Calories Count, but Steps Count Too! From 10 to 5k Steps/d W/Out Effect on Body Composition if Energy Intake is Mildly Reduced | Unlike Fatness, the Fitness Worsens, Though

Trust me, once you try to match your intake to your alleged expenditure via apps and trackers you WILL fail if you’re also working out regularly – so don’t extrapolate the results to: “Oh, I’ll just have that Pizza + IceCream, I burned 1,000kcal extra in the gym, I can afford it” – you can’t out-exercise overeating!

Those of you who’re friends with me on Facebook may have seen the link I posted to an article about an epic total bed rest study (yes, including bedpans, etc.) that’s currently recruiting volunteers. If it was not for the good of humanity – Mission to Mars etc. you know – I guess, studies in which you have to stay lying at a decline angle in bed for a whopping two months wouldn’t even pass the scrutiny of the ethics committee of (in this case) NASA… but I am digressing and things were significantly less bad and much more realistic in a recent study from the University of Missouri.

With this new study, Winn et al. (2019) wanted to quantify the ill effects of physical inactivity on glucose metabolism and energy balance; and ascertain that energy restriction (yes, calories count) does, as the researchers speculated based on previous studies, indeed blunt these adverse manifestations.

To give the study an extra-twist and shut the “calories don’t count”-crybabies up, the US researchers decided to go beyond a mere reduction of the energy intake and fed their subjects [inclusion criteria]…

“1) males and females between 18 and 45 yr of age; 2) body mass index (BMI) <28 kg/m² = normal or underweight; 3) no known cardiovascular, kidney, or liver disease; 4) no history of surgery for weight loss and weight stable for prior 3 months (weight change <3 kg); and 5) physically active individuals (90 min of primarily whole body aerobic physical activity >3 d/wk and taking greater than 10,000 steps/day) assessed via accelerometers,” (

Winn 2019)

… two different diets. More specifically, the subjects were assigned to either the ‘regular Western diet’ (64% carbohydrate, 20% fat, 16% protein) or “high” protein diet containing “only” 50% of the energy in form of carbohydrate, 20% fat, and a whopping 30% as protein [yeah, I know the crybabies are not going to happy with that, but I cannot change the study design and carb-restrict the “higher protein” group retrospectively, sorry ;-].

The number of subjects seems ridiculously low, no? You’re right it’s not exactly a large-scale study, but the sample size requirements for this study were calculated based on a type I error rate of 0.05; and according to this calculation an N = 10 subject (paired) design should yield a satisfactory 83% power to detect a 30% change in postprandial insulin AUC with an effect size of 1.0 – that’s everything but ideal, but if we’re looking for effects that are large enough to be physiologically relevant, this ‘accuracy’ should be about good enough to make some general statements.
Figure 1: Experimental design and physical activity/energy expenditure. Healthy physically active adults (n = 10) defined as exceeding 10,000 steps per day, completed (A) two periods of physical inactivity while consuming either a control diet or higher-protein diet in a randomized crossover design. Average B) daily steps and (C) energy expenditure (total and physical activity). Data are means ± SEM.  *P < 0.05 vs active. Horizontal arrows represent the number of days for a given data assessment, whereas vertical arrows indicate testing on a single day in the laboratory. Days 1 to 10 were “free-living.” White bars reflect the “active” phase and gray bars represent the ‘inactive’ period. CGMS, continuous glucose monitoring system; BP, blood pressure; DEXA, dual x-ray absorptiometry; EE, energy expenditure. n = 10/condition.

All in all, ten healthy adults met criteria 1-5 (see quote in the previous paragraph). They had a mean age of 24 ± 1 yr and regular activity level of 10,000+ steps per day. Now, these specimen may not necessarily be representative of ‘the average Westerner’ who’s (meanwhile) overweight and mostly sedentary, but the beauty is…

… the cohort of N=10 young adults is small, but it’s more representative of the average SuppVersity reader than participants in the average activity <> obesity study.

As you can see in Figure 1, the study used a cross-over design so that, after a 4-week washout those in the “high protein” group were switched to control diet and vice versa, which was then consumed for another 10 days of reduced activity (5,000 vs. 10,000+ steps per day).

As the smaller figures from the bottom tell you the ActiGraph GTX3 data Walk4Life™ told the researchers that the subjects ‘managed’ to move significantly less, with the average subject taking slightly less than the targeted 5,000 steps per day.

