Effect of FATmax-Intensity Exercise on Body Composition and Cardiovascular Health in Overweight and Obese Individuals: A Systematic Review and Meta-Analysis

Abstract

Purpose

To determine the effects of exercising at maximal fat oxidation (FATmax) intensity on body composition, cardiorespiratory fitness, and metabolism outcomes in overweight and obese individuals through a systematic review and meta-analysis.

Methods

Randomized controlled trials (RCTs) were retrieved from PubMed, Web of Science, CNKI, and the Cochrane Library. Search terms included FATmax or maximal fat oxidation, obesity or overweight, BMI, , diastolic blood pressure (DBP), systolic blood pressure (SBP), triglycerides (TG), total cholesterol (TC), high-density lipoprotein cholesterol (HDL-C), low-density lipoprotein cholesterol (LDL-C) and homeostasis model assessment of insulin resistance (HOMA-IR). Risk of bias was assessed using Cochrane guidelines and the quality of evidence using GRADE. A random-effects model (Stata 16.0) calculated pooled mean differences for outcomes.

Results

18 RCTs were finally analysed. Compared to non-exercising controls, FATmax-intensity exercise improved (i) body composition, including reduced body weight (WMD = −4.43 kg, 95% CI: −5.11, −3.75), fat mass (WMD = −3.68 kg, 95% CI: −4.31, −3.06), waist circumference (WMD = −4.36 cm, 95% CI: −6.73, −1.99), and waist-to-hip ratio (WMD=−0.04, 95% CI: −0.05, −0.03); (ii) cardiorespiratory fitness, evidenced by increased (WMD = 3.89 mL/(kg·min), 95% CI: 3.04, 4.74), reduced SBP (WMD = −1.73 mmHg, 95% CI: −6.60, 3.15) and DBP (WMD = −2.10 mmHg, 95% CI: −3.70, −0.49); (iii) metabolism outcomes, such as reduced TG (SMD = −0.80, 95% CI: −1.24, −0.36), TC (SMD = −0.37, 95% CI: −0.72, −0.02), LDL-C (SMD = −0.44, 95% CI:–0.78, −0.10), increased (HDL-C) (SMD = 0.97, 95% CI: 0.64, 1.30) and improved HOMA-IR (SMD = −0.81, 95% CI: −1.44, −0.18). Subgroup analyses suggested that age, sex, and intervention characteristics (eg, duration and frequency) moderated these outcomes to varying degrees.

Conclusions

FATmax-intensity exercise confers beneficial effects on body composition, glucose and lipid metabolism, and cardiorespiratory fitness in populations with overweight and obesity. Despite outcome-specific variations and methodological heterogeneity warranting cautious interpretation, FATmax training represents a promising, individualized strategy for cardiometabolic health management.

Introduction

Obesity is a globally prevalent chronic metabolic disease associated with metabolic disorders such as insulin resistance, atherosclerosis, and hypertension.^1,2 By 2050, the number of adults with overweight and obesity worldwide is projected to reach nearly 3.8 billion.³ Beyond its clinical risks, obesity imposes a severe economic burden; economic models project its global impact will reach 3.29% of GDP by 2060, disproportionately affecting lower-resource nations.⁴ Individuals with overweight or obesity often present with excess body fat and metabolic health complications, such as insulin resistance, elevated LDL, and low HDL cholesterol, which collectively serve as significant cardiovascular risk factors. Exercise is a cornerstone strategy for managing these conditions. Aerobic exercise, in particular, is widely recommended due to its cardiovascular benefits and its capacity to promote high energy and fat expenditure. Generally, fat oxidation increases from low to moderate exercise intensities but declines as intensity progresses toward high levels.⁵ Maximal fat oxidation (FATmax) refers to the specific exercise intensity at which lipid oxidation reaches its peak. This point marks the optimal balance in substrate utilization, where the body relies predominantly on fat rather than carbohydrates for energy production. FATmax is typically determined using a graded exercise testing combined with indirect calorimetry, which measures oxygen consumption () and carbon dioxide production () to estimate substrate oxidation.^6,7 It should be noted that the exercise intensity eliciting FATmax varies considerably among individuals. Even within healthy populations, the percentage of corresponding to FATmax exhibits significant inter-individual variability.⁸ FATmax typically occurs at low to moderate intensities, approximately 30–65% of ,^9–11 depending on fitness level, metabolic flexibility, and physiological factors such as age and sex. However, because individuals with obesity generally reach their FATmax at a significantly lower intensity (30–46% of ),^12–14 standard exercise prescriptions developed for the general population may not be suitable for this demographic. Therefore, designing individualized exercise programs based on FATmax may be crucial for optimizing fat metabolism to improve weight management and metabolic health outcomes.

Current exercise prescriptions primarily include MICT, HIIT, and other conventional aerobic exercise protocols. MICT is safe and widely recommended, whereas HIIT is more time-efficient and effective for improving cardiorespiratory fitness. However, both are generally prescribed based on relative exercise intensity rather than individual metabolic responses. These prescriptions generally target cardiorespiratory load, which may consequently limit fat-loss efficiency for individuals with obesity.⁸ For example, while exercising at approximately 65% of may maximize fat oxidation and intramuscular lipid utilization in healthy adults, this intensity is often not optimal for those with obesity. Due to greater body mass and reduced exercise economy, these individuals typically possess a lower absolute . Consequently, exercising at 65% of may cause them to exceed their FATmax, shifting their primary fuel reliance toward glycogen.^11,15 Furthermore, exercising at ~65% in individuals with obesity may increase incomplete fatty acid oxidation,¹⁶ a process that can impair insulin signalling and exacerbate insulin resistance.^17–19 These metabolic disturbances may lead to hyperglycaemia and hyperinsulinemia, which in turn suppress fat utilization during exercise.²⁰ Collectively, these processes contribute to a reduced capacity for fat oxidation and a loss of metabolic flexibility in individuals with obesity,²¹ consistent with evidence showing that FATmax occurs at lower intensities in this group compared with individuals without obesity.²² It is important to note that body fat reduction is a thermodynamic process dictated by a chronic negative energy balance;²³ thus, maximizing fat oxidation during an acute exercise bout is not strictly necessary for overall weight loss. Nevertheless, FATmax may provide an individualized exercise target by accounting for interindividual differences in fat oxidation capacity. Furthermore, as a low-to-moderate-intensity approach, it may enhance tolerability and long-term adherence,^24,25 especially for those with a sedentary or low physical activity baseline, as reported in 11 out of 18 studies reviewed. In brief, conventional aerobic exercise may not fully account for inter-individual differences in fat oxidation capacity among individuals with overweight and obesity, highlighting the need for a systematic evaluation of how FATmax training impacts their fat utilization and metabolic health.

