The impact of the COVID-19 pandemic and associated disruptions in health-care provision on clinical outcomes in people with diabetes: a systematic review.

The COVID-19 pandemic triggered disruptions to health care and lifestyles that could conceivably impact diabetes management. We set out to identify the impact of disruptions caused by COVID-19 on clinical outcomes in people with diabetes. We performed a systematic review of the available literature in the MEDLINE and OVID databases from Jan 1, 2020, to June 7, 2023, and included 138 studies (n>1 000 000 people). All but five studies were judged to be at some risk of bias. All studies compared prepandemic with pandemic periods. All-cause mortality (six studies) and diabetes-related mortality (13 studies) showed consistent increases, and most studies indicated increases in sight loss (six studies). In adult and mixed samples, data generally suggested no difference in diabetic ketoacidosis frequency or severity, whereas in children and adolescents most studies showed increases with some due to new-onset diabetes (69 studies). Data suggested decreases in hospital admissions in adults but increases in diabetes-related admissions to paediatric intensive care units (35 studies). Data were equivocal on diabetic foot ulcer presentations (nine studies), emergency department admissions (nine studies), and overall amputation rates (20 studies). No studies investigated renal failure. Where reported, the impact was most pronounced for females, younger people, and racial and ethnic minority groups. Further studies are needed to investigate the longer-term impact of the pandemic and the on potential differential impacts, which risk further exacerbating existing inequalities within people with diabetes.

Experiences of emotional eating in an Acceptance and Commitment Therapy based weight management intervention (SWiM): A qualitative study.

BACKGROUND: Emotional eating is a barrier to weight management. Interventions based on Acceptance and Commitment Therapy (ACT) promote the acceptance of uncomfortable feelings, which can reduce the urge to use food as a coping mechanism. We aimed to explore how participants of an ACT-based weight management intervention (WMI) experience emotional eating and relevant intervention content. METHODS: We conducted semi-structured telephone interviews with participants of a digital ACT-based guided self-help WMI. Fifteen participants were purposefully selected to represent a range of demographic characteristics and emotional eating scores. We used reflexive thematic analysis to explore experiences of emotional eating. RESULTS: We generated five themes. Participants improved emotional eating by disconnecting emotions from behaviours though increased self-awareness (theme 1) and by implementing alternative coping strategies, including preparation, substitution, and acceptance (theme 2). Most participants maintained improvements in emotional eating over time but wished for more opportunities to re-engage with intervention content, including more immediate support in triggering situations (theme 3). Participants who struggled to engage with emotional eating related intervention content often displayed an external locus of control over emotional eating triggers (theme 4). The perceived usefulness of the intervention depended on participants' prior experiences of emotional eating, and was thought insufficient for participants with complex emotional experiences (theme 5). DISCUSSION: This ACT-based WMI helped participants with emotional eating by improving self-awareness and teaching alternative coping strategies. Intervention developers may consider adding ongoing forms of intervention that provide both real-time and long-term support. Additionally, a better understanding of how to support people with an external locus of control and people with complex experiences of emotional eating is needed. Future research may explore ways of personalising WMIs based on participants' emotional needs.

The moderating and mediating role of eating behaviour traits in acceptance and commitment therapy-based weight management interventions: protocol for an individual participant data meta-analysis.

