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Socioeconomic inequalities in diets need to be tackled to improve population diets and prevent obesity and diet-related non-communicable diseases. The potential of food environment policies to reduce such inequalities has to date however not been appraised. The objective of this umbrella review was to assess the impact of food environment policies on socioeconomic inequalities in diets and to identify knowledge gaps in the existing literature, using the Healthy Food Environment Policy Index as a conceptual framework. The policies considered in the umbrella review are within six domains: 1) food composition 2) food labelling 3) food promotion 4) food provision 5) food retail 6) food pricing. A systematic search for systematic literature reviews on the effect of food environment policies on dietary-related outcomes across socioeconomic groups and published in English between 2004 and 2019 was conducted. Sixteen systematic literature reviews encompassing 159 primary studies were included, covering food composition ( n  = 2), food labelling ( n  = 3), food provision ( n  = 2), food prices ( n  = 13) and food in retail ( n  = 4). Quality assessment using the “Assessing the Methodological Quality of Systematic Reviews” quality rating scale showed that review quality was mainly low or critically low. Results suggest that food taxation may reduce socioeconomic inequalities in diets. For all other policy areas, the evidence base was poor. Current research largely fails to provide good quality evidence on impacts of food environment policies on socioeconomic inequalities in diets. Research to fill this knowledge gap is urgently needed.

Household food and nutrition insecurity continued to be a development and policy agenda in Ethiopia. Assessing the patterns and determinants of household dietary diversity is an important area of research given its importance for policy uptake in the country. This study is, therefore, initiated to identify the dominant food groups consumed by households and to investigate the determinants of household dietary diversity in the country. We used data from the 4th wave of the Ethiopian socioeconomic survey. The survey data for this study included 3,115 households living in rural areas (hereafter called 'rural households'). Household Dietary Diversity Score (HDDS) was calculated and categorized as per the FAO's recommendation: low HDDS category for those who consume three or less food groups, medium HDDS for those who consume four to six, and high HDDS for those who consume seven and more food groups during the past seven days. Ordinal logistic regression model was employed to estimate the determinants of rural household's dietary diversity. Cereals were the most dominant food group consumed by 96.4% of the households followed by pulses, which was consumed by 82% of the households Nutrition-dense food commodities such as lean meat, vegetables and fruits were the least consumed food groups by households in Ethiopia. In terms of determinants of dietary diversity, female headed households have 38% more chance of consuming diverse foods compared to their male-headed counterparts (AOR = 1.38, 95% CI: 1.10, 1.73). Household heads who completed secondary education and above have 62% more chance of consuming diverse foods compared to uneducated household heads (AOR = 1.62, 95% CI: 1.2, 2.30). Household heads who are single have 37% less chance of consuming diverse foods compared to those household heads who are married (AOR = 0.63, 95% CI: 0.50, 0.80). Those households located in Harari regional state and in the rural surroundings of Diredawa town have 6.56 times more chance of consuming diverse foods compared to those households living in Tigray and Amhara regional states (AOR = 6.56, 95% CI: 4.60, 9.37). The results also highlighted that households who are in the upper wealth category have 9 times more chance of consuming diverse foods compared to those households who are the lower wealth category (AOR = 8.54, 95% CI: 6.79, 11.98).

Background Disparities in the availability, distribution, and density of formal unhealthy and healthy food outlets around schools have been observed based on sociodemographic neighborhood characteristics; however, little is known about street food outlets (SFOs). Objective To analyze the spatial characteristics of healthy and unhealthy SFOs around public schools in a Mexico City neighborhood and their association with environmental factors. Methodology A cross-sectional study was conducted to identify SFOs located within a 500-meter buffer around 67 public schools situated in a neighborhood with diverse levels of marginalization in Mexico City. The nutritional healthfulness index (NH-index)—defined as the percentage of available healthful food and beverage groups—was calculated for each SFO using a validated tool for the Mexican context. Logistic regression analyses were performed to estimate the association between null healthfulness (null-NH), defined as 0% availability of healthy food groups, and environmental characteristics. Additionally, spatial analyses were conducted to examine the distribution and density of SFOs around schools. Results In total, 1296 SFOs were identified within 500 m around schools. In total, 42.4% of them were classified as unhealthy. SFOs located in areas with a very high SDI, farther from schools, and with a higher total population per block were less likely to be classified as null-NH. Conclusions Unhealthy street food outlets are highly concentrated near public schools in vulnerable areas of Mexico City. While new regulations aim to reduce exposure to these products, further research is needed to evaluate their impact.