Compared to traditional exercise prescriptions, such as MICT and HIIT, it remains unclear whether exercise protocols tailored to an individual’s FATmax yield comparable or additional metabolic and cardiovascular benefits. However, most available evidence compares FATmax-intensity exercise with non-exercising controls, limiting conclusions regarding its comparative benefits over other exercise intensities. Notably, an earlier meta-analysis by Chávez-Guevara et al²⁶ examining the effects of FATmax-intensity exercise concluded that medium-term interventions (8 to 20 weeks) with a training volume of 120–360 minutes per week yielded beneficial effects for individuals with obesity. However, their review was limited to outcomes related to body weight, fat mass, and maximal oxygen uptake, largely overlooking critical changes in metabolic health, substrate utilization, and cardiovascular parameters. Furthermore, the influences of intervention characteristics (eg, duration and frequency) and population-specific factors (eg, age and sex) were not examined. Given the central role of glucose and lipid metabolism in metabolic diseases, and the fact that fat oxidation during exercise is modulated by factors such as fitness level and sex, a comprehensive evaluation of the effects of FATmax exercise in this demographic is warranted. Although the broad benefits of exercise for obesity management are well established, evidence regarding the optimal exercise prescription parameters for training remains limited.¹³ There is an absence of comprehensive meta-analyses assessing the precise effects of FATmax training, which currently restricts the development of evidence-based clinical guidelines. Therefore, through a systematic review and meta-analysis, the present study aims to investigate the effects of FATmax-intensity exercise on body composition, glucose and lipid metabolism, and cardiovascular health in populations with overweight and obesity, while also examining potential response differences across various subgroups. By synthesizing the current evidence, this study seeks to provide a robust foundation for informing optimal exercise prescription parameters, including frequency, duration, and session length, tailored specifically to this population.

Materials and Methods

Registration of the Systematic Review and Meta-Analysis Number

This study followed the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA).²⁷ This study protocol was registered in the PROSPERO platform under registration number CRD420251128232. The literature search end date was updated from August 1, 2025, to March 1, 2026, to incorporate the most recent evidence prior to the final analysis. The PRISMA 2020 checklist for this review is provided in Supplementary Materials (Table S1).

Search Strategy

A comprehensive literature search was performed using CNKI, PubMed, Web of Science, and the Cochrane Library. Both subject terms (MeSH/controlled vocabulary) and free-text keywords in Chinese and English were used in combination. The search covered all records from database inception to March 1, 2026. The complete search strategies for each database are provided in Supplementary Materials (Table S2).

Inclusion and Exclusion Eligibility Criteria

Eligibility criteria were defined using the PICOS framework. The inclusion criteria were as follows: (1) participants were overweight or obese individuals, without restrictions on gender, ethnicity, or age, (2) the intervention involved FATmax-intensity exercise, (3) the comparators were controlled (waiting list, no intervention), (4) the outcomes included at least one of the following indicators: body mass index (BMI), body weight, fat mass, fat-free mass (FFM), body fat percentage, systolic blood pressure (SBP), diastolic blood pressure (DBP), maximal oxygen consumption (), triglycerides (TG), total cholesterol (TC), high-density lipoprotein cholesterol (HDL-C), low-density lipoprotein cholesterol (LDL-C), and homeostasis model assessment of insulin resistance (HOMA-IR), (5) the study design was a randomized controlled trial (RCT). We excluded studies if they were: (1) studies for which the full text or complete data could not be obtained, (2) duplicate publications or studies with overlapping data, (3) dissertations, conference papers, review articles, or non-RCT studies.

Study Selection

Initial records were imported into EndNote X20 (Clarivate Analytics, Philadelphia, PA, USA) for duplicate removal. Two reviewers (Zhao G, Yan Y) independently screened titles and abstracts, followed by a full-text review of potentially eligible studies. Any disagreements were resolved by consulting a third reviewer (Khong TK).

Data Extraction and Synthesis

The data were extracted by two researchers, and any discrepancies were resolved by a third researcher. The extracted information included: (1) basic study characteristics: year of publication and author information; (2) study design details: study population, age, gender, and sample size of the intervention and control groups; (3) exercise intervention details: intervention duration, type of exercise, and session length; (4) outcome measures.

All data were reported as mean _change ± SD _change. When studies reported standard errors (SE) instead of standard deviations (SD), SD were calculated using the following formula:²⁸

If the SD of the change for the included outcomes were not explicitly reported in the study, they were calculated using the following formula:²⁸

where SD_pre and SD_post represent the standard deviations before and after the intervention, respectively, and Corr (pre, post) denotes the within-participant correlation coefficient. If this correlation was not reported, a default value of 0.5 was assumed.^28,29

Risk of Bias and Study Quality Assessment

The quality of the included studies was assessed using the Cochrane Risk of Bias 2 (RoB 2) tool,³⁰ covering seven domains: random sequence generation, allocation concealment, blinding of participants, blinding of investigators, selective reporting, and other sources of bias. Two researchers (Zhao G, Yan Y) independently conducted the assessment. In addition, the methodological quality and reporting of the exercise interventions were assessed using the TESTEX scale, which specifically evaluates exercise-related study design and reporting characteristics. Any disagreements were resolved through discussion with a third reviewer (Khong TK) until consensus was reached.

Statistical Analysis

Statistical analyses were performed using Stata (Version 16.0; StataCorp., College Station, TX, USA). The results of the meta-analysis will be summarized using forest plots. Effect sizes were expressed as weighted mean differences (WMDs) with 95% confidence intervals (CI) when the outcome measures are reported in the same units; otherwise, standardized mean differences (SMDs) will be calculated using Hedges’ g,³¹ including for outcomes without specific measurement units. To evaluate clinical and practical relevance, established minimum clinically important differences (MCID) were referenced for outcomes reported as WMD (eg, body weight, BMI, blood pressure, ), while a distribution-based threshold of half the baseline standard deviation (0.5×SD) was applied for SMD.³² MICD thresholds were preferentially derived from published anchor-based or clinically established estimates which are provided in Supplementary Materials (Table S3). For outcomes reported as SMD, effect sizes were interpreted according to Cochrane guidelines: <0.40 (small), 0.40 to 0.70 (moderate), > 0.70 (large).²⁸ Statistical heterogeneity among studies was assessed using the I² statistic. I² values of approximately 25, 50, and 75% were considered to represent low, moderate, and high heterogeneity, respectively, with I² >50% indicating substantial heterogeneity. Subgroup analyses were based on clinically relevant participant characteristics (eg, age and sex) and intervention characteristics (eg, intervention duration and exercise frequency) to explore potential effect modifiers and sources of clinical heterogeneity. Sensitivity analyses were performed using the leave-one-out method to evaluate the robustness of the results. Publication bias will be assessed using funnel plots and Egger’s regression test.^33,34

Publication Bias Assessment

Funnel plot and Egger’s linear regression test were employed for outcomes with at least 10 included studies.

