246580.

This study is a review of published systematic reviews on the relation between the neighbourhood built environment and cardiovascular disease (CVD) in adults. There was strong evidence of a relation between increased air pollutants and a greater risk of CVD. There was also strong evidence of a relation between increased residential noise and a greater risk of CVD. There was highly suggestive evidence of a relation between increased ambient temperature and a greater risk of CVD. Systematic reviews that examined other aspects of the built environment, such as the physical activity environment, food environment, light pollution, and urbanization, were scarce or lacking.

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.

Associations between the neighbourhood food environment and cardiovascular disease: a systematic review.

AIMS: To systematically review the current evidence on the association between the neighbourhood food environment and cardiovascular disease (CVD) in adults. METHODS AND RESULTS: We searched the literature databases CINAHL, MEDLINE, and EMBASE for studies published between 1 January 2000 and 1 May 2022. Studies focusing on the indoor home, workplace, or school food environment were excluded. Two independent reviewers screened all records. Included studies were assessed for risk of bias using the shortened QUIPS tool, and relevant data were extracted. We summarized the findings using a narrative synthesis approach. We included 15 studies after screening 5915 original records. Most studies were published in the last 4 years and were predominantly conducted in North American or European countries. These studies focused on fast-food restaurant density in the residential neighbourhood. A higher fast-food restaurant density was most consistently associated with a higher prevalence and incidence of CVD and CVD mortality, but effect sizes were small. Evidence of an association between fast-food restaurant density and myocardial infarction, or stroke was inconsistent. The other aspects of the food environment were density of food service restaurants, unhealthy food outlets, and food access score. However, there was scant evidence for these aspects. CONCLUSION: We found evidence for associations between the neighbourhood food environment and CVD, suggesting that a higher fast-food restaurant density is associated with CVD and CVD mortality. Effect sizes were small but important, given the fact that a large population is exposed. Research is needed to assess the effects of other aspects of the food environment. SYSTEMATIC REVIEW REGISTRATION: PROSPERO CRD42022317407.

We conducted a systematic review to examine the relationship between the neighbourhood food environment and cardiovascular disease (CVD) in adults. We searched for studies published between 1 January 2000 and 1 May 2022 in 3 major medical databases and included 15 studies. These studies were mostly conducted in North American or European countries, and most of them focused on exposure to fast-food restaurants. Overall, these studies suggest that there is a relationship between a higher density of fast-food restaurants and CVD. Three studies also examined other aspects of the food environment, such as density of food service restaurants, unhealthy food outlets, and food access score, but the evidence for these aspects was scarce. We concluded that there is evidence to suggest that the neighbourhood food environment is associated with CVD, particularly a higher fast-food restaurant density. However, more research is needed to understand other aspects of the food environment.

The quality of OpenStreetMap food-related point-of-interest data for use in epidemiological research.

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 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.

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.

SNapp, a Tailored Smartphone App Intervention to Promote Walking in Adults of Low Socioeconomic Position: Development and Qualitative Pilot Study.

BACKGROUND: Adults of low socioeconomic position (SEP) are generally less physically active than those who are more socioeconomically advantaged, which increases their cardiovascular disease incidence risk. Moreover, individuals of low SEP are often less easily reached with physical activity (PA) interventions than individuals of higher SEP. Smartphone apps have been presented as a promising platform for delivering PA interventions to difficult-to-reach individuals of low SEP. Although PA apps are widely available, they are rarely based on health behavior theories and most predominantly offer generic PA advice. Consequently, it is unlikely that available apps are the most effective PA intervention tools. OBJECTIVE: To respond to these areas for improvement, we developed SNapp, an app-based intervention encouraging adults of low SEP to increase PA by providing tailored coaching messages targeting walking behavior. This study aimed to describe SNapp's stepwise development and pilot evaluation process. METHODS: We applied a stepwise approach: analyzing the health problem, developing a program framework, developing tailoring assessments, writing tailored messages, automating the tailoring process, and implementing and evaluating the program in a qualitative pilot study (11 participants). RESULTS: SNapp consisted of several elements. First, an app was developed to collect step count and geolocation data using smartphone sensor functionalities. In addition, a survey measure was created to assess users' behavior change technique (BCT) preferences. These 3 data types were used to tailor SNapp's coaching messages to stimulate walking. This allows SNapp to offer feedback on performance levels, contextually tailored prompts when users are near green spaces, and coaching content that aligns with individual BCT preferences. Finally, a server-based Python program that interacts with databases containing user data and tailored messages was built using Microsoft Azure to select and automatically send messages to users through Telegram messenger. Pilot study findings indicated that SNapp was rated positively, with participants reporting that its design, technical functioning, and message content were acceptable. Participants suggested additional functionalities that are worth considering for future updates. CONCLUSIONS: SNapp is an app-based intervention that aims to promote walking in adults of low SEP by offering tailored coaching messages. Its development is theory based, and it is among the first to incorporate contextualized feedback and content tailored to individual BCT preferences. The effectiveness of SNapp will be evaluated in a 12-month real-life parallel cluster-randomized controlled trial.

