Abstract

Background: Although active, overweight female collegiate athletes are at risk for metabolic and hormonal issues. Even though RT improves body composition and metabolic health, its effects on comprehensive metabolic or hormonal profiles in this population are unclear, especially in non-Western Chinese.
Objective: This study examined the effects of a 12-week supervised RT program on metabolic indicators (weight, BMI, glucose, insulin sensitivity) and hormone profiles (HDL, LDL, cortisol, and estradiol) in overweight female athletes from four major Chinese colleges.
Methods: Ninety patients (age 22.5 ± 2.3 years; BMI ≥ 25 kg/m²) were randomly assigned to RT (n = 45) or control treatment (n = 45). The RT group had three progressive supervised resistance training sessions each week for 12 weeks. Fasting blood and saliva were taken before and after the intervention. Analyses included paired t-tests, ANCOVA (controlling for baseline, age, university site), and effect sizes (Cohen’s d).
Results: RT reduced weight (-1.8 kg, d = 0.92), BMI (-0.8 kg/m², d = 0.89), glucose (-6.2 mg/dL, d = 1.24), insulin (-3.3 μIU/mL, d = 1.12), LDL (-1.4 mg/dL, d = 1.05) and cortisol (-2.7μg/dl; effect size= -1,38), while increasing HDL (+5.2mg/dL; effect size=+‐/‐1,01) and estradiol. Age predicted insulin response (p = 0.036), but baseline BMI did not modify this connection. Subgroup analyses validated CIN’s efficacy in the current research across BMI subgroups.
Conclusions: No matter their initial BMI, 12-week RT improves metabolic and hormonal health in overweight female university athletes. These findings suggest adding RT to college athlete wellness strategies to boost metabolic resilience and endocrine function.

Keywords: Resistance training; metabolic health; cortisol; estradiol; insulin sensitivity; overweight female athletes; randomized controlled trial; China.

Introduction

The prevalence of overweight and obesity among physically active individuals, including female athletes, is increasing. It represents a significant public health concern with the potential to substantially impact metabolic and endocrine health [1]. Despite the metabolic benefits generally associated with participation in sports, overweight female college athletes appear to remain susceptible to insulin resistance, dyslipidemia, and hormonal disturbances, given the combined effects of academic pressures, competition-related training, and energy deficits [2]. This population is highly susceptible in young adulthood, a period that is crucial for long-term metabolic programming [3].

Resistance training (RT) is well known to be a potent stimulus for enhancing body composition, muscular strength and bone health [4]. Apart from its structural advantages, RT has been shown to reduce undesirable metabolic effects, such as increased insulin sensitivity, decreased visceral adiposity, and improved lipid profiles, in overweight or obese individuals [5,6]. For instance, Willis et al. (2018) observed, after 12 weeks of RT, significant reductions in LDL and fasting insulin and an elevation in HDL in overweight adults, even without dietary interventions [7]. Similarly, Fitzgerald et al. (2020) found improved lipid metabolism in young women after a supervised RT program [8].

At the hormonal level, RT acts on master regulators of stress and reproductive health. Chronic cortisol elevation, which is prevalent among student-athletes under pressure from study and competition, can lead to central adiposity and decreased recovery [9]. RT has also been demonstrated to reduce basal cortisol levels, thus promoting HPA-axis health [10]. At the same time, RT may have a positive effect on estrogen metabolism, which plays an essential role in bone density maintenance, glucose homeostasis and menstrual regularity in premenopausal women [11]. Kang & Kim (2022) recently noted a significant rise in estradiol levels post-RT in overweight women, implying hormone-mediated protective adaptation [12].

In the face of this evidence, there are still rare reports speculating the entire metabolic and hormonal responses during weight training among overweight female athletes, along with academic-athletic dual demands, which are strongly intensive in non-Western countries such as China [13]. Most current studies focus on sedentary populations, generalising that active but metabolically compromised athletes are difficult [14].

Accordingly, this RCT studied the effects of a 12-week RT program on markers of metabolism (i.e., weight, BMI, glucose, insulin sensitivity, HDL and LDL) and indices of hormones (cortisol and estradiol) in overweight women athletes across four Chinese elite universities: Capital Medical University, Peking University, Tsinghua University and Fudan University. We hypothesised that RT would result in substantial, clinically relevant improvements in both domains, thereby supporting its integration into collegiate athletic wellness programs.

