New weight management medications, such as GLP-1 receptor agonists, have dramatically altered the landscape of obesity treatment. Weight change has traditionally been the only measure of obesity treatment efficacy, and the weight loss achieved with GLP-1 drugs outclasses prior pharmaceutical treatments and lifestyle interventions.  

However, the impact of GLP-1 medications on patient well-being is multifaceted, and key questions remain unanswered. One major concern is the loss of muscle mass by patients taking this treatment. Lean mass is crucial for overall health and functionality, and its loss leads to short and long-term adverse effects. It’s essential to address concerns like this and develop evidence-based guidelines to realize a sustainable option for obesity treatment. 

In our recent Digital Health Monthly webinar session, we were joined by -

• Dr. Glenn Gaesser, Professor at Arizona State University, who shared research from his decades of experience investigating the relationship between weight loss, physical activity, and cardiovascular fitness, and reviewed the impact these factors can have on overall health outcomes.
• Dr. Sylvain Zorman, Director of Digital Health at ActiGraph, discussed how objective, continuous data captured with medical-grade wearables in clinical trials (also referred to as wearable digital health technologies, DHTs) can give researchers a clearer picture of the level and quality of key factors such as physical activity and sleep behavior that can have an impact on the effectiveness of obesity treatment. 
  

Physical Fitness and Weight Loss: Impact on Mortality Risk 

Over the last 60 years, along with the growing incidence of obesity, weight loss attempt prevalence has been steadily increasing, with currently 40-50% of the US population attempting weight loss each year.

These trends highlight that the majority weight loss attempts are not effective or even deleterious – but why? 

One likely factor is that many individuals focus on weight loss alone, which is notoriously difficult to sustain in the long term. Dr. Gaesser outlined two approaches to obesity treatment. In a weight-centric approach, individuals lose weight but often regain it within a relatively short time, thereby losing the health benefits from the weight loss. Furthermore, where the initial weight loss is associated with loss of muscle mass, the following weight gain is mostly due to fat mass increase leading to a net loss of muscle mass. In a weight-neutral approach, individuals become more physically active and may or may not lose weight by substituting fat mass for lean mass, but most will experience health benefits. 

This concept is supported by data from the Aerobic Center Longitudinal Study, a cohort of adults that were assessed over 20 years, measuring both body mass index (BMI; weight/height²) and cardiovascular fitness levels. Independently of their BMI, participants were categorized as having low, moderate, or high fitness levels based on a standard treadmill test. During those 20 years, the all-cause mortality rate was substantially lower in the moderate and high fit individuals, even if they had a higher BMI. The inverse was observed in individuals with a low fitness rating; they had higher mortality rates even if they had a lower BMI.

This pattern - higher mortality risk for low-fit individuals regardless of BMI - was observed in a meta-analysis as well, suggesting that physical activity and cardiovascular fitness levels play a more important role in health than weight. 

The data supporting that higher physical activity and/or cardiorespiratory fitness is associated with significant reductions in mortality risk is consistent across multiple individual cohort studies, shown in the figures below. Increasing physical fitness results in a ~10-50% reduction in all-cause mortality risk and increasing cardiorespiratory fitness is associated with ~30-60% reduction in all-cause mortality risk.  

Further, increasing cardiorespiratory fitness by as little as 1 metabolic equivalent of task (MET), can lead to meaningful reductions in all-cause mortality in the range of ~15-30% (1 MET is expended during ~30min of slow walking or 10-15 of brisk walking). Attaining this increase in fitness, and therefore realizing the health benefit, does not require significantly intense fitness training. For example, in one study, Dr. Gaesser and his colleagues found that as little as 30-40 minutes of moderate (walking, gardening) or high intensity (running) exercise 3 days a week for 8 weeks can result in a change on average in 3-4 METs.  

Dr. Gaesser commented that improving fitness can be achieved with 30 minutes of brisk walking throughout the day; it doesn’t have to be consecutive minutes of activity (this is consistent with current public health messaging for individual physical activity recommendations). This level of physical activity is a general level of engagement that is within reach of most adults.   

Given that increasing physical activity and/or cardiorespiratory fitness can have a meaningful impact on health outcomes, including all-cause and cardiovascular disease-associated mortality risk, accurate measurements of physical activity and functioning can help researchers account for these variables during a study, potentially reducing noise and improving the power of the statistical analyses. Including these measures in obesity research can give a clearer picture of how treatments impact critical health outcomes beyond a decrease in body weight. 

