Nutrition practices of nurseries in England. Comparison with national guidelines.

Recent national guidelines call for improved nutrition within early years settings. The aim of this cross-sectional study was to describe foods and beverages served in nurseries, assess provider behaviors related to feeding, and compare these practices to national guidelines. We administered a mailed survey to a random sample of nurseries across England, stratifying by tertile of deprivation. A total of 851 nurseries returned the survey (54.3% response rate). We fitted separate multivariate logistic regression models to estimate the association of deprivation with each of the 13 food and beverage guidelines and the seven provider behavior guidelines. We also conducted a joint F-test for any deprivation effect, to evaluate the effect of the guidelines combined. After adjusting for confounders, we observed differences in the frequency of nurseries that reported serving healthier foods across the tertiles of deprivation (p = 0.02 for joint F test). These adjusted results were driven mainly by nurseries in more deprived areas serving more whole grains (OR 1.57 (95% CI 1.00, 2.46)) and legumes, pulses, and lentils (1.40 (1.01, 2.14)). We also observed differences in the frequency of nurseries reporting more provider behaviors consistent with national guidelines across the tertiles of deprivation (p = 0.01 for joint F test). Nurseries in more deprived areas were more likely to dilute juice with water (2.35 (1.48, 3.73)), allow children to select their own portions (1.09 (1.06, 1.58)), and sit with children during meals (1.84 (1.07, 3.15)). While nurseries in the most deprived areas reported serving more healthy foods, a large percentage were still not meeting national guidelines. Policy and intervention efforts may increase compliance with national guidelines in nurseries in more deprived areas, and across England.This work was undertaken by the Centre for Diet and Activity Research (CEDAR), a UK Clinical Research Collaboration (UKCRC) Public Health Research Centre of Excellence. Funding from the British Heart Foundation, Economic and Social Research Council, Medical Research Council, the National Institute for Health Research and the Wellcome Trust under the auspices of the UK Clinical Research Collaboration, is gratefully acknowledged.This is the final published version. It first appeared at http://www.sciencedirect.com/science/article/pii/S0195666314005145#

The impact of the novel coronavirus movement restrictions in the United Kingdom on food outlet usage and body mass index

Research funding University of Tabuk. Grant Number: 14451 ACKNOWLEDGMENTS The authors thank Vasileios Kyparissis and Florina Birkert for their work with us in distributing and collecting the surveys. Ahmad Albalawi was supported by a studentship from the University of Tabuk, Saudi Arabia (KSA) project code CF10434-63. John R, Speakman was supported by a Wolfson merit award from the Royal Society and a Presidents International Fellowship Initiative award from the Chinese Academy of Sciences.Peer reviewedPublisher PD

Associations between BMI and home, school and route environmental exposures estimated using GPS and GIS: do we see evidence of selective daily mobility bias in children?

BACKGROUND: This study examined whether objective measures of food, physical activity and built environment exposures, in home and non-home settings, contribute to children's body weight. Further, comparing GPS and GIS measures of environmental exposures along routes to and from school, we tested for evidence of selective daily mobility bias when using GPS data. METHODS: This study is a cross-sectional analysis, using objective assessments of body weight in relation to multiple environmental exposures. Data presented are from a sample of 94 school-aged children, aged 5-11 years. Children's heights and weights were measured by trained researchers, and used to calculate BMI z-scores. Participants wore a GPS device for one full week. Environmental exposures were estimated within home and school neighbourhoods, and along GIS (modelled) and GPS (actual) routes from home to school. We directly compared associations between BMI and GIS-modelled versus GPS-derived environmental exposures. The study was conducted in Mebane and Mount Airy, North Carolina, USA, in 2011. RESULTS: In adjusted regression models, greater school walkability was associated with significantly lower mean BMI. Greater home walkability was associated with increased BMI, as was greater school access to green space. Adjusted associations between BMI and route exposure characteristics were null. The use of GPS-actual route exposures did not appear to confound associations between environmental exposures and BMI in this sample. CONCLUSIONS: This study found few associations between environmental exposures in home, school and commuting domains and body weight in children. However, walkability of the school neighbourhood may be important. Of the other significant associations observed, some were in unexpected directions. Importantly, we found no evidence of selective daily mobility bias in this sample, although our study design is in need of replication in a free-living adult sample.Funding from the British Heart Foundation, Economic and Social Research Council, Medical Research Council, the National Institute for Health Research and the Wellcome Trust under the auspices of the UK Clinical Research Collaboration, is gratefully acknowledged. This study was supported, in part, by a grant from the Robert Wood Johnson Foundation, Active Living Research.This is the final published version. It first appeared at http://www.ij-healthgeographics.com/content/14/1/8

Examining the validity and utility of two secondary sources of food environment data against street audits in England