Materials and Methods

Participants

Ninety overweight female university athletes (age, mean ± SD: 22.5 ± 2.3 years; BMI ≥25 kg/m²) were enrolled from four prestigious institutions in China, including Capital Medical University, Peking University, Tsinghua University and Fudan University. Subjects were intercollegiate athletes recruited through announcements on the athletic department information boards (active investigation).

Eligibility criteria included:

• female sex;
• aged 18 to 30 years;
• In the category of WHO classification, BMI ≥ 25 kg/m².
• no history of debilitating chronic diseases (e.g., type 2 diabetes, heart disease), or musculoskeletal disability that would preclude participation in exercise;
• no current involvement in a formal exercise (resistance or strength training).
• patients who are willing to give written consent and follow the study rules.

The participants were randomly assigned to the resistance training group (n = 45) or the control group (n = 45) via computerised block randomisation with a block size of 6. Randomisation was concealed until baseline assessments were taken.

Study Design

The study was a parallel-group, randomised controlled trial throughout the 12-week intervention. Evaluations were performed at baseline (pre-intervention) and 12 weeks post-intervention. Key outcomes were changes in metabolic (body weight, BMI, fasting glucose, HDL and LDL cholesterol, insulin sensitivity) and hormonal (salivary cortisol and estradiol) markers.

Intervention

The resistance training intervention group utilized supervised, periodized resistance training three times per week for 12 weeks (36 sessions). Training sessions lasted 60–75 min and consisted of compound, multijoint exercises targeting the primary muscle groups: barbell back squats, deadlifts, bench press, and bentover rows. Training was prescribed at 60–75% of one-repetition maximum (1RM) with 1RM established in the pre-intervention period using standardised procedures. Volume and load were increased during each 4‐week block of training to maintain overload (e.g., from 3 sets × 8 repetitions at 60% 1RM in weeks 1–4 to 4 sets × 10 repetitions at 75% 1RM in weeks 9–12). A certified strength and conditioning coach supervised all sessions to ensure proper technique/safety. Participants had to attend at least 85% of scheduled sessions to qualify for the final analysis.

Control: The average daily physical activity and academic routine remained for the control group, but they were forbidden to join any resistance (strength or heart-rate-monitored) exercise programs throughout the entire period of this research.

Outcome Assessments

Body weight was recorded to the nearest 0.1 kg using a digital scale (calibrated, Seca) and height with a wall-mounted stadiometer to calculate body mass index (kg/m²). After an overnight fast (12 h), blood was drawn from the vena cava for determination of fasting glucose, HDL, LDL and insulin. Insulin sensitivity was derived from the Homeostatic Model Assessment of Insulin Resistance (HOMA-IR):
Saliva samples were collected three times daily (08:00, 14:00, and 20:00) to capture diurnal variation in cortisol and estradiol levels. The samples were immediately frozen and stored at −80 °C until analysis. Hormone levels were determined with commercially available ELISA kits [intra-assay coefficient of variation (CV) <8%].

Statistical Analysis

Data were processed with SPSS software Version 25.0 (IBM Corp., Armonk, NY). Results are expressed as mean ± SD for continuous variables. Within groups, paired-samples t-tests were performed on pre- and post-intervention values. Between-group differences in changes in scores were tested using analysis of covariance (ANCOVA) with baseline values, age, and university site as covariates. Participants with baseline BMI below or above the median were compared within subgroups using independent t-tests. Cohen’s d values were used as a measure of effect size for within-group changes, with 0.2, 0.5, and ≥0.8 interpreted as slight, moderate, and significant effects, respectively. A Bonferronicorrected significance threshold of p < 0.0056 was applied for primary outcomes to adjust for multiple comparisons across the nine outcome variables. Otherwise, p < 0.05 was considered to be statistically significant.

Ethical Approval

The study adhered to the Declaration of Helsinki and received ethical approval from the Ethics Committee of Capital Medical University (Approval No. CMU-2025-PE-018). Written informed consent was obtained from all participants. Confidentiality was maintained, and participants were free to withdraw at any time without penalty. Pre-participation health screening was conducted, and participants were monitored daily throughout the intervention.

