By the year 2050, one in three individuals will be diagnosed with Type 2 diabetes (4), a disease characterized by skeletal muscle insulin resistance (31). Skeletal muscle is the largest site for glucose disposal, which, in part, is regulated by insulin (10). Insulin-mediated skeletal muscle glucose disposal is also regulated by the vasculature (2,9,38). Insulin in muscle and endothelial cells stimulates the insulin receptor to activate phosphatidylinositide 3-kinase and protein kinase B/AKT (13). In muscle, this results in the translocation of glut-4 to the plasma membrane to uptake glucose (17). In endothelial cells, activation of AKT stimulates the production of nitric oxide (NO), a vasodilator (13), as well as endothelin-1 (ET-1), a vasoconstrictor (13). In normal healthy subjects, the stimulation of insulin on the endothelial cell results in vasodilation. However, with reductions in insulin sensitivity, an imbalance in the production of NO and ET-1 occurs, favoring vasoconstriction of blood vessels (14). Insulin-stimulated blood flow has been shown to account for up to 40% of glucose uptake (2); thus, reducing the blood flow response to insulin may also reduce the ability of the muscle to uptake glucose.
We have previously shown that short-term reductions in physical activity in healthy individuals lead to increased postprandial blood glucose (PPG) responses (25). This alteration is important because previous studies show that an elevated PPG is associated with increased cardiovascular disease morbidity and mortality (27). Our laboratory also recently demonstrated that short-term reductions in daily physical activity impair endothelial function (5). Given the importance of the endothelium for insulin-stimulated blood flow responses, this finding may be related to impaired glycemic control with physical inactivity. However, it is unclear whether blood flow responses to insulin are impaired after reduced physical activity and occur in parallel with reductions in glycemic control and insulin sensitivity. In addition, although it is known that a single bout of exercise can improve insulin sensitivity (11) and glycemic control in sedentary individuals (28), it is unknown if one bout of exercise can restore free-living glycemic control and insulin sensitivity in subjects who were acutely transitioned to reduced daily activity or if these changes will track with insulin-stimulated blood flow responses.
The purpose of this study was to determine whether an acute transition to reduced daily physical activity (from >10,000 to <5000 steps per day) for 5 d (RA5) in healthy, recreationally active men reduced skeletal muscle blood flow responses after glucose ingestion and glycemic control in parallel. We also examined if a 1-d return to physical activity (>10,000 steps per day) (RTA1) improved these outcomes. An oral glucose tolerance test (OGTT) was used to increase plasma insulin levels, while femoral and brachial artery blood flow were measured. Insulin sensitivity was assessed via the Matsuda index. In addition, to assess the PPG response in free-living conditions, we used continuous glucose monitoring systems (CGMS) and standardized meals across the study intervention. We hypothesized that blood flow responses to an OGTT would be reduced with 5 d of physical inactivity concurrently with reduced glycemic control and that a 1-d return to physical activity would improve these outcomes.
Protocols were approved by the University of Missouri Health Sciences Institutional Review board, and written informed consent was obtained from all subjects. Healthy, recreationally active, young (24 ± 1.1 yr) men (n = 14) were recruited for the study. Completing at least 90 min of primarily aerobic lower body exercise ≥3 d·wk−1 (self-reported) and taking >10,000 steps per day (verified by pedometers) defined recreationally active for this study. Exclusion criteria included smoking, recent (<2 mo) change in body weight, or training for competitive endurance events. A subset of data examining endothelial function after 5 d of reduced activity from 12 subjects recruited for this study has been previously published (5).
Before the study intervention, body composition was assessed by DEXA (Hologic) and fitness by a graded maximal treadmill test to elicit maximal oxygen uptake (V˙O2max). Subjects were provided with breakfast, lunch, dinner, and snacks for three consecutive days before testing to determine daily energy intake. Specifically, because of the habitual eating patterns of young adult Americans (26), the breakfast meal was standardized to 15% of daily energy (∼450 kcal) and lunch was standardized to 24% of daily energy intake (∼850 kcal). Morning and afternoon snacks were also provided (∼200 kcal per snack). Lastly, an ad libitum dinner was provided to allow the participants to adjust their intake according to their habitual dietary pattern. All meals were composed of 57% carbohydrate, 28% fat, and 15% protein. Daily energy intake during the 3 d was then determined. Subjects were asked to fill out a questionnaire to assess compliance to the diet and were also asked to return any uneaten food in packed out containers back to the laboratory. Subjects also monitored daily steps for 3 d via a pedometer and average daily energy expenditure above 3 METs (kJ) via a physical activity monitor (Body Media). Kilojoules were then converted to kilocalories by the following equation: kilocalories = (kilojoules × 0.239). Average daily energy expenditure was not calculated in two subjects because of software malfunction of the physical activity monitor. The activity monitor also recorded wear time so that compliance could be verified.
