An Exploratory Study Comparing the Metabolic Responses between the 12-3-30 Treadmill Workout and Self-Paced Treadmill Running

Abstract

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.

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 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]).

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.

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 α = .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	40.56
Run	23.89 (2.81)	309.74 (59.70)	13.08 (2.60)	67.47	33.12

Data are reported as means (standard deviations). n = sample size; min = minute; kcal = kilocalorie; %C(1H1.O31 )= percent carbohydrate; %FAT = percent fat.

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 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.

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.