Grading the Evidence

The certainty of evidence according to the Grading of Recommendations Assessment, Development and Evaluation (GRADE) tool,³⁵ with a range from very low to high certainty. Randomized-trial evidence was downgraded for risk of bias, inconsistency, indirectness, imprecision, or publication bias.

Results

Study Selection

A total of 541 records were initially identified through database searching, including CNKI (n = 20), PubMed (n = 108), Web of Science (n = 128), and Cochrane Library (n = 285). After removing duplicates (n = 32), 509 records remained. Following title and abstract screening, 455 records were excluded as irrelevant. Of the remaining 54 full-text articles assessed for eligibility, 32 were excluded based on PICOS criteria, 5 had incomplete data, and 3 were suspected of duplicate publication. Additionally, 4 eligible studies were identified through reference tracing. A total of 18 studies from 18 reports were included in the final analysis. The study selection process is illustrated in Figure 1.

Figure 1.

PRISMA flow diagram of the search process for studies.

Description of Included Studies

This study included 18 reports comprising 18 randomized controlled trials (RCTs), with a total of 744 participants—388 in the exercise groups and 356 in the control groups. Most interventions involved aerobic exercise (eg, running, jumping, and game-based activities), while three studies incorporated bodyweight training as part of a FATmax-based circuit protocol. The intervention durations ranged from 8 to 18 weeks, with a frequency of 3 to 5 sessions per week, and each session lasted 40 to 90 minutes. The studies defined obesity and overweight using BMI, body fat percentage and amongst youth, age-specific percentile (>95% in Chinese and >97% in Tunisian). FATmax was primarily quantified using indirect calorimetry and heart rate, with talk test and RPE used sparingly. Detailed characteristics of the interventions are summarised in Table 1.

Table 1.

Characteristics of the Studies Included in the Meta-Analysis

NO.	Study; Year; Country	Sample size; Age; Gender	Definition of Overweight/Obesity	FATmax Verification/Monitoring Method	Exercise Type	Training Volume (Duration, Frequency, Intensity)	Outcomes
1	Ben Ounis 2008a; Tunisia36	Total n=12, female Exercise: n=6, age: 13.0± 0.4 Control: n=6, age: 13.4± 0.2	BMI greater than 97th percentile	Indirect calorimetry/HR monitoring	Running, jumping and playing with a ball	90 minutes per session, 4 times per week for 8 weeks, NA	(1) (2) (4) (7) (8) (9) (10) (11) (13)
2	Ben Ounis 2008b; Tunisia37	Total n=16, male Exercise: n=8, age: 13.3 ± 0.7 Control: n=8, age: 13.1 ± 0.7	BMI greater than 97th percentile	Indirect calorimetry/HR monitoring	Running, jumping and playing with a ball	90 minutes per session, 4 times per week for 8 weeks, NA	(1) (2) (4) (5) (7) (8) (9) (10) (11) (13) (14)
3	Ben Ounis 2009; Tunisia38	Total n=36, males and females Exercise: n=18, age: 13.1 ± 0.9 Control: n=18, age: 13.3 ± 0.6	BMI greater than 97th percentile	Indirect calorimetry/HR monitoring	Running, jumping	90 minutes per session, 4 times per week for 8 weeks, NA	(1) (2) (4) (5) (13) (14)
4	Tan 2012; China39	Total n=48, female Age range: 20–23 Exercise: n=29, Control: n=19	BMI >25 kg/m2, BF% >30%	Indirect calorimetry/HR monitoring	Running	60 minutes per session, 5 times per week for 8 weeks, 134± 3/bpm	(1) (2) (3) (4) (5) (6) (8) (9) (12) (15)
5	Wang 2015; China40	Total n=26, female Exercise: n=15, age: 50.7 ± 5.5 Control: n=11, age: 49.7 ± 7.9	BMI >25 kg/m2, BF% >30%	Indirect calorimetry/HR monitoring	Walking, running	60 minutes per session, 5 times per week for 10 weeks, 106± 8/bpm	(1) (2) (3) (4) (5) (6) (12)
6	Tan 2016; China41	Total n=24, male Exercise: n=11, age: 9.0±0.9 Control: n=13, age: 9.4±1.3	BMI >95th age-specific percentile	Indirect calorimetry/HR monitoring	Walking, running, and ball game	60 minutes per session, 5 times per week for 10 weeks, 140 ± 6/bpm	(1) (2) (4) (5) (6)
7	Huang 2018; China42	Total n=32, male Exercise: n=16, age: 20.7 ± 1.1 Control: n=16, age: 20.3 ± 1.1	BMI≥25 kg/m2	Indirect calorimetry/Counting Talk Test	Walking, running	40–60 minutes per session, 3–5 times per week for 12 weeks, 51.5%±7.3%	(1) (2) (3) (4) (6) (8) (9) (10) (11) (12)
8	Cao 2019; China43	Total n=28, female Exercise: n=13, age: 63.8 ± 5.9 Control: n=15, age: 64.0 ± 4.6	BMI >25 kg/m2	Indirect calorimetry/HR monitoring	Walking, jogging	60 minutes per session, 3 times per week for 12 weeks, 101 ± 9/bpm, 34.5 ± 8.0%	(1) (2) (3) (4) (5) (6) (8) (10) (11) (12) (13)
9	Guo 2021; China44	Total n=120, male Age range: 18~22 Exercise: n=60, Control: n=60	Male with BF% ≥25%	Indirect calorimetry/HR monitoring	Running, walking, jumping	60 minutes per session, 5 times per week for 12 weeks, 48.66%±7.64 - 53.21%±8.23	(2) (3) (6) (12) (15)
10	Yang 2021; China45	Total n=56, males and females Exercise: n=28, age: 21.0±1.1 Control: n=28, age: 21.2±0.7	Male with BF%: 20–30%/ Female with BF%: 30–40%/ BMI in 24–30 kg/m2	Indirect calorimetry/HR monitoring	Running	90 minutes per session, 4 times per week for 12 weeks, 126±13/bpm	(1) (2)
11	Zhang 2021; China46	Total n=30, female Age range: 20~30 Exercise: n=15, Control: n=15	BMI≥28 kg/m2	Indirect calorimetry/HR monitoring	Walking, running	40–60 minutes per session, 4 times per week for 12 weeks, NA	(1) (2) (4) (5) (6)
12	Peng 2022; China47	Total n=50, males and females Exercise: n=25, age: 21.3±1.0 Control: n=25, age: 21.8±0.8	Male with BF%:>20%/ Female with BF%:>30%/ BMI >24 kg/m2	Indirect calorimetry/HR monitoring	Running	90 minutes per session, 4 times per week for 12 weeks, 124±16/bpm	(1) (2) (7) (8) (10) (11)
13	Xiao 2022; China48	Total n=66, 24 males and 42 females Exercise 1: n=22, age: 20.8±1.1 Exercise 2: n=22, age: 20.8±1.8 Control: n=22, age: 20.9±1.7	Male with BF%:>20%/ Female with BF%:>30%/ BMI >24 kg/m2	Indirect calorimetry/HR monitoring	Running, bodyweight training	60 minutes per session, 4 times per week for 10 weeks, 128±16-135±20/bpm	(1) (2) (3) (7)
14	Lu 2023; China49	Total n=25, male Exercise: n=12, age: 63.54±3.87 Control: n=13, age: 62.82±3.56	Exercise:25.37 ± 2.56 Control 25.40 ± 2.31 BMI reported; diagnostic criterion not specified	Indirect calorimetry/HR monitoring and RPE	Running, bodyweight training	70 minutes per session, 4 times per week for 16 weeks, 106.31±13.1/bpm, 42.03%±6.25	(1) (2) (3) (4) (6) (8) (9) (10) (11) (12) (13) (14) (15)
15	Yang 2023; China50	Total n=54, 32 males and 22 females Exercise: n=27, age: 21.3 ± 1.0 Control: n=27, age: 21.8 ± 0.8	BMI ≥ 25 kg/m2,	Indirect calorimetry/HR monitoring	Jogging	60 minutes persession, 4 times per week for 12 weeks, 124 ± 16–127 ± 19/bpm	(1) (2) (3)
16	Lin 2024; China51	Total n=36, 9 males and 27 females Exercise: n=19, age: 51.79± 10.01 Control: n=17, age: 46.81 ± 15.46	BMI ≥ 24.0 kg/m2	Indirect calorimetry/HR monitoring	Brisk walking, jogging	40–60 minutes per session, 5 times per week for 12 weeks, NA	(1) (3) (4)
17	Yang 2025; China52	Total n=48, females Exercise: n=24 Control: n=24	BMI >28 kg/m2	Indirect calorimetry/HR monitoring	Running	60 minutes per session, 3 times per week for 12 weeks, 50.39%, 135.67/bpm	(1) (2) (3) (15)
18	Lu 2026; China53	Total n=37, males Exercise: n=18, age: 64.38± 4.73 Control: n=19, age: 63.79 ± 5.27	Exercise:26.21 ± 2.46 Control 25.88 ± 2.36 BMI reported; diagnostic criterion not specified	Indirect calorimetry/HR monitoring and RPE	Running, bodyweight training	60 minutes per session, 4 times per week for 18 weeks, 106.31±13.1/bpm, 42.57%± 5.83	(1) (2) (3) (5) (12) (13) (14) (15)

