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Original Research
An Exploratory Study Comparing the Metabolic Responses between the 12-3-30
Treadmill Workout and Self-Paced Treadmill Running
Michael W.H. Wong†, Dustin W. Davis†, Olivia R. Perez*, Bianca Weyers*, Devin M. Green*,
Alan V. Garcia*, James W. Navalta‡
Department of Kinesiology and Nutrition Sciences, University of Nevada, Las Vegas, Las Vegas,
NV, USA
*Denotes student, †Denotes early-career investigator ‡Denotes established investigator
Abstract
International Journal of Exercise Science 18(6): 56-64, 2025. https://doi.org/
10.70252/UBIX5911 The fitness movement in the United States has evolved substantially since its emergence
in the late 20th century, with social media platforms like YouTube and TikTok now playing a pivotal role in
disseminating fitness programs and associated claims. One program that has gained considerable popularity is the
12-3-30 treadmill workout (12-3-30), which involves walking at a 12% grade at 3 mph for 30 minutes. Despite
widespread claims about its effectiveness in burning fat and calories, there is a lack of peer-reviewed scientific
studies evaluating these claims. The present study investigated metabolic responses to 12-3-30 compared to self-
paced treadmill running, with both sessions matched for total energy expenditure. Sixteen participants (7 female,
9 male) completed both sessions in a controlled laboratory setting, where metabolic data were collected using a
metabolic analyzer. The measures recorded were completion time, total energy expenditure, energy expenditure
rate, and substrate utilization (percentage of carbohydrate [%CHO] and fat [%FAT]). The results showed that, when
matched for total energy expenditure, 12-3-30 had a significantly longer completion time, lower energy expenditure
rate, higher %FAT, and lower %CHO than self-paced running. While 12-3-30 may be less time efficient than self-
paced running for expending energy, it may be more advantageous for individuals aiming to increase fat
utilization. The present study enhances our understanding of the metabolic demands associated with a trending
fitness program and highlights the importance of scientifically evaluating such programs to provide evidence-
based recommendations.
Keywords: Aerobic exercise, incline walking, submaximal exercise, exercise intensity, metabolic
cost, fitness influencers
Introduction
The present-day enthusiasm for and focus on physical fitness in the United States belies its
humble and recent origins. The roots of the fitness movement are traceable to the late 20th
century and the pioneering advocacy of Bernarr Macfadden, who popularized physical fitness,
fasting, and other health topics through his influential magazines like Physical Culture.1 But it
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was the advent of television in the 1940s, and widespread accessibility to it in the 1950s, that
catapulted fitness into the mainstream. Figures like Jack LaLanne leveraged the growing
popularity of television to bring exercise directly into the living rooms of millions through his
eponymous show.2 The movement gained momentum with the creation of commercial gyms
like Gold’s Gym in 1965 and the publication of Jogging in 1967.3 The 1970s and 1980s brought
icons like Arnold Schwarzenegger and Jane Fonda who further shaped the movement with their
respective influences on bodybuilding and aerobics. Step aerobics and Zumba gained popularity
in the 1990s and, in the 21st century, so has Pilates, yoga, and functional fitness training. In recent
years, social media platforms like YouTube, Instagram, and TikTok have revolutionized the
movement, empowering fitness influencers to drive and disseminate exercise programs to
millions of people globally. Given the massive audiences reachable, bold claims made, and lack
of unified oversight of information on social media platforms, it is crucial for trained experts in
exercise science, sports and exercise physiology, and related fields to investigate the accuracy of
claims and efficacy of programs popularized on these platforms.
One such program, the 12-3-30 treadmill workout (12-3-30), has garnered an impressive level of
attention, amassing over 1.6 million views on YouTube4 and 14 million views on TikTok.5
Developed by health and beauty influencer Lauren Giraldo, 12-3-30 involves a structured
routine of walking on a treadmill at a 12% grade and 3 mph (1.34 m/s) for 30 minutes. In her
TikTok video, which is a short repost of the original YouTube video from a year before, Giraldo
claimed to have lost 30 pounds and maintained a lower weight for approximately two years
without dieting or counting calories. In the video, she says, 12-3-30 "is like all I do," completing
it approximately five days per week.5 Giraldo’s videos and claims sparked widespread
commentary, results, and testimonial videos about the original program and its variations.
