Differences in weight change trajectory patterns in a publicly funded adult weight management centre

Weight Loss Trajectories and Short-Term Prediction in an Online Weight Management Program

The extent to which early weight loss in behavioral weight control interventions predicts long-term success remains unclear. In this study, we developed an algorithm aimed at classifying weight change trajectories and examined its ability to predict long-term weight loss based on weight early change. We utilized data from 667 de-identified individuals who participated in a commercial weight loss program (Instinct Health Science), comprising 69,363 weight records. Sequential polynomial regression models were employed to classify participants into distinct weight trajectory patterns based on key model parameters. Next, we applied multinomial logistic models to evaluate if early weight loss in the first 14 days and prolonged duration of participation were significantly associated with long-term weight loss patterns. The mean percentage of weight loss was 7.9 ± 5.1% over 133 ± 69 days. Our analysis revealed four main weight loss trajectory patterns: a steady decrease over time (30.6%), a decrease to a plateau with subsequent decline (15.8%), a decrease to a plateau with subsequent increase (46.9%), and no substantial decrease (6.7%). Early weight change rate and total participating duration emerged as significant factors in differentiating long-term weight loss patterns. These findings contribute to support the provision of tailored advice in the early phase of behavioral interventions for weight loss.

Association between weight-loss history and weight loss achieved in clinical obesity management: Retrospective chart review

OBJECTIVE

Weight history and its association with the weight loss achieved in a publicly funded clinical obesity management program were examined in 9348 patients.

METHODS

Weight history (frequency and magnitude of weight losses) was collected through questionnaires at enrollment, and weight change was assessed with retrospective electronic medical chart review.

RESULTS

The majority of patients reported developing overweight prior to the age of 40 years and having lost at least 4.5 kg (10 lb) of weight at least once in their lifetime. Those who had an earlier onset of overweight had a higher frequency of past weight loss and had more cumulative weight loss over their lifetime. In women, but not men, earlier age of overweight onset and lifetime weight loss were associated with modestly greater weight loss at the clinic.

CONCLUSIONS

Women with greater weight-loss history also have modestly greater weight loss at the obesity management clinic. Thus, successful long-term obesity management, particularly for women, may include a series of repeated attempts at weight loss that should not be viewed as failures but could be viewed instead as practice.

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.

Weight Loss Trajectories and Related Factors in a 16-Week Mobile Obesity Intervention Program: Retrospective Observational Study

Background

In obesity management, whether patients lose ≥5% of their initial weight is a critical factor in clinical outcomes. However, evaluations that take only this approach are unable to identify and distinguish between individuals whose weight changes vary and those who steadily lose weight. Evaluation of weight loss considering the volatility of weight changes through a mobile-based intervention for obesity can facilitate understanding of an individual’s behavior and weight changes from a longitudinal perspective.

Objective

The aim of this study is to use a machine learning approach to examine weight loss trajectories and explore factors related to behavioral and app use characteristics that induce weight loss.

Methods

We used the lifelog data of 13,140 individuals enrolled in a 16-week obesity management program on the health care app Noom in the United States from August 8, 2013, to August 8, 2019. We performed k-means clustering with dynamic time warping to cluster the weight loss time series and inspected the quality of clusters with the total sum of distance within the clusters. To identify use factors determining clustering assignment, we longitudinally compared weekly use statistics with effect size on a weekly basis.

Results

The initial average BMI value for the participants was 33.6 (SD 5.9) kg/m², and it ultimately reached 31.6 (SD 5.7) kg/m². Using the weight log data, we identified five clusters: cluster 1 (sharp decrease) showed the highest proportion of participants who reduced their weight by >5% (7296/11,295, 64.59%), followed by cluster 2 (moderate decrease). In each comparison between clusters 1 and 3 (yo-yo) and clusters 2 and 3, although the effect size of the difference in average meal record adherence and average weight record adherence was not significant in the first week, it peaked within the initial 8 weeks (Cohen d>0.35) and decreased after that.

Conclusions

Using a machine learning approach and clustering shape-based time series similarities, we identified 5 weight loss trajectories in a mobile weight management app. Overall adherence and early adherence related to self-monitoring emerged as potential predictors of these trajectories.