Notes: Data are presented as mean ± standard deviation. (1) Weight; (2) Body mass index; (3) Body fat percentage; (4) Fat mass; (5) Fat-free mass; (6); (7) Homeostatic model assessment of insulin resistance; (8) Triglycerides; (9) Total cholesterol; (10) High-density lipoprotein cholesterol; (11) Low-density lipoprotein cholesterol; (12) Blood Pressure; (13) Waist circumference; (14) Hip circumference; (15) Waist-to-hip ratio; HR: heart rate; RPE: Rating of perceived exertion.

Risk of Bias and Study Quality Assessment

According to the Cochrane Risk of Bias 2.0 tool, in the domain of Randomization process, 94.4% of studies were judged as having “some concerns”, and almost all studies failed to report details of allocation concealment. For Deviations from intended interventions, 66.6% of studies were assessed as low risk, 16.7% as “some concerns”, while 16.7% were rated as high risk due to participant dropout or training absences. In the domain of Missing outcome data, 83.3% of studies were considered low risk. For the Measurement of the outcome, all studies (100%) were judged as low risk. Regarding the Selection of the reported results, 22.2% of studies were rated as “some concerns” because they did not report ethical approval. Overall, 83.3% of the included studies were rated as “some concerns”, while 16.7% were assessed as high risk. Details of the risk of bias assessment are presented in Figure 2.

Figure 2.

Risk of bias assessment.

The methodological quality and reporting of the included exercise interventions were assessed using the TESTEX scale. Across the 18 included studies, total TESTEX scores ranged from 7 to 12, indicating generally good methodological quality and reporting (Supplementary Materials and Table S4). However, several criteria were infrequently satisfied, particularly those related to randomization, allocation concealment, blinding, and certain aspects of intervention monitoring and reporting. These limitations may have contributed to methodological heterogeneity across the included trials.

Meta-Analysis

Figure 3 shows the meta-analysis of changes in body composition, cardiovascular, lipid profile, cardiorespiratory, and metabolic outcomes.

Figure 3.

Forest plot of the effects of FATmax-intensity exercise on body composition and metabolic outcomes. In the forest plots, for variables where a reduction is clinically beneficial (eg, body weight, BMI, fat mass, LDL-C), values < 0 indicate a favourable effect of FATmax training. Conversely, for variables where an increase is beneficial (eg,, HDL-C), values > 0 indicate a favourable effect of FATmax training.

Abbreviations: WMD, weighted mean difference; Hedges’ g, the effect size indicator used in the pooled; CI, confidence interval; I², heterogeneity statistic; GRADE, grading of recommendations assessment, development and evaluation; BMI, body mass index; WHR, waist-to-hip ratio; HDL-C, high-density lipoprotein cholesterol; LDL-C, low-density lipoprotein cholesterol; HOMA-IR, homeostatic model assessment of insulin resistance.

Impact of FATmax Exercise on Body Composition Outcomes

• (1)Across 17 studies, a total of 624 participants provided body weight data. A random-effects model meta-analysis showed a significant reduction in weight following FATmax-intensity exercise (WMD = –4.43 kg, 95% CI (–5.11, –3.75), I² = 0%, p < 0.001; Supplementary Materials: Figure S1).
• (2)Across 17 studies, a total of 708 participants provided BMI data. A random-effects model meta-analysis demonstrated a significant reduction in BMI (WMD = –1.74, 95% CI (–1.93, –1.56), I² = 0%, p < 0.001; Supplementary Materials: Figure S1).
• (3)Across 12 studies, a total of 544 participants provided body fat percentage data. A random-effects model meta-analysis revealed a significant reduction in body fat percentage (WMD = –3.73 %, 95% CI (–4.29, –3.16), I² = 5.7%, p < 0.001; Supplementary Materials: Figure S1).
• (4)Across 11 studies, a total of 313 participants provided fat mass data. A random-effects model meta-analysis demonstrated a significant decrease in fat mass (WMD = –3.68 kg, 95% CI (–4.31, –3.06), I² = 0.6%, p < 0.001; Supplementary Materials: Figure S1)
• (5)Across 8 studies, a total of 245 participants provided fat-free mass data. A random-effects model meta-analysis showed no significant effect of FATmax-intensity exercise on fat-free mass (WMD = –0.36 kg, 95% CI (–0.98, 0.26), I² = 0%, p = 0.252; Supplementary Materials: Figure S1).
• (6)Six studies reported waist circumference, including 154 participants. The random-effects meta-analysis showed a significant reduction in waist circumference (WMD=−4.36 cm, 95% CI (−6.73, −1.99, I²=0%, p < 0.001; Supplementary Materials: Figure S1).
• (7)Four studies reported hip circumference, including 114 participants. The random-effects meta-analysis showed no significant effect on hip circumference (WMD=−2.21 cm, 95% CI (−4.61, 0.19, I²=0%, p =0.071; Supplementary Materials: Figure S1).
• (8)Five studies reported waist-to-hip ratio (WHR), including 278 participants. The random-effects meta-analysis showed a statistically significant reduction in WHR (WMD=−0.04, 95% CI (−0.05, −0.03, I²=0%, p <0.001; Supplementary Materials: Figure S1).

