Determining patient attendance, access to interventions and clinical outcomes in a publicly funded obesity programme: Results from the Canberra Obesity Management Service

Developing a Decision Aid for Clinical Obesity Services in the Real World: the DACOS Nationwide Pilot Study

PURPOSE

The purpose of this study is to develop a decision aid tool using "real-world" data within the Australian health system to predict weight loss after bariatric surgery and non-surgical care.

MATERIALS AND METHODS

We analyzed patient record data (aged 16+years) from initial review between 2015 and 2020 with 6-month (n=219) and 9-/12-month (n=153) follow-ups at eight clinical obesity services. Primary outcome was percentage total weight loss (%TWL) at 6 months and 9/12 months. Predictors were selected by statistical evidence (p<0.20), effect size (±2%), and clinical judgment. Multiple linear regression and bariatric surgery were used to create simple predictive models. Accuracy was measured using percentage of predictions within 5% of the observed value, and sensitivity and specificity for predicting target weight loss of 5% (non-surgical care) and 15% (bariatric surgery).

RESULTS

Observed %TWL with bariatric surgery vs. non-surgical care was 19% vs. 5% at 6 months and 22% vs. 5% at 9/12 months. Predictors at 6 months with intercept (non-surgical care) of 6% include bariatric surgery (+11%), BMI>60 (-3%), depression (-2%), anxiety (-2%), and eating disorder (-2%). Accuracy, sensitivity, and specificity were 58%, 69%, and 56%. Predictors at 9/12 months with intercept of 5% include bariatric surgery (+15%), type 2 diabetes (+5%), eating disorder (+4%), fatty liver (+2%), atrial fibrillation (-4%), osteoarthritis (-3%), sleep/mental disorders (-2-3%), and ≥10 alcohol drinks/week (-2%). Accuracy, sensitivity, and specificity were 55%, 86%, and 53%.

CONCLUSION

Clinicians may use DACOS to discuss potential weight loss predictors with patients after surgery or non-surgical care.

Effectiveness of eHealth weight management interventions in overweight and obese adults from low socioeconomic groups: a systematic review

Background

Low socioeconomic status (SES) is associated with increased rates of overweight and obesity. Proponents of electronic health (eHealth) hypothesise that its inclusion in weight management interventions can improve efficacy by mitigating typical barriers associated with low SES.

Objectives

To establish the scope of eHealth weight management interventions for people with overweight and obesity from a low SES. Secondary objectives were to determine the efficacy of eHealth interventions in facilitating weight loss, physical activity and fitness improvements.

Methods

Four databases and grey literature were systematically searched to identify eligible studies published in English from inception to May 2021. Studies examining an eHealth intervention with low SES participants were included. Outcomes included temporal change in weight and BMI, anthropometry, physiological measures and physical activity levels. The number and heterogeneity of studies precluded any meta-analyses; thus, a narrative review was undertaken.

Results

Four experimental studies with low risk of bias were reviewed. There was variance in how SES was defined. Study aims and eHealth media also varied and included reducing/maintaining weight or increasing physical activity using interactive websites or voice responses, periodic communication and discourse via telephone, social media, text messaging or eNewsletters. Irrespectively, all studies reported short-term weight loss. eHealth interventions also increased short-term physical activity levels where it was assessed, but did not change anthropometry or physiological measures. None reported any effect on physical fitness.

Conclusions

This review revealed short-term effects of eHealth interventions on weight loss and increased physical activity levels for low SES participants. Evidence was limited to a small number of studies, with small to moderate sample sizes. Inter-study comparison is challenging because of considerable variability. Future work should prioritise how to utilise eHealth in the longer term either as a supportive public health measure or by determining its long-term efficacy in engendering volitional health behaviour changes.

Systematic review registration

PROSPERO CRD42021243973

Supplementary Information

The online version contains supplementary material available at 10.1186/s13643-023-02207-3.

