Patient-centricity in digital measure development: co-evolution of best practice and regulatory guidance.

Digital health technologies (DHTs) have the potential to modernize drug development and clinical trial operations by remotely, passively, and continuously collecting ecologically valid evidence that is meaningful to patients' lived experiences. Such evidence holds potential for all drug development stakeholders, including regulatory agencies, as it will help create a stronger evidentiary link between approval of new therapeutics and the ultimate aim of improving patient lives. However, only a very small number of novel digital measures have matured from exploratory usage into regulatory qualification or efficacy endpoints. This shows that despite the clear potential, actually gaining regulatory agreement that a new measure is both fit-for-purpose and delivers value remains a serious challenge. One of the key stumbling blocks for developers has been the requirement to demonstrate that a digital measure is meaningful to patients. This viewpoint aims to examine the co-evolution of regulatory guidance in the United States (U.S.) and best practice for integration of DHTs into the development of clinical outcome assessments. Contextualizing guidance on meaningfulness within the larger shift towards a patient-centric drug development approach, this paper reviews the U.S. Food and Drug Administration (FDA) guidance and existing literature surrounding the development of meaningful digital measures and patient engagement, including the recent examples of rejections by the FDA that further emphasize patient-centricity in digital measures. Finally, this paper highlights remaining hurdles and provides insights into the established frameworks for development and adoption of digital measures in clinical research.

The Case for the Patient-Centric Development of Novel Digital Sleep Assessment Tools in Major Depressive Disorder.

Background: Depression imposes a major burden on public health as the leading cause of disability worldwide. Sleep disturbance is a core symptom of depression that affects the vast majority of patients. Nonetheless, it is frequently not resolved by depression treatment and may even be worsened through some pharmaceutical interventions. Disturbed sleep negatively impact patients' quality of life, and persistent sleep disturbance increases the risk of recurrence, relapse, and even suicide. However, the development of novel treatments that might improve sleep problems is hindered by the lack of reliable low-burden objective measures that can adequately assess disturbed sleep in this population. Summary: Developing improved digital measurement tools that are fit for use in clinical trials for major depressive disorder could promote the inclusion of sleep as a focus for treatment, clinical drug development, and research. This perspective piece explores the path toward the development of novel digital measures, reviews the existing evidence on the meaningfulness of sleep in depression, and summarizes existing methods of sleep assessments, including the use of digital health technologies. Key Messages: Our objective was to make a clear call to action and path forward for the qualification of new digital outcome measures which would enable assessment of sleep disturbance as an aspect of health that truly matters to patients, promoting sleep as an important outcome for clinical development, and ultimately ensure that disturbed sleep will not remain the forgotten symptom of depression.

Capturing Measures That Matter: The Potential Value of Digital Measures of Physical Behavior for Alzheimer's Disease Drug Development.

Alzheimer's disease (AD) is a devastating neurodegenerative disease and the primary cause of dementia worldwide. Despite the magnitude of AD's impact on patients, caregivers, and society, nearly all AD clinical trials fail. A potential contributor to this high rate of failure is that established clinical outcome assessments fail to capture subtle clinical changes, entail high burden for patients and their caregivers, and ineffectively address the aspects of health deemed important by patients and their caregivers. AD progression is associated with widespread changes in physical behavior that have impacts on the ability to function independently, which is a meaningful aspect of health for patients with AD and important for diagnosis. However, established assessments of functional independence remain underutilized in AD clinical trials and are limited by subjective biases and ceiling effects. Digital measures of real-world physical behavior assessed passively, continuously, and remotely using digital health technologies have the potential to address some of these limitations and to capture aspects of functional independence in patients with AD. In particular, measures of real-world gait, physical activity, and life-space mobility captured with wearable sensors may offer value. Additional research is needed to understand the validity, feasibility, and acceptability of these measures in AD clinical research.

Appetitive and Metabolic Responses to an Exercise versus Dietary Intervention in Adults with Obesity.