Impact of FATmax Exercise on Cardiovascular Outcomes

Across 7 studies, a total of 316 participants provided blood pressure data. For SBP, the random-effects model meta-analysis indicated WMD = −1.73 mmHg, 95% CI (−6.60, 3.15), I² = 60.1%, p = 0.488; Supplementary Material: Figure S2. For DBP, WMD = −2.10 mmHg, 95% CI (−3.70, −0.49), I² = 5.8%, p = 0.011; Supplementary Material: Figure S2.

Impact of FATmax Exercise on Lipid Profile Outcomes

• (1)Across 7 studies, a total of 211 participants provided TG data. The random-effects model indicated SMD = –0.80, 95% CI (–1.24, –0.36), I² = 53.5%, p < 0.001; Supplementary Materials: Figure S3.
• (2)Across 5 studies, a total of 133 participants provided TC data. The random-effects model indicated SMD = –0.37, 95% CI (–0.72, -0.02), I² = 0%, p = 0.036; Supplementary Materials: Figure S3.
• (3)Across 6 studies, a total of 163 participants provided HDL-C data. The random-effects model indicated SMD = 0.97, 95% CI (0.64, 1.30), I² = 0%, p < 0.001; Supplementary Materials: Figure S3.
• (4)Across 6 studies, a total of 163 participants provided LDL-C data. The random-effects model indicated SMD = –0.44, 95% CI (–0.78, -0.10), I² = 11.1%, p = 0.011; Supplementary Materials: Figure S3.

Impact of FATmax Exercise on Cardiorespiratory and Metabolic Outcomes

• (1)Eight studies reported VẋO₂max, including 333 participants. The random-effects meta-analysis showed a significant improvement in VẋO₂max WMD=3.89 mL/(kg·min), 95% CI (3.04, 4.74), I²=0%, p <0.001; Supplementary Materials Figure S4.
• (2)Four studies reported HOMA-IR, including 144 participants. The random-effects meta-analysis showed a significant reduction in insulin resistance SMD=−0.81, 95% CI (−1.44, −0.18), I²=64.6%, p =0.012; Supplementary Materials: Figure S4.

Publication Bias

Funnel plot and Egger’s linear regression test were employed for outcomes with at least 10 included studies (BMI, body weight, body fat percentage, and fat mass). The funnel plot (Figure 4) showed generally symmetrical distributions, except for the body fat percentage outcome, which showed a slight asymmetry that may indicate potential publication bias or small-study effects. However, the results of Egger’s tests for these four outcomes (P > 0.05) indicated no significant publication bias (Table 2). Overall, the risk of publication bias was considered low, and the findings were reliable.

Figure 4.

Funnel plot of the effects of FATmax-intensity exercise on body composition (studies ≥10). (A) Weight; (B) BMI; (C) body fat percentage; (D) fat mass. Heterogeneity is quantified by the I² statistic. p-values indicate the statistical significance of the subgroup effects.

Abbreviation: CI, Confidence Intervals.

Table 2.

Egger’s Linear Regression for Publication Bias

Outcomes	β	SE	t	p>|t|	95% CI
Weight	−0.136	0.194	−0.70	0.493	(−0.548, 0.276)
BMI	0.031	0.282	0.11	0.913	(−0.567, 0.630)
Body fat percentage	0.264	0.487	0.54	0.598	(−0.807, 1.335)
Fat mass	0.571	0.406	1.41	0.193	(−0.347, 1.490)

Abbreviations: SE, standard error; CI, confidence interval.

Subgroup Analysis

Subgroup analyses were conducted to explore potential differences in the effects of FATmax-intensity exercise across participant and intervention characteristics (Supplementary Material: Table S5). Analyses were performed only when at least two studies were available for a given category. Participants were stratified by sex (male, female), age (<18 years, 18–45 years, ≥45 years), exercise frequency (3, 4, or 5 sessions/week), intervention duration (8, 10, or ≥12 weeks), and session length (40–60 or >60 minutes). Overall, significant reductions in body weight and BMI were observed primarily among adults (18–45 years) and older adults (≥45 years), while improvements in waist circumference and DBP were more consistently observed in older adults. Youth (<18 years) showed improvements in metabolic outcomes, including HOMA-IR, TG, and LDL-C. Intervention duration, training frequency, and session length showed outcome-specific effects, though no single pattern was consistent across outcomes. Among metabolic outcomes, HDL-C showed the most consistent improvements, with significant effects across all evaluated age groups, intervention durations, and session lengths, whereas effects on TG, TC, LDL-C, and HOMA-IR varied across subgroups. These findings should be interpreted cautiously given the limited number of studies available for some subgroup comparisons and the substantial heterogeneity observed in several analyses.

Sensitivity Analysis

A sensitivity analysis was conducted to assess the influence of individual studies on the overall pooled results (Supplementary Material: Figures S5–Figure S8). After sequentially excluding each study, the pooled effect sizes remained robust and unchanged for most outcomes, except for TC, SBP, DBP and HOMA-IR. For SBP, exclusion of Huang (2018) yielded a significant effect (WMD = −4.57 mmHg, 95% CI: −7.04 to −2.10). For DBP, exclusion of Guo (2021) resulted in a nonsignificant effect (WMD = −1.91 mmHg, 95% CI: −4.04 to 0.21). For TC, exclusion of Tan (2012) (SMD = −0.20, 95% CI: −0.63 to 0.23) altered the result (SMD = −0.37, 95% CI: −0.72, −0.02). Exclusion of Xiao (2022) slightly attenuated the pooled effect for HOMA-IR (SMD=−0.55, 95% CI: −1.10, 0.00), and the confidence interval touched the line of no effect. These findings indicate that the overall results were generally stable, but several indicators were sensitive to the inclusion of specific studies, with substantial changes in heterogeneity observed. Thus, caution is needed when interpreting the results for these outcomes.

