Participants' experiences of mental health during a COVID-19 tailored ACT-based behavioural weight management intervention: a qualitative study.

PURPOSE: We aimed to explore participants' experiences of mental health during an acceptance and commitment therapy (ACT)-based guided self-help intervention to support weight management in adults with overweight or obesity during the COVID-19 pandemic (SWiM-C: Supporting Weight Management during COVID-19). METHODS: We conducted semi-structured telephone interviews with twenty participants and used reflexive thematic analysis to identify patterns of meaning across the dataset relevant to mental health. RESULTS: Four themes were conceptualized: i) Mental health changes associated with SWiM-C, ii) External factors negatively impacted mental health and intervention engagement, iii) Use and impact of coping responses, and iv) Intervention preferences based on psychological needs. CONCLUSIONS: Findings suggest that participants were exposed to multiple factors, both related to and external to the intervention, that negatively impact their mental health, yet ACT-based aspects of the SWiM-C intervention appeared to support participants to adaptively manage the decline in their mental health. The findings can be used to inform the development of future weight management interventions, such as through intervention personalization and the inclusion of more strategies that target emotional regulation.Trial registration: ISRCTN 12107048, https://www.isrctn.com/ISRCTN12107048.

Recommendations from a Working Group on Obesity Care Competencies for Healthcare Education in the UK: A Report by the Steering Committee.

INTRODUCTION: Obesity significantly increases the risk of developing (or worsening) more than 200 chronic diseases, and it is also a risk factor for severe COVID-19. With the rising prevalence of obesity in the UK, there is a need to develop obesity care competencies that apply to healthcare professionals (HCPs) at all levels of the health service, to increase the capacity for contemporary, evidence-based treatment that is effective, compassionate, and avoids stigmatising patients. METHODS: A UK Obesity Care Competencies Working Group consisting of experts by profession and experts by experience was created to provide a framework of obesity care competencies for HCPs involved in specialist obesity care (tiers 2-4 in the UK). The framework was adapted from a set of competencies recently published by the USA-based Obesity Medicine Education Collaborative (OMEC) and was intended to be adaptable to nurses and allied health professionals, as well as physicians, owing to the multidisciplinary team approach used in healthcare in the UK. RESULTS: The UK Obesity Care Competencies Working Group developed a set of 29 competencies, divided into five focal areas, namely obesity knowledge, patient care and procedural skills, practice-based learning and improvement, professionalism and interpersonal communication skills, and systems-based practice. The working group recommends that the obesity care competencies are targeted at HCPs training as specialists. The competencies could be imported into existing training programmes to help standardise obesity-related medical education and could also be used to direct a new General Practitioner with Extended Role (GPwER) qualification. CONCLUSION: This list of obesity care competencies aims to provide an initial framework to improve education for HCPs and therefore to improve patient care in obesity. The acceptance and integration of these competencies into the healthcare system should provide a stepping stone toward addressing trends in health inequality.

Body Mass Index, Multi-Morbidity, and COVID-19 Risk Factors as Predictors of Severe COVID-19 Outcomes.

PURPOSE: The purpose of the present study was to investigate body mass index, multi-morbidity, and COVID-19 Risk Score as predictors of severe COVID-19 outcomes. PATIENTS: Patients from this study are from a well-characterized patient cohort collected at Mayo Clinic between January 1, 2020 and May 23, 2020; with confirmed COVID-19 diagnosis defined as a positive result on reverse-transcriptase-polymerase-chain-reaction (RT-PCR) assays from nasopharyngeal swab specimens. MEASURES: Demographic and clinical data were extracted from the electronic medical record. The data included: date of birth, gender, ethnicity, race, marital status, medications (active COVID-19 agents), weight and height (from which the Body Mass Index (BMI) was calculated, history of smoking, and comorbid conditions to calculate the Charlson Comorbidity Index (CCI) and the U.S Department of Health and Human Services (DHHS) multi-morbidity score. An additional COVID-19 Risk Score was also included. Outcomes included hospital admission, ICU admission, and death. RESULTS: Cox proportional hazards models were used to determine the impact on mortality or hospital admission. Age, sex, and race (white/Latino, white/non-Latino, other, did not disclose) were adjusted for in the model. Patients with higher COVID-19 Risk Scores had a significantly higher likelihood of being at least admitted to the hospital (HR = 1.80; 95% CI = 1.30, 2.50; P < .001), or experiencing death or inpatient admission (includes ICU admissions) (HR = 1.20; 95% CI = 1.02, 1.42; P = .028). Age was the only statistically significant demographic predictor, but obesity was not a significant predictor of any of the outcomes. CONCLUSION: Age and COVID-19 Risk Scores were significant predictors of severe COVID-19 outcomes. Further work should examine the properties of the COVID-19 Risk Factors Scale.

A Midwest COVID-19 Cohort for the Evaluation of Multimorbidity and Adverse Outcomes from COVID-19.

OBJECTIVE: To describe the process and outcome of creating a patient cohort in the early stages of the COVID-19 pandemic in order to better understand the process of and predict the outcomes of COVID-19. PATIENTS AND METHODS: A total of 1169 adults aged 18 years of age or older who tested positive in Mayo Clinic Rochester or the Mayo Clinic Midwest Health System between January 1 and May 23 of 2020. RESULTS: Patients were on average 43.9 years of age and 50.7% were female. Most patients were white (69.0%), and Blacks (23.4%) and Asians (5.8%) were also represented in larger numbers. Hispanics represented 16.3% of the sample. Just under half of patients were married (48.4%). Common comorbid conditions included: cardiovascular diseases (25.1%), dyslipidemia (16.0%), diabetes mellitus (11.2%), chronic obstructive pulmonary disease (6.6%), asthma (7.5%), and cancer (5.1%). All other comorbid conditions were less the 5% in prevalence. Data on 3 comorbidity indices are also available including the: DHHS multi-morbidity score, Charlson Comorbidity Index, and Mayo Clinic COVID-19 Risk Factor Score. CONCLUSION: In addition to managing the ever raging pandemic and growing death rates, it is equally important that we develop adequate resources for the investigation and understanding of COVID-19-related predictors and outcomes.