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Aims: This study aimed to evaluate the effectiveness of the Local Authority commissioned large-scale public health service that provided a 6-week school-based weight management intervention for children aged 4-19 years.Methods: A quantitative retrospective cohort study identified participants from 130 schools consisting of 8550 potential children aged 4-19 years across a mixture of Lower Super Output Area (LSOA) deprivation groups. Participants were invited to take part in a 5- to 12-week Healthy Lifestyles intervention with a focus on weight management delivered by OneLife Suffolk between 1 January 2017 and 1 January 2020. This resulted in a final sample of 5163 participants. The following information for each child was collected anonymously: (1) age, (2) gender, (3) preprogramme body mass index (BMI), (4) postprogramme BMI, (5) weight category and (6) LSOA category.Results: Following the 6-week school-based intervention, there was a significant decrease in mean ΔBMI SDS (standardised body mass index) of -0.07 (-14.89%) among participants. Wilcoxon signed-rank test showed a significant change in weight status post 6-week weight management programme (WMP): BMI (Z = -15.87, p < .001), BMI SDS (Z = -21.54, p < .001), centile (Z = -20.12, p < .01) and weight category (Z = -7.89, p < .001), whereas Mann-Whitney U test showed no statistically significant difference in mean BMI SDS change between gender groups (p = .24) and Kruskal-Wallis test revealed no statistically significant differences in mean BMI SDS change between child LSOA groups (c2(4) = 1.67, p = .796), school LSOA groups (c2(4) = 4.72, p = .317), ethnic groups (c2(4) = 2.53, p = .640) and weight category at the start of the intervention (c2(3) = 6.20, p = .102).Conclusions: This study contributes to the growing body of evidence demonstrating the efficacy of multicomponent school-based weight management interventions and demonstrates that such interventions can be successfully implemented as part of a wider healthy lifestyles service, without widening health inequalities. [ABSTRACT FROM AUTHOR]

Smoking is a leading cause of preventable morbidity and mortality globally. During the COVID-19 pandemic, Smoking Cessation (SC) services faced many challenges, including lockdown and social distancing restrictions. Consequently, SC services had to adapt to the challenges in different ways or halt delivery. This research evaluated the impact of COVID-19 on the delivery and outcomes of SC services. This was achieved by comparing service delivery and outcomes pre-COVID-19 and during the pandemic and drawing insights for the delivery of SC services post-pandemic. Secondary analysis was performed on the data of 11,533 participants who attended the One Life Suffolk (OLS) SC services pre- and during the COVID-19 pandemic. A total of 4923 and 6610 participants attended SC services pre-COVID-19 and during COVID-19 respectively. Fifty-four percent of participants achieved quit status at week-4 while attending the SC services during the COVID-19 pandemic, compared with 46% pre-COVID-19, (X2(1) = 38.2, p-value<0.001). Participants who attended the SC services during the COVID-19 period were 1.7 times more likely to achieve quit status at week-4 than pre-COVID-19. However, the proportion of participants lost-to-follow-up (LTF) was significantly higher during the COVID-19 period (11%) compared to pre-COVID-19 (7%), (X2(1) = 51.4, p-value <0.001). There was an increased participation and quit rate during the pandemic for modified, remotely delivered SC services indicating successful delivery of remote services during the pandemic. Although switching from face-to-face to online helped some smokers to access the service at a time of motivational readiness, despite the COVID-19 restrictions, some smokers could not access or use some aspects of the remote delivery due to a lack of internet access, poor digital literacy, no peer support and no commitment to a group during face-to-face sessions, contributing to an increased rate of LTF. Posing a major challenge to SC services delivery, COVID-19 compelled OLS SC services to adapt and be more innovative in their delivery. SC services need to continue to evolve and adapt by applying the lessons learnt during the pandemic in terms of flexibility and person-centered delivery given what did and did not work well for different demographics within the population., Competing Interests: All authors of this article have read the journal’s policy. Dr Windi Marwa and Dr Claire Griffiths have no competing interests. Competing interests for other authors are as follows: Prof. Carlton Cooke is an employee of Leeds Beckett University and is a board member of MoreLife; Caroline Marshall is an employee of MoreLife; Prof. Paul Gately is an employee of Leeds Beckett University and CEO and shareholder of MoreLife; Dr Sophie Edwards is an employee of MoreLife and a Leeds Beckett University Associate Staff member. OneLife Suffolk was a partnership between Leeds Beckett University and MoreLife, commissioned by Suffolk County Council to deliver integrated healthy lifestyles services, including smoking cessation services. This does not alter our adherence to all the PLOS ONE policies., (Copyright: © 2024 Marwa et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.)

Background: Obesity remains one of the most challenging public health issues of our modern time. Despite the face validity of claims for influence, studies on the causes of obesity have reported the influence of the food environment to be inconsistent. This inconsistency has been attributed to the variability of measures used by researchers to represent the food environments-Researcher-Defined Food Environments (RDFE) like circular, street-network buffers, and others. This study (i.) determined an individual's Activity Space (AS) (ii.) explored the accuracy of the RDFE in representing the AS, (iii.) investigated the accuracy of the RDFE in representing actual exposure, and (iv.) explored whether exposure to food outlet reflects the use of food outlets., Methods: Data were collected between June and December 2018. A total of 65 participants collected Global Positioning System (GPS) data, kept receipt of all their food purchases, completed a questionnaire about their personal information and had their weight and height measured. A buffer was created around the GPS points and merged to form an AS (GPS-based AS)., Results: Statistical and geospatial analyses found that the AS size of participants working away from home was positively related to the Euclidean distance from home to workplace; the orientation (shape) of AS was also influenced by the direction of workplace from home and individual characteristics were not predictive of the size of AS. Consistent with some previous studies, all types and sizes of RDFE variably misrepresented individual exposure in the food environments. Importantly, the accuracy of the RDFE was significantly improved by including both the home and workplace domains. The study also found no correlation between exposure and use of food outlets., Conclusions: Home and workplace are key activity nodes in modelling AS or food environments and the relationship between exposure and use is more complex than is currently suggested in both empirical and policy literature., (© 2021. The Author(s).)

This systematic review quantifies methods used to measure the 'retail food environment' (RFE), appraises the quality of methodological reporting, and examines associations with obesity, accounting for differences in methods. Only spatial measures of the RFE, such as food outlet proximity were included. Across the 113 included studies, methods for measuring the RFE were extremely diverse, yet reporting of methods was poor (average reporting quality score: 58.6%). Null associations dominated across all measurement methods, comprising 76.0% of 1937 associations in total. Outcomes varied across measurement methods (e.g. narrow definitions of 'supermarket': 20.7% negative associations vs 1.7% positive; broad definitions of 'supermarket': 9.0% negative associations vs 10.4% positive). Researchers should report methods more clearly, and should articulate findings in the context of the measurement methods employed., (Copyright © 2019 The Authors. Published by Elsevier Ltd.. All rights reserved.)