Grading the Evidence

Although the certainty of evidence for some outcomes was downgraded due to inconsistency and imprecision, the overall findings were generally consistent. The pooled analyses indicate that FATmax-intensity exercise has beneficial effects on body weight, BMI, fat mass, waist circumference, WHR, DBP, blood lipids (TG, TC, HDL-C, LDL-C), HOMA-IR, and in overweight and obese populations, with the certainty of evidence ranging from moderate to high. Fat-free mass and hip circumference showed no significant effects, with moderate-certainty evidence, whereas SBP remained uncertain with very low certainty of evidence. The details are provided in Supplementary Material (Table S6).

Discussion

To our knowledge, this review is to provide empirical evidence regarding the impact of FATmax-intensity exercise on body composition, metabolic health (glucose and lipid profiles), and cardiovascular health ( and blood pressure) in populations with overweight and obesity. Our findings reveal that exercising at FATmax intensity significantly improves body composition measures in these groups, driving reductions in body weight, BMI, body fat percentage, fat mass, waist circumference, and WHR. Additionally, this exercise intensity reduces DBP, TG, TC and LDL-C levels, while improving insulin resistance, HDL-C levels, and maximal oxygen uptake. However, these collective effects appear to be influenced by several moderating factors, including age, sex, and exercise prescription variables (eg, frequency and duration). This review provides robust evidence that exercising at FATmax intensity is a highly beneficial strategy for optimizing fat metabolism and improving weight management outcomes among individuals with overweight and obesity.

Body Composition Responses to FATmax: Benefits and Physiological Constraints

The present study found that for populations with overweight and obesity, exercising at FATmax intensity maximizes lipid oxidation and leads to significant reductions in fat mass. This finding is consistent with a previous review by Chávez-Guevara.²⁶ Collectively, the included studies in this study reported estimated fat mass reductions of 0.7 to 5.8 kg, clearly demonstrating that exercising at FATmax can effectively reduce peripheral body fat. While moderate-to-vigorous aerobic exercise is also associated with improvements in body weight, waist circumference, and body fat,^54–56 our meta-analysis demonstrated that training at FATmax, despite representing a relatively low exercise intensity, is sufficient to improve fat-related outcomes (eg, BMI, fat mass, body fat percentage, and WHR) in individuals with obesity, underscoring its efficacy for body composition management. Previous meta-analyses have found modest improvements in body composition with both HIIT/SIT and MICT, noting reductions in BF% of 1.26 and 1.48% and in fat mass of 1.38 kg and 0.91 kg, respectively.⁵⁷ Compared with non-exercise controls, HIIT has been associated with reductions of approximately 1.53–3.05% in BF% and 1.86 kg in fat mass, whereas MICT has generally achieved reductions in BF% ranging from 2.05 to 2.16%.^58,59 In comparison, our pooled analysis demonstrated substantial improvements relative to non-exercise controls, with reductions in body weight (−4.43 kg), fat mass (−3.68 kg), and BF% (−3.73%), all of which exceed recognized MCID thresholds for obesity management. Although direct comparisons between FATmax training and other exercise modalities cannot be definitively made across separate meta-analyses, these findings suggest that FATmax training can achieve clinically meaningful improvements in body composition comparable to those reported for conventional exercise interventions.

These reductions in fat mass, body weight, and BMI are evidently more pronounced in adults and older individuals compared to adolescents. This discrepancy may be related to differences in baseline metabolic rates and energy balance patterns across life stages.^60,61 With advancing age into adulthood and beyond, changes in body composition, specifically reductions in lean mass (particularly organ and skeletal muscle mass) and the metabolic rate per unit of tissue,⁶² contribute to declines in both basal and total energy expenditure.^60,63 In the context of this review, adults and older individuals experiencing declining basal metabolism are likely to show more significant improvements in body weight and BMI when subjected to the additional energy expenditure induced by FATmax-intensity exercise, compared to adolescents.

Although FATmax-intensity exercise had no significant effect on hip circumference, it did significantly reduce both waist circumference and WHR. A plausible explanation for this is the predominance of male participants in the included studies. At similar levels of weight loss, men tend to exhibit greater reductions in waist circumference but smaller changes in hip circumference, resulting in a more pronounced decrease in WHR.⁶⁴ Furthermore, when comparing intervention protocols and outcomes, longer interventions appeared to be associated with larger reductions in waist circumference, consistent with previous research.⁵⁶ However, this observation should be interpreted cautiously, as dose-response analyses were not conducted in the current study.

Conversely, exercising at FATmax intensity does not induce improvements in FFM. FATmax typically corresponds to low-to-moderate intensity exercise (30–65% ); while this is optimal for fat oxidation, it provides far weaker anabolic stimulation for muscle protein synthesis compared with high-intensity or resistance training.^60,65 Moreover, participants with overweight or obesity often exhibit anabolic resistance and impaired skeletal muscle adaptive responses,⁶⁶ which may further limit gains in FFM during FATmax training.

It also appears that changes in body weight indices are associated with age and exercise prescription parameters. Specifically, intervention duration and exercise frequency are closely tied to fat mass outcomes, with higher training frequency serving to stabilise individual responses and reduce variability in fat mass reduction. Interestingly, while intervention durations lasting 8 weeks or ≥12 weeks effectively reduced fat mass, those lasting 10 weeks did not yield significant effects. This discrepancy is likely a statistical artifact driven by the specific characteristics of the included studies. Notably, the pooled effect for 8-week interventions was heavily influenced by Tan (2012) (which carried a large weight of 74.34%), while the ≥12-week outcome was heavily bolstered by Zhang (2021) (which reported a large effect size, WMD = −5.80 kg). Therefore, these temporal findings should be interpreted with caution as statistical phenomena rather than strict physiological timelines or adaptation plateaus. Future dose-response studies are required to confirm the optimal intervention duration.

In summary, these results suggest that FATmax-intensity exercise effectively promotes lipid oxidation, reduces body weight and fat mass, and improves body shape in individuals with obesity. These benefits are influenced by exercise frequency, duration, and population characteristics, with adults and older individuals showing greater improvements than adolescents due to metabolic differences. However, FATmax-intensity exercise does not appear to improve FFM, likely due to insufficient anabolic stimulation and the underlying metabolic constraints of individuals with overweight and obesity. While reductions in waist circumference and WHR were observed, the inconsistent changes in hip circumference may reflect sex-specific fat distribution patterns. Overall, the findings reinforce the effectiveness of FATmax-intensity exercise for reducing fat mass while acknowledging its limitations regarding muscle mass accretion.

Does Training at FATmax Affect Cardiovascular Health?

