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BACKGROUND AND AIMS: There are few data on the feasibility of population screening for paroxysmal AF using hand-held ECG devices outside a specialist setting or in people over the age of 75. We investigated the feasibility of screening when conducted without face-to-face contact ('remote') or via in-person appointments in primary care, and explored impact of age on screening outcomes. METHODS: People aged \u226565 years from 13 general practices in England participated in screening during 2019-20. This involved attending a practice nurse appointment (10 practices) or receiving an ECG device by post (3 practices). Participants were asked to use a handheld ECG for 1-4 weeks. Screening outcomes included: uptake, quality of ECGs, AF detection rates, and uptake of anticoagulation if AF was detected. RESULTS: Screening was carried out by 2,141 (87.5%) of people invited to practice nurse-led screening and by 288 (90.0%) invited to remote screening. At least 56 interpretable ECGs were provided by 98.0% of participants who participated for 3 weeks, with no significant differences by setting or age, except people aged 85 or over (91.1%). Overall, 2.6% (64/2,429) screened participants had AF, with detection rising with age (9.2% in people aged 85 or over). 53/64 (82.8%) people with AF commenced anticoagulation. Uptake of anticoagulation did not vary by age. CONCLUSION: Population screening for paroxysmal AF is feasible in general practice and without face-to-face contact, and in all ages over 64 years, including in people aged 85 and over.
\n \n\n \n \nAs of March 2023, when the Office for National Statistics stopped collecting data on this condition, 1.879 million individuals had self-assessed as having long covid - symptoms lasting more than 12 weeks following acute covid-19 infection. Of these, the proportion of individuals with symptoms lasting two years or more is around 42%, suggesting a decline in new cases of long covid but a persistence of those with ongoing symptoms.1 Some systematic reviews and meta-analyses have reported that up to a third of such individuals have persistent symptoms of cognitive impairment,23 but estimates vary widely and are complicated by methodological heterogeneity - eg, study size, assessment approach, follow-up duration, and different sampling frames (from self-reported surveys4 to large retrospective matched cohort studies of health records5), as discussed in a recent meta-analysis.6
\n \n\n \n \nOBJECTIVE: We aimed to determine whether urine tenofovir (TFV) and dried blood spot (DBS) tenofovir diphosphate (TFV-DP) concentrations are associated with concurrent HIV viraemia. DESIGN: Cross-sectional study among people with HIV (PWH) receiving tenofovir disoproxil fumarate (TDF)-based antiretroviral therapy (ART). METHODS: We used dual tandem liquid chromatography and mass spectrometry to measure urine TFV and DBS TFV-DP concentrations, and evaluated their associations with concurrent viraemia \u22651000\u200acopies/mL using logistic regression models. In exploratory analyses, we used receiver operating curves to estimate optimal urine TFV and DBS TFV-DP thresholds to predict concurrent viraemia. RESULTS: Among 124 participants, 68 (54.8%) were women, median age was 39\u200ayears (interquartile range [IQR] 34-45) and 74 (59.7%) were receiving efavirenz versus 50 (40.3%) receiving dolutegravir. Higher concentrations of urine TFV (1000\u200ang/mL increase, odds ratio [OR] 0.97 95%CI 0.94-0.99, p\u200a=\u200a0.005) and DBS TFV-DP (100\u200afmol/punch increase, OR 0.76, 95%CI 0.67-0.86, p\u200a
\n \n\n \n \nINTRODUCTION: Ethnic minorities (also called racialised groups) are more likely to experience severe mental illness (SMI). People with SMI are more likely to experience multimorbidity (MM), making psychosis among racialised groups more likely to lead to MM, poor outcomes, disability and premature mortality. METHODS AND ANALYSIS: This National Institute for Health and Care Research-funded study (151887) seeks to use innovative participatory methods including photovoice and biographical narrative interviews in urban and rural areas of England to assemble experience data. These data will be subjected to polytextual thematic analysis, and alongside pictures and captions, will inform an experienced-based co-design of interventions, the implementation of which will be evaluated. There will be an economic analysis and a process evaluation of the implementation. ETHICS AND DISSEMINATION: This programme of work has received ethical (IRAS 322421; Newcastle North Tyneside Research Ethics Committee 23/NE/0143) and sponsor approval. The findings will be disseminated in galleries showing the creative work, as lay and academic summaries and infographics; as practice briefings for practitioners, commissioners and policy makers; peer-reviewed publications. TRIAL REGISTRATION NUMBER: https://www.researchregistry.com/browse-the-registry%23home/registrationdetails/649c08111c037d0027b17d17/.