INTRODUCTION: Precision medicine approaches to obesity aim to maximise treatment effectiveness by matching weight management interventions (WMIs) to characteristics of individuals, such as eating behaviour traits (EBTs). Acceptance and commitment therapy (ACT)-based WMIs may address EBTs such as emotional and uncontrolled eating more effectively than standard interventions, and might be most effective in people with high levels of these traits. However, few studies have examined this directly. We will examine (a) whether ACT-based interventions are more effective for people with certain levels of EBTs (ie, moderation) and (b) whether ACT-based interventions operate through changes in EBTs (ie, mediation). METHODS AND ANALYSIS: This individual participant data (IPD) meta-analysis will follow the Preferred Reporting Items for Systematic Reviews and Meta-Analyses of Individual Participant Data guidance. We will include studies on ACT-based WMIs that assessed EBTs in people with a body mass index ≥25 kg/m2. We identified studies by screening studies included in a previous review of third wave cognitive behavioural interventions, and updating the search to 20 June 2022. We will request IPD from eligible published and unpublished studies. We will harmonise and re-analyse data using a two-stage random effects meta-analysis pooling within-trial interactions to investigate moderating effects and using a one-stage simultaneous equation model to examine mediating effects. We will assess the risk of bias in included studies using the Cochrane Risk of Bias tool 2 and the Risk of Bias in Non-randomised Studies of Interventions tool. ETHICS AND DISSEMINATION: Ethical approval has been obtained from the Cambridge Psychology Research Ethics Committee (Application No: PRE.2023.121). Data sharing will follow data transfer agreements and coauthorship will be offered to investigators contributing data. Findings will be disseminated through peer-reviewed journals and conferences and will contribute to the lead author's PhD thesis. PROSPERO REGISTRATION NUMBER: CRD42022359691.

Physical activity in young children across developmental and health states: the ActiveCHILD study.

Background: Evidence about physical activity of young children across developmental and health states is very limited. Using data from an inclusive UK cohort, ActiveCHILD, we investigated relationships between objectively measured physical activity, child development, social context, and health-related quality of life (HRQoL). Methods: Children (12-36 months), purposively sampled across health pathways, developmental abilities, and sociodemographic factors, were recruited through thirteen National Health Service organisations in England. Data were collected from 07/2017 to 08/2019 on: weekly physical activity (3-7 days) using waist-worn accelerometer (ActiGraph 3GTX); sociodemographics, parent actions, child HRQoL, and child development using questionnaires; and child health conditions using clinical records. A data-driven, unsupervised method, called hidden semi-Markov model (HSMM) segmented the accelerometery data and provided estimates of the total time spent active (any intensity) and very active (greater intensity) for each child. Relationships with the explanatory factors were investigated using multiple linear regression. Findings: Physical activity data were obtained for 282 children (56% females, mean age 21 months, 37.5% with a health condition) covering all index of multiple deprivation deciles. The patterns of physical activity consisted of two daily peaks, children spending 6.44 (SD = 1.39) hours active (any intensity), of which 2.78 (SD = 1.38) hours very active, 91% meeting WHO guidelines. The model for total time active (any intensity) explained 24% of variance, with mobility capacity the strongest predictor (ß = 0.41). The model for time spent very active explained 59% of variance, with mobility capacity again the strongest predictor (ß = 0.76). There was no evidence of physical activity explaining HRQoL. Interpretation: The findings provide new evidence that young children across developmental states regularly achieve mainstream recommended physical activity levels and challenges the belief that children with development problems need lower expectations for daily physical activity compared to peers. Advancing the rights of all children to participate in physical activity requires inclusive, equally ambitious, expectations for all. Funding: Niina Kolehmainen, HEE/NIHR Integrated Clinical Academic Senior Clinical Lecturer, NIHR ICA-SCL-2015-01-00, was funded by the NIHR for this research project. Christopher Thornton, Olivia Craw, Laura Kudlek, and Laura Cutler were also funded from this award. Tim Rapley is a member of the NIHR Applied Research Collaboration North East and North Cumbria, with part of his time funded through the related award (NIHR200173). The views expressed in this publication are those of the author(s) and not necessarily those of the NIHR, NHS, or the UK Department of Health and Social Care. The work of Kianoush Nazarpour is supported by Engineering and Physical Sciences Research Council (EPSRC), under grant number EP/R004242/2.

The impact of the COVID-19 pandemic on glycaemic control in people with diabetes: A systematic review and meta-analysis.