Intervention (5 d of reduced physical activity and 1 d return to activity)
Figure 1 shows the timeline of the overall study design. Subjects began the 5 d of reduced daily physical activity intervention (<5000 steps per day) after baseline testing, as previously described by our laboratory (5). To achieve this, subjects were instructed to refrain from structured exercise, take the elevator instead of stairs, and/or park closer to the door entrance. After the 5-d inactivity intervention testing, subjects immediately began a 1-d return to physical activity. During this phase, subjects resumed normal physical activity levels in addition to performing a supervised bout of aerobic exercise that was of similar duration and magnitude as baseline testing. The exercise bout was performed in the morning (∼7 a.m.) before breakfast at both baseline and during the 1-d return to activity visits. This intervention was chosen for the return to physical activity because one bout of exercise in previously sedentary individuals has been shown to improve insulin sensitivity and glycemic control (28,36). Pedometers were worn for subjects to quantitatively assess daily steps.
Subjects wore a pedometer and physical activity monitor for 3 d before baseline testing and were instructed to follow normal physical activity patterns. A continuous glucose monitor was inserted subcutaneously in the abdomen of each subject for recording of interstitial blood glucose (24,25). During the 2 d before baseline testing and throughout the entire study intervention, the subjects received eucaloric meals and snacks based on their respective measured intake determined during the preintervention testing. A 45-min supervised treadmill exercise session at 60% of HR reserve was performed 24 h before baseline testing to control for the amount and time of day when the subjects received their last bout of structured physical activity. This was done to control for exercise-induced hyperemia on the vasculature (21,30) as well as exercise-induced increases in insulin sensitivity. Additional exercise was avoided after this exercise bout.
Study visits were conducted between 7:00 a.m. and 10:00 a.m. in a temperature-controlled room kept at 21°C–22°C. Height and weight were obtained via standard methods. After resting in a supine position, an intravenous catheter was placed. After a 15-min rest period, baseline blood samples were obtained for measurement of glucose and insulin. Blood flow and vascular conductance were measured via Doppler ultrasound in two limbs: one that underwent large alterations in physical activity with the study intervention (femoral artery) and one in which physical activity changes were likely minimized during the reduced daily steps intervention (brachial artery) (5,33). An OGTT was performed as previously described by our laboratory (23). Briefly, subjects drank a 75-g glucose drink within 1 min, and blood samples were drawn every 30 min for 2 h. Blood flow through the femoral and brachial arteries was measured every 30 min for the duration of the OGTT. Brachial and femoral blood flows during the OGTT were performed at baseline, RA5, and RTA1.
Blood flow measures
Blood flow to the femoral (Logiq P5; GE Medical Systems, Milwaukee, WI) and brachial (Logiq7; GE Medical Systems) arteries was measured simultaneously using duplex Doppler ultrasound with a linear array transducer (10–12 MHz), as previously described by our laboratory (5,23,33). Blood velocity was obtained simultaneously with diameter in pulsed-wave mode at an insonation angle of 60° and operating at a frequency of 5 MHz with the velocity cursor set midvessel. Sample volume was maximized to encompass the entire vessel lumen without extending beyond it. Limbs were secured and transducer stabilized using a custom-designed clamp. Baseline blood flows in the femoral and brachial arteries were recorded for 5 min before glucose ingestion and every 30 min for 2 h after ingestion of glucose. The same Doppler ultrasound unit (Logiq P5 and Logiq 7) and ultrasonographer were used to measure blood flow in each limb across the three study visits. Blood flow measurements were not performed in one subject due to technical difficulties. A custom-designed edge-detection and wall-tracking software measured diameter and velocity (LabView; National Instruments) as previously described in detail (15,29,33). Blood flow (milliliters per minute) was calculated as follows: blood flow = π × (diameter/2)2 × Vmean × 60, where Vmean = mean velocity. Peak blood flow was determined as the maximum blood flow response after the OGTT for each subject. Conductance was calculated as peak blood flow divided by mean arterial pressure. Finger photoplethysmography was used to measure beat-to-beat blood pressure (Finometer; Finapres Medical Systems, Amsterdam, The Netherlands). Return-to-flow calibrations were performed before each Finometer recording.