Individuals with overweight or obesity typically exhibit a lower than normal-weight controls, which can significantly limit their endurance capacity.⁶¹ The present study found that FATmax-intensity exercise significantly improved . Furthermore, training at this intensity has been shown to improve skeletal muscle adaptations and metabolic flexibility, such as increased mitochondrial content and capillarization.^62,63 These adaptations can improve metabolic efficiency, delay the onset of fatigue, and increase exercise tolerance, serving as the primary drivers for enhancement in this population.^62,67 Subsequently, this enhanced oxygen uptake increases fat oxidation and energy expenditure,⁶⁸ supporting further improvements in body composition and physical activity capacity.

Interestingly, this review also reveals that exercising at FATmax reduces DBP but not SBP in the primary analysis. In individuals with overweight or obesity, elevations in DBP primarily reflect functional changes in peripheral vascular resistance during the early stages of metabolic and vascular dysfunction,^69–71 which can be reversed through exercise.^72–74 Low-to-moderate intensity exercise is linked to favourable metabolic and vascular changes related to DBP,^{48,50,75–78} particularly following long-term training.^79,80 FATmax training is typically performed at a low-to-moderate intensity, a range that has been shown to enhance endothelial function by increasing nitric oxide (NO) bioavailability through shear stress-mediated mechanisms.^74,81 Increased NO bioavailability could augment endothelium-dependent vasodilation, thereby reducing DBP, while concurrently avoiding the excessive oxidative stress commonly associated with high-intensity exercise, which can impair NO bioavailability.^75,82

Furthermore, the pooled effect for SBP was highly sensitive to specific intervention protocols. As demonstrated by the sensitivity analysis, the SBP results were heavily driven by the study conducted by Huang.⁴² Removal of this study during the leave-one-out analysis resulted in a significant pooled effect, eliminated heterogeneity, and indicated that FATmax can effectively reduce SBP. The Huang⁴² study was the only included trial that reported an increase in SBP (WMD = 7.00 mmHg, 95% CI: 0.71 to 13.29). An improvement in SBP following FATmax training is physiologically expected and can be attributed to enhanced central arterial compliance via NO-dependent vasodilation, which improves arterial elasticity, and optimized autonomic regulation through increased parasympathetic activity, which lowers resting heart rate.^83–86

Collectively, FATmax-intensity exercise confers beneficial effects on cardiovascular health, reflected by improvements in and blood pressure indices, while simultaneously promoting weight and fat loss in populations with overweight and obesity. In the long term, these cardiovascular improvements can enhance blood perfusion and skeletal muscle glucose uptake, which in turn reduces the risk of obesity-related metabolic disorders.

How Do Metabolic Changes at FATmax Affect Individuals with Overweight and Obesity?

FATmax-intensity exercise is associated with significant improvements in glucose and lipid metabolism, evidenced by reductions in TG, TC, LDL-C and HOMA-IR, alongside increases in HDL-C. These changes indicate highly favourable metabolic adaptations. Hypertriglyceridemia is a core feature of metabolic syndrome and a major contributor to cardiovascular risk in individuals with obesity.^87–89 Chronic elevations in TG and ectopic lipid accumulation induce lipotoxicity,⁹⁰ leading to endothelial dysfunction, accelerated atherosclerosis, and impaired insulin signalling,^91,92 thereby increasing the risk of cardiovascular disease and type 2 diabetes mellitus.^92,93 Notably, FATmax-intensity exercise reduces TG and maximizes fatty acid oxidation, which alleviates lipotoxicity, promotes the utilization of ectopic fat stores, and improves mitochondrial function.^94,95 This enhancement in oxidative capacity allows for the efficient utilization of intramyocellular lipids.^96,97 Collectively, these adaptations facilitate the restoration of insulin sensitivity,⁹⁶ aligning with the significant decrease in HOMA-IR observed in the present study. However, this finding should be interpreted with caution. Our sensitivity analysis revealed that the significant improvement in HOMA-IR was heavily driven by a study (Xiao, 2022). Notably, this specific trial arm employed a combined intervention of aerobic and resistance training, whereas the other arm utilized aerobic exercise alone. This suggesting that the addition of resistance training might enhance skeletal muscle glucose disposal and contribute to improvements in insulin sensitivity. Crucially, the recovery of insulin sensitivity extends beyond glucose homeostasis; it reinstates insulin-mediated vasodilation, a key mechanism contributing to the regulation of blood pressure and vascular tone.^98,99

In addition, increases in HDL-C not only indicate enhanced reverse cholesterol transport but also confer substantial cardiovascular protection.^100,101 The favourable modulation of this lipid profile is thought to involve the upregulation of endothelial nitric oxide synthase (eNOS) and NO bioavailability. This serves to preserve endothelial function and reduce inflammation while inhibiting vascular smooth muscle cell proliferation and platelet aggregation, ultimately mitigating the risk of restenosis.^102,103 These adaptive changes are critical for ameliorating atherosclerosis and maintaining hemodynamic stability.

TC reflects the overall cholesterol content in the blood, while LDL-C constitutes the largest proportion of this total and is the primary contributor to atherosclerotic plaque formation.^104,105 It should be noted that the pooled effects for TC (Tan, 2012) were not robust and were highly sensitive to the exclusion of this specific study (Figure S7). Differences in supervision and exercise protocols across trials may have limited participant adherence and intensity control, contributing to the observed heterogeneity.^106,107 Together with the increase in HDL-C, these changes are expected to improve composite lipid measures and atherogenic lipid indices, including non-HDL cholesterol and the HDL-C/LDL-C and TC/HDL-C ratios. These indices are widely used to predict cardiovascular events, assess atherosclerotic burden^108,109 and serve as predictive markers for insulin resistance,¹¹⁰ as they provide a more comprehensive assessment of cardiometabolic risk than individual lipid parameters.

Overall, while the specific effects of FATmax-intensity exercise on TC remain somewhat inconclusive based on the primary analysis, its highly favourable effects on TG, HDL-C, LDL-C and insulin sensitivity are well-supported by the present evidence. These metabolic responses underscore the significant potential benefits of FATmax exercise for improving body composition and reducing cardiometabolic risk in individuals with obesity.

Practical Applications

The present findings demonstrate that FATmax-intensity exercise is an effective intervention for improving weight management, metabolic health, and cardiovascular function in individuals with obesity. To our knowledge, this is the most comprehensive meta-analysis to synthesize the effects of FATmax intensity on metabolism outcomes and blood pressure, extending the literature well beyond simple weight-loss outcomes. The results establish FATmax training as a highly viable non-pharmacological and non-invasive intervention strategy tailored to this population.