Almost five years after the original videos, online health magazines still publish articles
discussing the workout and its purported benefits for energy expenditure, fat loss, and
metabolic health.6,7 Despite the program’s popularity, the authors of the present study are not
aware of any published peer-reviewed research on 12-3-30.
Peer-reviewed research on 12-3-30 is crucial for helping both academic and lay readers
understand its metabolic cost and make informed choices about whether to adopt 12-3-30 or
alternative treadmill workouts such as flat walking or running. Research so far has focused on
joint kinematics rather than metabolic responses. Franz and Kram8 reported greater activity in
lower-limb extensor muscles during incline walking than flat walking. Orozco et al.9 similarly
noted trends of greater activity at steeper grades, albeit without significant temporal differences.
Greater muscle activity during incline walking aligns with the increased demands of lifting the
body against gravity while maintaining stability, thereby resulting in greater energy
expenditure. Silder, Besier, and Delp10 reported a 113 ± 32% greater metabolic cost for incline
walking than flat walking, using a 10% grade and a speed similar to 12-3-30. To comprehensively
understand the metabolic responses specific to 12-3-30, controlled scientific studies are
imperative. Therefore, the present study measured and compared metabolic responses between
12-3-30 and self-paced treadmill running, hypothesizing differences in completion time, energy
expenditure rate (kcal/min), and substrate utilization (percent carbohydrate [%CHO] and
percent fat [%FAT]).
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Methods
Participants
The study recruited a convenience sample from the university and surrounding community,
including undergraduate and graduate kinesiology students, staff, and faculty. Participants
were eligible if they were 18 years or older, regularly engaged in physical activity (≥ 30 minutes
≥ 3 times per week for ≥ last 3 months), and were comfortable walking and running on a
treadmill for 30 minutes. Participants were excluded if they were pregnant or may be pregnant,
had underlying chronic conditions such as diabetes, coronary heart disease, or kidney disease,
or did not meet the physical activity inclusion criterion.
Because of the nascent literature on 12-3-30, there was a lack of comparable literature to guide
the determination of a priori sample size or to conduct a traditional power analysis. Therefore,
no formal power analysis was conducted prior to the study. Consequently, sample size was
determined based on practical considerations such as participant availability and the concurrent
evaluation of post hoc power as explained below. Sixteen participants enrolled (n = 7 female, n
= 9 male, no other sexes reported) with a mean ± standard deviation age, height, and mass of
25.31 ± 7.97 y, 172.39 ± 8.60 cm, and 75.42 ± 15.96 kg, respectively. Participants reported their sex
without being given a list of options. Gender identity was not collected. All participants gave
verbal and written informed consent to participate in the study, which had approval by the
Institutional Review Board of the University of Nevada, Las Vegas (UNLV-2021-65). This
research was carried out fully in accordance with the ethical standards of the International Journal
of Exercise Science.11 One female participant could not complete the 12-3-30 session, and another
female participant dropped out after the 12-3-30 session because of the inability to schedule the
self-paced run.
Protocol
Participants visited the Exercise Physiology Laboratory twice: once to complete 12-3-30
(23.07 ± 0.80 °C, 768.62 ± 5.27 mmHg) and again within seven days to complete a self-paced run
(23.13 ± 0.64 °C, 769.03 ± 5.64 mmHg). Participants were instructed to refrain from eating for at
least three hours prior to their scheduled visit to minimize the impact of nutrient intake on
substrate utilization during 12-3-30 and self-paced running. During both sessions, participants
wore a two-way non-rebreathing oro-nasal facemask (Hans Rudolph Inc., Shawnee, KS) fitted
using the manufacturer's mask-sizing caliper. The mask was connected to a metabolic analyzer
(TrueOne 2400, ParvoMedics, Salt Lake City, UT), which was calibrated daily according to the
manufacturer's guidelines. The sampling frequency of expired air was breath-by-breath.