In a similar vein, the scientists’ were able to confirm that the subjects actually hit their energy deficit goal of -400kcal/day (measured by the doubly labeled water technique | Chomistek 2017).

Why -400kcal? Well, the specific reduction in energy intake, i.e. 400kcal below maintenance was selected to “account for reduced energy expenditure associated with inactivity” (Winn 2019). 

With another 5 subjects completing the 10-day inactivity cycles consuming 35% excess of their basal energy requirements, the scientists hoped to be able to understand the interaction of sedentary behavior, energy intake and expenditure, and the subject’s glucose management by comparing their primary outcome, the subjects gluco-metabolic response to their combined diet + physical activity intervention.

Table 1: Metabolic Implications of Diet and Energy Intake during Physical Inactivity (Winn 2019).

To this ends, Winn et al. used continuous glucose monitoring and OGTT blood collections at 10, 20, 30, 60, 90, 120, 150, and 180 min after ingestion of the oral glucose solution and compared the restricted control and “high protein” diets to the positive control condition (overfeeding + inactivity).

Why only N=5 subjects in the positive (overfeeding + inactivity) control condition? Well after intervention #1 (energy reduction), only N=5 subjects volunteered to participate in another 10-day study… and that despite the fact that the extra calories were primarily comprised of dessert-like foods that were provided by research staff (those left the subjects with extra ~880 kcal/day (macros of the diet 50% carbohydrate, 43% fat, and 7% protein).

“What on earth? Why only 7% protein in the overfeeding study?” What I like about the study at hand is that the researchers have addressed all these questions and explain that “[…t]his behavior [meaning to eat an even ‘junkier’ diet] is typical of the Western holiday seasons, which are characterized by periods of physical inactivity and overconsumption of calories creating a net positive energy balance” (Winn 2019).

Figure 3: In an energy-balanced scenario, medium-intensity exercise does not improve your insulin sensitivity on the day after your workout. High-intensity interval training, on the other hand, works even if it doesn’t induce an energy deficit (Fisher 2019).

Calories count – for the benefits of exercise, too! Alongside the study under review, a new paper from Fisher et al. was published that shows that the improvement you see if you move more (including moderate intensity exercise) is also mostly a function of an energy deficit. In the corresponding experiment, the scientists assessed the effect of 8 to 16 wk of aerobic exercise training on the insulin sensitivity (SI) of untrained women under rigorously controlled energy-balanced conditions and found that only high-intensity interval (HII | 84% VO2peak) training had energy-independent beneficial effects on the N= 28 untrained female study participants.

The ladies’ insulin sensitivity was assessed 22 h after either a medium-intensity cycling (MIC | 50% VO2peak) or the previously referenced HII workout using a hyperinsulinemic–euglycemic clamp. During the whole procedure, the participants were in a whole-room indirect calorimeter during each condition, and food intake was adjusted to ensure energy balance across 23 h before each clamp, the scientists can be sure that “[t]here were no significant differences in acute energy balance between each condition” (Fisher 2019). By excluding the influence of an energy deficit, the scientist were thus able to show that medium-intensity cycling, alone – in the absence of a caloric deficit or at least changes in the energy balance will not improve the insulin sensitivity of untrained, still normal-weight (BMI < 28, but >37% body fat) women; or, as the scientists interpret their own results…

“the reported improvements in SI [insulin sensitivity] in response to chronic exercise training may be mediated in part by shifts in energy balance” (

Fisher 2019).

That sounds like bad news, but we should not forget that Fisher et al. were also able to show that “an acute bout of HII exercise may increase SI even in the context of energy balance” (Fisher 2019). Plus, all exercise groups saw increases in physical fitness (VO2max, p > 0.05 for inter-group differences); a benefit of which the study by Winn et al. suggests that it can be undone by only 10 days of limited physical activity – even if the reduced energy expenditure is accounted for.

Another strength of the study is its decently tight control and the fact that we know that the subjects actually went from their initial 12,154 ± 308 steps per day to a rather meager 4275 ± 269 steps per day (P < 0.05) during the 10-day intervention study… Figure 4 shows the primary outcome, the measures of glucose metabolism.

