Group Aerobic Exercise Improves Body Composition and Lipid Profile in Young Women with Elevated BMI: A Randomized Controlled Trial

Abstract

Sedentary behavior among young women is increasingly associated with adverse metabolic and cardiovascular outcomes. The aim of this randomized controlled trial was to evaluate and compare the effects of three structured group fitness programs on anthropometric parameters, body composition, and lipid profile in overweight young women (N = 111, age 18–25, BMI ≥ 25). Participants were assigned to mix aerobics (E1, n = 27), kickbox aerobics (E2, n = 28), step aerobics (E3, n = 27), or a control group (C, n = 29). Each intervention lasted 12 weeks, with sessions conducted three times per week, each lasting 60 min. The results were analyzed using repeated measures ANOVA. Significant reductions were observed in body weight (−4.8 kg in E1, p < 0.01), waist circumference (−5.3 cm in E1, p < 0.001), and body fat percentage (−3.6% in E1, p < 0.01). High-density lipoprotein (HDL) increased by 7.4 mg/dL (p < 0.01), while low-density lipoprotein (LDL), total cholesterol, and triglycerides decreased by 12.1 mg/dL, 18.6 mg/dL, and 19.4 mg/dL, respectively (all p < 0.01). The most pronounced overall improvements were found in the mix aerobics group. In contrast, the control group showed significant deterioration in most variables, including a 2.1 kg weight gain and a 6.3 mg/dL increase in total cholesterol (p < 0.05). These findings confirm the superior effectiveness of mix aerobics as a non-pharmacological intervention to improve body composition (notably through reductions in body weight, fat percentage, and waist circumference) and cardiovascular biomarkers (such as increased HDL and decreased LDL, total cholesterol, and triglycerides) in young overweight women. Compared to kickboxing and step aerobics, mix aerobics consistently achieved the greatest improvements across all measured parameters, making it the most comprehensive and effective option among the three programs tested.

1. Introduction

A sedentary lifestyle is increasingly prevalent and is characterized by a lack of physical activity, which tends to worsen over time [1,2]. This behavioral pattern has become a major public health concern due to its long association with multiple chronic conditions. Specifically, it raises the risk of diabetes by 112%, cardiovascular diseases [such as heart attacks and strokes) by 147%, cardiovascular-related mortality by 90%, and all-cause mortality by 49% [3]. The accumulation of excess body fat, often resulting from prolonged physical inactivity, contributes significantly to these risks. Increased body fat and a high rate of obesity, resulting from physical inactivity, are considered among the most serious health risk factors [4]. Obesity is a complex metabolic disorder characterized by excessive accumulation of body fat, which poses a serious threat to overall health [5].

According to reports from the World Health Organization (WHO), more than 60% of the global population is affected by overweight or obesity, placing this issue among the leading global health challenges. Obesity is recognized as the fifth most significant risk factor for mortality, with at least 2.8 million adults dying annually due to obesity-related complications [6]. WHO data from 2000 indicate that approximately 1.6 billion adults have a BMI over 25 kg/m², and at least 400 million are obese with a BMI over 30 kg/m². Body fat percentage and BMI are key metrics that negatively impact physical performance, as supported by research on younger populations [7,8]. A body fat percentage between 21% and 33% is associated with more favorable health outcomes, while optimal body composition requires a balance between muscle mass and body fat [9].

Body composition plays a significant role in determining physical performance, thus serving as a critical indirect indicator of health-related fitness, which naturally evolves in response to regular physical activity [10,11]. Changes in body composition are influenced by an array of interconnected factors, including fat mass, sex, age, genetic predispositions, physical training type, and dietary pattern [12]. Aerobic activities notably impact body composition, with structured exercise programs combined with appropriate nutrition being key to weight and fat reduction [13]. The synergistic effect of regular physical exercise and a balanced diet is essential for altering body composition [14].