Introduction/Purpose: Dietary restriction (DIET) and aerobic exercise (AEX) interventions may impact energy balance differently. Our aim was to describe the effects of weight loss interventions via DIET or AEX on measures of energy balance. Methods: Adults with overweight or obesity were randomized to 12 weeks of DIET or AEX with similar calorie deficit goals. A study day was conducted before and after the intervention to assess subjective and hormonal (ghrelin, peptide-YY, glucagon-like peptide-1) appetite responses to a control meal, ad libitum energy intake (EI) at a single meal, and over three days of free-living conditions and eating behavior traits. Resting metabolic rate (RMR) was measured with indirect calorimetry and adjusted for body composition measured by dual X-ray absorptiometry. Non-exercise activity was measured using accelerometers. Results: Forty-four individuals were included (age: 37 ± 9 years, body mass index: 30.6 ± 3.1 kg/m2). Both interventions resulted in weight and fat mass loss. The DIET group lost fat-free mass, although differences between groups were not significant (DIET: -1.2 ± 1.7 kg, p<0.001; AEX: 0.4 ± 1.5 kg, p=0.186; p=0.095 interaction). There were no differences in RMR after body composition adjustment. Both interventions were associated with an increase in dietary restraint (DIET: 4.9 ± 1.2, AEX: 2.8 ± 0.7; p<0.001 in both groups). Hunger decreased with DIET (-1.4 ± 0.5, p=0.003), and disinhibition decreased with AEX (-1.5 ± 0.5, p<0.001), although these changes were not different between groups (i.e., no group × time interaction). No other differences in appetite, EI, or non-exercise physical activity were observed within or between groups. Conclusions: AEX did not result in compensatory alterations in appetite, ad libitum EI, or physical activity, despite assumed increased energy expenditure. Modest evidence also suggested that disinhibition and hunger may be differentially impacted by weight loss modality.

Creating an algorithm to identify indices of sleep quantity and quality from a wearable armband in adults.

Objective: To develop an algorithm to quantify indices of sleep quantity and quality using the SenseWear armband (SWA) and to compare indices of sleep from this novel algorithm to standard wrist actigraphy (Actiwatch 2; AW2) under free-living conditions. Material and Methods: Thirty participants (47±10 years; 33.0±4.8kg/m2) wore the SWA and AW2 for seven consecutive days. Participants self-reported bedtime and waketime across these 7 days. Bedtime, sleep onset, sleep offset, waketime, total sleep time (TST), time in bed (TIB), sleep effciency (SE), sleep onset latency (SOL), wake after sleep onset (WASO), sleep fragmentations (SF), sleep regularity (calculated as SD of waketime), and mid-point of sleep were calculated using each device. Results: There was significant evidence for equivalence of means (or mean ranks) for bedtime, sleep onset, sleep offset, waketime, TST, TIB, SOL, WASO, and midpoint of sleep measured by the SWA and AW2 (p<0.05). There was insuffcient evidence for equivalence of means in SF (SW: 25±6 vs. AW2: 10±3 events; p=1.0), mean ranks in sleep regularity (SW: 58±33 vs. AW2: 68±40 min; p=0.11), and mean ranks in SE (SW: 84.7±5.1% vs. AW2: 86.3±5.5%; p=0.05). When comparing minute-by-minute sleep/wake status, the sensitivity and specificity of the SWA were 0.94 (95%CI: 0.93, 0.95) and 0.88 (95%CI: 0.85, 0.90), respectively, using AW2 as the criterion measure. Conclusion: The algorithm developed for the SWA produced relatively accurate and consistent measurements of sleep quantity, timing, and quality compared to the AW2 under free-living conditions. Thus, the SWA is a viable alternative to standard wrist actigraphy.

Effect of sleep on weight loss and adherence to diet and physical activity recommendations during an 18-month behavioral weight loss intervention.