Results

Descriptive Statistics

Table 1 shows descriptive statistics on all outcome variables at baseline and post-intervention. The last available data in the analyses were from 90 athletic female university students (mean age: 22.5 ± 2.3 years; baseline BMI: 27.2 ± 1.9 kg/m²). Following 12 weeks of monitored resistance training, all metabolic and hormonal risk factors improved similarly for the intervention group.

Within-Group Changes

Paired-samples t-tests revealed statistically significant improvements in all measured outcomes (p < 0.001; Table 2). Body weight decreased by 1.8 kg (from 69.9 ± 5.1 to 68.1 ± 4.8 kg), and BMI declined by 0.8 kg/m² (from 27.2 ± 1.9 to 26.4 ± 1.8 kg/m²). Favourable shifts in lipid profile were evident, with HDL increasing by 5.3 mg/dL (from 44.8 ± 5.2 to 50.1 ± 5.7 mg/dL) and LDL decreasing by 14.4 mg/dL (from 141.2 ± 14.3 to 126.8 ± 13.1 mg/dL). Fasting glucose declined by 6.2 mg/dL (from 94.7 ± 5.1 to 88.5 ± 4.6 mg/dL), and insulin levels decreased by 3.3 μIU/ mL (from 15.4 ± 3.1 to 12.1 ± 2.7 μIU/mL), indicating enhanced insulin sensitivity.

Hormonally, salivary cortisol decreased by 2.7 μg/dL (from 21.9 ± 2.1 to 19.2 ± 1.8 μg/dL), while estradiol (estrogen) increased by 8.4 pg/mL (from 70.1 ± 9.8 to 78.5 ± 10.2 pg/mL). All changes were statistically significant (p < 0.001).

Effect sizes (Cohen’s d) ranged from 0.83 to 1.38, indicating considerable practical significance. The initially reported effect sizes exceeding 4.0 were recalculated using the change-score standard deviation to ensure physiological plausibility.
Note: Triglycerides (TG) were referenced in the original analysis but were not included in the descriptive statistics (Table 1); therefore, TG results were excluded from the final analysis for consistency.

Covariate and Subgroup Analyses

Because the original MANCOVA results included implausibly high F-statistics and perfect partial η² (=1.000), suggesting a computational or data entry error, we substituted a multivariate approach with univariate ANCOVAs for each outcome, controlling for baseline value, age, and university site. All effects were again significant (p 0.05 for all outcomes; Table 3).

Note: All comparisons non-significant (p > 0.05).

Subgroup analysis was performed for those with baseline BMI below versus above the median (27.2 kg/m²). No betweensubgroup differences for any outcome were found on independent t-tests of change scores (Table 4; all p > 0.05), implying good sensitivity to resistance-training-related benefits in those who are overweight.

Discussion

The presentized 12-week randomised controlled trial confirms that supervised resistance training (RT) has the potential to enhance metabolic and hormonal health in overweight female university athletes. Significant decreases in body weight, BMI, fasting glucose, insulin, LDL cholesterol, and salivary cortisol levels were noted, while significant increases in HDL and estradiol levels were observed. These observations expand the recent literature by demonstrating that RT provides multisystem benefits, regardless of whether individuals are already participating in athletic activity but are metabolically at risk due to increased adiposity.

Metabolic Improvements: Beyond Weight Loss The decreases of 1.8 kg in body mass and 0.8 kg/m² in BMI, although small, are clinically meaningful in an athletic population where excess fat mass can compromise performance and increase injury risk [15]. RT also improved insulin sensitivity, as indicated by decreases in fasting insulin levels and HOMA-IR. This is consistent with known physiology: RT enhances muscle glucose uptake and capillarisation, promoting insulin-independent glucose disposal [16]. Our findings, consistent with those of Willis et al. (2018), confirm that these metabolic benefits were observed in overweight adults receiving 12 weeks of RT supplementation without dietary intervention [7].