Numerous studies underscore the positive effects of various aerobic programs on body composition and anthropometric characteristics [15]. Anthropometric indicators such as waist circumference and waist-to-hip ratio (WHR) are pivotal in assessing metabolic disease risk. A waist circumference greater than 80 cm significantly elevates the risk of cardiovascular diseases and diabetes [16], while an optimal WHR should be below 0.85—higher values are associated with greater health risks [17,18]. Regular physical activity plays an essential role in alleviating the global burden of chronic diseases, particularly those linked to overweight and obesity [19,20,21].

In addition to anthropometric measurements, blood biochemical parameters are invaluable tools for evaluating and quantifying obesity. Key indicators include fasting blood glucose (FBS), high-density lipoprotein (HDL), low-density lipoprotein (LDL), total cholesterol (TC), and triglycerides (TG) [22]. Lifestyle modifications, particularly regular and adequate physical activity, are among the most effective strategies for preventing obesity and metabolic syndrome. Physical activity positively influences metabolic disorders associated with obesity [23], and LDL and HDL levels are crucial for assessing cardiovascular disease risk [24,25]. As a result, research on the effects of aerobic exercises on lipid profiles is essential for cardiovascular health promotion [26]. Vigorous aerobic exercise is linked to the stabilization of both traditional and emerging cardiovascular risk factors [19,27].

Among contemporary aerobic fitness programs, kickbox aerobics stands out as an exceptionally effective exercise modality, blending dynamic cardio workouts with martial arts elements. This training offers comprehensive physical stimulation, improving endurance, strength, and coordination, making it particularly suitable for individuals aiming to enhance physical health and self-confidence [28]. Similarly, mix aerobics, combining energetic music with a variety of movements (e.g., steps, turns, hops, and jumps), not only improves cardiovascular endurance but also promotes weight loss and positive alterations in body composition, offering a fun and challenging exercise form [29,30]. Step aerobics, involving stepping on and off a platform, provides increased training intensity and engages key muscle groups, particularly the legs, glutes, and core, delivering a comprehensive workout that contributes to body toning and improved physical fitness [31].

From previous research, it is evident that all observed programs, mix aerobics, Step aerobics and kickboxing, are effective in burning calories, as well as in improving motor and functional abilities. The study by Špirtović et al. [32] showed positive effects of mix aerobics on body composition in healthy adult women. Similarly, the results of the research by Nikić et al. [33] and Spirtovic et al. [30] confirmed the effectiveness of Step aerobics in transforming anthropometric characteristics and body composition in young women. Also, Khosravi et al. [34] showed positive effects of kickboxing, with the inclusion of a control group, which further confirms the reliability of the results obtained. However, in the available literature, we did not find a study that simultaneously organizes all three types of group fitness programs, which was the main motivation for this study.

The selected fitness programs—mix aerobics, kickbox aerobics, and step aerobics-were chosen due to their widespread use in recreational settings, high popularity, and ease of implementation in various fitness environments [31]. Their anatomical and functional diversity allows for a complete investigation of the effects of various aerobic exercise methods on anthropometric features, body composition, and lipid profiles. However, there have been few comparative studies on these specific fitness regimens among young women, who are underrepresented in current research. This study attempts to fill the gap by giving extensive insights into the differential effects of mix aerobics, kickbox aerobics, and step aerobics on various health metrics. The aim of this study was to examine the effects of a twelve-week program of various group fitness programs on anthropometric characteristics, body composition, and blood lipid profiles in young women.

2. Materials and Methods

2.1. Participants

Participants were voluntarily recruited through university advertisements and social media. Eligible individuals were females aged 18 to 25 years with a BMI of 25 kg/m² or higher. Inclusion criteria required stable body weight during the previous three months and the absence of metabolic, hormonal, orthopedic, cardiovascular, or infectious diseases, as well as no regular medication use. Stable body weight during the preceding three months was assessed via self-report during screening, with participants excluded if they reported any change exceeding ±2 kg. To reduce potential confounding, participants were instructed to maintain their habitual diet and refrain from engaging in any additional structured physical activity beyond their daily routine during the intervention period. Individuals who did not match these criteria were excluded from the study.

