Changes in the prevalence of U.S. adults using diet, exercise, pharmaceuticals and diet products for weight loss over time: Analysis of NHANES 1999-2018.

To examine changes in the use of diet, exercise, and pharmacological/diet product weight loss (WL) practices over time, and differences in these trends by sex and obesity status, data from the National Health and Examination Survey (NHANES Continuous 1999-2018) was used. The prevalence of diet, exercise and use of WL drugs and products over time were examined in men and women with and without obesity in a series of cross-sectional nationally representative samples (n = 43,020). Women and those with obesity were more likely to engage in WL practices over the past year, with an increased prevalence of WL efforts over time (38.4 to 43.2%). Amongst those who engaged in WL attempts, diet-related WL was most common (87-93%), followed by exercise-related WL (47-68%), whereas use of WL drugs and products was the least common (5-21%). There were modest differences in the prevalence of diet or exercise WL over time, with some differences by sex and obesity status. Most notable was the increase in the prevalence of exercise WL practices in women with obesity, with no differences among men or women without obesity. When examining specific types of diets, there were more clear differences in the adoption of diets over time, with the use of more traditional calorie/portion/fat restriction diets becoming less prevalent, and sugar/carbohydrate restriction becoming more prevalent over time (P<0.005). Changes over time in the use of diets were, were however, similar in men and women with and without obesity. Use of pharmacotherapy/diet products tended to decline in prevalence over time but was consistently highest in women with obesity. Thus, there are differences in the types of WL strategies individuals have employed over time, with variations in their popularity of use by sex and obesity status. However, the pattern of changes over time were quite similar in men and women with and without obesity.

Is anyone truly healthy? Trends in health risk factors prevalence and changes in their associations with all-cause mortality.

OBJECTIVE: The purpose of the study was to determine trends in the prevalence of individual health risk factors across time and to examine if their associations with mortality have changed over time. METHODS: Data from the National Health and Nutrition Examination Surveys (NHANES III- 1988-1994 and NHANES 1999-2014; age ≥20 years) was used to examine differences in the odds ratio (OR) of 5-year mortality risk associated with various common health risk factors over the two survey periods using weighted logistic regression analysis adjusting for age, sex, obesity category and white ethnicity (n = 28,279). RESULTS: Over 97% of individuals had at least one of the 19 risk factors examined with no difference in the prevalence over time (P>0.34). The prevalence of lifestyle, social/mental and physical risk factors (2.2 to 19.1%) increased over time (P<0.0002), while the prevalence of having physiological risk factors decreased by ~6.5% (P<0.0001). Having any lifestyle or social/mental risk factor was significantly associated with a higher 5-year OR for mortality risk in 1999-2014, than 1988-94. In particular, having low education or use of mental health medication were not associated with mortality risk in 1988-94 (P>0.1), but were significantly associated with a higher 5-year OR for mortality in 1999-2014 (P<0.0001). Conversely, physiological risk factors were more weakly related with mortality risk in 1988-1994, than 1999-2014. Having any physical risk factor, and poor self-rated health were similarly related with 5-year mortality risk at both timepoints. CONCLUSION: Health risk factors have both increased and decreased in prevalence over time, along with changes in the association between many of the risk factors and mortality risk. Taken together, these changes complicate interpretation of temporal trends and warrant cautious interpretation of population health patterns based on surveillance data.

The association of objectively and subjectively measured physical activity and sedentary time with prediabetes and type 2 diabetes in adults: a cross-sectional study in Framingham Heart Study cohorts.

The purpose of this study was to examine whether using both objectively (accelerometer) and subjectively (questionnaire) measured moderate- to vigorous-intensity physical activity (MVPA) and sedentary time (SED) improves the prediction of prediabetes and type 2 diabetes (pre/T2D) using data from the Framingham Heart Study (n = 4200). Logistic regression was used to examine the odds ratio of pre/T2D in groups cross-classified by subjective and objective MVPA and SED. Less than half of participants fell into concordant categories of MVPA and SED using subjective and objective measures, with 7.0%-9.4% of participants in the extreme discordant categories of high-low or low-high subjective-objective MVPA or SED. Low objective MVPA, regardless of subjective MVPA status, was associated with a higher prevalence of pre/T2D (P < 0.05). When cross-classifying by MVPA and SED, the majority of participants fell into concordant categories of MVPA-SED, with <4% of participants in the extreme discordant categories of MVPA-SED. Low objective MVPA, regardless of objective SED, was associated with a higher prevalence of pre/T2D (P < 0.05). These findings suggest that low objectively measured MVPA appears more closely associated with pre/T2D risk compared with subjective measures, and there does not appear to be an additive effect of SED on pre/T2D risk after accounting for MVPA.