Participant recruitment, baseline characteristics and at-home-measurements of cardiometabolic risk markers: insights from the Supreme Nudge parallel cluster-randomised controlled supermarket trial.

BACKGROUND: Recruiting participants for lifestyle programmes is known to be challenging. Insights into recruitment strategies, enrolment rates and costs are valuable but rarely reported. We provide insight into the costs and results of used recruitment strategies, baseline characteristics and feasibility of at-home cardiometabolic measurements as part of the Supreme Nudge trial investigating healthy lifestyle behaviours. This trial was conducted during the COVID-19 pandemic, requiring a largely remote data collection approach. Potential sociodemographic differences were explored between participants recruited through various strategies and for at-home measurement completion rates. METHODS: Participants were recruited from socially disadvantaged areas around participating study supermarkets (n = 12 supermarkets) across the Netherlands, aged 30-80 years, and regular shoppers of the participating supermarkets. Recruitment strategies, costs and yields were logged, together with completion rates of at-home measurements of cardiometabolic markers. Descriptive statistics are reported on recruitment yield per used method and baseline characteristics. We used linear and logistic multilevel models to assess the potential sociodemographic differences. RESULTS: Of 783 recruited, 602 were eligible to participate, and 421 completed informed consent. Most included participants were recruited via letters/flyers at home (75%), but this strategy was very costly per included participant (89 Euros). Of paid strategies, supermarket flyers were the cheapest (12 Euros) and the least time-invasive (< 1 h). Participants who completed baseline measurements (n = 391) were on average 57.6 (SD 11.0) years, 72% were female and 41% had high educational attainment, and they often completed the at-home measurements successfully (lipid profile 88%, HbA1c 94%, waist circumference 99%). Multilevel models suggested that males tended to be recruited more often via word-of-mouth (ORfemales 0.51 (95%CI 0.22; 1.21)). Those who failed the first attempt at completing the at-home blood measurement were older (ß 3.89 years (95% CI 1.28; 6.49), whilst the non-completers of the HbA1c (ß - 8.92 years (95% CI - 13.62; - 4.28)) and LDL (ß - 3.19 years (95% CI - 6.53; 0.09)) were younger. CONCLUSIONS: Supermarket flyers were the most cost-effective paid strategy, whereas mailings to home addresses recruited the most participants but were very costly. At-home cardiometabolic measurements were feasible and may be useful in geographically widespread groups or when face to face contact is not possible. TRIAL REGISTRATION: Dutch Trial Register ID NL7064, 30 May 2018, https://trialsearch.who.int/Trial2.aspx?TrialID=NTR7302.

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.

Higher Neighborhood Drivability Is Associated With a Higher Diabetes Risk in Younger Adults: A Population-Based Cohort Study in Toronto, Canada.

OBJECTIVE: Car dependency contributes to physical inactivity and, consequently, may increase the likelihood of diabetes. We investigated whether neighborhoods that are highly conducive to driving confer a greater risk of developing diabetes and, if so, whether this differs by age. RESEARCH DESIGN AND METHODS: We used administrative health care data to identify all working-age Canadian adults (20-64 years) who were living in Toronto on 1 April 2011 without diabetes (type 1 or 2). Neighborhood drivability scores were assigned using a novel, validated index that predicts driving patterns based on built environment features divided into quintiles. Cox regression was used to examine the association between neighborhood drivability and 7-year risk of diabetes onset, overall and by age-group, adjusting for baseline characteristics and comorbidities. RESULTS: Overall, there were 1,473,994 adults in the cohort (mean age 40.9 ± 12.2 years), among whom 77,835 developed diabetes during follow-up. Those living in the most drivable neighborhoods (quintile 5) had a 41% higher risk of developing diabetes compared with those in the least drivable neighborhoods (adjusted hazard ratio 1.41, 95% CI 1.37-1.44), with the strongest associations in younger adults aged 20-34 years (1.57, 95% CI 1.47-1.68, P < 0.001 for interaction). The same comparison in older adults (55-64 years) yielded smaller differences (1.31, 95% CI 1.26-1.36). Associations appeared to be strongest in middle-income neighborhoods for younger residents (middle income 1.96, 95% CI 1.64-2.33) and older residents (1.46, 95% CI 1.32-1.62). CONCLUSIONS: High neighborhood drivability is a risk factor for diabetes, particularly in younger adults. This finding has important implications for future urban design policies.