Following recruitment, eligible participants (N = 125) were assigned to four groups using a computer-generated randomization process via SPSS software (version 26). A simple randomization procedure with a 1:1:1:1 allocation ratio was applied, without stratification or blocking. The randomization sequence was generated by an independent researcher not involved in recruitment or assessments to ensure concealment and prevent selection bias. Group assignments were disclosed only after baseline measurements were completed.

The study was approved by the Ethics Committee of the State University of Novi Pazar (Approval No. 4957/24) and was registered in the Open Science Framework (OSF) registry (registration DOI: https://doi.org/10.17605/OSF.IO/5HECX (accessed on 4 June 2025). All participants provided informed consent and completed the International Physical Activity Questionnaire (IPAQ) before the experiment [35]. No statistically significant baseline differences were observed between the experimental and control groups in terms of age, height, weight, BMI, waist circumference, or body fat percentage.

Out of 125 participants who were initially randomized, 111 completed the intervention and participated in both baseline and post-intervention assessments. The final distribution of participants was as follows: mix aerobic (E1, n = 27), kickbox aerobic (E2, n = 28), step aerobic (E3, n = 27), and control (C, n = 29). A total of 14 participants did not complete the study: nine were excluded due to low attendance (defined as participation in less than 75% of the scheduled sessions), and five withdrew voluntarily, citing minor illness or scheduling conflicts (Figure 1). These dropouts were evenly distributed across the groups and did not affect the randomization balance. No adverse events related to the interventions were reported.

2.2. Outcome Measures

The effects of the fitness programs were assessed through changes in body weight, height, BMI, waist circumference, skinfold thickness (upper arm, abdomen, thigh), body fat percentage, muscle mass percentage, and blood lipid parameters (HDL, LDL, total cholesterol, and triglycerides).

Anthropometric measurements were conducted according to the International Standards for Anthropometric Assessment (ISAK) [36], using standardized procedures and equipment, including a Harpenden skinfold caliper and the TANITA UM-72 bioelectrical impedance analyzer [37].

Standing height was measured with Martin’s anthropometer with participants standing barefoot, heels together, arms at their sides, and the head positioned in the Frankfurt horizontal plane. The measurement was taken from the vertex to the floor and recorded to the nearest 0.1 cm.

Waist circumference was measured at the midpoint between the lower margin of the last palpable rib and the top of the iliac crest, using a flexible, non-elastic anthropometric tape, with the participant in a standing position after a normal expiration.

Skinfold thicknesses were measured at the triceps, abdomen, and thigh using a Harpenden caliper, on the right side of the body. The skinfold was grasped firmly between the thumb and index finger, and the caliper was applied 1 cm below the fingers, perpendicular to the fold. Readings were recorded 2 s after application, in accordance with ISAK guidelines.

Body composition parameters (body fat and muscle mass percentages) were assessed using the TANITA UM-72 device (Tanita Corporation, Tokyo, Japan), which applies bioelectrical impedance analysis (BIA). Standardized pre-test conditions were ensured, including assessments conducted in a hydrated state and during morning hours.

All instruments were calibrated before the assessment phase, and anthropometric measurements were conducted by ISAK-certified technicians. To evaluate intra-rater reliability, the Intraclass Correlation Coefficient (ICC) was calculated for all anthropometric variables.