An analysis of weight loss efforts and expectations in a Canadian Cohort: A retrospective medical chart review

The weight loss history and weight loss goals were examined in 4108 patients referred to a publicly funded evidence-based clinical weight management program using a retrospective chart review. The majority of patients were white females, aged of 50.1 ± 13.7 years and a BMI of 39.0 ± 7.5 kg/m² . Pregnancy was the most common reason for weight gain in women (17.7%) and while the reasons in men are more varied (injury, stress and medication: all ~5%). Over 50% of patients cited no specific reason for their weight gain. Self-directed diet and exercise were the most commonly used self-reported weight loss methods. Women were more likely to report using medication and bariatric surgical weight loss methods than men (P < .05), and only 5% of women and 12.8% men report never having tried to lose weight in the past. Patients had an ideal weight loss goal of 28.9% to 34.4%, which was similar to the patient's lowest reported adult weight. Approximately 70% of patients enrolling at the clinic had previously lost at least 4.5 kg (10 lb) one or more times and 16.7% lost weight at least 5 times in their life, but patient weight at enrolment was similar to their highest adult reported weight. Thus, most patients referred to this clinical weight management program have previously attempted self-directed diet and exercise weight loss. Patients were close to their highest adult weight and had very large weight loss goals, similar to what is typically achieved only by surgical intervention, despite having already had several bouts of weight loss.

Predictors of Weight Loss and Weight Gain in Weight Management Patients during the COVID-19 Pandemic

OBJECTIVE

To examine the associations between patient struggles, health, and weight management changes during the COVID-19 pandemic.

METHODS

585 patients attending a publicly funded clinical weight management program responded to an electronic survey.

RESULTS

Over half of the patients reported worsened overall health, mental health, physical activity, or diet during the pandemic. Approximately 30% of patients lost ≥3% of their body weight and 21% gained ≥3% of their body weight between March and July of the pandemic. Reports of social isolation was associated with increased odds for weight loss in women (OR = 2.0, 1.2-3.3), while low motivation (OR = 1.9, 1.0-3.7), depression (OR = 2.5, 1.0-6.3), and struggles with carbohydrate intake (OR = 2.1, 1.0-4.3) were associated with weight gain. Cooking more at home/eating less take out was associated with increased likelihood of weight loss (OR = 2.1, 1.1-3.9) and lower odds for weight gain (OR = 0.2, 0.1 to 0.97). Working from home was not associated with weight loss or weight gain (P > 0.6).

CONCLUSION

The COVID-19 pandemic is associated with certain factors that may facilitate weight loss and other factors that promote weight gain. Thus, depending on the patient experience during the pandemic, prevention of weight gain may be more appropriate than weight loss.

Effect of a 30-Month Health-Promoting Program on the Prevalence of Cardiovascular Risk Factors in Patients With First Episode Schizophrenia

BACKGROUND

Lifestyle interventions aimed at reducing cardiovascular risk factors in patients with first-episode schizophrenia (FES) have shown modest efficacy, probably owing to a short observation period and the presumption of linear trajectories of cardiovascular risk factors.

STUDY QUESTION

How prevalent are abnormal cardiovascular values in patients with FES and how do cardiovascular risk factors develop during a 30-month program?

STUDY DESIGN

A 30-month naturalistic longitudinal study of 136 consecutively referred patients with FES from 2 outpatient clinics. The health-promoting program consisted of individual guidance, group sessions, and normal treatment and care.

MEASURES AND OUTCOMES

The prevalence of abnormal cardiovascular risk factors (body mass index, waist circumference (WC), body fat percentage, systolic and diastolic blood pressure, pulse, total cholesterol, high- and low-density lipoproteins, triglycerides, mean glucose, and visceral adiposity index) was estimated at index. The cardiovascular risk factor trajectories were analyzed with longitudinal mixed-effect models.

RESULTS

The patient with FES showed elevated cardiovascular risk factors at index. Thus, 56.8% of the patients were overweight in different grades and 50.4% had increased WC. A total of 81.8% had high level of body fat and hypertension prevalence with only 20% with normal blood pressure. Important changes during the intervention period were that the risk factors weight and WC were increasing the first 581 and 646 days, after which they decreased. Almost all cardiovascular risk factors worsened initially, improving after 1-2 years.

CONCLUSIONS

Patients with FES show increases in cardiovascular risk factors at index. Short observation periods and the presumption of linear trajectories may indicate that the effect of health-promoting programs is ineffective, as the effects are curvilinear and improvements appear only after 1 year. The implication clinically is the importance of a long intervention period regarding lifestyle modifications to ascertain improvement among patients with FES.

Absolute Weight Loss, and Not Weight Loss Rate, Is Associated with Better Improvements in Metabolic Health

OBJECTIVE

To determine if the rate of weight loss (WL) is associated with metabolic changes independent of the absolute WL.

METHODS

WL and health changes were assessed in 11,281 patients attending a publicly funded clinical weight management program over a treatment period of 12.7 months. Early weight loss rate (WLR) in the first 3-6 months and overall WLR were categorized as Fast WLR (≥1 kg/wk), Recommended WLR (0.5 to 0.9 kg/wk), or Slow WLR (<0.5 kg/wk).