Continuous glucose monitoring
Glycemic control was assessed for a 48-h period at baseline and for two separate 24-h periods during RA5 and RTA1 using a CGMS (iPro CGM; Medtronic Diabetes, Minneapolis, MN), as previously described by our laboratory (24,25). A glucose sensor was inserted subcutaneously into the abdomen of each subject, and the CGMS was connected to the sensor. The CGMS measures interstitial blood glucose every 5 min during the 24-h period. Study food logs containing the start times of each meal and at least four blood glucose recordings from finger sticks (Accu-check Compact Plus; Roche Diagnostics Peak) were collected from subjects, and the CGMS data were analyzed using Solutions Software for CGMS iPro (Medtronic Diabetes). Blood glucose responses during 48 h were analyzed for baseline and 24 h for RA5 and RTA1. Peak PPG was measured by averaging the largest blood glucose response during the 2-h period after breakfast, lunch, and dinner. Continuous overlapping net glycemic action (CONGA-2), a measure of blood glucose variability, was measured by assessing the standard deviation of PPG for 2 h after each meal. The 2-h glucose area under the curve (AUC) was calculated from the averaged glucose AUC response from each meal consumed during the different phases of the study. Glycemic control was not assessed in two subjects during RTA1 because of software malfunction of the CGMS.
Blood sample analysis from OGTT
Serum blood glucose measures were made using the glucose oxidase method (Sigma, St. Louis, MO). Insulin was measured via enzyme-linked immunosorbent assays (Immulite 1000 Analyzer; Siemens, Deerfield, IL). Insulin sensitivity was assessed using the Matsuda index as previously described by our laboratory and others (22,23). Insulin and glucose measurements were not performed in one subject because of problems obtaining intravenous catheter placement.
Data were analyzed using Sigma Stat. A one-way repeated-measures ANOVA was used to analyze the Matsuda index, peak PPG, CONGA-2, and PPG AUC across the three study visits, as well as average daily steps and kilocalories per day across the study intervention. Rank order testing was applied where necessary. A two-way repeated-measures ANOVA was used to assess the glucose and insulin response to the OGTT, the blood flow in the brachial and femoral arteries, and conductance responses from baseline to peak response across the three study visits. Least significant difference post hoc testing was applied where significant main effects were found. Significance was set at P < 0.05. All data are presented as means ± SEM.
Baseline subject characteristics of the male subjects were age = 24 ± 1.1 yr, body mass index = 24.4 ± 0.8 kg·m−2, body fat = 19.2% ± 0.9%, and V˙O2max = 52.6 ± 2.5 mL·kg−1·min−1.
Physical activity measures and diet
Steps per day and kilocalories expended above 3 METs·d−1 were significantly decreased after 5 d of reduced activity (Fig. 2; P < 0.05 from baseline). Further, all were significantly elevated back to baseline values after the 1-d return to activity (P > 0.05 from baseline). The physical activity monitor recorded that subjects wore the monitor approximately 18 h·d−1 (minus bathing and sleep time). For the standardized diet, subjects were compliant in eating all of the packed out food as recorded in the questionnaire and the return of empty food containers.
Insulin-stimulated blood flow and vascular conductance
Blood flow in the femoral (Fig. 3A) and brachial arteries (Fig. 3B) increased during the OGTT (both P < 0.05 from 0 min of OGTT). However, no significant differences occurred in the femoral or brachial artery blood flow responses across the study interventions (P > 0.05 from baseline). Similar results were obtained for peak femoral and brachial artery conductance, with increases during the OGTT that were unaffected by changes in physical activity (P > 0.05 from baseline).
The glucose response to the OGTT across the phases of the study was not significantly different (P > 0.05 from baseline; Fig. 4A). However, the insulin response to the OGTT displayed a significant main effect for the study interventions without an interaction (Fig. 4B). Furthermore, insulin sensitivity, measured by the Matsuda index, was significantly reduced after RA5 and remained suppressed during RTA1 compared to baseline (P < 0.05; Fig. 4C).
Peak PPG (a marker of free-living postprandial glycemic control) and CONGA-2 response (a marker of free-living glycemic variability) were significantly elevated after RA5 (Fig. 5A and C; P < 0.05 from baseline) compared to baseline. Peak PPG remained significantly elevated after RTA1 (Fig. 5A; P < 0.05). The 2-h AUC response averaged across meals trended to be different between the three study interventions (P = 0.067; Fig. 5B). Upon further investigation with paired t-tests, RA5 and RTA1 were elevated above baseline (P < 0.05). In line with this finding, the impairments in free-living glycemic control with the physical inactivity intervention can be readily appreciated from the visual inspection of the minute-by-minute blood glucose measures obtained between 7 a.m. and 8 p.m. across study interventions (Fig. 6).