BACKGROUND/OBJECTIVES: To examine the association between indices of sleep quantity and quality with dietary adherence, physical activity adherence, and weight loss during a behavioral weight loss intervention. METHODS: Adults (n = 156) with overweight and obesity (40 ± 9 years, 84% female, BMI: 34.4 ± 4.2 kg/m2) participated in an 18-month behavioral weight loss intervention which prescribed a reduced calorie diet (1200-1800 kcal/d) and increased physical activity (300 min/wk). Body weight, indices of sleep (SenseWear armband; SWA), energy intake (EI, 3-day food records), and moderate-to-vigorous physical activity (SWA) were measured at baseline, 6, 12, and 18 months. Linear mixed effects models examined the association between sleep and weight change over time. Additional models were adjusted for covariates including age, BMI, sex, race, ethnicity, study completion, randomization, EI, and physical activity. Secondary analyses examined the association between sleep and adherence to diet and physical activity recommendations. RESULTS: Mean weight loss was 7.7 ± 5.4, 8.4 ± 7.9, and 7.1 ± 9.0 kg at 6, 12, and 18 months, respectively. Lower sleep efficiency, higher wake after sleep onset (WASO), more awakenings, and higher sleep onset latency (SOL) were significantly associated with attenuated weight loss (p < 0.05). Lower sleep efficiency, more awakenings, and higher SOL remained significantly associated with blunted weight loss after adjustment for covariates (p < 0.05). Later waketime, longer time in bed, longer sleep duration, higher WASO, more awakenings, and higher SOL were associated with lower odds of achieving ≥300 min/wk of moderate-to-vigorous physical activity, adjusted for covariates (FDR p < 0.05). CONCLUSIONS: Future studies should evaluate whether incorporating strategies to improve sleep health within a behavioral weight loss intervention leads to improved adherence to diet and physical activity recommendations and enhanced weight loss. CLINICAL TRIALS IDENTIFIER: NCT01985568.

Impairments in glycemic control during Eastbound transatlantic travel in healthy adults.

Study Objectives: Repeated bouts of circadian misalignment impair glucose tolerance. However, whether circadian misalignment associated with travel and jet lag impair glucose homeostasis in a free-living population is not known. The goal of the present study was to examine glycemic control during one week of Eastbound transatlantic travel in healthy men and women. Methods: Seven healthy participants (5 women; age: 35.6 ± 2.5 years, BMI: 23.9 ± 2.4 m/kg2) traveled from Colorado, USA (GMT-7) to Europe (GMT and GMT+1) and wore a continuous glucose monitor (Freestyle Libre Pro) for 8-14 days before, during, and after travel. Indices of glycemic control were summarized over 24-hour periods and by day and night. Results: Mean glucose, peak glucose, and time spent in hyperglycemia increased linearly throughout the travel period relative to baseline levels. Mean glucose concentrations rose 1.03 mg/dL (95% CI: 0.34, 1.74) and duration of hyperglycemia increased by 17 min (95% CI: 5.5, 28.6) each 24-hour period. Increases in 24-hour glucose were primarily driven by increases in daytime parameters with rising mean glucose (0.72 mg/dL per day, [95% CI: -0.1, 1.5]) and duration of hyperglycemia (13.2 min per day [95% CI: 4.3, 22.1]). Mean glucose, but not peak glucose or time spent in hyperglycemia, increased each night (0.7 mg/dL per night [95% CI: 0.2, 1.2]). Conclusions: Eastbound transatlantic travel induced a progressive worsening of glucose metrics during 24-hour, day, and night periods. Future research on managing glycemic control during jet lag in people with metabolic disorders is warranted. Clinical Trial Registration: None.

Predictors of long-term weight loss trajectories during a behavioral weight loss intervention: An exploratory analysis.

BACKGROUND: Substantial interindividual variability in response to behavioral weight loss interventions remains a critical challenge in obesity treatment. An improved understanding of the complex factors that contribute to this variability may improve obesity treatment outcomes. OBJECTIVE: To identify weight change trajectories during a behavioral weight loss intervention and to explore differences between trajectory groups in sociodemographic, biologic, behavioral, and psychosocial factors. METHODS: Adults (n = 170, 40 ± 9 years, BMI 34 ± 4 kg/m2, 84% female) participated in an 18-month behavioral weight loss intervention. Weight was measured at 0, 3, 6, 9, 12, 15, 18, and 24 months. Among participants with at least two weights after baseline (n = 140), clusters of longitudinal trajectories of changes in weight were identified using a latent class growth mixture model. The association between baseline factors or changes in factors over time and trajectory group was examined. RESULTS: Two weight change trajectories were identified: "weight regainers" (n = 91) and "weight loss maintainers" (n = 49). Black participants (90%, 19/21) were more likely than non-Black participants to be regainers versus maintainers (p < 0.01). Maintainers demonstrated greater increases in device-measured physical activity, autonomous motivation for exercise, diet self-efficacy, cognitive restraint, and engagement in weight management behaviors and greater reductions in barriers for exercise, disinhibition, and depressive symptoms over 24 months versus regainers (p < 0.05). CONCLUSION: Maintainers and regainers appear to be distinct trajectories that are associated with specific sociodemographic, behavioral, and psychosocial factors. Study results suggest potential targets for more tailored, multifaceted interventions to improve obesity treatment outcomes.

