Policy implementation and priorities to create healthy food environments using the Healthy Food Environment Policy Index (Food-EPI): A pooled level analysis across eleven European countries

Background: Food environments have been recognised as highly influential on population diets. Government policies have great potential to create healthy food environments to promote healthy diets. This study aimed to evaluate food environment policy implementation in European countries and identify priority actions for governments to create healthy food environments. Methods: The Healthy Food Environment Policy Index (Food-EPI) was used to evaluate the level of food environment policy and infrastructure support implementation in Estonia, Finland, Germany, Ireland, Italy, the Netherlands, Norway, Poland, Portugal, Slovenia, and Spain in 20192021. Evidence of implementation of food environment policies was compiled in each country and validated by government officials. National experts evaluated the implementation of policies and identified priority recommendations. Findings: Finland had the highest proportion (32%, n = 7/22) of policies shaping food environments with a high level of implementation. Slovenia and Poland had the highest proportion of policies rated at very low implementation (42%, n = 10/24 and 36%, n = 9/25 respectively). Policies regarding food provision, promotion, retail, funding, monitoring, and health in all policies were identified as the most important gaps across the European countries. Experts recommended immediate action on setting standards for nutrients of concern in processed foods, improvement of school food environments, fruit and vegetable subsidies, unhealthy food and beverage taxation, and restrictions on unhealthy food marketing to children. Interpretation: Immediate implementation of policies and infrastructure support that prioritize action towards healthy food environments is urgently required to tackle the burden of obesity and diet-related non-communicable diseases in Europe. Funding: This project has received funding from the European Union's Horizon 2020 research and innovation programme under grant agreement No 774548 and from the Joint Programming Initiative A Healthy Diet for a Healthy Life. (c) 2022 The Author(s

How does bridging social capital relate to health-behavior, overweight and obesity among low and high educated groups?: A cross-sectional analysis of GLOBE-2014

BACKGROUND: Social capital is an important determinant of health, but how specific sub-dimensions of social capital affect health and health-related behaviors is still unknown. To better understand its role for health inequalities, it is important to distinguish between bonding social capital (connections between homogenous network members; e.g. similar educational level) and bridging social capital (connections between heterogeneous network members). In this study, we test the hypotheses that, 1) among low educational groups, bridging social capital is positively associated with health-behavior, and negatively associated with overweight and obesity, and 2) among high educational groups, bridging social capital is negatively associated with health-behavior, and positively with overweight and obesity. METHODS: Cross-sectional data on educational level, health-behavior, overweight and obesity from participants (25-75 years; Eindhoven, the Netherlands) of the 2014-survey of the GLOBE study were used (N = 2702). Social capital ("How many of your close friends have the same educational level as you have?") was dichotomized as: bridging ('about half', 'some', or 'none of my friends'), or bonding ('all' or 'most of my friends'). Logistic regression models were used to study whether bridging social capital was related to health-related behaviors (e.g. smoking, food intake, physical activity), overweight and obesity, and whether these associations differed between low and high educational groups. RESULTS: Among low educated, having bridging social capital (i.e. friends with a higher educational level) reduced the likelihood to report overweight (OR 0.73, 95% CI 0.52-1.03) and obesity (OR 0.58, 95% CI 0.38-0.88), compared to low educated with bonding social capital. In contrast, among high educated, having bridging social capital (i.e. friends with a lower educational level) increased the likelihood to report daily smoking (OR 2.11, 95% CI 1.37-3.27), no leisure time cycling (OR 1.55, 95% CI 1.17-2.04), not meeting recommendations for vegetable intake (OR 2.09, 95% CI 1.50-2.91), and high meat intake (OR 1.39, 95% CI 1.05-1.83), compared to high educated with bonding social capital. CONCLUSIONS: Bridging social capital had differential relations with health-behavior among low and high educational groups. Policies aimed at reducing segregation between educational groups may reduce inequalities in overweight, obesity and unhealthy behaviors

Food and health promotion literacy among employees with a low and medium level of education in the Netherlands