The major novel findings of this study are that 1) impairments in glycemic control after changes in physical activity are not paralleled by reductions in blood flow responses after an OGTT and 2) a 1-d return to daily ambulatory activity after 5 d of reduced daily physical activity did not restore free-living glycemic control or insulin sensitivity measured by an OGTT. Overall, these data demonstrate that acute physical inactivity reduces insulin sensitivity and glycemic control, but this occurs without changes in blood flow responses to an OGTT.
Previous studies have examined the effects of insulin to increase blood flow to skeletal muscle (2,6,19,20). These studies establish an important link in the role of insulin-stimulated blood flow to regulate glucose disposal into skeletal muscle. However, whether reducing insulin sensitivity via reductions in physical activity impairs the blood flow response to an OGTT has not been examined extensively. One study found that detraining in endurance-trained subjects reduced the blood flow response to an OGTT (1). However, the subjects in this study were of high fitness (V˙O2max = 63 mL·kg−1·min−1), which does not describe the majority of individuals. Further, the study examined detraining and not reductions in daily ambulatory activity. In contrast, our subjects were recreationally active men (>10,000 steps per day) who reduced their total physical activity slightly below that of the average, sedentary US citizen (<5000 steps per day) (5,37).
In the present study, we demonstrate that the blood flow response to the OGTT is not related to decreased insulin sensitivity and glycemic control after 5 d of physical inactivity and a 1-d return to activity in young healthy previously active men. In a previous study, we found that adding physical activity, through 7 d of aerobic exercise (1 h·d−1), increased blood flow responses to an OGTT in subjects with Type 2 diabetes—responses that tracked with improved glycemic control and insulin sensitivity (23,24). Previous evidence showed that impairing insulin-stimulated blood flow through endotheial nitric oxide synthase (eNOS) inhibition reduced skeletal muscle glucose disposal by 40% (2), leading us to posit that the increase in insulin sensitivity and blood flow responses to an OGTT were linked. However, we did not find the same relationship with reduced activity in the current study. Certainly exercise and increased physical activity are not necessarily the inverse of reduced activity (35). Moreover, these data suggest that factors other than blood flow are driving the decline in glycemic control and insulin sensitivity observed after acute reductions in physical activity. Nevertheless, it is possible that longer-term reductions in physical activity (>5 d) would impair the blood flow response to an OGTT, further reducing glycemic control and insulin sensitivity. This warrants further study.
Previous studies have shown that 6 d of detraining reduces the glucose transporter protein, Glut-4, in skeletal muscle (39). Both insulin and exercise stimulate increases in glucose uptake via Glut-4 translocation in muscle (12), and it is generally recognized that Glut-4 content tracks with insulin sensitivity. Rodent studies using an analogous method to reduce daily physical activity, for example, the wheel lock model, show that insulin signaling proteins and insulin-stimulated skeletal muscle glucose uptake are both reduced during a transition to lower daily activity (18). Interestingly, there is strong evidence that one bout of exercise may increase Glut-4 protein expression (32) and repeatedly increases insulin sensitivity in healthy subjects and in subjects with diseases (36) but the 1-d return to activity in the present study did not restore insulin sensitivity or glycemic control. The exact reason for these disparate responses is unclear. However, most studies that have examined one bout of exercise and the effect on insulin sensitivity used techniques that focused on skeletal muscle insulin sensitivity via a hyperinsulinemic–euglycemic clamp or insulin exposure to skeletal muscle, whereas this study used an OGTT, which relies on various tissue responses including but not limited to muscle, liver, and pancreas. Also, in general agreement with our findings, Heath et al. (16) reported that cessation of exercise training for 10 d in endurance athletes led to higher insulin and glucose responses to an OGTT, and although one exercise bout tended to return glucose and insulin responses back toward predetraining values, it did not completely restore responses. Nevertheless, it should be noted that “exercise training cessation” and “imposing physical inactivity” where daily ambulation is lowered are two different stimuli and may not evoke similar results. This is similar to the concept that bedrest studies do not accurately reflect the physical inactivity most people experience in their daily life where they maintain some level of ambulation.