Separate and combined relationships for cardiorespiratory fitness and muscular strength with visceral fat and insulin sensitivity in adolescents with obesity.

We examined the separate and combined associations for cardiorespiratory fitness (CRF) and muscular strength (MS) with total and regional fat, and insulin sensitivity (IS) in 204 adolescents (BMI ≥85th percentile, 12-18 years) at UPMC Children's Hospital of Pittsburgh. CRF was measured by maximum oxygen consumption during a graded treadmill test. MS was quantified by combining 1-repetition maximum test for the leg and bench press. Participants were stratified as having either high or low CRF and MS based on sex-specific median split. Both high CRF and high MS groups had lower (P < 0.05) total fat after adjustment for sex, Tanner stage and ethnicity than the low CRF and MS groups (Difference: 6.6, 2.6-9.6% and 5.4, 2.4-8.3%, respectively). High CRF, but not high MS, had lower visceral (67.5 versus 77.9 cm2, P < 0.01) and intermuscular fat (3.6 versus 4.0 kg, P = 0.01) than the low CRF groups. Differences by CRF remained significant after adjustment for MS. High CRF, but not high MS, was associated (P < 0.05) with lower fasting glucose and higher IS after accounting for sex, Tanner stage and ethnicity than the low CRF group, and high CRF remained associated with these markers after adjustment for MS. High CRF is associated with lower total and regional fat, and higher IS after adjustment for MS. Novelty: CRF is associated with lower total fat, visceral and intermuscular fat, and higher insulin sensitivity adjusting for muscular strength. Muscular strength is not associated with regional body fat and insulin sensitivity after accounting for CRF.

Carbohydrate Requirements for Prolonged, Fasted Exercise With and Without Basal Rate Reductions in Adults With Type 1 Diabetes on Continuous Subcutaneous Insulin Infusion.

OBJECTIVE: Exercising while fasted with type 1 diabetes facilitates weight loss; however, the best strategy to maintain glucose stability remains unclear. RESEARCH DESIGN AND METHODS: Fifteen adults on continuous subcutaneous insulin infusion completed three sessions of fasted walking (120 min at 45% VO2max) in a randomized crossover design: 50% basal rate reduction, set 90 min pre-exercise (-90min50%BRR); usual basal rate with carbohydrate intake of 0.3 g/kg/h (CHO-only); and combined 50% basal rate reduction set at exercise onset with carbohydrate intake of 0.3 g/kg/h (Combo). RESULTS: Combo had a smaller change in glucose (5 ± 47 mg/dL) versus CHO-only (-49 ± 61 mg/dL, P = 0.03) or -90min50%BRR (-34 ± 45 mg/dL). The -90min50%BRR strategy produced higher ß-hydroxybutyrate levels (0.4 ± 0.3 vs. 0.1 ± 0.1 mmol/L) and greater fat oxidation (0.51 ± 0.2 vs. 0.39 ± 0.1 g/min) than CHO-only (both P < 0.05). CONCLUSIONS: All strategies examined produced stable glycemia for fasted exercise, but a 50% basal rate reduction, set 90 min pre-exercise, eliminates carbohydrate needs and enhances fat oxidation better than carbohydrate feeding with or without a basal rate reduction set at exercise onset.

Diabetes Technology and Exercise.

Advances in technologies such as glucose monitors, exercise wearables, closed-loop systems, and various smartphone applications are helping many people with diabetes to be more physically active. These technologies are designed to overcome the challenges associated with exercise duration, mode, relative intensity, and absolute intensity, all of which affect glucose homeostasis in people living with diabetes. At present, optimal use of these technologies depends largely on motivation, competence, and adherence to daily diabetes care requirements. This article discusses recent technologies designed to help patients with diabetes to be more physically active, while also trying to improve glucose control around exercise.