RESULTS

On average, patients attained a 6.6 ± 7.3 kg (5.8 ± 5.7%) WL over 12.8 ± 13.1 months. Prior to adjusting for covariates, patients with Fast WLR (-24.7 ± 13.4 kg) at 3-6 months had a greater overall WL as compared to those with Recommended WLR (-13.3 ± 8.7 kg) and Slow WLR (-5.0 ± 5.4 kg). Fast WLR also had greater improvements in the overall waist circumference and blood pressure than patients with Slow or Recommended WLR. However, after adjustment for absolute WL, Early and overall Recommended and Fast WLR did not differ in the changes in any of the health markers (P > 0.05). Conversely, the absolute WL sustained is significantly associated with changes in metabolic health independent of WLR (P < 0.001). Similar results were observed with WLR over the entire treatment period.

CONCLUSIONS

Faster rates of WL are associated with a greater absolute WL and larger improvements in waist circumference and blood pressure. However, after adjusting for the larger absolute WL sustained, early and overall faster WLR do not appear to have advantages for improving metabolic health markers. Thus, the absolute WL attained may be the most important factor for improving metabolic health.

Individuals with obesity but no other metabolic risk factors are not at significantly elevated all-cause mortality risk in men and women

Studies have examined mortality risk for metabolically healthy obesity, defined as zero or one metabolic risk factors but not as zero risk factors. Thus, we sought to determine the independent mortality risk associated with obesity or elevated glucose, blood pressure or lipids in isolation or clustered together. The sample included 54 089 men and women from five cohort studies (follow-up = 12.8 ± 7.2 years and 4864 [9.0%] deaths). Individuals were categorized as having obesity or elevated glucose, blood pressure or lipids alone or clustered with obesity or another metabolic factor. In our study sample, 6% of individuals presented with obesity but no other metabolic abnormalities. General obesity (hazard ratios [HR], 95% CI = 1.10, 0.8-1.6) and abdominal obesity (HR = 1.24, 0.9-1.7) in the absence of metabolic risk factors were not associated with mortality risk compared to lean individuals. Conversely, diabetes, hypertension and dyslipidaemia in isolation were significantly associated with mortality risk (HR range = 1.17-1.94, P < 0.05). However, when using traditional approaches, obesity (HR = 1.12, 1.02-1.23) is independently associated with mortality risk after statistical adjustment for the other metabolic risk factors. Similarly, metabolically healthy obesity, when defined as zero or one risk factor, is also associated with increased mortality risk (HR = 1.15, 1.01-1.32) as compared to lean healthy individuals. Obesity in the absence of metabolic abnormalities may not be associated with higher risk for all-cause mortality compared to lean healthy individuals. Conversely, elevation of even a single metabolic risk factor is associated with increased mortality risk.

Differences in weight change trajectory patterns in a publicly funded adult weight management centre

Objective

To describe differences in weight loss (WL) trajectory patterns at a publicly funded clinical weight management centre.

Methods

Groups with differences in the attainment of a 5% total body WL and percentage WL patterns over time were identified in 7,121 patients who attended a physician lead multi‐disciplinary clinical lifestyle weight management that predominantly focused on education and diet counselling. Resultant health differences were examined.

Results

Patients had 3.2 ± 6.3%WL with 35% of patients achieving and maintaining a 5%WL. Half of these patients achieved the 5%WL within 6 months, while the other half had a more gradual approach. Another 10% achieved 5%WL, but regained weight after 6 months. There were seven distinct WL patterns identified: LargeWL (Mean WL: 21.2 ± 8.1%; Probability of group membership (PGM): 2.4%), ModerateWL (15.1 ± 5.1%WL; 5.4%PGM), SlowWL (6.7 ± 3.2%WL; 20.1%PGM) and MinimalWL (2.4 ± 2.2%WL; 34.6%PGM), WL Regain (9.4 ± 3.5%WL; 8.2%PGM), Weight Stable (1.2 ± 3.2%WL; 28.5%PGM) and Weight Gain (18.4 ± 11.2%WG; 0.8%PGM) groups. Improvements in blood pressure, lipids and glucose were generally related to the magnitude of WL achieved more than the pattern or speed of WL.

Conclusions

There are large differences in the absolute WL attained and the pattern of WL during a publicly funded weight management program. Changes in clinical health markers appear to be more strongly related with the absolute WL attained as opposed to patterns of weight change. © 2016 The Authors. Obesity Science & Practice published by John Wiley & Sons Ltd, World Obesity and The Obesity Society.