Venous blood samples for lipid profile analysis (total cholesterol, HDL cholesterol, LDL cholesterol, and triglycerides) were collected in the morning, between 8:00 and 10:00 a.m., after a fasting period of 9 to 12 h, from the antecubital vein while participants were in a seated position, in cooperation with the Bosfor Polyclinic in Novi Pazar. The analyses were conducted in their accredited medical-biochemical laboratory using a standardized and validated direct enzymatic method on the automated biochemical analyzer Roche Cobas C311 (Roche Diagnostics, Mannheim, Germany), with original Roche reagents, in accordance with the manufacturer’s recommendations and international laboratory standards. Total cholesterol and triglycerides were determined using the classical colorimetric method, while HDL and LDL cholesterol were analyzed using the direct enzymatic method, which provides higher accuracy in determining these fractions due to the variability of lipoprotein subfractions. When applicable, LDL cholesterol values were also automatically calculated by the analyzer using a validated formula based on the concentrations of total cholesterol, triglycerides, and HDL: LDL-C (mmol/L) = total cholesterol − HDL-C − (triglycerides/2.2). This formula is valid only when triglyceride levels are below 4.5 mmol/L. The laboratory is also equipped with reagents for direct LDL cholesterol determination, further enhancing the reliability of the results.

All samples were processed within two hours of collection and analyzed under the same laboratory conditions by licensed professionals. Participants were advised to refrain from consuming alcohol, carbonated beverages, and fatty foods during the 48 h prior to blood sampling. All analyses were consistently performed at the same time of day (8:00–10:00 a.m.), within five days before the beginning and after the completion of the twelve-week intervention, to ensure maximum reliability and repeatability of measurements. The training protocol began in April 2024 and ended in July of the same year.

2.3. Training Program

The experimental intervention included three aerobic programs: mix aerobics (E1), kickbox aerobics (E2), and step aerobics (E3;

Table 1. Training structure of mix aerobics, box aerobics, and step aerobics.

Mix Aerobics			Kickbox Aerobics			Step Aerobics
Part of the Training	Duration (% of Time)	Activities/Content	Part of the Training	Duration (% of Time)	Activities/Content	Part of the Training	Duration (% of Time)	Activities/Content
Warm-up	6 min	Walking, running in place, dynamic jumps, hand and leg coordination to the rhythm of music.	Warm-up	6 min	Light running in place, jump rope, arm and leg circles with rhythmic music.	Warm-up	6 min	Walking in place, marching, basic step movements with slow music.
Main part/aerobics	33 min	Combination of basic aerobics steps (Basic step, V-step, Leg lift, Over the top, Repeater).	Main part/aerobics	33 min	Basic punches: Jab, Cross, Front kick, Side kick.	Main part/aerobics	33 min	Basic steps: Basic step, V-step, Alternating basic step.
		Interval segments: high intensity (10 min)—jumps, circular punches, steps with pace changes.			Interval segments: combinations of punches and jumps.			Combinations with arms: raising arms to the rhythm of the music.
					Dynamic exercises for balance and strength: High knees + circular punches.			Advanced steps: leg lift, turn step, over the top, repeater.
Cool-down	6 min	Static stretching: stretching leg, back, and arm muscles. Focus on relaxation.	Cool-down	6 min	Static stretching: Glute Stretch, inner thigh stretch, quadriceps stretch, hamstrings stretch, shoulder stretch. Focus on relaxation.	Cool-down	6 min	Static stretching: stretching leg, back, and arm muscles. Body relaxation and deep breathing to restore balance after the intense part of the training.

). Each program was conducted three times per week for 12 weeks (36 sessions total). Each session included a warm-up (6 min), main aerobic workout (33 min), and cool-down (6 min). The warm-up involved mobility and light cardio exercises (90–110 bpm), the main workout consisted of dynamic aerobic exercises set to music (116–163 bpm), and the cool-down included stretching and relaxation exercises. Training intensity was individualized and progressed based on participant fitness levels, guided by real-time heart rate monitoring using Polar V800 heart rate monitors (Kempele, Finland). Target heart rate zones were calculated as 60–85% of the estimated maximal heart rate (HRmax), determined using the standard formula HRmax = 220 − age. These zones were then adjusted every four sessions to ensure progressive overload and adherence to aerobic training guidelines. All sessions were led by certified group fitness instructors trained in exercise science.