Lag Time Remains with Newer Real-Time Continuous Glucose Monitoring Technology During Aerobic Exercise in Adults Living with Type 1 Diabetes.

Background: Real-time continuous glucose monitoring (CGM) devices help detect glycemic excursions associated with exercise, meals, and insulin dosing in patients with type 1 diabetes (T1D). However, the delay between interstitial and blood glucose may result in CGM underestimating the true change in glycemia during activity. The purpose of this study was to examine CGM discrepancies during exercise and the meal postexercise versus self-monitoring of blood glucose (SMBG). Methods: Seventeen adults with T1D using insulin pump therapy and CGM completed 60 min of aerobic exercise on three occasions. A standardized meal was given 30 min postexercise. SMBG was measured during exercise and in recovery using OmniPod® Personal Diabetes Manager (PDM; Insulet, Billerica, MA) with built-in glucose meter (FreeStyle; Abbott Laboratories, Abbott Park, IL), while CGM was measured with Dexcom G4® with 505 algorithm (n = 4) or G5® (n = 13), which were calibrated with subjects' own PDM. Results: SMBG showed a large drop in glycemia during exercise, while CGM showed a lag of 12 ± 11 (mean ± standard deviation) minutes and bias of -7 ± 19 mg/dL/min during activity. Mean absolute relative difference (MARD) for CGM versus SMBG was 13 (6-22)% [median (interquartile range)] during exercise and 8 (5-14)% during mealtime. Clarke error grids showed CGM values were in zones A and B 94%-99% of the time for SMBG. Conclusion: In summary, the drop in CGM lags behind the drop in blood glucose during prolonged aerobic exercise by 12 ± 11 min, and MARD increases to 13 (6-22)% during exercise as well. Therefore, if hypoglycemia is suspected during exercise, individuals should confirm glucose levels with a capillary glucose measurement.

Improved Open-Loop Glucose Control With Basal Insulin Reduction 90 Minutes Before Aerobic Exercise in Patients With Type 1 Diabetes on Continuous Subcutaneous Insulin Infusion.

OBJECTIVE: To reduce exercise-associated hypoglycemia, individuals with type 1 diabetes on continuous subcutaneous insulin infusion typically perform basal rate reductions (BRRs) and/or carbohydrate feeding, although the timing and amount of BRRs necessary to prevent hypoglycemia are unclear. The goal of this study was to determine if BRRs set 90 min pre-exercise better attenuate hypoglycemia versus pump suspension (PS) at exercise onset. RESEARCH DESIGN AND METHODS: Seventeen individuals completed three 60-min treadmill exercise (∼50% of VO2peak) visits in a randomized crossover design. The insulin strategies included 1) PS at exercise onset, 2) 80% BRR set 90 min pre-exercise, and 3) 50% BRR set 90 min pre-exercise. RESULTS: Blood glucose level at exercise onset was higher with 50% BRR (191 ± 49 mg/dL) vs. 80% BRR (164 ± 41 mg/dL; P < 0.001) and PS (164 ± 45 mg/dL; P < 0.001). By exercise end, 80% BRR showed the smallest drop (-31 ± 58 mg/dL) vs. 50% BRR (-47 ± 50 mg/dL; P = 0.04) and PS (-67 ± 41 mg/dL; P < 0.001). With PS, 7 out of 17 participants developed hypoglycemia versus 1 out of 17 in both BRR conditions (P < 0.05). Following a standardized meal postexercise, glucose rose with PS and 50% BRR (both P < 0.05), but failed to rise with 80% BRR (P = 0.16). Based on interstitial glucose, overnight mean percent time in range was 83%, 83%, and 78%, and time in hypoglycemia was 2%, 1%, and 5% with 80% BRR, 50% BRR, and PS, respectively (all P > 0.05). CONCLUSIONS: Overall, a 50-80% BRR set 90 min pre-exercise improves glucose control and decreases hypoglycemia risk during exercise better than PS at exercise onset, while not compromising the postexercise meal glucose control.