\n \n\n \n \nIntroduction The diagnosis of asthma can be challenging and often requires multiple diagnostic tests and forced expiratory manoeuvres, such as spirometry with reversibility testing or regular peak flow measurements in order to capture variable airflow obstruction. Objective To assess the performance of a diagnostic model in its classification of participants with and without asthma, built using interpretable data processing and machine learning techniques applied to a dataset of CO2 breath records (75 seconds of tidal breathing), captured on TidalSense\u2019s N-Tidal\u2122 handheld capnometer. Methods Participant records were drawn from 4 clinical studies (GBRS, ABRS, CBRS, CBRS2). This pooled dataset included participants recruited from primary and secondary care. Two XGBoost models were trained and validated on 82 features derived from the high-resolution CO2 data of 146 asthmatic and 133 non-asthmatic participants (which included healthy volunteers, those with COPD, bronchiectasis, pulmonary fibrosis, heart failure, anaemia, and other cardiorespiratory conditions). The model used breath waveform features from a single breath record. The model was trained using 117 asthmatic, and 106 non-asthmatic participants and performance metrics were generated from an unseen validation set of 29 asthmatic, and 27 non-asthmatic participants. This was repeated 20 times with different validation participants for additional statistical power, and the average and variability of these metrics were recorded. Results The classification model achieved AUROC of 0.908 \u00b1 0.016, sensitivity of 0.800 \u00b1 0.043, specificity of 0.883 \u00b1 0.012, positive predictive value (PPV) of 0.873 \u00b1 0.010, and negative predictive value (NPV) of 0.817 \u00b1 0.031 in detecting asthma from a single breath record. Conclusion TidalSense\u2019s N-TidalTM capnometer and machine learning classifier could be used as an accurate, rapid, point-of-care diagnostic test for asthma, particularly in primary care. Future work will incorporate longitudinal capnography data into a diagnostic classifier.
\n \n\n \n \nOBJECTIVE: To understand preferences for features of weight loss programs among adults with or at risk of type 2 diabetes in the U.K. RESEARCH DESIGN AND METHODS: We conducted a discrete choice experiment with 3,960 U.K. adults living with overweight (n = 675 with type 2 diabetes). Preferences for seven characteristics of weight loss programs were analyzed. Simulations from choice models using the experimental data predicted uptake of available weight loss programs. Patient groups comprising those who have experience with weight loss programs, including from minority communities, informed the experimental design. RESULTS: Preferences did not differ between individuals with and without type 2 diabetes. Preferences were strongest for type of diet. Healthy eating was most preferred relative to total diet replacement (odds ratio [OR] 2.24; 95% CI 2.04-2.44). Individual interventions were more popular than group interventions (OR 1.40; 95% CI 1.34-1.47). Participants preferred programs offering weight loss of 10-15 kg (OR 1.37; 95% CI 1.28-1.47) to those offering loss of 2-4 kg. Online content was preferred over in-person contact (OR 1.24; 95% CI 1.18-1.30). There were few differences in preferences by gender or ethnicity, although weight loss was more important to women than to men, and individuals from ethnic minority populations identified more with programs where others shared their characteristics. Modeling suggested that tailoring programs to individual preferences could increase participation by \u223c17 percentage points (68% in relative terms). CONCLUSIONS: Offering a range of weight loss programs targeting the preferred attributes of different patient groups could potentially encourage more people to participate in weight loss programs and support those living with overweight to reduce their weight.