Descriptive Epidemiology of Interruptions to Free-Living Sitting Time in Middle-Age and Older Adults.

PURPOSE: To describe the frequency and characteristics (i.e., duration, stepping time, and estimated intensity) of all interruptions and physically active interruptions to adults' free-living sitting time (i.e., transitions from sitting to upright posture) across segments of the population. METHODS: Australian Diabetes, Obesity and Lifestyle study participants (321 men; 406 women; mean ± standard deviation, 58.0 ± 10.3 yr) wore the activPAL3™ for ≥1 valid day. The characteristics of interruptions from laboratory studies demonstrating health benefits were selected to define active interruptions (≥5 min upright and/or ≥2 min stepping) and ambulatory interruptions (≥2 min stepping). The frequency and characteristics of all, active, and ambulatory interruptions were described and compared by age, sex, diabetes status, and body mass index. RESULTS: Adults averaged 55.0 ± 21.8 interruptions per day, but only 20.3 ± 6.7 were active and 14.0 ± 5.4 were ambulatory. Median (25th, 75th percentile) duration was 2.6 min (0.9, 7.8 min), stepping time was 0.8 min (0.3, 2.0 min), and estimated energy expenditure was 4.3 metabolic equivalents (MET)·min-1 (1.4, 12.5 MET·min-1). Those who were older, had obesity, or had diabetes had significantly (P < 0.05) fewer interruptions of all types and less stepping time during active interruptions than their counterparts (Cohen's d < 0.2). CONCLUSIONS: Free-living interruptions were often less active than interruptions performed in effective acute laboratory studies and their content varied widely between population groups. Monitoring all interruptions, as well as those that are more active, is advisable to provide a comprehensive understanding of free-living sedentary behavior.

Examining the Role of Exercise Timing in Weight Management: A Review.

Many adults cite exercise as a primary strategy for losing weight, yet exercise alone is modestly effective for weight loss and results in variable weight loss responses. It is possible that some of the variability in weight loss may be explained by the time of day that exercise is performed. Few studies have directly compared the effects of exercise performed at different times of the day (i. e., morning versus evening exercise). Results from these existing studies are mixed with some studies demonstrating superior weight and fat mass loss from morning exercise, while other studies have found that evening exercise may be better for weight management. Exercise timing may alter modifiable lifestyle behaviors involved in weight management, such as non-exercise physical activity, energy intake, and sleep. The purpose of this review is to summarize evidence for and against time-of-day dependent effects of exercise on weight management. Although limited, we also review studies that have examined the effect of exercise timing on other lifestyle behaviors linked to body weight regulation. While exercise at any time of day is beneficial for health, understanding whether there is an optimal time of day to exercise may advance personalized treatment paradigms for weight management.

Patterns of Sitting, Standing, and Stepping After Lower Limb Amputation.

OBJECTIVE: The objectives of this study were to describe sitting, standing, and stepping patterns for people with lower limb amputation (LLA) and to compare sitting, standing, and stepping between people with dysvascular LLA and people with traumatic LLA. METHODS: Participants with dysvascular or traumatic LLA were included if their most recent LLA was at least 1 year earlier, they were ambulating independently with a prosthesis, and they were between 45 and 88 years old. Sitting, standing, and stepping were measured using accelerometry. Daily sitting, standing, and stepping times were expressed as percentages of waking time. Time spent in bouts of specified durations of sitting (<30, 30-60, 60-90, and >90 minutes), standing (0-1, 1-5, and >5 minutes), and stepping (0-1, 1-5, and >5 minutes) was also calculated. RESULTS: Participants (N = 32; mean age = 62.6 [SD = 7.8] years; 84% men; 53% with dysvascular LLA) spent most of the day sitting (median = 77% [quartile 1 {Q1}-quartile 3 {Q3} = 67%-84%]), followed by standing (median = 16% [Q1-Q3 = 12%-27%]) and stepping (median = 6% [Q1-Q3 = 4%-9%]). One-quarter (median = 25% [Q1-Q3 = 16%-38%]) of sitting was accumulated in bouts of >90 minutes, and most standing and stepping was accrued in bouts of <1 minute (standing: median = 42% [Q1-Q3 = 34%-54%]; stepping: median = 98% [Q1-Q3 = 95%-99%]). Between-etiology differences included proportion of time sitting (traumatic: median = 70% [Q1-Q3 = 59%-78%]; dysvascular: median = 79% [Q1-Q3 = 73%-86%]) and standing (traumatic: median = 23% [Q1-Q3 = 16%-32%]; dysvascular: median = 15% [Q1-Q3 = 11%-20%]). CONCLUSION: Participants had high daily volumes of long durations of sitting. Further, these individuals accumulated most physical activity in bouts of <1 minute. IMPACT: High levels of sedentary behavior and physical inactivity patterns may place people with LLA at greater mortality risk relative to the general population. Interventions to minimize sedentary behaviors and increase physical activity are potential strategies for improving poor outcomes of physical therapy after LLA.