Reproducibility in the cardiometabolic responses to high-intensity interval exercise in adults with type 1 diabetes.

AIMS: Patients with type 1 diabetes (T1D) often report a rise in their blood glucose level following brief intense exercise. We sought to determine the reproducibility of the cardiometabolic responses to high-intensity interval training (HIIT). METHODS: Sixteen adults with T1D, using an optimized multiple daily injection with basal insulin glargine 300 U/mL (Gla-300), performed four fasted HIIT sessions over a 4-6-week period. Exercise consisted of high-intensity interval cycling and multimodal training over 25 min. RESULTS: Heart rate and rating of perceived exertion rose similarly in all sessions, as did lactate, catecholamine and growth hormone levels. Plasma glucose increased in response to HIIT in 62 of 64 visits (97%), with an overall increase of 3.7 ±â€¯1.6 mmol/L (Mean ±â€¯SD) (P < 0.001). In within-patient comparisons, the change in plasma glucose among the four HIIT sessions was significantly correlated with a composite correlation of 0.58 ([r2 = 0.34]; 95% CI 0.35-0.80; P < 0.01). CONCLUSIONS: Intersession observations of four separate HIIT sessions showed high intrasubject reproducibility in the cardiometabolic responses to exercise, including the rise in plasma glucose, when adults with T1D perform the activity in a fasted state.

Accuracy of Wrist-Worn Activity Monitors During Common Daily Physical Activities and Types of Structured Exercise: Evaluation Study.

BACKGROUND: Wrist-worn activity monitors are often used to monitor heart rate (HR) and energy expenditure (EE) in a variety of settings including more recently in medical applications. The use of real-time physiological signals to inform medical systems including drug delivery systems and decision support systems will depend on the accuracy of the signals being measured, including accuracy of HR and EE. Prior studies assessed accuracy of wearables only during steady-state aerobic exercise. OBJECTIVE: The objective of this study was to validate the accuracy of both HR and EE for 2 common wrist-worn devices during a variety of dynamic activities that represent various physical activities associated with daily living including structured exercise. METHODS: We assessed the accuracy of both HR and EE for two common wrist-worn devices (Fitbit Charge 2 and Garmin vívosmart HR+) during dynamic activities. Over a 2-day period, 20 healthy adults (age: mean 27.5 [SD 6.0] years; body mass index: mean 22.5 [SD 2.3] kg/m2; 11 females) performed a maximal oxygen uptake test, free-weight resistance circuit, interval training session, and activities of daily living. Validity was assessed using an HR chest strap (Polar) and portable indirect calorimetry (Cosmed). Accuracy of the commercial wearables versus research-grade standards was determined using Bland-Altman analysis, correlational analysis, and error bias. RESULTS: Fitbit and Garmin were reasonably accurate at measuring HR but with an overall negative bias. There was more error observed during high-intensity activities when there was a lack of repetitive wrist motion and when the exercise mode indicator was not used. The Garmin estimated HR with a mean relative error (RE, %) of -3.3% (SD 16.7), whereas Fitbit estimated HR with an RE of -4.7% (SD 19.6) across all activities. The highest error was observed during high-intensity intervals on bike (Fitbit: -11.4% [SD 35.7]; Garmin: -14.3% [SD 20.5]) and lowest error during high-intensity intervals on treadmill (Fitbit: -1.7% [SD 11.5]; Garmin: -0.5% [SD 9.4]). Fitbit and Garmin EE estimates differed significantly, with Garmin having less negative bias (Fitbit: -19.3% [SD 28.9], Garmin: -1.6% [SD 30.6], P<.001) across all activities, and with both correlating poorly with indirect calorimetry measures. CONCLUSIONS: Two common wrist-worn devices (Fitbit Charge 2 and Garmin vívosmart HR+) show good HR accuracy, with a small negative bias, and reasonable EE estimates during low to moderate-intensity exercise and during a variety of common daily activities and exercise. Accuracy was compromised markedly when the activity indicator was not used on the watch or when activities involving less wrist motion such as cycle ergometry were done.