The structure and content of the aerobic programs were developed based on established principles of aerobic exercise programming and supported by prior studies that demonstrated the effectiveness of choreographed and combat-inspired aerobic training in improving body composition and cardiovascular fitness in women [38,39,40,41]. The mix aerobics and step aerobics routines were modeled on traditional group fitness methods with proven efficacy, while kickbox aerobics was adapted from cardio-kickboxing formats validated in similar research contexts [30,32]. The training load (3 sessions/week, 12 weeks total) aligns with international recommendations for achieving significant aerobic and metabolic adaptations.

Throughout the 12-week period, exercise intensity was progressively increased using a combination of heart rate control and movement complexity. Target heart rate zones were recalculated biweekly to reflect individual progress, and instructors introduced more complex step combinations and higher-impact movements in weeks 5–12. In this way, the progression ensured both physiological adaptation and sustained motivation in subjects.

2.4. Statistical Analysis

To assess reliability, intraclass correlation coefficients (ICCs) were calculated for both the experimental and control groups, along with their corresponding 95% confidence intervals. Additionally, coefficients of variation were computed. Each group and each variable underwent two separate measurements conducted by at least two evaluators. A two-way mixed-effects model was used for the analysis. Interpretation and model selection followed the guidelines proposed by Koo and Li [42].

The Shapiro–Wilk test was employed to assess the normality of distribution, as it is considered one of the most reliable normality tests for small sample sizes [43]. The test was performed separately for both the first and second measurements. Normality testing was conducted both for the entire sample and separately for the experimental and control groups. A two-way analysis of variance (ANOVA) was performed to determine the effects of repeated measurements while controlling for group membership, the effect of group membership while controlling for the time of measurement, and the interaction effect between group and time on the investigated variables. Results were presented using partial eta squared (η²), which reflects the proportion of variance in the dependent variable explained by the observed effects. Additionally, paired-sample t-tests were conducted to examine the significance of differences between the first and second measurements for each group individually. Cohen’s d was calculated to estimate the effect size [44]. Values of Cohen’s d greater than 0.6 indicate that significant changes were observed in most participants, whereas values closer to 0 suggest that increased variance reflects changes in only a small number of individuals.

Bartlett’s test of sphericity was used to determine the significance of sphericity, i.e., the overall correlation among the variables examined [45]. This correlation indicates the presence of shared characteristics among the measured variables, supporting the consistency of the study. To assess the effect of the intervention in the final measurement only, a one-way ANOVA was conducted with post hoc tests to determine which specific training programs produced significant effects. The results were further verified using the Mann–Whitney test.

3. Results

The study involved one control group (n = 29) and three experimental groups: mix aerobics (E1, n = 27), kickbox aerobics (E2, n = 28), and step aerobics (E3, n = 27). Average values for body mass, height, and BMI were comparable across all groups. Specifically, BMI ranged from 26.1 to 27.0, and no statistically significant differences were found at baseline in body mass (p = 0.353–0.366) or BMI (p = 0.437).

3.1. Reliability

The results of the reliability analysis are presented in the following table.

For all variables (

Table 2. Reliability and variability analysis of the sample for the research variables using ICC and the coefficient of variation.

Variable	ICC (95%)	Coefficient of Variation (%)
BW	0.982 (0.948–0.994)	8.262
BMI	0.988 (0.965–0.996)	9.175
TSF-TH	0.989 (0.968–0.996)	30.475
TSF-UA	0.985 (0.956–0.995)	55.238
WC	0.962 (0.892–0.987)	8.638
BF%	0.984 (0.952–0.994)	14.912
MM%	0.957 (0.874–0.985)	13.687
TSF-AB	0.983 (0.951–0.994)	34.038
TG	0.924 (0.776–0.974)	2.438
HDL	0.976 (0.928–0.992)	3.800
LDL	0.811 (0.447–0.935)	1.725
TC	0.907 (0.728–0.968)	1.225

BW—body weight; BMI—body mass index; TSF-TH—skinfold thickness (thigh); TSF-UA—skinfold thickness (upper arm); WC—waist circumference; BF%—body fat percentage; MM%—muscle mass percentage; TSF-AB—skinfold thickness (abdomen); TG—triglycerides; HDL—high-density lipoprotein; LDL—low-density lipoprotein; TC—total cholesterol.