AIM: To identify, appraise and synthesize the available evidence on the impact of the coronavirus disease 2019 (COVID-19) pandemic and lockdown (LD) on glycaemic control in people with diabetes. MATERIALS AND METHODS: We searched multiple databases up to 2 February 2021 for studies reporting HbA1c, time in range (TIR), average or fasting glucose, severe hypoglycaemia and diabetic ketoacidosis. Data were pooled using random effects meta-analysis and are presented as mean difference (MD) with 95% confidence intervals (CI). This review was preregistered on PROSPERO (CRD42020179319). RESULTS: We include 59 studies; 44 (n = 15 464) were included in quantitative syntheses and 15 were narratively synthesized. Pooled data were grouped by diabetes type. Results from 28 studies (n = 5048 type 1 diabetes [T1D] and combined diabetes participants) showed that TIR increased during LD compared with before LD (MD 2.74%, 95% CI 1.80% to 3.69%). Data from 10 studies (n = 1294 T1D participants) showed that TIR increased after LD compared with before LD (MD 5.14%, 95% CI 3.12% to 7.16%). Pooled results from 12 studies (n = 4810 T1D and type 2 diabetes participants) resulted in average glucose decreasing after LD compared with before LD (MD -6.86 mg/dl, 95% CI -8.54 to -5.18). Results for other outcomes, including HbA1c, were not statistically significantly different. CONCLUSIONS: The COVID-19 pandemic was associated with small improvements across multiple outcomes of glycaemic control, although there was insufficient evidence to suggest that this led to changes in HbA1c. Most evidence came from people with access to diabetes technologies in high-income countries; more research is needed in less advantaged populations.

Interventions for preventing weight gain after smoking cessation.