Background: Secondary data containing the locations of food outlets is increasingly used in nutrition and obesity research and policy. However, evidence evaluating these data is limited. This study validates two sources of secondary food environment data: Ordnance Survey Points of Interest data (POI) and food hygiene data from the Food Standards Agency (FSA), against street audits in England and appraises the utility of these data. Methods: Audits were conducted across 52 Lower Super Output Areas in England. All streets within each Lower Super Output Area were covered to identify the name and street address of all food outlets therein. Audit-identified outlets were matched to outlets in the POI and FSA data to identify true positives (TP: outlets in both the audits and the POI/FSA data), false positives (FP: outlets in the POI/FSA data only) and false negatives (FN: outlets in the audits only). Agreement was assessed using positive predictive values (PPV: TP/(TP+FP)) and sensitivities (TP/(TP+FN)). Variations in sensitivities and PPVs across environment and outlet types were assessed using multi-level logistic regression. Proprietary classifications within the POI data were additionally used to classify outlets, and agreement between audit-derived and POI-derived classifications was assessed. Results: Street audits identified 1172 outlets, compared to 1100 and 1082 for POI and FSA respectively. PPVs were statistically significantly higher for FSA (0.91, CI: 0.89-0.93) than for POI (0.86, CI: 0.84-0.88). However, sensitivity values were not different between the two datasets. Sensitivity and PPVs varied across outlet types for both datasets. Without accounting for this, POI had statistically significantly better PPVs in rural and affluent areas. After accounting for variability across outlet types, FSA had statistically significantly better sensitivity in rural areas and worse sensitivity in rural middle affluence areas (relative to deprived). Audit-derived and POI-derived classifications exhibited substantial agreement (p < 0.001; Kappa = 0.66, CI: 0.63 - 0.70). Conclusions: POI and FSA data have good agreement with street audits; although both datasets had geographic biases which may need to be accounted for in analyses. Use of POI proprietary classifications is an accurate method for classifying outlets, providing time savings compared to manual classification of outlets

Kilocalorie labelling in the out-of-home sector: an observational study of business practices and consumer behaviour prior to implementation of the mandatory calorie labelling policy in England, 2022

Background: Regulations mandating kilocalorie (kcal) labelling for large businesses in the out-of-home food sector (OHFS) came into force on 6th April 2022 as a policy to reduce obesity in England. To provide indicators of potential reach and impact, kcal labelling practices were studied in the OHFS, and customer purchasing and consumption behaviours prior to implementation of the mandatory kcal labelling policy in England. Methods: From August-December 2021, large OHFS businesses subject to the kcal labelling regulations were visited prior to regulations coming into force on 6th April 2022. 3308 customers were recruited from 330 outlets and collected survey information on the number of kcal purchased and consumed by customers, customers’ knowledge of the kcal content of their purchases, and customers noticing and use of kcal labelling. In a subset of 117 outlets, data was collected on nine recommended kcal labelling practices. Results: The average number of kcals purchased (1013 kcal, SD = 632 kcal) was high with 69% of purchases exceeding the recommendation of a maximum of 600 kcal per meal. Participants underestimated the energy content of their purchased meals by on average 253 kcal (SD = 644 kcals). In outlets providing kcal labelling in which customer survey data was collected, a minority of customers reported noticing (21%) or using (20%) kcal labelling. Out of the 117 outlets assessed for kcal labelling practices, 24 (21%) provided any in-store kcal labelling. None of the outlets met all nine aspects of recommended labelling practices. Conclusions: Prior to implementation of 2022 kcal labelling policy, the majority of sampled OHFS large business outlets in England did not provide kcal labelling. Few customers noticed or used the labels and on average customers purchased and consumed substantially more energy than recommended in public health guidelines. The findings suggest that reliance on voluntary action for kcal labelling implementation failed to produce widespread, consistent, and adequate kcal labelling practices

Point-of-choice kilocalorie labelling practices in large, out-of-home food businesses: a preobservational versus post observational study of labelling practices following implementation of The Calorie Labelling (Out of Home Sector) (England) Regulations 2021.

BACKGROUND AND OBJECTIVES: On 6 April 2022, the UK government implemented mandatory kilocalorie (kcal) labelling regulations for food and drink products sold in the out-of-home food sector (OHFS) in England. Previous assessments of kcal labelling practices in the UK OHFS found a low prevalence of voluntary implementation and poor compliance with labelling recommendations. This study aimed to examine changes in labelling practices preimplementation versus post implementation of mandatory labelling regulations in 2022. METHODS: In August-December 2021 (preimplementation) and August-November 2022 (post implementation), large OHFS businesses (250 or more employees) subject to labelling regulations were visited. At two time points, a researcher visited the same 117 food outlets (belonging to 90 unique businesses) across four local authorities in England. Outlets were rated for compliance with government regulations for whether kcal labelling was provided at any or all point of choice, provided for all eligible food and drink items, provided per portion for sharing items, if labelling was clear and legible and if kcal reference information was displayed. RESULTS: There was a significant increase (21% preimplementation vs 80% post implementation, OR=40.98 (95% CI 8.08 to 207.74), p<0.001) in the proportion of outlets providing any kcal labelling at point-of-choice post implementation. Only 15% of outlets met all labelling compliance criteria post implementation, with a minority of outlets not presenting labelling in a clear (33%) or legible (29%) way. CONCLUSION: The number of large businesses in the OHFS providing kcal labelling increased following the implementation of mandatory labelling regulations. However, around one-fifth of eligible outlets sampled were not providing kcal labelling 4-8 months after the regulations came into force, and the majority of businesses only partially complied with government guidance. More effective enforcement may be required to further improve kcal labelling practices in the OHFS in England. PREREGISTRATION: Study protocol and analysis strategy preregistered on Open Science Framework (https://osf.io/pfnm6/)

Can big data solve a big problem? Reporting the obesity data landscape in line with the Foresight obesity system map.