Abstract Background Prior research indicates a positive association between socioeconomic position and health literacy levels. We hypothesize comparable socioeconomic gradients for food literacy. This study aims to determine the level of self-perceived food literacy and health promotion literacy among adults with a low and medium level of education and from various subgroups, as well as the association between these food and health literacy levels. Furthermore, this study aims to explore the associations of self-perceived food literacy (SPFL) and health promotion literacy (HPL) in BMI. Methods A cross-sectional study was conducted among employees with a low and medium level of education. Descriptive analyses were performed to compute SPFL and HPL levels. Analyses of variance were performed to test differences between subgroups. The correlation between SPFL and HPL was computed by Pearson’s r. Multivariate linear regression analyses were used to explore 1) the association between SPFL and HPL adjusted for demographic characteristics 2) the associations between SPFL and HPL in BMI. Results The majority (63.1%) of all participants (n = 222) scored low on SPFL and 34.5% scored inadequate or problematic on HPL. No significant educational or weight-status differences were found in SPFL or HPL levels. On most levels, women compared to men and older compared to younger employees scored significantly higher. A small positive correlation between the two mean levels was found, r = .25, P &lt; .001 (n = 203). Multivariate linear regression analyses showed a significant association between SPFL and HPL (B = .31, 95% CI = .15–.48). No significant associations between SPFL and HPL in BMI were found. Conclusions This study suggests there is room for improvement in SPFL and HPL among adults with a low and medium level of education. Future research should consider comparing low and middle socioeconomic with high socioeconomic groups when exploring food and health literacy. Regarding health promotion activities for adults with a low and medium level of education, it is recommended to focus on improving both food and health literacy. Furthermore, more research is needed to explore direct proxies of weight-status to better understand the role of food and health literacy in overweight patterns. </jats:sec

Relations between the residential fast-food environment and the individual risk of cardiovascular diseases in The Netherlands : A nationwide follow-up study

Background The food environment has been hypothesized to influence cardiovascular diseases such as hypertension and coronary heart disease. This study determines the relation between fast-food outlet density (FFD) and the individual risk for cardiovascular disease, among a nationwide Dutch sample. Methods After linkage of three national registers, a cohort of 2,472,004 adults (≥35 years), free from cardiovascular disease at January 1st 2009 and living at the same address for ≥15 years was constructed. Participants were followed for one year to determine incidence of cardiovascular disease, including coronary heart disease, stroke and heart failure. Street network-based buffers of 500 m, 1000 m and 3000 m around residential addresses were calculated, while FFD was determined using a retail outlet database. Logistic regression analyses were conducted. Models were stratified by degree of urbanization and adjusted for age, sex, ethnicity, marital status, comorbidity, neighbourhood-level income and population density. Results In urban areas, fully adjusted models indicated that the incidence of cardiovascular disease and coronary heart disease was significantly higher within 500 m buffers with one or more fast-food outlets as compared with areas with no fast-food outlets. An elevated FFD within 1000 m was associated with an significantly increased incidence of cardiovascular disease and coronary heart disease. Evidence was less pronounced for 3000 m buffers, or for stroke and heart-failure incidence. Conclusions Elevated FFD in the urban residential environment (≤1000 m) was related to an increased incidence of cardiovascular heart disease and coronary heart disease. To better understand how FFD is associated with cardiovascular disease, future studies should account for a wider range of lifestyle and environmental confounders than was achieved in this study

Relations between the residential fast-food environment and the individual risk of cardiovascular diseases in The Netherlands : A nationwide follow-up study

Background The food environment has been hypothesized to influence cardiovascular diseases such as hypertension and coronary heart disease. This study determines the relation between fast-food outlet density (FFD) and the individual risk for cardiovascular disease, among a nationwide Dutch sample. Methods After linkage of three national registers, a cohort of 2,472,004 adults (≥35 years), free from cardiovascular disease at January 1st 2009 and living at the same address for ≥15 years was constructed. Participants were followed for one year to determine incidence of cardiovascular disease, including coronary heart disease, stroke and heart failure. Street network-based buffers of 500 m, 1000 m and 3000 m around residential addresses were calculated, while FFD was determined using a retail outlet database. Logistic regression analyses were conducted. Models were stratified by degree of urbanization and adjusted for age, sex, ethnicity, marital status, comorbidity, neighbourhood-level income and population density. Results In urban areas, fully adjusted models indicated that the incidence of cardiovascular disease and coronary heart disease was significantly higher within 500 m buffers with one or more fast-food outlets as compared with areas with no fast-food outlets. An elevated FFD within 1000 m was associated with an significantly increased incidence of cardiovascular disease and coronary heart disease. Evidence was less pronounced for 3000 m buffers, or for stroke and heart-failure incidence. Conclusions Elevated FFD in the urban residential environment (≤1000 m) was related to an increased incidence of cardiovascular heart disease and coronary heart disease. To better understand how FFD is associated with cardiovascular disease, future studies should account for a wider range of lifestyle and environmental confounders than was achieved in this study