Background There are well documented socioeconomic disparities in diet quality and obesity. Menu energy labelling is a public health policy designed to improve diet and reduce obesity. However, it is unclear whether the impact energy labelling has on consumer behaviour is socially equitable or differs based on socioeconomic position (SEP). Methods Systematic review and meta-analysis of experimental (between-subjects) and pre-post implementation field studies examining the impact of menu energy labelling on energy content of food and/or drink selections in higher vs. lower SEP groups. Results Seventeen studies were eligible for inclusion. Meta-analyses of 13 experimental studies that predominantly examined hypothetical food and drink choices showed that energy labelling tended to be associated with a small reduction in energy content of selections that did not differ based on participant SEP (X 2 (1) = 0.26, p  = .610). Effect estimates for higher SEP SMD = 0.067 [95% CI: -0.092 to 0.226] and lower SEP SMD = 0.115 [95% CI: -0.006 to 0.237] were similar. A meta-analysis of 3 pre-post implementation studies of energy labelling in the real world showed that the effect energy labelling had on consumer behaviour did not significantly differ based on SEP (X 2 (1) = 0.22, p  = .636). In higher SEP the effect was SMD = 0.032 [95% CI: -0.053 to 0.117] and in lower SEP the effect was SMD = -0.005 [95% CI: -0.051 to 0.041]. Conclusions Overall there was no convincing evidence that the effect energy labelling has on consumer behaviour significantly differs based on SEP. Further research examining multiple indicators of SEP and quantifying the long-term effects of energy labelling on consumer behaviour in real-world settings is now required. Review registration Registered on PROSPERO (CRD42022312532) and OSF ( https://doi.org/10.17605/OSF.IO/W7RDB ).

As the main force and practice subject of rural revitalisation, farmers' health is intricately linked to agricultural production and the rural economy. This study utilizes open data from the 2015 China Nutrition and Health Survey and employs the Least Absolute Shrinkage and Selection Operator (LASSO) method to explore the factors influencing farmers' self-assessment of health. The findings reveal that education level, proactive nutrition knowledge seeking, healthy dietary preferences and habits, and the use of clean cooking fuel positively impact farmers' health self-assessment. Conversely, age, history of illness or injury, and participation in medical insurance negatively affect their self-assessment. Furthermore, factors influencing farmers' health self-assessment exhibit heterogeneity across regions. Our findings suggest that promoting health education, disseminating nutritional dietary knowledge, and enhancing rural household infrastructure play an important role in improving farmers' self-evaluation of health. Therefore, policymakers should design more targeted health interventions and infrastructure improvement plans based on farmers' self-assessment of health and the level of regional economic development.

Background Communities in the United States (US) exist on a continuum of urbanicity, which may inform how individuals interact with their food environment, and thus modify the relationship between food access and dietary behaviors. Objective This cross-sectional study aims to examine the modifying effect of community type in the association between the relative availability of food outlets and dietary inflammation across the US. Methods Using baseline data from the REasons for Geographic and Racial Differences in Stroke study (2003–2007), we calculated participants’ dietary inflammation score (DIS). Higher DIS indicates greater pro-inflammatory exposure. We defined our exposures as the relative availability of supermarkets and fast-food restaurants (percentage of food outlet type out of all food stores or restaurants, respectively) using street-network buffers around the population-weighted centroid of each participant’s census tract. We used 1-, 2-, 6-, and 10-mile (~ 2-, 3-, 10-, and 16 km) buffer sizes for higher density urban, lower density urban, suburban/small town, and rural community types, respectively. Using generalized estimating equations, we estimated the association between relative food outlet availability and DIS, controlling for individual and neighborhood socio-demographics and total food outlets. The percentage of supermarkets and fast-food restaurants were modeled together. Results Participants (n = 20,322) were distributed across all community types: higher density urban (16.7%), lower density urban (39.8%), suburban/small town (19.3%), and rural (24.2%). Across all community types, mean DIS was − 0.004 (SD = 2.5; min = − 14.2, max = 9.9). DIS was associated with relative availability of fast-food restaurants, but not supermarkets. Association between fast-food restaurants and DIS varied by community type ( P for interaction = 0.02). Increases in the relative availability of fast-food restaurants were associated with higher DIS in suburban/small towns and lower density urban areas (p-values < 0.01 ) ; no significant associations were present in higher density urban or rural areas. Conclusions The relative availability of fast-food restaurants was associated with higher DIS among participants residing in suburban/small town and lower density urban community types, suggesting that these communities might benefit most from interventions and policies that either promote restaurant diversity or expand healthier food options.