Metrics of Diabetes Risk Are Only Minimally Improved by Exercise Training in Postmenopausal Breast Cancer Survivors.

CONTEXT: Insulin resistance is a risk factor for breast cancer recurrence. How exercise training changes fasting and postglucose insulin resistance in breast cancer survivors is unknown. OBJECTIVE: To evaluate exercise-induced changes in postglucose ingestion insulin concentrations, insulin resistance, and their associations with cancer-relevant biomarkers in breast cancer survivors. SETTING: The University of Massachusetts Kinesiology Department. PARTICIPANTS: 15 postmenopausal breast cancer survivors not meeting the physical activity guidelines (150 min/week of exercise). INTERVENTION: A supervised 12-week aerobic exercise program (60 min/day, 3-4 days/week). MAIN OUTCOME MEASURES: Postglucose ingestion insulin was determined by peak insulin and area under the insulin curve (iAUC) during a 5-sample oral glucose tolerance test. Insulin sensitivity was estimated from the Matsuda composite insulin sensitivity index (C-ISI). Changes in fitness and body composition were determined from submaximal VO2peak and dual energy X-ray absorptiometry. RESULTS: Participants averaged 156.8 ± 16.6 min/week of supervised exercise. Estimated VO2peak significantly increased (+2.8 ± 1.4 mL/kg/min, P < .05) and body weight significantly decreased (-1.1 ± 0.8 kg, P < .05) following the intervention. There were no differences in fasting insulin, iAUC, C-ISI, or peak insulin following the intervention. Insulin was only significantly lower 120 min following glucose consumption (68.8 ± 34.5 vs 56.2 ± 31.9 uU/mL, P < .05), and there was a significant interaction with past/present aromatase inhibitor (AI) use for peak insulin (-11.99 non-AI vs +13.91 AI uU/mL) and iAUC (-24.03 non-AI vs +32.73 AI uU/mL). CONCLUSIONS: Exercise training had limited overall benefits on insulin concentrations following glucose ingestion in breast cancer survivors but was strongly influenced by AI use.

Managing free-living hyperglycemia with exercise or interrupted sitting in type 2 diabetes.

Breaking up sitting with light physical activity (PA) is effective in reducing hyperglycemia in the laboratory. Whether the same effects are observed in the free-living environment remains unknown. We evaluated how daily and postprandial glycemia is impacted by 20, 40, or 60 min of activity performed as either breaks from sitting after each meal (BR) or as one continuous walk after breakfast (WALK). Thirty individuals with type 2 diabetes completed three experimental conditions [BR, WALK, and control (CON)] in a randomized crossover design. Conditions were performed in a free-living environment with strict dietary control over 7 days. Participants increased PA in BR and WALK by 20, 40, or 60 min ( n = 10 in each group) and maintained habitual levels of PA during CON. A continuous glucose monitor (iPro2) and activPAL activity monitor were worn to quantify glycemic control and PA. Using linear mixed models with repeated measures, we 1) compared postprandial glucose (PPG) across conditions and 2) assessed the relationship between activity volume and glucose responses. Whereas WALK tended to shorten the daily duration of hyperglycemia compared with CON ( P = 0.0875), BR was not different from CON. BR and WALK significantly attenuated the breakfast PPG versus CON ( P ≤ 0.05), but lunch and dinner PPG were unaffected by BR and WALK. In conclusion, continuous walking was more effective than breaks from sitting in lowering daily hyperglycemia for the group, but both conditions lowered breakfast PPG. In contrast to tightly controlled laboratory studies, breaks from sitting did not lower hyperglycemia in the free-living environment. NEW & NOTEWORTHY Our "ecolabical" approach is new and noteworthy. This approach combines the external validity of the free-living environment (ecological) with the control of key confounding variables in the laboratory and allows for highly translatable findings by minimizing confounding variables. We found that both postmeal continuous walking and short breaks from sitting similarly attenuated the postprandial glucose (PPG) response to breakfast. Unlike previous laboratory studies, neither condition (walk after breakfast or postmeal breaks) significantly impacted PPG at lunch or dinner.