While other exercise modalities, such as HIIT, may demonstrate superior efficacy in improving cardiorespiratory fitness and specific cardiometabolic risk factors, including HOMA-IR and lipid profiles,¹¹¹ this study confirms that FATmax-intensity exercise still yields significant, clinically relevant metabolic and cardiovascular benefits. Compared with conventional prescriptions, FATmax is individualized according to each participant’s maximal fat oxidation rate, thereby accounting for inter-individual metabolic variability and offering a practical approach to exercise prescription. FATmax is typically determined using a graded exercise test combined with indirect calorimetry, after which the corresponding individualized heart rate can be used to monitor and maintain the prescribed intensity during subsequent training sessions. Indeed, previous FATmax interventions have successfully utilised heart rate monitoring to maintain the prescribed exercise intensity.¹¹² Evidence indicates that moderate-intensity exercise is associated with better long-term adherence than vigorous-intensity exercise, while lower exercise intensities generally elicit more positive affective responses that predict future physical activity participation.^24,25,113 In sedentary individuals with overweight, peak fat oxidation has been shown to occur during moderate-intensity walking (approximately 5.0–5.5 km/h), supporting the feasibility of translating individually determined FATmax into practical exercise prescriptions.¹¹⁴ Consequently, these findings suggest that FATmax training, which is typically performed at a low-to-moderate intensity, represents a highly accessible, safe, and tolerable exercise modality. These characteristics confer strong practical feasibility and substantial potential for broader implementation in clinical practice and community settings. Nevertheless, several challenges remain before FATmax-guided exercise can be widely implemented. First, although FATmax training itself is highly feasible for individuals with low fitness levels, accurate identification of the individual FATmax zone currently requires a graded exercise test combined with indirect calorimetry. The reliance on laboratory-based equipment substantially limits its accessibility and widespread clinical implementation. Future research must prioritize developing accessible field tests to estimate FATmax accurately, thereby facilitating the broader translation into routine obesity management. Furthermore, although FATmax training produces clinically meaningful improvements in body composition and metabolic health, maintaining these benefits remains challenging. Exercise cessation often leads to weight regain and the recurrence of metabolic abnormalities, a pattern similar to that observed following bariatric surgery.¹¹⁵ These findings emphasize the importance of translating FATmax interventions into sustainable, lifelong physical activity habits to preserve long-term metabolic health.

Limitations and Recommendations

A critical consideration when interpreting our findings is the substantial methodological heterogeneity across the included trials, particularly regarding exercise intensity monitoring and training protocols. Although FATmax was initially determined using indirect calorimetry, most studies subsequently relied on -matched heart rate to maintain the prescribed intensity during training. In deconditioned individuals with overweight or obesity, heart rate may not precisely reflect metabolic intensity due to substantial inter-individual and intra-individual variability in cardiovascular responses. Furthermore, the evidence base was predominantly derived from Asian adults using Asian BMI classification, alongside some evidence from adolescents in Asian and North African, who were classified using age-specific BMI criteria. Although age- and sex-based subgroup analyses were conducted, these demographic differences may contribute to clinical heterogeneity. Consequently, isolating the true efficacy of FATmax training remains challenging.

Beyond the primary literature, this study has several limitations that should be acknowledged. First, moderate to high heterogeneity was observed across some outcome measures. This variability is likely attributable to differences in participant characteristics and intervention protocols among the included studies, which may limit the generalizability of these findings. Second, in this review, we attempted to explore the dose-response relationship of FATmax training through subgroup analyses, such as training frequency. However, these results must be interpreted with caution. Because total weekly training volume was not strictly matched across the included trials, the “frequency subgroups” most likely reflect the effect of total weekly exercise dose rather than the isolated physiological stimulus of frequency itself. Furthermore, limited data precluded a robust dose-response meta-analysis of FATmax training. While ACSM guidelines¹¹⁶ emphasise that total energy expenditure drives fat loss, current FATmax trials lack isocaloric (volume-matched) designs and exhibit high volume heterogeneity. Therefore, it is currently impossible to isolate whether observed benefits stem from the specific FATmax intensity or merely total caloric expenditure. Future trials must employ isocaloric designs to rigorously determine the true dose-response effects. Third, due to the limited number of studies reporting specific metabolic variables (eg, HOMA-IR), comprehensive correlation analyses could not be conducted. Finally, the majority of the included trials did not adequately report the participants’ daily behaviours, such as sedentary time and other unprescribed physical activity, or their concurrent dietary habits. These unmeasured variables may have significantly influenced body composition, metabolic parameters, and cardiorespiratory outcomes, but they could not be accounted for in our pooled analyses. Finally, a primary limitation is that the included RCTs mainly compared FATmax to non-exercising controls rather than to other modalities under isocaloric conditions. Thus, while confirming the efficacy of FATmax’s over inactivity, we cannot claim its superiority over other exercise intensities (eg, HIIT or vigorous continuous training). Future isocaloric RCTs are needed to clarify its distinct metabolic benefits.

Despite these limitations, the available data provide actionable clinical insights. Future studies should prioritize well-designed, adequately powered randomized controlled trials that include comprehensive reporting of lifestyle behaviours and dietary intake. Such methodological rigor is necessary to more precisely evaluate and optimize the efficacy of FATmax-intensity exercise interventions in populations with overweight and obesity.

Conclusion

FATmax-intensity exercise was associated with improvements in body composition, metabolic health, and cardiovascular outcomes in individuals with overweight or obesity. Significant benefits were observed for body weight, BMI, fat mass, HOMA-IR, lipid profile and DBP outcomes. Subgroup analyses revealed distinct trends based on participant and intervention characteristics, though no single pattern was consistent across all outcomes. However, these findings should be interpreted cautiously given the methodological heterogeneity and the limited number of studies in some subgroups. Overall, FATmax-intensity exercise represents a promising individualized exercise strategy for improving metabolic and cardiovascular health in individuals with overweight or obesity.

Funding Statement

This study did not receive any funding.

Abbreviations

FATmax, maximal fat oxidation; RCTs, Randomized controlled trials; WMD, weighted mean differences; SMD, standardized mean differences; CI, confidence interval; I², heterogeneity statistic; GRADE, grading of recommendations assessment, development and evaluation; SE, standard error; SD, standard deviation; BMI, body mass index; FFM, fat-free mass; HOMA-IR, homeostatic model assessment of insulin resistance; WHR, waist-to-hip ratio; TG, triglycerides; TC, total cholesterol; HDL-C, high-density lipoprotein cholesterol; LDL-C, low-density lipoprotein cholesterol; SBP, systolic blood pressure; DBP, diastolic blood pressure;, maximal oxygen consumption.

Data Sharing Statement

The datasets used and/or analysed during the current study are available from the corresponding author on reasonable request.

Author Contributions

Teng Keen Khong: Data Curation, Formal Analysis, Writing – review & editing. Ge Zhao: Conceptualization, Data Curation, Formal Analysis, Writing – original draft. Yanqing Yan: Data Curation, Writing – review & editing. Ashril Yusof: Supervision, Validation, Writing – review & editing. All authors gave final approval of the version to be published; have agreed on the journal to which the article has been submitted; and agree to be accountable for all aspects of the work.

Disclosure

The authors have no conflicts of interest to declare.