Evaluation of Excessive Daytime Sleepiness, Anxiety and Depression Symptomatologies in Obesity

Aim: In this study, it was aimed to evaluate the excessive daytime sleepiness, anxiety and depression symptomatology in normal-weight, overweight and obese individuals. Methods: In the study, 605 people who applied to the family medicine outpatient clinic between 2020 November 25 and 2021 March 5 were included. The questionnaire form evaluating the sociodemographic characteristics of the participants, the Hospital Anxiety and Depression Scale and the Epworth Sleepiness Scale were administered using a face-to-face interview technique. Results: Overweight status in primary school, high school/adolescence, and university/twenties were higher in obese than in overweight. Additionally, it was higher in overweight than in normal weight. The risk of being overweight was 2.19 times higher and the risk of being obese was 6.07 times higher than those with obesity in their family compared to those who did not. Excessive daytime sleepiness was 2.95 times higher in obese than in normal weight. Anxiety symptoms were 1.97 times higher in obese than in normal weight. Depression symptoms were 2.77 times more in overweight and 2.99 times more in obese compared to normal-weight individuals. Conclusion: As a result of this study, it was revealed that excessive daytime sleepiness, anxiety and depression symptomatologies are more common in obese compared to normal weight. Keywords: obesity, overweight, depression, anxiety, disorders of excessive somnolence

Assessing service provision and outcomes at the Canberra Obesity Management Service: A retrospective chart review

OBJECTIVE

This study aimed to evaluate the multidisciplinary care model of the Canberra Obesity Management Service (COMS) with regard to patient demographics and clinical outcomes, particularly in comparison with previous COMS outcome reviews.

METHODS

A retrospective chart review was carried out on all patients attending an initial assessment at COMS between July 2018 and June 2019. Existing patients attending follow-up reviews were excluded so as to avoid repeating analyses of data from previous COMS reviews. Patient data were recorded and deidentified and underwent descriptive analyses.

RESULTS

A total of 234 patients with a mean age of 45.6 (SD = 13.9) years, mean BMI of 50.1 kg/m² (SD = 8.5), and a female majority (72.2%) were analyzed. Of the 165 patients who attended follow-up appointments, 27.9% experienced ≥10% weight loss (46/165). Sleeve gastrectomy was associated with the largest mean weight reduction (15.6% at 6 months [n = 18]).

CONCLUSIONS

Compared with previous COMS studies, both the throughput and proportion of participants achieving clinically meaningful weight reduction were observed to have increased. Further studies assessing service cost-effectiveness, the development of standardized treatment pathways, and the use of a systematic data collection system would be valuable in allowing comparison between outcomes with similar obesity services in Australia and internationally.

Long-Term Trajectories in Weight and Health Outcomes Following Multidisciplinary Publicly Funded Bariatric Surgery in Patients with Clinically Severe Obesity (≥ 3 Associated Comorbidities): A Nine-Year Prospective Cohort Study in Australia

Background: Real-world data on long-term (> 5 years) weight loss and obesity-related complications after newer bariatric surgical procedures are currently limited. The aim of this longitudinal study was to examine the effectiveness and sustainability of bariatric surgery in a cohort with clinically severe obesity in a multidisciplinary publicly funded service in two teaching hospitals in New South Wales, Australia. Methods: Patients were adults with complex clinically severe obesity with a BMI ≥ 35 kg/m2 and at least three significant obesity-related comorbidities, who underwent bariatric surgeries between 2009 and 2017. Detailed obesity-related health outcomes were reported from annual clinical data and assessments for up to 9 years of follow-up. Data were also linked with the national joint replacement registry. Results: A total of 65 eligible patients were included (mean, 7; range, 3−12 significant obesity-related comorbidities); 53.8% female; age 54.2 ± 11.2 years, with baseline BMI 52.2 ± 12.5 kg/m2 and weight 149.2 ± 45.5 kg. Most underwent laparoscopic sleeve gastrectomy (80.0%), followed by laparoscopic adjustable gastric banding (10.8%) and one anastomosis gastric bypass (9.2%). Substantial weight loss was maintained over 9 years of follow-up (p < 0.001 versus baseline). Significant total weight loss (%TWL ± SE) was observed (13.2 ± 2.3%) following an initial 1-year preoperative intensive lifestyle intervention, and ranged from 26.5 ± 2.3% to 33.0 ± 2.0% between 1 and 8 years following surgery. Type 2 diabetes mellitus (T2DM), osteoarthritis-related joint pain and depression/severe anxiety were the most common metabolic, mechanical and mental health comorbidities, with a baseline prevalence of 81.5%, 75.4% and 55.4%, respectively. Clinically significant composite cumulative rates of remission and improvement occurred in T2DM (50.0−82.0%) and hypertension (73.7−82.9%) across 6 years. Dependence on continuous positive airway pressure treatment in patients with sleep-disordered breathing fell significantly from 63.1% to 41.2% in 6 years. Conclusion: Bariatric surgery using an intensive multidisciplinary approach led to significant long-term weight loss and improvement in obesity-related comorbidities among the population with clinically complex obesity. These findings have important implications in clinical care for the management of the highest severity of obesity and its medical consequences. Major challenges associated with successful outcomes of bariatric surgery in highly complex patients include improving mental health in the long run and reducing postoperative opioid use. Long-term follow-up with a higher volume of patients is needed in publicly funded bariatric surgery services to better monitor patient outcomes, enhance clinical data comparison between services, and improve multidisciplinary care delivery.