Figure 4: Effect of physical inactivity on glucose tolerance and indices of insulin sensitivity/resistance in response to a control diet and higher-protein diet. Physically active and physically inactive (A) glucose, (B) insulin, and (C) NEFA curves with corresponding 3-h AUC (inset) after a 75-g oral glucose challenge during the control diet and higher-protein diet conditions. (D) Two-hour glucose and (E) 2-h insulin during the OGTT. (F) HOMA-IR. Data are means ± SEM. *P < 0.05 vs Active. Two-way ANOVA with activity and diet as factors was used for statistical comparisons. Post hoc comparisons with Tukey correction were run when a significant main effect was observed. n = 10/condition. (Winn 2019)

And what do the graphs tell us? Well, as long as you reduce your energy intake appropriately, taking less than half your usual steps per day does not impair your glucose metabolism – that is, allegedly, over a very short time-frame.

You want to do some damage? Don’t adapt your energy intake to your (new) sedentary lifestyle!

Table 2: Age, body composition, and blood chemistry in the “holiday” (=reduced activity + extra 800kcal energy intake) experiment (Winn 2019).

As Table 2 on the right shows, the inertness of reduced activity in an isocaloric/deficit scenario is in contrast to the consequences of the “holiday lifestyle” (sit around and eat trash) that was simulated in experiment #2. When the energy intake was increased and the physical activity was reduced, there were ill effects on body weight (+1kg) and BMI, body fat and (+0.7%), fat mass (0.8 kg), as well as a significant worsening of glucose, insulin, C-peptide, and the clearance of insulin (learn more) by the liver…

Similar, albeit less pronounced, effects can be expected for lower mismatches of energy intake and expenditure as they can easily occur when people become progressively more sedentary without adapting their diet (the “I’ve always had three slices of toast for breakfast”-phenomenon) – over months+years most of us accumulate a mismatch and hence risk fat gain and diabetes.

Unfortunately, the experiment #2 in the study at hand was not designed to investigate the effects of macronutrients, which could be significant, even if it didn’t do shit in energy balance/deficit, where  the scientists didn’t observe “higher protein” magic in form of differential effects on glucose management or additional effects on body composition, aerobic capacity, and energy expenditure. What the high protein diet in experiment #1 did do, though, was to lower the level of triglycerides, which increased by 15mg/dL (+21%) on the control diet and declined by 27mg/dL (-26% | albeit from higher baseline levels) in the “high protein” group.

Don’t make the unwarranted assumption that you just have to work out more to compensate for Pizzas & co. While this may work for additional intakes of 100-400kcal/d even the most active of us don’t burn enough to “afford” eating the average sized extra meal | learn more.

So, I can get away with sitting around? For 10 days, you can, but the short nature of the study is not the only reason I would not throw away my step-counter, yet.

After all, the subjects’ fitness deteriorated significantly within only 10 days with a VO2max going down by −1.8 ± 0.7 mL/kg/min (P < 0.05) – and that independent of the diet conditions, as a consequence of the prescribed decrease in steps.

How’s that significant? Well, physical fitness – and VO2max is still one of the best all-around measures of that – has been convincingly linked to health & longevity (or your ‘healthspan’). Hence, reducing your VO2max by ~2% in only 10 days is bad news (Ozemec 2018).

You don’t care about health? Well, what about the latest data from Shad et al. (2019) whose recent one week study, in which eleven healthy men reduced the number of daily steps from ~13,000 to ~1,200 steps per day, reports a whopping -27% reduction in myofibrillar protein synthesis … 😲 Ok, the study was not ideal as the subject’s diets were not prescribed and the protein intake of the subjects dropped from 2.1g/kg to 1.8g/kg (p < 0.05) in the high physical activity (HPA >10,000) vs. step reduction (SR | <1,300) condition | Comment on Facebook


  • Chomistek, Andrea K., et al. “Physical Activity Assessment with the ActiGraph GT3X and Doubly Labeled Water.” Medicine and science in sports and exercise 49.9 (2017): 1935-1944.
  • Fisher, et al. “Acute Effects of Exercise Intensity on Insulin Sensitivity under Energy Balance.” Medicine & Science in Sports & Exercise: May 2019 – Volume 51 – Issue 5 – p 988–994
  • Ozemek, Cemal, et al. “An update on the role of cardiorespiratory fitness, structured exercise and lifestyle physical activity in preventing cardiovascular disease and health risk.” Progress in cardiovascular diseases (2018).
  • Shad et al. “One Week of Step Reduction Lowers Myofibrillar Protein Synthesis Rates in Young Men.” Medicine & Science in Sports & Exercise: May 7, 2019 < ahead of print > 
  • Winn, Nathan C., et al. “Metabolic Implications of Diet and Energy Intake during Physical Inactivity.” Medicine and science in sports and exercise 51.5 (2019): 995-1005.


Skip to toolbar