), the ICC is greater than 0.9, except for LDL (0.811, with 95% confidence interval ranging from 0.447 to 0.935), which indicates excellent reliability of the measurements. For triglyceride, HDL, LDL, and cholesterol scores, the coefficient of variation is below 5%, which, along with the ICC coefficients, indicates reliable measurements. However, only three variables (body weight, body mass index, and waist circumference) have a coefficient of variation below 10%, indicating sample heterogeneity. In the case of body fat percentage and muscle percentage, the values are 14.912% and 13.687%, respectively, and for the skinfolds of the thigh, arm, and abdomen, the coefficient of variation is even greater than 30%, meaning that repeated measurements could yield different results for the average value. In some cases, this could affect the reliability of the measurements. Bartlett’s test of sphericity indicates the presence of a statistically significant combined correlation among the study variables (H = 1607.721; p < 0.001).

3.2. Normality Testing

Both the Kolmogorov–Smirnov and Shapiro–Wilk tests show that the deviation of variables from a normal distribution for all variables, when considering the entire sample, is statistically significant (p < 0.01).

Similar results are obtained when considering specific groups into which the participants are divided, or specific measurements, with rare exceptions where a result indicating normality is achieved. This means that parametric methods, in the case of smaller samples (n < 30), may provide incorrect results, and that measures of central tendency as well as confidence intervals and tests based on them may not provide information relevant to the variable. Therefore, the results of parametric methods will be checked using non-parametric methods where possible.

3.3. Analysis of Variance

The results of the analysis of variance are presented in the following two tables.

For the control group (

Table 3. Mean values of all research variables presented by groups and measurements, including Cohen’s d and its significance in testing the significance of differences between measurements.