\n \n\n \n \nAbstract\nFamily group conferences (FGCs) in child welfare share decision-making with family members by bringing the immediate and wider family together to make a plan to meet a child\u2019s needs. This paper reports survey findings on FGC provision in the UK in 2022 and explores whether in England the presence of an FGC service and the rate of FGC provision is associated with the rate of children in care, entering care, in kinship foster care and leaving care. Seventy-nine per cent (n\u2009=\u2009167) of local authorities in the UK provided FGCs to families, and 14 per cent (n\u2009=\u200929) did not. Services that were more established offered a more diverse range of FGCs. The introduction of FGCs in English local authorities was associated with a higher rate of children in care, but also higher rates of kinship foster care, a key goal of FGCs where it is not possible for children to stay with their parents. Higher rates of FGCs were associated with more children leaving care, possibly due to reunification with birth families. To understand in more detail, the circumstances of children in and leaving care in local authorities with FGCs, individual data linkage studies are needed.
\n \n\n \n \nCONTEXT: X-linked hypophosphataemia (XLH) is a rare genetic disorder causing renal phosphate wasting, which predicates musculoskeletal manifestations such as rickets. Diagnosis is often delayed. OBJECTIVE: To explore the recording of clinical features, and the diagnostic odyssey of children and adolescents with XLH in primary care electronic healthcare records (EHR) in the United Kingdom. METHODS: Using the Optimum Patient Care Research Database, individuals aged 20 years or younger after 1st Jan 2000 at date of recorded XLH diagnosis were identified using SNOMED/Read codes, and age-matched to 100 controls. Recording of XLH-related clinical features was summarised, then compared between cases and controls using Chi-squared or Fisher's exact tests. RESULTS: 261 XLH cases were identified; 99 met inclusion criteria. Of these, 84/99 had at least 1 XLH-related clinical feature recorded in their primary care EHR. Clinical codes for rickets, genu varum and low phosphate were recorded prior to XLH diagnosis in under 20% of cases (median of 1, 1, and 3 years prior, respectively). Rickets, genu varum, low phosphate, nephrocalcinosis and growth delay were significantly more likely to be recorded in cases. CONCLUSION: This characterisation of the EHR phenotypes of children and adolescents with XLH may inform future case-finding approaches to expedite diagnosis in primary care.
\n \n\n \n \nBackground Body mass index (BMI) has been identified as a risk factor for clinical outcomes in patients with COVID-19. Studies identifying this risk have used electronic health record (EHR) platforms in which clinical conditions must be properly identified. We set out to define and evaluate various methods of deriving BMI measurements in OpenSAFELY-TPP, an EHR platform that has been used in many studies relating to the COVID-19 pandemic. Methods With the approval of NHS England, we use routine clinical data from >22 million patients in England to define four derivations of BMI. We compare the number of patients with each type of BMI measurement and the number of measurements themselves. We also examine the plausibility of each derivation by looking at the distribution of measurements and counting values out of the expected range. To evaluate how frequently the BMI derivations are recorded, we track the number of new measurements recorded over time and the average time between updates in patients with multiple measurements. Results Primary constraints in creating the optimal BMI derivation is coverage, accuracy, and computational complexity. BMI derivations calculated from height and weight contain a few extreme outliers that affect aggregated statistics. SNOMED-recorded BMI records are more accurate on average and offer better coverage across the population. The canonical OpenSAFELY definition \u2013 which uses calculated BMI as a first instance and SNOMED-recorded BMI if missing \u2013 offers the best coverage, but contains the same extreme outliers found in calculated BMI and is the most computationally expensive of all methods. Conclusions Across all derivations, some cleaning should be performed to drop implausible outliers. Using calculated BMI on its own does not offer the best coverage or accuracy. In choosing between SNOMED-recorded BMI and the current OpenSAFELY implementation, users should decide whether they would like to maximise computational efficiency or coverage.