Although the primary reason for the lack of a change in blood flow during the OGTT after reductions in physical activity is unknown, several possibilities warrant discussion. First, we measured conduit artery blood flow. Whereas the assumption is that changes in conduit artery blood flow are representative of alterations in downstream arteriolar and capillary beds of skeletal muscle, this might not always be the case. It is possible that changes within the skeletal muscle microcirculation occurred with a lack of change in conduit artery blood flow. In this regard, skeletal muscle microcirculation blood flow is increased with lower levels of circulating plasma insulin compared to conduit artery blood flow (9). Thus, in the present study, it is possible that alterations in microvascular blood flow tracked with alterations in glycemic control and insulin sensitivity, which were not demonstrated with conduit artery blood flow. The concept of nutritive and nonnutritive blood flow is important to consider when examining the links between insulin-stimulated blood flow and glucose disposal (3,8,9). Nonnutritive blood flow is considered microvascular blood flow, which perfuses tissue with relatively low metabolic demand (i.e., connective tissue), whereas nutritive blood flow perfuses skeletal muscle microvasculature with high metabolic demand and glucose transport (8,9). Nonnutritive blood flow is thought to serve as a reservoir for nutritive capillaries such that, when meal-induced insulin stimulation occurs, blood flow carrying glucose and insulin is shunted toward nutritive capillaries in skeletal muscle (9). Thus, via a redistribution of blood flow from nonnutritive capillaries to nutritive capillaries during insulin stimulation, it is possible to recruit skeletal muscle capillaries without increasing conduit artery or bulk flow.
Furthermore, it must be acknowledged that the lack of change in blood flow in femoral and brachial arteries to reductions in daily physical activity may be due to a compensatory increase in plasma insulin after changes in physical activity (see Fig. 4). Given that the 2-h glucose curves during the OGTT are overlaid on top of each other from baseline to reduced daily physical activity, increased plasma insulin to the OGTT after inactivity must be accounting for reduced insulin sensitivity as assessed by the Matsuda index. Thus, increased plasma insulin during reduced daily activity may be providing for a normal conduit artery blood flow response. Although it is tempting to speculate that a similar plasma insulin level to baseline (active phase) would result in a reduced blood flow response to the OGTT after reduced activity, this would require future studies. It is also possible that blood flow to the OGTT in the current study would be decreased after a longer-term reduced physical activity/insulin sensitivity intervention, given that individuals with chronic insulin resistance display blunted blood flow responses to insulin stimulation (19,23).
A potential limitation of this study is that it was a single-group, time-series design, without a randomized control comparison group (or condition). Therefore, it is possible that habituation or decreased stress levels with repeated laboratory visits may have influenced responses to the testing procedures rather than the imposed physical inactivity. However, all subjects visited the laboratory several times before the study began and were familiarized with the procedures before any measures. Also, using a similar study design, we previously reported that a measure of vascular function (flow-mediated dilation) was not altered from baseline with repeat visits during 5 d of maintaining normal physical activity, giving us some assurance that this was likely not a problem in the outcomes of our study (5). We also used a standardized diet throughout to control for fluctuations in diet and their potential impact on study outcomes.
In summary, our data suggest that impaired insulin sensitivity and glycemic control to reductions in daily physical activity do not occur in parallel with alterations in the blood flow response to an OGTT. Further, our data suggest that 1-d return to physical activity after 5 d of reduced daily activity in previously active individuals is not sufficient to restore insulin sensitivity or glycemic control. Further, these data build on our previous findings that daily physical activity is important in regulating glycemic control (24,25) and suggest that inactivity may play a permissive role in the development of conditions like Type 2 diabetes where glycemic control is impaired. More specifically, our data show that acute reductions in ambulatory activity lead to greater variability in blood glucose throughout the day (CONGA) and greater postprandial swings in blood glucose, both of which are increasingly being linked to cardiovascular risk (7,34). Collectively, our results suggest that acute inactivity leads to deleterious impairments in insulin sensitivity and glycemic control but that these changes are not due to postprandial blood flow impairments.
This work was supported in part by National Institutes of Health grants R01-HL093167 (P.J.F.). J.P.T. was partially supported by NIH R01DK088940. D.P.C. and S.W.H. were supported by an NIH T32-AR048523. LJR was supported by an ACSM Foundation Research Grant from the American College of Sports Medicine Foundation and an American Heart Association Pre-Doctoral Fellowship (12PRE12080242). The results of this study do not constitute endorsement by the American College of Sports Medicine.
The authors have no conflicts of interest.
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