For 12-3-30, participants straddled the treadmill, which was set to 3.0 mph (1.34 m/s) and a 12%
grade on a Woodway treadmill (4Front, Woodway USA Inc., Waukesha, WI). Participants then
stepped onto the treadmill belt to begin the test, and researchers started the 30-minute timer.
Participants were prohibited from changing the treadmill settings, holding the handrails,
reading, or using digital devices. After 30 minutes, the energy expenditure rate and substrate
utilization (%CHO and %FAT) were recorded.
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The self-paced run followed the same protocol, except participants self-selected their starting
running speed before stepping onto the treadmill belt. Participants were allowed to adjust the
speed at any point during the run, provided they maintained a gait with a flight phase. The
treadmill grade was set to 0%. Participants continued running until they expended the same
number of kcal as during 12-3-30. At that point, researchers stopped the test and recorded the
run completion time, energy expenditure rate, and substrate utilization.
Statistical Analysis
Five variables were compared between 12-3-30 and the self-paced run: completion time, energy
expenditure, energy expenditure rate, %CHO, and %FAT. Only data from participants who fully
completed both sessions were included in the analyses. Completion time was the duration of
the recorded test on the metabolic cart. Energy expenditure rate was calculated by dividing each
participant’s energy expenditure in kcal on the metabolic cart by the completion time. Both
%CHO and %FAT were calculated as the arithmetic mean of all breath-by-breath measurements
across 12-3-30 and the self-paced run. Single-breath measurements of %CHO or %FAT below
0.00% or above 100.00% were adjusted to 0.00% and 100.00%, respectively, before calculating
these means.
All statistical analyses were conducted by using Microsoft Excel for Mac version 16.77.1
(Microsoft Corporation, Redmond, WA, USA), SPSS (IBM, Armonk, NY, USA), and ChatGPT.
(OpenAI, San Francisco, CA, USA). All variables were compared using two-tailed dependent-
samples t-tests when assumptions were met (scale of measurement, normality, independence,
and absence of outliers), otherwise the Wilcoxon-signed rank test was used. The significance
level was set at ɑ = .05, with significance accepted at p < .05. Cohen’s d was calculated as the
effect size, interpreted as small (0.2), medium (0.5), and large (0.8) according to Cohen.12 Post
hoc power analyses were performed on each variable by using G*Power 3.1.13
Results
Participants’ metabolic responses to 12-3-30 and the self-paced run are shown in Table 1. There
was no significant difference in energy expenditure, indicating that the sessions were matched
for energy expenditure as designed. There were significant differences in completion time,
energy expenditure rate, and substrate utilization between the two sessions (Table 2).
Table 1. Completion time, energy expenditure, energy expenditure rate, %CHO, and %FAT of 12-3-30 and self-
paced run (n = 14).
Condition
Completion Time (min)
Energy Expenditure (kcal)
Energy Expenditure Rate
(kcal/min)
%CHO
%FAT
12-3-30
30.08 (0.08)
307.58 (58.73)
10.23 (1.96)
59.98
(12.12)
40.56
(12.04)
Run
23.89 (2.81)
309.74 (59.70)
13.08 (2.60)
67.47
(11.38)
33.12
(11.31)
Data are reported as means (standard deviations). n = sample size; min = minute; kcal = kilocalorie; %CHO =
percent carbohydrate; %FAT = percent fat.
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Table 2. Comparison of metabolic responses between 12-3-30 and self-paced run (n = 14).