\n \n\n \n \nBACKGROUND: COVID-19 pandemic restrictions may have influenced behaviours related to weight. AIMS: To describe patterns of weight change amongst adults living in England with Type 2 Diabetes (T2D) and/or hypertension during the COVID-19 pandemic. Design and Setting With the approval of NHS England, we conducted an observational cohort study using the routinely collected health data of approximately 40% of adults living in England, accessed through the OpenSAFELY service inside TPP. METHOD: We investigated clinical and sociodemographic characteristics associated with rapid weight gain (>0\u00b75kg/m2/year) using multivariable logistic regression. RESULTS: We extracted data on adults with T2D (n=1,231,455, 44% female, 76% white British) or hypertension (n=3,558,405, 50% female, 84% white British). Adults with T2D lost weight overall (median \u03b4 = -0.1kg/m2/year [IQR: -0.7, 0.4]), however, rapid weight gain was common (20.7%) and associated with sex (male vs female: aOR 0.78[95%CI 0.77, 0.79]); age, older age reduced odds (e.g. 60-69-year-olds vs 18-29-year-olds: aOR 0.66[0.61, 0.71]); deprivation, (least-deprived-IMD vs most-deprived-IMD: aOR 0.87[0.85, 0.89]); white ethnicity (Black vs White: aOR 0.95[0.92, 0.98]); mental health conditions (e.g. depression: aOR 1.13 [1.12, 1.15]); and diabetes treatment (non-insulin treatment vs no pharmacological treatment: aOR 0.68[0.67, 0.69]). Adults with hypertension maintained stable weight overall (median \u03b4 = 0.0kg/m2/year [ -0.6, 0.5]), however, rapid weight gain was common (24.7%) and associated with similar characteristics as in T2D. CONCLUSION: Amongst adults living in England with T2D and/or hypertension, rapid pandemic weight gain was more common amongst females, younger adults, those living in more deprived areas, and those with mental health condition.
\n \n\n \n \nBackground: Timely evidence of the comparative effectiveness between COVID-19 therapies in real-world settings is needed to inform clinical care. This study aimed to compare the effectiveness of nirmatrelvir/ritonavir versus sotrovimab and molnupiravir in preventing severe COVID-19 outcomes in non-hospitalised high-risk COVID-19 adult patients during Omicron waves. Methods: With the approval of NHS England, we conducted a real-world cohort study using the OpenSAFELY-TPP platform. Patient-level primary care data were obtained from 24 million people in England and were securely linked with data on COVID-19 infection and therapeutics, hospital admission, and death, covering a period where both nirmatrelvir/ritonavir and sotrovimab were first-line treatment options in community settings (February 10, 2022\u2013November 27, 2022). Molnupiravir (third-line option) was used as an exploratory comparator to nirmatrelvir/ritonavir, both of which were antivirals. Cox proportional hazards model stratified by area was used to compare the risk of 28-day COVID-19 related hospitalisation/death across treatment groups. Findings: A total of 9026 eligible patients treated with nirmatrelvir/ritonavir (n = 5704) and sotrovimab (n = 3322) were included in the main analysis. The mean age was 52.7 (SD = 14.9) years and 93% (8436/9026) had three or more COVID-19 vaccinations. Within 28 days after treatment initiation, 55/9026 (0.61%) COVID-19 related hospitalisations/deaths were observed (34/5704 [0.60%] treated with nirmatrelvir/ritonavir and 21/3322 [0.63%] with sotrovimab). After adjusting for demographics, high-risk cohort categories, vaccination status, calendar time, body mass index and other comorbidities, we observed no significant difference in outcome risk between nirmatrelvir/ritonavir and sotrovimab users (HR = 0.89, 95% CI: 0.48\u20131.63; P = 0.698). Results from propensity score weighted model also showed non-significant difference between treatment groups (HR = 0.82, 95% CI: 0.45\u20131.52; P = 0.535). The exploratory analysis comparing nirmatrelvir/ritonavir users with 1041 molnupiravir users (13/1041 [1.25%] COVID-19 related hospitalisations/deaths) showed an association in favour of nirmatrelvir/ritonavir (HR = 0.45, 95% CI: 0.22\u20130.94; P = 0.033). Interpretation: In routine care of non-hospitalised high-risk adult patients with COVID-19 in England, no substantial difference in the risk of severe COVID-19 outcomes was observed between those who received nirmatrelvir/ritonavir and sotrovimab between February and November 2022, when Omicron subvariants BA.2, BA.5, or BQ.1 were dominant. Funding: UK Research and Innovation, Wellcome Trust, UK Medical Research Council, National Institute for Health and Care Research, and Health Data Research UK.