BACKGROUND: Most people who stop smoking gain weight. This can discourage some people from making a quit attempt and risks offsetting some, but not all, of the health advantages of quitting. Interventions to prevent weight gain could improve health outcomes, but there is a concern that they may undermine quitting. OBJECTIVES: To systematically review the effects of: (1) interventions targeting post-cessation weight gain on weight change and smoking cessation (referred to as 'Part 1') and (2) interventions designed to aid smoking cessation that plausibly affect post-cessation weight gain (referred to as 'Part 2'). SEARCH METHODS: Part 1 - We searched the Cochrane Tobacco Addiction Group's Specialized Register and CENTRAL; latest search 16 October 2020. Part 2 - We searched included studies in the following 'parent' Cochrane reviews: nicotine replacement therapy (NRT), antidepressants, nicotine receptor partial agonists, e-cigarettes, and exercise interventions for smoking cessation published in Issue 10, 2020 of the Cochrane Library. We updated register searches for the review of nicotine receptor partial agonists. SELECTION CRITERIA: Part 1 - trials of interventions that targeted post-cessation weight gain and had measured weight at any follow-up point or smoking cessation, or both, six or more months after quit day. Part 2 - trials included in the selected parent Cochrane reviews reporting weight change at any time point. DATA COLLECTION AND ANALYSIS: Screening and data extraction followed standard Cochrane methods. Change in weight was expressed as difference in weight change from baseline to follow-up between trial arms and was reported only in people abstinent from smoking. Abstinence from smoking was expressed as a risk ratio (RR). Where appropriate, we performed meta-analysis using the inverse variance method for weight, and Mantel-Haenszel method for smoking. MAIN RESULTS: Part 1: We include 37 completed studies; 21 are new to this update. We judged five studies to be at low risk of bias, 17 to be at unclear risk and the remainder at high risk.  An intermittent very low calorie diet (VLCD) comprising full meal replacement provided free of charge and accompanied by intensive dietitian support significantly reduced weight gain at end of treatment compared with education on how to avoid weight gain (mean difference (MD) -3.70 kg, 95% confidence interval (CI) -4.82 to -2.58; 1 study, 121 participants), but there was no evidence of benefit at 12 months (MD -1.30 kg, 95% CI -3.49 to 0.89; 1 study, 62 participants). The VLCD increased the chances of abstinence at 12 months (RR 1.73, 95% CI 1.10 to 2.73; 1 study, 287 participants). However, a second study  found that no-one completed the VLCD intervention or achieved abstinence. Interventions aimed at increasing acceptance of weight gain reported mixed effects at end of treatment, 6 months and 12 months with confidence intervals including both increases and decreases in weight gain compared with no advice or health education. Due to high heterogeneity, we did not combine the data. These interventions increased quit rates at 6 months (RR 1.42, 95% CI 1.03 to 1.96; 4 studies, 619 participants; I2 = 21%), but there was no evidence at 12 months (RR 1.25, 95% CI 0.76 to 2.06; 2 studies, 496 participants; I2 = 26%). Some pharmacological interventions tested for limiting post-cessation weight gain (PCWG) reduced weight gain at the end of treatment (dexfenfluramine, phenylpropanolamine, naltrexone). The effects of ephedrine and caffeine combined, lorcaserin, and chromium were too imprecise to give useful estimates of treatment effects. There was very low-certainty evidence that personalized weight management support reduced weight gain at end of treatment (MD -1.11 kg, 95% CI -1.93 to -0.29; 3 studies, 121 participants; I2 = 0%), but no evidence in the longer-term 12 months (MD -0.44 kg, 95% CI -2.34 to 1.46; 4 studies, 530 participants; I2 = 41%). There was low to very low-certainty evidence that detailed weight management education without personalized assessment, planning and feedback did not reduce weight gain and may have reduced smoking cessation rates (12 months: MD -0.21 kg, 95% CI -2.28 to 1.86; 2 studies, 61 participants; I2 = 0%; RR for smoking cessation 0.66, 95% CI 0.48 to 0.90; 2 studies, 522 participants; I2 = 0%). Part 2: We include 83 completed studies, 27 of which are new to this update. There was low certainty that exercise interventions led to minimal or no weight reduction compared with standard care at end of treatment (MD -0.25 kg, 95% CI -0.78 to 0.29; 4 studies, 404 participants; I2 = 0%). However, weight was reduced at 12 months (MD -2.07 kg, 95% CI -3.78 to -0.36; 3 studies, 182 participants; I2 = 0%). Both bupropion and fluoxetine limited weight gain at end of treatment (bupropion MD -1.01 kg, 95% CI -1.35 to -0.67; 10 studies, 1098 participants; I2 = 3%); (fluoxetine MD -1.01 kg, 95% CI -1.49 to -0.53; 2 studies, 144 participants; I2 = 38%; low- and very low-certainty evidence, respectively). There was no evidence of benefit at 12 months for bupropion, but estimates were imprecise (bupropion MD -0.26 kg, 95% CI -1.31 to 0.78; 7 studies, 471 participants; I2 = 0%). No studies of fluoxetine provided data at 12 months. There was moderate-certainty that NRT reduced weight at end of treatment (MD -0.52 kg, 95% CI -0.99 to -0.05; 21 studies, 2784 participants; I2 = 81%) and moderate-certainty that the effect may be similar at 12 months (MD -0.37 kg, 95% CI -0.86 to 0.11; 17 studies, 1463 participants; I2 = 0%), although the estimates are too imprecise to assess long-term benefit. There was mixed evidence of the effect of varenicline on weight, with high-certainty evidence that weight change was very modestly lower at the end of treatment (MD -0.23 kg, 95% CI -0.53 to 0.06; 14 studies, 2566 participants; I2 = 32%); a low-certainty estimate gave an imprecise estimate of higher weight at 12 months (MD 1.05 kg, 95% CI -0.58 to 2.69; 3 studies, 237 participants; I2 = 0%). AUTHORS' CONCLUSIONS: Overall, there is no intervention for which there is moderate certainty of a clinically useful effect on long-term weight gain. There is also no moderate- or high-certainty evidence that interventions designed to limit weight gain reduce the chances of people achieving abstinence from smoking.