12-3-30 vs. Run
df
t-statistic
Mean
Difference
95% CI
Lower
95% CI
Upper
p-value
Cohen's d
Completion Time (min)
13
−3.30a
6.18
4.56
7.81
0.00098
−0.88b
(large)
Energy Expenditure (kcal)
13
−1.73
−2.16
−4.87
0.54
0.10774
−0.46
(medium)
Energy Expenditure Rate (kcal/min)
13
−6.87
−2.86
−3.76
−1.96
0.00001
−1.84
(large)
%CHO
13
−4.35
−7.48
−11.2
−3.77
0.00079
−1.16
(large)
%FAT
13
4.35
7.43
3.74
11.13
0.00079
1.16
(large)
aWilcoxon signed-rank test statistic (𝑊) instead of the t-statistic. n = sample size; df = degrees of freedom; CI =
confidence interval; kcal = kilocalorie; min = minute; %CHO = percent carbohydrate; %FAT = percent fat.
In alignment with the Sex and Gender Equity in Research (SAGER) guidelines, which advocate for the
presentation of disaggregated data14, we report the metabolic variables disaggregated by sex in Table 3.
Although the primary focus of this study was not to explore potential differences based on sex or gender,
and the study was not designed or powered for such comparisons, we include this data to adhere to SAGER
guidelines and support future meta-analytical efforts.
Table 3. Completion time, energy expenditure, energy expenditure rate, %CHO, and %FAT of 12-3-30 and self-
paced run disaggregated by sex.
Sex
Condition
Completion Time
(min)
Energy Expenditure
(kcal)
Energy Expenditure Rate
(kcal/min)
%CHO
%FAT
Female
(n=5)
12-3-30
30.08 (0.09)
253.87 (34.60)
8.44 (1.14)
67.03
(14.77)
33.55
(14.68)
Run
25.00 (2.80)
255.25 (35.54)
10.26 (1.43)
70.37
(12.53)
30.23
(12.46)
Male
(n=9)
12-3-30
30.07 (0.08)
337.42 (46.93)
11.22 (1.57)
56.07
(9.01)
44.45
(8.95)
Run
23.28 (2.79)
340.01 (47.67)
14.65 (1.49)
65.86
(11.13)
34.73
(11.05)
Data are reported as means (standard deviations). n = sample size; min = minute; kcal = kilocalorie; %CHO =
percent carbohydrate; %FAT = percent fat.
Post hoc power analyses showed that power for completion time, energy expenditure, energy
expenditure rate, %CHO, and %FAT were 1.00, 0.05, 0.99, 0.60, and 0.60, respectively. This
indicates that our study was moderately-to-strongly powered to detect effects for all variables
except for energy expenditure.
Discussion
Before the present study, research primarily examined the biomechanical aspects of incline
walking, revealing increased lower-limb muscle activity and higher energy expenditure than
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flat walking.8,9 Notably, one study reported a mean 113% greater metabolic cost for 10% grade
walking than flat walking.10 Building on this foundation, our study specifically compared
metabolic responses between a specific type of incline walking, 12-3-30, and self-paced running
matched for total energy expenditure, providing insights into 12-3-30’s metabolic effects for
academic audiences, fitness enthusiasts, and the general public. To our knowledge, this is the
first study to directly compared metabolic responses between 12-3-30 and self-paced running.
We hypothesized differences in completion time, energy expenditure rate, and substrate
utilization (%CHO and %FAT). The findings supported our hypotheses: 12-3-30 had a
significantly longer completion time, lower energy expenditure rate, lower %CHO, and higher
%FAT than the self-paced run.
The higher %FAT during 12-3-30 than the self-paced run was expected due to the difference in
absolute intensity, as indicated by the latter’s higher energy expenditure rate. Exercise intensity
is a central determinant of substrate utilization such that higher intensities of aerobic activities
like running and sprinting result in lower fat and higher carbohydrate utilization.15 While not
groundbreaking to exercise scientists, these findings are important for non-experts who might
misunderstand bioenergetics and believe higher fat utilization during exercise is crucial. In
reality, increasing energy expenditure in support of achieving negative energy balance is the
main determinant for weight loss.16 Thus, higher intensity activities like self-paced running
could be preferable modalities for achieving a negative energy balance, especially if efficiency
is important, as participants expended energy faster and completed the exercise in less time than
during 12-3-30.