Effects of Providing High-Fat versus High-Carbohydrate Meals on Daily and Postprandial Physical Activity and Glucose Patterns: a Randomised Controlled Trial.

We determined the effects of altering meal timing and diet composition on temporal glucose homeostasis and physical activity measures. Eight sedentary, overweight/obese men (mean ± SD, age: 36 ± 4 years; BMI: 29.8 ± 1.8 kg/m²) completed two × 12-day (12-d) measurement periods, including a 7-d habitual period, and then 5 d of each diet (high-fat diet [HFD]: 67:15:18% fat:carbohydrate:protein versus high-carbohydrate diet [HCD]: 67:15:18% carbohydrate:fat:protein) of three meals/d at ±30 min of 0800 h, 1230 h, and 1800 h, in a randomised order with an 8-d washout. Energy intake (EI), the timing of meal consumption, blood glucose regulation (continuous glucose monitor system (CGMS)), and activity patterns (accelerometer and inclinometer) were assessed across each 12-d period. Meal provision did not alter the patterns of reduced physical activity, and increased sedentary behaviour following dinner, compared with following breakfast and lunch. The HCD increased peak (+1.6 mmol/L, p < 0.001), mean (+0.5 mmol/L, p = 0.001), and total area under the curve (+670 mmol/L/min, p = 0.001), as well as 3-h postprandial meal glucose concentrations (all p < 0.001) compared with the HFD. In overweight/obese males, the provision of meals did not alter physical activity patterns, but did affect glycaemic control. Greater emphasis on meal timing and composition is required in diet and/or behaviour intervention studies to ensure relevance to real-world behaviours.

Exercise training and metformin, but not exercise training alone, decreases insulin production and increases insulin clearance in adults with prediabetes.

Adding metformin to exercise does not augment the effect of training alone to boost whole body insulin sensitivity and lower circulating insulin concentrations. Although lower insulin concentrations (lower supply) following lifestyle and/or pharmacological interventions are primarily attributed to reductions in insulin secretion that match increases in peripheral insulin sensitivity (lower demand), it is unclear whether exercise and/or metformin exert direct effects on insulin production, extraction, or clearance. Thirty-six middle-aged, obese, sedentary adults with prediabetes were randomized to placebo (P), metformin (M), exercise and placebo (E+P), or exercise and metformin (E+M) for 12 wk. Fasting plasma proinsulin (an indicator of insulin production), C-peptide, insulin, and glucose were collected before and after the intervention. Peripheral insulin sensitivity (euglycemic clamp), hepatic insulin extraction, insulin clearance, body weight, and cardiorespiratory fitness were also measured. Fasting proinsulin was unchanged following P (19.4 ± 10.1 vs. 22.6 ± 15.0 pmol/l), E+P (15.1 ± 7.4 vs. 15.5 ± 7.4 pmol/l), or M (24.8 ± 18.9 vs. 16.7 ± 20.3 pmol/l) but was significantly reduced after E+M (18.6 ± 11.9 vs. 13.9 ± 6.7 pmol/l; P = 0.04). Insulin clearance was significantly greater following M (384.6 ± 19.4 vs. 477.4 ± 49.9; P = 0.03) and E+M (400.1 ± 32.0 vs. 482.9 ± 33.9; P = 0.02) but was unchanged in P or E+P. In this study, metformin combined with exercise training reduced circulating proinsulin, and both groups taking metformin increased insulin clearance. This suggests that adding metformin to exercise may augment or attenuate training effects depending on the outcome or organ system being assessed.NEW & NOTEWORTHY Exercise is increasingly viewed as medication, creating a need to understand its interactions with other common medications. Research suggests metformin, a widely prescribed diabetes medication, may diminish the benefits of exercise when used in combination. In this study, however, metformin combined with exercise training, but not exercise alone, lowered proinsulin concentrations and increased insulin clearance in adults with prediabetes. This may directly influence personalized prescriptions of lifestyle and/or pharmacology to reduce diabetes risk.