Variable	Group	Mean of 1st Measurement	Mean of 2nd Measurement	d
BW	K	75.82 ± 6.08	77.83 ± 6.15	0.90 ***
	E1	79.11 ± 6.95	73.94 ± 6.40	2.86 ***
	E2	80.03 ± 6.95	75.24 ± 6.85	2.54 ***
	E3	78.90 ± 6.06	74.32 ± 5.53	2.54 ***
BMI	K	26.11 ± 1.99	26.45 ± 2.00	0.89 ***
	E1	26.40 ± 2.68	24.69 ± 2.63	3.09 ***
	E2	26.95 ± 2.58	25.36 ± 2.72	2.81 ***
	E3	26.74 ± 2.16	25.21 ± 2.23	2.90 ***
TSF-TH	K	19.71 ± 6.29	19.89 ± 6.17	0.50 **
	E1	19.62 ± 5.90	16.53 ± 5.49	2.72 ***
	E2	18.86 ± 5.39	16.12 ± 4.96	2.20 ***
	E3	17.41 ± 4.94	15.00 ± 4.47	1.88 ***
TSF-UA	K	12.07 ± 6.47	12.21 ± 6.27	0.28
	E1	12.47 ± 6.00	9.18 ± 5.50	1.98 ***
	E2	11.53 ± 6.25	8.48 ± 5.42	1.66 ***
	E3	11.66 ± 6.07	9.09 ± 5.33	1.92 ***
WC	K	86.69 ± 6.51	87.50 ± 6.60	3.19 ***
	E1	84.71 ± 7.29	77.09 ± 7.39	2.28 ***
	E2	83.09 ± 7.12	76.37 ± 6.84	1.99 ***
	E3	81.21 ± 7.52	75.72 ± 6.78	2.13 ***
BF%	K	37.30 ± 5.47	37.98 ± 5.43	0.96 ***
	E1	37.94 ± 6.00	33.54 ± 6.00	2.87 ***
	E2	36.59 ± 5.54	33.08 ± 5.11	2.72 ***
	E3	35.81 ± 4.94	33.13 ± 4.38	1.69 ***
MM%	K	21.21 ± 3.07	21.08 ± 3.28	0.13
	E1	20.80 ± 3.52	24.60 ± 2.97	3.28 ***
	E2	21.48 ± 3.41	25.10 ± 2.80	2.46 ***
	E3	22.15 ± 2.77	24.71 ± 2.68	2.06 ***
TSF-AB	K	15.42 ± 5.14	15.81 ± 5.39	0.62 **
	E1	15.84 ± 6.01	11.65 ± 5.21	2.96 ***
	E2	15.07 ± 4.95	11.98 ± 4.83	2.58 ***
	E3	13.59 ± 2.67	10.69 ± 3.14	2.78 ***
TG	K	1.25 ± 0.03	1.26 ± 0.02	0.43
	E1	1.30 ± 0.04	0.96 ± 0.03	28.03 ***
	E2	1.29 ± 0.04	1.01 ± 0.02	17.41 ***
	E3	1.27 ± 0.03	1.07 ± 0.02	9.66 ***
HDL	K	1.40 ± 0.06	1.40 ± 0.05	0.10
	E1	1.45 ± 0.07	1.81 ± 0.07	40.68 ***
	E2	1.42 ± 0.07	1.73 ± 0.06	48.74 ***
	E3	1.41 ± 0.06	1.64 ± 0.04	9.73 ***
LDL	K	2.58 ± 0.04	2.59 ± 0.04	0.63 *
	E1	2.57 ± 0.04	2.11 ± 0.06	14.65 ***
	E2	2.58 ± 0.03	2.20 ± 0.04	17.03 ***
	E3	2.58 ± 0.05	2.16 ± 0.03	8.67 ***
TC	K	4.58 ± 0.05	4.59 ± 0.05	0.60 **
	E1	4.57 ± 0.06	3.74 ± 0.07	16.81 ***
	E2	4.58 ± 0.05	3.93 ± 0.06	25.18 ***
	E3	4.57 ± 0.04	3.87 ± 0.04	31.61 ***

* 0.05 <= p <= 0.1; ** p < 0.05; *** p < 0.01; BW—body weight; BMI—body mass index; TSF-TH—skinfold thickness (thigh); TSF-UA—skinfold thickness (upper arm); WC—waist circumference; BF%—body fat percentage; MM%—muscle mass percentage; TSF-AB—skinfold thickness (abdomen); TG—triglycerides; HDL—high-density lipoprotein; LDL—low-density lipoprotein; TC—total cholesterol.

), there were no significant changes in the final measurement compared to the initial measurement for the variables: skinfold of the arm (d = 0.28, p > 0.1), muscle percentage (d = 0.13, p > 0.1), triglycerides (d = 0.43, p > 0.1), and HDL (d = 0.10, p > 0.1). The skinfold of the thigh (d = 0.5, p < 0.1) and LDL (d = 0.63, p = 0.05) increased significantly at the 10% error probability level, and the skinfold of the abdomen (d = 0.62, p < 0.05) and cholesterol (d = 0.60, p < 0.05) at the 5% error probability level. Therefore, the effect of the control group’s condition on the thigh and abdominal skinfolds, LDL, and cholesterol is moderate. For all other variables, the participants in the control group showed statistically significant increases (strong effects of the control group’s condition) in the final measurement compared to the initial one (d ≥ 0.89, p < 0.01). It should be noted that the effect of the control group’s condition was opposite to the desired one (there was a deterioration in body characteristics). For all experimental groups, there was an improvement in body characteristics, i.e., a statistically significant desired effect, for all variables investigated (d ≥ 1.66, p < 0.01). Therefore, each of the investigated training programs was successful. By comparing Cohen’s d, it can be concluded which training program yielded the best results. It was shown that Cohen’s d was largest for the mix aerobics group for each of the body characteristic variables, indicating that the effect of this type of training was the greatest and, consequently, provided the best results. The scores for triglycerides, HDL, LDL, and cholesterol also significantly improved (decreased) in all experimental groups, with a very strong effect for each training program. For the first three scores, the best effect was achieved by the kickboxing group, while for cholesterol, the best effect was seen in the step aerobics group. The non-parametric Wilcoxon test confirms the obtained results and conclusions.