The Vicious Effects of Weight Cycling 

Data from research into the effect of intentional weight loss on mortality risk is less consistent, sometimes showing a reduction in certain studies of 10-20%, and in other studies, there isn’t a substantial change. However, weight loss has been shown to have a positive impact on intermediate health outcomes such as blood pressure, glycemic control, blood lipids, and vascular control. Studies of exercise training interventions show that there is a comparable, positive effect on these intermediate health outcomes as well. These data are summarized in the table below and reviewed in more detail in this publication from Dr. Gaesser and his colleague.  

Even though past research suggests that weight loss alone does not have as robust of an effect on mortality risk as increasing physical activity/fitness, data does show that weight loss interventions have a positive impact on intermediate health outcomes. The disconnect between these two data points could be due to the high prevalence of weight cycling that is often associated with weight loss interventions such as dieting. 

However, there is data to suggest that weight cycling, i.e., the repeated loss and gain of weight, is associated with negative effects on health outcomes. Dr. Gaesser presented a recent review of data from multiple studies in type 2 diabetes, a population that is frequently diagnosed with obesity as well, where weight cycling was associated with increased mortality risk and increased risk of cardiovascular events (including congestive heart failure, myocardial infarction, stroke, peripheral vascular disease, and A-fib). 

What Are Important Measures Beyond Weight Loss? 

Dr. Gaesser emphasized that he was not presenting this as an either/or (either weight loss of exercise training interventions; either weight loss of fitness measures), but that he’d like to shift the focus of obesity research towards including a fitness or activity approach. Based on his experience, Dr. Gaesser suggested including the following outcome measures in obesity treatment research: 

• Cardiorespiratory Fitness 

• Daily moderate-to-vigorous physical activity (MVPA) 

• Sedentary time, including the frequency and duration of breaks in sedentary time 

• Posture allocation 

Benefits of Objective, Continuous, and Remote Data Capture 

As activity in the obesity treatment pharmaceutical R&D pipeline continues to grow, the need for evidence generation of health benefits beyond weight loss, such as those discussed above, as well as improved clinical trial design, will be critical for the successful development of sustainable obesity treatments.  

In obesity drug development, physical activity and fitness are measured using patient report diaries and/or questionnaires. Those patient-reported outcomes in the form of have well-known shortcomings, such as recall and/or reporting bias, and correlate poorly with the actual day-to-day amount and intensity of physical activity or the participants.  

Adding wearable or digital health technology (DHT)-derived digital measures of physical activity and fitness can address these limitations through objective and continuous data capture measuring what participants do in their daily life, increasing the patient centricity of the measure to capture information about real world functioning that affects quality of life. Wearable DHTs are also a low burden for participants, allowing for remote data capture over long periods of time at home.  

How Digital Measures Can Enhance Obesity Research  

Objective, continuous, and multidimensional data capture is particularly relevant to obesity studies. Since part of the weight lost during treatment with GLP-1 therapies is from lean mass loss, this can negatively impact physical fitness as well as contribute to side effects such as fatigue. Medical-grade wearable devices can capture objective fitness data through physical activity, gait and mobility characteristics, and VO2Max* measures.  

As per their label claims GLP-1 obesity drugs should always be prescribed along with increased physical activity and a reduced calorie. Increasing physical activity implies burning calories, which also contributes to patient weight loss. Objective physical activity measures allow researchers and drug developers to measure the impact of energy expenditure on weight loss, improving their study and the way the data is analyzed.  

Including a physical activity measure, particularly in the early phases of a clinical development program, can help the study team gain a deeper understanding of potential bias due to physical activity levels and why some patients may show different responses. 

Another important variable that can be measured with wearables in clinical trials that we haven’t touched on yet is sleep behavior. It is not uncommon for individuals with obesity to experience sleep disturbances, such as obstructive sleep apnea and insomnia. Sleep impairments can also impact calorie intake and metabolism. Obtaining continuous, objective measures of sleep in the participant’s natural environment is also a critical component of understanding treatment efficacy in obesity clinical trials. 

Developing a consensus on key digital measures to include in obesity research and drug development can help enhance the development of novel therapies. However, developing these novel digital measures can be time and resource-intensive for pharmaceutical companies. ActiGraph has taken the approach of forming pre-competitive collaborative working groups (such as the DECODE: Nocturnal Scratch working group) as a framework to advance digital measures by 

• Creating a platform to address evidence gaps 

• Reach critical mass and consensus across key industry stakeholders 

• Scale to address more use cases 

ActiGraph is leading a new DECODE: Obesity working group that will focus on generating new clinical evidence, engaging with regulators, and establishing an evidence-based package to enhance clinical programs in obesity with mature assessments of physical activity and function. To learn more or to join the working group, visit the DECODE: Obesity webpage: https://theactigraph.com/decode/obesity  

* VO₂Max measure would be co-developed by sponsor and ActiGraph teams.