\n \n\n \n \nBackground: Sepsis, characterised by significant morbidity and mortality, is intricately linked to socioeconomic disparities and pre-admission clinical histories. This study aspires to elucidate the association between non-COVID-19 related sepsis and health inequality risk factors amidst the pandemic in England, with a secondary focus on their association with 30-day sepsis mortality. Methods: With the approval of NHS England, we harnessed the OpenSAFELY platform to execute a cohort study and a 1:6 matched case-control study. A sepsis diagnosis was identified from the incident hospital admissions record using ICD-10 codes. This encompassed 248,767 cases with non-COVID-19 sepsis from a cohort of 22.0 million individuals spanning January 1, 2019, to June 31, 2022. Socioeconomic deprivation was gauged using the Index of Multiple Deprivation score, reflecting indicators like income, employment, and education. Hospitalisation-related sepsis diagnoses were categorised as community-acquired or hospital-acquired. Cases were matched to controls who had no recorded diagnosis of sepsis, based on age (stepwise), sex, and calendar month. The eligibility criteria for controls were established primarily on the absence of a recorded sepsis diagnosis. Associations between potential predictors and odds of developing non-COVID-19 sepsis underwent assessment through conditional logistic regression models, with multivariable regression determining odds ratios (ORs) for 30-day mortality. Findings: The study included 224,361 (10.2%) cases with non-COVID-19 sepsis and 1,346,166 matched controls. The most socioeconomic deprived quintile was associated with higher odds of developing non-COVID-19 sepsis than the least deprived quintile (crude OR 1.80 [95% CI 1.77\u20131.83]). Other risk factors (after adjusting comorbidities) such as learning disability (adjusted OR 3.53 [3.35\u20133.73]), chronic liver disease (adjusted OR 3.08 [2.97\u20133.19]), chronic kidney disease (stage 4: adjusted OR 2.62 [2.55\u20132.70], stage 5: adjusted OR 6.23 [5.81\u20136.69]), cancer, neurological disease, immunosuppressive conditions were also associated with developing non-COVID-19 sepsis. The incidence rate of non-COVID-19 sepsis decreased during the COVID-19 pandemic and rebounded to pre-pandemic levels (April 2021) after national lockdowns had been lifted. The 30-day mortality risk in cases with non-COVID-19 sepsis was higher for the most deprived quintile across all periods. Interpretation: Socioeconomic deprivation, comorbidity and learning disabilities were associated with an increased odds of developing non-COVID-19 related sepsis and 30-day mortality in England. This study highlights the need to improve the prevention of sepsis, including more precise targeting of antimicrobials to higher-risk patients. Funding: The UK Health Security Agency, Health Data Research UK, and National Institute for Health Research.