Objective The aim of this study was to understand the prevalence and potential risk factors of Helicobacter pylori ( H. pylori ) infection in Hainan Province, China. Methods We conducted this study in 21 health service stations in 5 cities of Hainan Province from August 2022 to April 2023. We selected the various participants based on a stratified whole-group sampling method. The 14C-UBT was used to analyze H. pylori infection in 3632 participants. We also analyzed the possible relationship between variables and H. pylori infection based on chi-square test and multifactorial logistic regression. The model was evaluated by performing a Hosmer–Lemeshow goodness-of-fit test and plotting receiver operating characteristic(ROC) curves. Results In total, the results of 3632 eligible participants (age: 14 to 93 years) were included in the analysis. The total prevalence of H. pylori infection in Hainan Province was approximately 38.7%. The prevalence of H. pylori infection was found to increase with age, stabilized in the age group of 45 to 64 years, but peaked in the age group of 65 years and older. In multifactorial analysis, the prevalence of H. pylori infection was positively associated with middle-aged adults (45–64 years), older adults (≥ 65 years), drinking, farmers, natural labor, routinely share utensils, have habit of frequent betel nut consumption, upper gastrointestinal symptoms, and family history of gastric cancer. The factors negatively associated with prevalence included family size ≤ 3, washing hands often before meals, frequent exercise, regular meals, and frequent consumption of fruits and vegetables. In addition, the Hosmer–Lemeshow test showed a good fit (χ 2  = 12.983, P  = 0.112) and the area under ROC was 0.631 (95%CI: 0.613 ~ 0.649). Conclusion The prevalence of H. pylori infection in Hainan Province was observed to be moderate and closely related to age, local socioeconomic conditions, hygienic status and dietary habits.

To understand the contribution of regional differentials in dietary exposures to regional gradients in health, we examined 20-year trends in the association of US census region of residence with nutritional biomarkers and dietary intakes of American adults. Observational. The biomarker and 24 h dietary recall data were from the National Health and Nutrition Examination Surveys (NHANES) conducted during 1988-1994 and 1999-2010. The US census region was operationalized as Northeast, Midwest, South and West. Nutritional biomarker outcomes were serum folate, vitamins B6, B12, C, D and E, and carotenoids; dietary outcomes were intakes of nutrients, food groups and eating patterns. US adults, n>8000-40 000 for biomarkers and >43 000 for dietary outcomes. The interactions of survey time period and region were not significant for the examined biomarker and dietary outcomes, indicating similar secular trends among regions. The main effect of region was significant for all nutritional biomarkers except serum vitamin B6, most dietary micronutrients, food groups and eating patterns (P<0·001). The mean serum folate, vitamins B12, C and E, and all carotenoid (except lycopene) biomarker levels, and intakes of dietary fibre, vitamins A, E, C and B6, folate, K, Ca, Mg and Fe, fruits, vegetables and whole grains, were higher in the West and Northeast regions, relative to the South and Midwest regions. Overall, the regional gradients in dietary exposure, expressed objectively as biomarkers or as self-reported nutrient and food group intakes, paralleled trajectories reported for health outcomes and were remarkably persistent over time.

Background A better understanding of lifestyle behaviours of children < 7 years and the relation with childhood overweight is needed. The aim of our prospective study was to examine how lifestyle patterns in young children are associated with the development of childhood overweight. As ecological models suggest focusing on not only the child as an individual, but also their environment, we also considered the role of socio-economic status (SES) and spatial clustering of lifestyle and body mass index (BMI). Methods In 1792 children (aged 3–6 years) participating in the GECKO Drenthe cohort, diet, screen time, outdoor play and sleep were assessed by questionnaires and moderate-to-vigorous physical activity and sedentary time by accelerometry (Actigraph GT3X). At 10–11 years, height and weight were measured to calculate age- and sex-specific standardized BMI z-scores (zBMI). Lifestyle patterns were identified using principal component analysis. To assess spatial clustering for the lifestyle patterns and zBMI, we calculated the Global Moran’s I statistic. Linear- and logistic regression models, taking into account SES, were performed to examine the association between the lifestyle patterns and the development of overweight. For the spatial analyses, we added spatial terms for the determinants, the outcome, and the error term. Results Three lifestyle patterns were identified: (1) ‘high activity’, (2) ‘low screen time, high sleep and healthy diet’, and (3) ‘high outdoor play’. No associations were observed between the ‘high activity’ or ‘high outdoor play’ patterns at young age with the development of childhood overweight (all p > 0.05). In contrast, children who adhered to the ‘low screen time, high sleep and healthy diet’ pattern had lower odds to become overweight and a lower zBMI at 10–11 years (odds ratio [95% CI] = 0.766 [0.65; 0.90]). These findings remained similar after taking SES into account. Regarding the spatial analyses, we found spatial clustering of zBMI, but no spatial clustering of the lifestyle patterns. Conclusions Low screen time, high sleep duration and a healthy diet cluster into a pattern that seems favourable in the prevention of childhood overweight, independent of individual SES. The spatial analyses suggest that there are likely other neighbourhood factors that contribute to the spatial clustering of childhood overweight.