Interrupting prolonged sitting in type 2 diabetes: nocturnal persistence of improved glycaemic control.

AIMS/HYPOTHESIS: We aimed to examine the effect of interrupting 7 h prolonged sitting with brief bouts of walking or resistance activities on 22 h glucose homeostasis (including nocturnal-to-following morning hyperglycaemia) in adults with type 2 diabetes. METHODS: This study is an extension of a previously published randomised crossover trial, which included 24 inactive overweight/obese adults with type 2 diabetes (14 men; 62 ± 6 years) who completed three 7 h laboratory conditions, separated by 6-14 day washout periods: SIT: (1) prolonged sitting (control); (2) light-intensity walking (LW): sitting plus 3 min bouts of light-intensity walking at 3.2 km/h every 30 min; (3) simple resistance activities (SRA): sitting plus 3 min bouts of simple resistance activities (alternating half-squats, calf raises, brief gluteal contractions and knee raises) every 30 min. In the present study, continuous glucose monitoring was performed for 22 h, encompassing the 7 h laboratory trial, the evening free-living period after leaving the laboratory and sleeping periods. Meals and meal times were standardised across conditions for all participants. RESULTS: Compared with SIT, both LW and SRA reduced 22 h glucose [SIT: 11.6 ± 0.3 mmol/l, LW: 8.9 ± 0.3 mmol/l, SRA: 8.7 ± 0.3 mmol/l; p < 0.001] and nocturnal mean glucose concentrations [SIT: 10.6 ± 0.4 mmol/l, LW: 8.1 ± 0.4 mmol/l, SRA: 8.3 ± 0.4 mmol/l; p < 0.001]. Furthermore, mean glucose concentrations were sustained nocturnally at a lower level until the morning following the intervention for both LW and SRA (waking glucose both -2.7 ± 0.4 mmol/l compared with SIT; p < 0.001). CONCLUSIONS/INTERPRETATION: Interrupting 7 h prolonged sitting time with either LW or SRA reduced 22 h hyperglycaemia. The glycaemic improvements persisted after these laboratory conditions and nocturnally, until waking the following morning. These findings may have implications for adults with relatively well-controlled type 2 diabetes who engage in prolonged periods of sitting, for example, highly desk-bound workers. TRIAL REGISTRATION: anzctr.org.au ACTRN12613000576729 FUNDING: : This research was supported by a National Health and Medical Research Council (NHMRC) project grant (no. 1081734) and the Victorian Government Operational Infrastructure Support scheme.

Effects of subtracting sitting versus adding exercise on glycemic control and variability in sedentary office workers.

Recent evidence suggests that, like adding exercise, reducing sitting time may improve cardiometabolic health. There has not been a direct comparison of the 2 strategies with energy expenditure held constant. The purpose of this study was to compare fasting and postmeal glucose and insulin concentrations in response to a day with frequent breaks from sitting but no exercise versus considerable sitting plus moderate exercise. Ten sedentary overweight/obese office workers were tested in 3 conditions: (i) walking per activity guidelines (AGW): sitting for majority of workday with a 30 min pre-lunch walk; (ii) frequent long breaks (FLB): no structured exercise but frequent breaks from sitting during workday with energy expenditure matched to AGW; and (iii) frequent short breaks (FSB): number of breaks matched to FLB, but duration of breaks were shorter. Plasma glucose and insulin areas under the curve were measured in response to a meal tolerance test (MTT) at the end of the workday and interstitial glucose was evaluated throughout the day and overnight using continuous glucose monitoring. Using repeated-measures linear mixed models, area under the curve of plasma glucose or insulin after the MTT was not different between conditions. Glycemic variability was lower in FLB compared with AGW (p < 0.05), and nocturnal duration of elevated glucose (>7.8 mmol/L) was shorter after FLB (2.5 ± 2.5 min) than AGW (32.7 ± 16.4 min) or FSB (45.6 ± 29.6 min, p = 0.05). When energy expenditure was matched, breaks from sitting approximated the effects of moderate-intensity exercise on postmeal glucose and insulin responses and more effectively constrained glycemic variability.