\n \n\n \n \nBackground The COVID-19 pandemic affected how care was delivered to vulnerable patients, such as those with dementia or learning disability. Objective To explore whether this affected antipsychotic prescribing in at-risk populations. Methods With the approval of NHS England, we completed a retrospective cohort study, using the OpenSAFELY platform to explore primary care data of 59 million patients. We identified patients in five at-risk groups: autism, dementia, learning disability, serious mental illness and care home residents. We calculated the monthly prevalence of antipsychotic prescribing in these groups, as well as the incidence of new prescriptions in each month. Findings The average monthly rate of antipsychotic prescribing increased in dementia from 82.75 patients prescribed an antipsychotic per 1000 patients (95% CI 82.30 to 83.19) in January-March 2019 to 90.1 (95% CI 89.68 to 90.60) in October-December 2021 and from 154.61 (95% CI 153.79 to 155.43) to 166.95 (95% CI 166.23 to 167.67) in care homes. There were notable spikes in the rate of new prescriptions issued to patients with dementia and in care homes. In learning disability and autism groups, the rate of prescribing per 1000 decreased from 122.97 (95% CI 122.29 to 123.66) to 119.29 (95% CI 118.68 to 119.91) and from 54.91 (95% CI 54.52 to 55.29) to 51.04 (95% CI 50.74 to 51.35), respectively. Conclusion and implications We observed a spike in antipsychotic prescribing in the dementia and care home groups, which correlated with lockdowns and was likely due to prescribing of antipsychotics for palliative care. We observed gradual increases in antipsychotic use in dementia and care home patients and decreases in their use in patients with learning disability or autism.
\n \n\n \n \nBACKGROUND: Germ Defence ( www.germdefence.org ) is an evidence-based interactive website that promotes behaviour change for infection control within households. To maximise the potential of Germ Defence to effectively reduce the spread of COVID-19, the intervention needed to be implemented at scale rapidly. METHODS: With NHS England approval, we conducted an efficient two-arm (1:1 ratio) cluster randomised controlled trial (RCT) to examine the effectiveness of randomising implementation of Germ Defence via general practitioner (GP) practices across England, UK, compared with usual care to disseminate Germ Defence to patients. GP practices randomised to the intervention arm (n\u2009=\u20093292) were emailed and asked to disseminate Germ Defence to all adult patients via mobile phone text, email or social media. Usual care arm GP practices (n\u2009=\u20093287) maintained standard management for the 4-month trial period and then asked to share Germ Defence with their adult patients. The primary outcome was the rate of GP presentations for respiratory tract infections (RTI) per patient. Secondary outcomes comprised rates of acute RTIs, confirmed COVID-19 diagnoses and suspected COVID-19 diagnoses, COVID-19 symptoms, gastrointestinal infection diagnoses, antibiotic usage and hospital admissions. The impact of the intervention on outcome rates was assessed using negative binomial regression modelling within the OpenSAFELY platform. The uptake of the intervention by GP practice and by patients was measured via website analytics. RESULTS: Germ Defence was used 310,731 times. The average website satisfaction score was 7.52 (0-10 not at all to very satisfied, N\u2009=\u20099933). There was no evidence of a difference in the rate of RTIs between intervention and control practices (rate ratio (RR) 1.01, 95% CI 0.96, 1.06, p\u2009=\u20090.70). This was similar to all other eight health outcomes. Patient engagement within intervention arm practices ranged from 0 to 48% of a practice list. CONCLUSIONS: While the RCT did not demonstrate a difference in health outcomes, we demonstrated that rapid large-scale implementation of a digital behavioural intervention is possible and can be evaluated with a novel efficient prospective RCT methodology analysing routinely collected patient data entirely within a trusted research environment. TRIAL REGISTRATION: This trial was registered in the ISRCTN registry (14602359) on 12 August 2020.