BACKGROUND: Obesity research at a population level is multifaceted and complex. This has been characterised in the UK by the Foresight obesity systems map, identifying over 100 variables, across seven domain areas which are thought to influence energy balance, and subsequent obesity. Availability of data to consider the whole obesity system is traditionally lacking. However, in an era of big data, new possibilities are emerging. Understanding what data are available can be the first challenge, followed by an inconsistency in data reporting to enable adequate use in the obesity context. In this study we map data sources against the Foresight obesity system map domains and nodes and develop a framework to report big data for obesity research. Opportunities and challenges associated with this new data approach to whole systems obesity research are discussed. METHODS: Expert opinion from the ESRC Strategic Network for Obesity was harnessed in order to develop a data source reporting framework for obesity research. The framework was then tested on a range of data sources. In order to assess availability of data sources relevant to obesity research, a data mapping exercise against the Foresight obesity systems map domains and nodes was carried out. RESULTS: A reporting framework was developed to recommend the reporting of key information in line with these headings: Background; Elements; Exemplars; Content; Ownership; Aggregation; Sharing; Temporality (BEE-COAST). The new BEE-COAST framework was successfully applied to eight exemplar data sources from the UK. 80% coverage of the Foresight obesity systems map is possible using a wide range of big data sources. The remaining 20% were primarily biological measurements often captured by more traditional laboratory based research. CONCLUSIONS: Big data offer great potential across many domains of obesity research and need to be leveraged in conjunction with traditional data for societal benefit and health promotion

A multi-country comparison of jurisdictions with and without mandatory nutrition labelling policies in restaurants: analysis of behaviors associated with menu labelling in the 2019 International Food Policy Study

Objective: To examine differences in noticing and use of nutrition information comparing jurisdictions with and without mandatory menu labelling policies and examine differences among sociodemographic groups. Design: Cross-sectional data from the International Food Policy Study (IFPS) online survey. Setting: IFPS participants from Australia, Canada, Mexico, United Kingdom and United States in 2019. Participants: Adults aged 18-99; n=19,393. Results: Participants in jurisdictions with mandatory policies were significantly more likely to notice and use nutrition information, order something different, eat less of their order, and change restaurants compared to jurisdictions without policies. For noticed nutrition information, the differences between policy groups were greatest comparing older to younger age groups and comparing high education (difference of 10.7%, 95% CI 8.9 to 12.6) to low education (difference of 4.1%, 95% CI 1.8 to 6.3). For used nutrition information, differences were greatest comparing high education (difference of 4.9%, 95% CI 3.5 to 6.4) to low education (difference of 1.8%, 95% CI 0.2 to 3.5). Mandatory labelling was associated with an increase in ordering something different among the majority ethnicity group and a decrease among the minority ethnicity group. For changed restaurant visited, differences were greater for medium and high education compared to low education, and differences were greater for higher compared to lower income adequacy. Conclusions: Participants living in jurisdictions with mandatory nutrition information in restaurants were more likely to report noticing and using nutrition information, as well as greater efforts to modify their consumption. However, the magnitudes of these differences were relatively small

Using Routinely Collected Administrative Data in Public Health Research: Geocoding Alcohol Outlet Data

We describe our process of geocoding alcohol outlets to create a national longitudinal exposure dataset for Wales, United Kingdom from 2006 to 2011. We investigated variation in the availability of data items and the quality of alcohol outlet addresses held within unitary authorities. We used a standard geocoding method augmented with a manual matching procedure to achieve a fully spatially referenced dataset. We found higher quality addresses are held for outlets based in urban areas, resulting in the automatic geocoding of 68 % of urban outlets, compared to 48 % in rural areas. Missing postcodes and a lack of address structure contributed to a lower geocoding proportion. An urban rural bias was removed with the development of a manual matching procedure. Only one-half of the unitary authorities provided data on on/off sales and opening times, which are important availability factors. The resulting outlet dataset is suitable for contributing to the evidence-base of alcohol availability and alcohol-related harm. Local government should be encouraged to use standardised data fields, including addresses, to enable accurate geocoding of alcohol outlets and facilitate research that aims to prevent alcohol-related harm. Standardising data collection would enable efficient secondary data reuse using record linkage techniques, allowing the retrospective creation and evaluation of population-based natural experiments to provide evidence for policy and practice