Association of clinically significant weight loss with number of patient visits and months of attendance at an Australian multidisciplinary weight management clinic

Despite the obesity epidemic, there are relatively few multidisciplinary obesity services in Australia, and only limited data on the effectiveness of these services. The aim of this study was to evaluate the effectiveness of a university hospital-based weight management clinic-the 'Healthy Weight Clinic' in supporting patients to achieve clinically significant weight loss (≥5% reduction in body weight), weight maintenance, and changes in body composition. A retrospective review was conducted to determine weight and associated health outcomes in patients who attended an initial consultation in the first 2 years of the clinic-between March 2017 and March 2019. Follow up was at least 1 year for all patients. Patients who underwent bariatric surgery were excluded. Of 213 total patients, 172 patients attended more than one follow-up consultation for lifestyle modification. Mean weight change and percentage total weight change at last follow-up was -6.2 kg (SD 7.4) and - 6.0% (SD 6.9), respectively. For every additional clinic follow-up, there was 21.4% increased odds of achieving clinically significant weight loss, and for every additional month of follow-up, there was 10.1% increased odds of achieving clinically significant weight loss. Twenty percent of patients (34/172) maintained ≥5% of initial body weight loss for at least 1 year. Body composition measurements were also favourable, with significant changes in percentage skeletal muscle mass of +0.8% (SD 1.5) and in percentage fat mass by -1.4% (SD 3.2). Regular support in a structured holistic multidisciplinary obesity service enables patients to achieve clinically meaningful weight loss and improved skeletal muscle mass to body fat ratio, and maintain this loss for at least 1 year. Improved weight loss was associated with more patient visits and longer duration of attendance at the clinic.

Mental illness as a predictor of patient attendance and anthropometric changes: observations from an Australian publicly funded obesity management service

OBJECTIVE

Obesity is associated with co-morbid mental illness. The Canberra Obesity Management Service (OMS) supports adults with severe obesity who have the psychosocial capacity to engage. This study will determine whether mental illness is a predictor of OMS attendance and anthropometric changes.

METHOD

A retrospective audit was performed from July 2016 to June 2017. Baseline characteristics, attendance and anthropometrics were stratified according to the presence of mental illness. Outcomes included weight stabilisation and clinically significant weight loss. Descriptive analyses were performed.

RESULTS

Mental illness was present in 60/162 patients (37%). Attendance was similar for those with and without mental illness. Patients with mental illness had twice as many co-morbidities (p = .001). Depressive disorders were most common (n = 28, 47%). Anxiety, schizophrenia spectrum and other psychotic disorders, and trauma- and stressor-related disorders also featured. Weight stabilisation was achieved by 25 patients (66%) with mental illness and 25 (35%) without. Clinically significant weight loss was observed in 10 patients (26%) with and 26 (40%) without mental illness.

CONCLUSION

The presence of mental illness did not impact OMS attendance or weight stabilisation. The higher rate of co-morbidities in those with mental illness highlights the challenges faced by this vulnerable population.