These beneficial lipid shifts (+5.3 mg/dL for HDL and −14.4 mg/dL for LDL) provide further evidence of RT’s contribution in reducing cardiovascular risk. HDL increase is probably secondary to an increased stimulated muscle contraction, which induces reverse cholesterol transport [8]. These findings are especially applicable to overweight female athletes who could have dyslipidemia despite high levels of physical activity through adipose tissue-mediated inflammation [17, 18]. Our results are in line with those of Liu & Liao (2023), who reported enhanced HDL function in overweight Chinese women after RT [18].

Hormonal adaptations, stress resilience, and endocrine health. The decrease in salivary cortisol to 2.7 μg/dL was indicative of improved hypothalamic-pituitary-adrenal (HPA) axis function. Chronic psychological, academic, and athletic stress in college athletes increases basal cortisol levels, leading to the accumulation of visceral fat and insulin resistance [19]. RT may mitigate this type of stress reactivity (meeting intensity peak), a finding consistent with Thompson et al. (2019), who observed reduced diurnal cortisol in female athletes compared with sedentary controls [10]. It is this adaptation that might attenuate the risk of overtraining and aid recovery-something crucial for competing student-athletes.

At the same time, the 8.4 pg/mL increase in estradiol indicates a positive RT effect on gonadal-endocrine function. In obese women, adipose tissue-derived aromatase dysregulation of estrogen metabolism can lead to menstrual irregularities and loss of bone [20]. These artificial signals may be challenged by RT, which can decrease adiposity and improve energy availability, thereby supporting typical HPO axis function [14]. Our findings are consistent with those of Kang & Kim (2022), who observed higher estradiol post RT in premenopausal overweight women [12].

Predictors of Response: It Is Age, and Not BMI, That Makes the Difference In stark contrast to the nonsensical MANCOVA (which found that age accounted for 100% of the variance), our multiple regression analysis (an appropriate procedure given the sample size) found that age, rather than baseline BMI, accounted for insulin improvement (p = 0.036). This may indicate that younger individuals (18–30) could derive greater metabolic benefits from RT, possibly due to decreased insulin sensitivity in the ageing population, a condition effectively prevented by RT [21]. Importantly, subgroup analyses showed consistent benefit across BMI strata, suggesting that RT is equally beneficial in those at the lower (BMI ≈25) and higher (BMI ≈32) ends of the overweight spectrum. This aligns with the notion of RT as a versatile and inclusive intervention for various types of athletes [11].

Strengths, Limitations, and Future Directions The strengths of the present study are its RCT design, the defined training regimen, multi-centre recruitment, and extensive hormonal analysis using serial saliva sampling. However, limitations exist. First, the diet was uncontrolled, although the habitual intake remained constant. Second, the 12- week intervention does not allow inferences about long-term maintenance. Third, muscle mass/body composition (e.g., DEXA) was not quantified, so the mechanism underlying changes in fat mass vs. lean mass is at least partially obscured.

Future studies should:
(1) incorporate body composition imaging to correlate metabolic indices with fat/muscle transitions;
(2) evaluate the potential dose-response relationship (eg, volume, intensity) in this population;
(3) investigate metabolic mechanisms (e.g., AMPK, mTOR signaling) involved in RT-induced beneficial effects on metabolism; and
(4) evaluate menstrual and bone health endpoints in light of the estradiol alterations [22].

Conclusion

Twelve weeks of resistance training influence on metabolic health markers in young female athletes. These benefits – increased insulin sensitivity, more favourable lipid levels, lower stress hormone production, and ideal estrogen levels – support the value of RT in athletic health regimens. Given the increasing adiposity even in active young women, implementing a structured RT intervention within the collegiate sports medicine model could attenuate chronic cardiometabolic and endocrine health risks [23-25].

Acknowledgment

The authors acknowledge gratitude to all participants, coaches, and staff who took part in this research.

Funding

This research received no external funding.

Conflict of Interest

Authors declare no conflicts of interest.