To 12-3-30’s credit, %FAT was 7.48% lower than during self-paced running. For exercisers
aiming for higher fat loss in addition to weight loss, and who are not concerned with optimal
time efficiency, 12-3-30 may be more effective than self-paced running. However, 12-3-30 might
be too intense to maximize percent fat utilization, as participants' mean %FAT was only 40.56%.
This suggests that for optimal fat utilization, the intensity might need to be reduced by lowering
the speed or grade. This information is particularly relevant for athletes and bodybuilders
seeking to expend energy without substantially depleting glycogen stores. Although this study
does not address glycogen effects directly, it suggests that 12-3-30 may elicit a higher exercise
intensity than these populations might desire.
The present study cannot conclude long-term metabolic responses to 12-3-30 or self-paced
running due to its cross-sectional design. Future research should include randomized controlled
trials to investigate changes in aerobic capacity, muscular endurance, glycogen kinetics, and
body composition over time. Investigating perceptual responses to 12-3-30 could also be fruitful,
as its creator Lauren Giraldo claims it provides structure and motivation. Giraldo mentioned in
her original video, “I used to be so intimidated by the gym, and it wasn’t motivating, but now I
go, I do this one thing, and I can feel good about myself …”.4 Future studies could incorporate
subjective measures of exercise intensity and enjoyment, such as the Rating of Perceived
Exertion scale17 and the Physical Activity Enjoyment Scale18, to investigate these claims.
Furthermore, a longitudinal study could provide insights into adherence to a structured
program like 12-3-30 when compared with traditional aerobic exercise modalities.
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A few limitations of the present study should be noted. First, this exploratory study had a small
convenience sample of mostly college-aged, recreationally active adults, limiting the statistical
power and generalizability of the findings. However, the sample was large enough to avoid
incorrectly rejecting the null hypotheses. Second, participants were not allowed to hold the
handrails during 12-3-30, while the original program did not specify this restriction. Giraldo4
mentioned that she alternates between holding and not holding the handrails during the
workout (30% on, 70% off). Our restriction might have influenced the intensity and subjective
experience of the workout but reduced inter-participant variability to support internal validity.
Third, participants could adjust their speed during the self-paced run. While this introduced
inter-participant variability, it supported external validity. In real-world conditions, running
speed naturally varies based on terrain and individual pacing. Allowing speed adjustments on
the treadmill reflects this variability and mimics typical exercise behavior, thereby supplying
more realistic and applicable data. Still, future studies may wish to standardize and report
running speeds to improve replicability and reproducibility. Lastly, while both male and female
participants were included in this study, we acknowledge that sex-specific differences in
substrate utilization may arise due to differences in circulating hormonal levels, adrenergic
activation, and body composition.19 Future research could explore these sex-specific effects more
comprehensively.
The evolution of the fitness movement in the United States, from Bernarr Macfadden's early
20th-century advocacy to the rise of social media fitness influencers, underscores the dynamic
landscape of fitness trends and the need to scrutinize popular programs. Platforms like YouTube
and TikTok, where 12-3-30 gained traction, amplify the importance of evaluating such programs
through scientific investigation. Our study found that 12-3-30 presents a unique metabolic
challenge compared to self-paced running. Participants expended the same amount of energy
more slowly, had a lower energy expenditure rate, and exhibited higher fat utilization during
12-3-30 than self-paced running. These findings lay a foundation for further research into the
metabolic responses to 12-3-30 and its practical applications. Future studies should also explore
perceptual responses to 12-3-30, as perceived exertion, enjoyment, and adherence are crucial for
long-term exercise adoption and effectiveness.
Acknowledgements
We thank all the participants who volunteered for this study and the staff of the Department of
Kinesiology and Nutrition Sciences at the University of Nevada, Las Vegas, for their support
and assistance. We also thank Jacob Baca and Setareh Zarei for their help collecting data.
The University of Nevada, Las Vegas is situated on the traditional homelands of Indigenous
groups, including the Nuwu or Nuwuvi, Southern Paiute People, descendants of the Tudinu, or
Desert People.
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