\n \n\n \n \nContext: Corporate engagement with food and beverage companies who produce food associated with health harms is a divisive topic in the global nutrition community, with high-profile cases of conflict of interest increasingly coming under scrutiny. There is a need for an agreed method to support health organizations in deciding whether and how to engage with large food and beverage manufacturers. Aim: The aim of this study was to develop a method to quantify the proportion of sales from food and beverage companies that are derived from unhealthy foods to support organizations in determining which companies might be considered high-risk for engagement. Methods: The 2015 WHO Euro nutrient profile model was applied to 35,550 products from 1294 brands manufactured by the top 20 global food and beverage companies from seven countries (Australia, Brazil, China, India, South Africa, UK and USA). For the purpose of this study, products that met the WHO Euro criteria were classified as \u201chealthier\u201d and those that failed were classified as \u201cunhealthy\u201d. Products were grouped by brand and weighted by the brand\u2019s value sales for 2020. The primary outcome was the proportion of each company\u2019s sales that were classified as unhealthy and healthier by company and category. Results: Overall, 89% of the top 20 companies\u2019 brand sales were classified as unhealthy. For every USD$10 spent on the top 20 companies\u2019 brands, only $1.10 was spent on products considered healthier. All companies saw the majority of their sales come from unhealthy foods, including soft drinks, confectionery and snacks. None of Red Bull or Ferrero\u2019s sales were classified as healthier and less than 5% of total sales were healthier for Mondel\u0113z, Mars, and PepsiCo. Some companies had higher proportions of sales deriving from healthier products, including Grupo Bimbo (48%), Danone (34%) and Conagra (32%), although the majority of their sales were still derived from unhealthy foods. Discussion: The results presented in this study highlight the reliance the leading food and beverage companies have on sales of unhealthy products that are contributing to diet-related disease globally. The method and steps we have laid out here could be used by organizations in the global health community to identify companies that have conflicts of interest when it comes to engaging with governments, international organizations and public health bodies on issues of policy and regulation.
\n \n\n \n \nBackground: Achieving a sustained energy deficit is essential for weight loss, but the cognitive and behavioral strategies that support this goal are unclear. Objective: The goal of this study was to investigate the number and type of cognitive and behavioral strategies used by participants who were enrolled in a 1-year weight loss trial and to explore associations between strategies and magnitude of weight loss at 3 months and 1 year. Design: The study is a secondary post-hoc exploratory analysis of data collected as part of the Doctor Referral of Overweight People to Low-Energy total diet replacement Treatment (DROPLET), a randomized controlled trial conducted in general practices in England, United Kingdom, between January 2016 and August 2017. Participants/setting: This study involved 164 participants from both intervention and control groups of the DROPLET trial who completed the Oxford Food and Behaviours (OxFAB) questionnaire to assess the use of 115 strategies grouped into 21 domains used to manage their weight. Interventions: Participants were randomized to either a behavioral weight loss program involving 8 weeks total diet replacement (TDR) and 4 weeks of food reintroduction or a program delivered by a medical practice nurse over a 3-month period (usual care [UC]). Main outcome measures: Weight was objectively measured at baseline, 3 months, and 1 year. Cognitive and behavioral strategies used to support weight loss were assessed using the OxFAB questionnaire at 3 months. Statistical analysis performed: Exploratory factor analysis was used to generate data-driven patterns of strategy use, and a linear mixed-effects model was used to examine associations between use of these patterns and weight change. Results: No evidence was found of a difference in the number of strategies (mean difference, 2.41; 95% confidence interval [CI], \u22120.83, 5.65) or the number of domains used (mean difference, \u22120.23; 95% CI, \u22120.69, 0.23) between the TDR group and the UC group. The number of strategies was not associated with weight loss at either 3 months (\u22120.02 kg; 95% CI, \u22120.11, 0.06) or 1 year (\u22120.05 kg; 95% CI, \u22120.14, 0.02). Similarly, the number of domains used was not associated with weight loss at 3 months (\u22120.02 kg; 95% CI, \u22120.53, 0.49) or 1 year (\u22120.07 kg; 95% CI, \u22120.60, 0.46). Factor analysis identified four coherent patterns of strategy use, identified as Physical Activity, Motivation, Planned Eating, and Food Purchasing patterns. Greater use of strategies in the Food Purchasing (\u22122.6 kg; 95% CI, \u22124.42, \u22120.71) and Planned Eating patterns (\u22123.20 kg; 95% CI, \u22124.94, \u22121.46) was associated with greater weight loss at 1 year. Conclusions: The number of cognitive and behavioral strategies or domains used does not appear to influence weight loss, but the types of strategy appear of greater importance. Supporting people to adopt strategies linked to planned eating and food purchasing may aid long-term weight loss.
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