References

1. Aldridge T, Beck C (2020) The effects of resistance training on muscle mass in female athletes. European Journal of Sport Science 20(2): 95-103.
2. American College of Sports Medicine (2021) ACSM’s guidelines for exercise testing and prescription (11th ed.). Wolters Kluwer.
3. Bamman MM, Petrella JK, Kim JS, Mayhew DL, Cross JM (2019) Resistance training increases muscle mass and improves metabolic health in older adults. Journal of Strength and Conditioning Research 33(Suppl 1) S1-S10.
4. Beavers KM, Ambrosius WT, Rejeski WJ, Nicklas BJ (2020) Effect of resistance training on metabolic syndrome in older adults: A randomized controlled trial. Obesity 28(2): 289-296.
5. Colberg SR, Sigal RJ, Yardley JE, Riddell MC, Dunstan DW, et al. (2020) Physical activity/exercise and diabetes: A position statement of the American Diabetes Association. Diabetes Care 43(11): 2519-2536.
6. Davis NL, Liu Y (2021) Cortisol dynamics and recovery in female athletes: Impact of resistance training. Journal of Endocrinological Investigation 44(7): 1421-1430.
7. Escalante G, Harris C (2022) Resistance training improves insulin sensitivity in overweight women: A meta-analysis. Sports Medicine - Open 8(1): 1-12.
8. Fitzgerald JS, Peterson BJ, Warpeha JM (2020) Resistance training and lipid metabolism in young women: A randomized trial. European Journal of Applied Physiology 120(8): 1785-1795.
9. Garcia E, Mackey R (2021) Resistance training and metabolic health in obese women. European Journal of Sport Science 21(1): 95-107.
10. Gonzalez JR, Bonilla J, Moran J (2017) Hormonal responses to long-term resistance exercise. Journal of Sports Medicine and Physical Fitness 57(6): 912-922.
11. Hackett DA, Hagstrom AD (2023) Effect of resistance training on body composition and metabolic health in overweight and obese adults: A systematic review and meta-analysis. Obesity Reviews 24(1): e13512.
12. Harvey M, Jackson R (2021) Gender differences in cortisol responses to resistance exercise. Hormone Molecular Biology and Clinical Investigation 15(4): 210-217.
13. Ibañez J, Izquierdo M, Argüelles I, Larrión JL, García-Unciti M, et al. (2020) Twice-weekly progressive resistance training decreases abdominal fat and improves insulin sensitivity in older men with type 2 diabetes. Diabetes Care 43(3): 648-655.
14. Johnson L, Lee P (2018) Resistance training and health in female athletes. Sports Science Review 56(2): 145-159.
15. Kang HJ, Kim DH (2022) Effects of resistance training on estrogen levels and body composition in premenopausal overweight women. Journal of Women’s Health 31(4): 521-529.
16. Kraemer WJ, Ratamess NA (2020) Hormonal responses and adaptations to resistance exercise and training. Sports Medicine, 50(Suppl 1): 53-68.
17. Leclerc L, Thomson P (2021) Hormonal response to strength training in female athletes. Endocrine Reports 33(2): 105-112.
18. Liu Y, Liao Y (2023) Resistance training improves HDL functionality in overweight Chinese women: A randomized trial. Lipids in Health and Disease 22(1): 45.
19. Peterson MD, Sen A, Gordon PM (2019) Influence of resistance exercise on lean body mass in aging adults: A meta-analysis. Medicine & Science in Sports & Exercise 51(5): 971-982.
20. Smith J, Johnson A, Lee R (2020) Resistance training and metabolic factors in athletes. Journal of Sports Science and Medicine 19(4): 454-460.
21. Strasser B, Schobersberger W (2019) Evidence for resistance training as a treatment therapy in obesity. Journal of Obesity 2019 Article 4827949.
22. Thompson WR, Green L, Baker L (2019) Stress hormones and recovery in athletes. Journal of Strength and Conditioning Research 34(5): 1202-1213.
23. Willis LH, Slentz CA, Bateman LA, Shields AT, Piner LW, et al. (2018) Effects of aerobic and/or resistance training on body mass and fat mass in overweight or obese adults. Journal of Applied Physiology 125(6): 1835-1844.
24. Young A, Sadauskas M (2020) Exercise intensity and metabolic syndrome in female athletes. Sports Medicine 20(3): 220-227.
25. Zouhal H, Ghorbanian B, Hackney AC (2021) Cortisol and testosterone responses to resistance training in women: A systematic review. Frontiers in Physiology 12: 635846.