The results from

Table 4. Results of two-way analysis of variance with squared partial eta coefficient and p-value indicating the significance of the effect measured by this coefficient.

Variable	$\mathbf{Analysis} \mathbf{of} \mathbf{Variance} \mathit{p}\left({\mathit{\eta }}_{\mathit{p}}^2\right)$
	Group	Measurement	Group × Measurement
BW	0.879 (0.006)	0.004 (0.069) ***	0.235 (0.037)
BMI	0.658 (0.014)	0.012 (0.055) **	0.340 (0.029)
TSF-TH	0.098 (0.054) *	0.045 (0.035) **	0.674 (0.013)
TSF-UA	0.555 (0.013)	0.043 (0.035) **	0.688 (0.013)
WC	<0.001 (0.177) ***	<0.001 (0.108) ***	0.115 (0.050)
BF%	0.122 (0.049)	0.012 (0.054) **	0.313 (0.031)
MM%	0.025 (0.078) **	<0.001 (0.146) ***	0.070 (0.060) *
TSF-AB	0.058 (0.063) *	0.006 (0.066) ***	0.318 (0.030)
TG	<0.001 (0.725) ***	<0.001 (0.925) ***	<0.001 (0.825) ***
HDL	<0.001 (0.684) ***	<0.001 (0.800) ***	<0.001 (0.580) ***
LDL	<0.001 (0.829) ***	<0.001 (0.934) ***	<0.001 (0.827) ***
TC	<0.001 (0.904) ***	<0.001 (0.965) ***	<0.001 (0.900) ***

* 0.05 <= p <= 0.1; ** p < 0.05; *** p < 0.01; BW—body weight; BMI—body mass index; TSF-TH—skinfold thickness (thigh); TSF-UA—skinfold thickness (upper arm); WC—waist circumference; BF%—body fat percentage; MM%—muscle mass percentage; TSF-AB—skinfold thickness (abdomen); TG—triglycerides; HDL—high-density lipoprotein; LDL—low-density lipoprotein; TC—total cholesterol.

, provide us a significant effect of group membership (control, mix aerobics, kickboxing, step aerobics) when controlling for measurement (first or second) occurs for waist circumference with a significance threshold of less than 1% (p < 0.001), for muscle percentage with a significance threshold of 5% (p = 0.025), and for the skinfold of the thigh (p = 0.098) and the skinfold of the abdomen (p = 0.058) with a significance threshold of 10%. This effect explains 17.7% of the variability in waist circumference score, 7.8% in muscle percentage score, 5.4% in the skinfold of the thigh, and 6.3% in the skinfold of the abdomen. For the scores of triglycerides, HDL, LDL, and cholesterol, this effect explains 72.5%, 68.4%, 82.9%, and 90.4% of the variability, respectively. More precise information is provided below using post hoc tests (

Table 5. Post hoc test results for differences in effects between groups. Display of pairs for which a statistically significant difference was detected.

Variable	Pairs	Mean Difference	95% CI for the Mean
WC	K-E1	6.19 **	1.34	11.03
	K-E2	7.36 **	2.51	12.21
	K-E3	8.63 **	3.78	13.47
MM%	K-E2	−2.15 *	−4.26	−0.03
	K-E3	−2.29 *	−4.40	−0.17
TG	K-E1	0.13 **	0.11	0.15
	K-E2	0.11 **	0.09	0.13
	K-E3	0.08 **	0.06	0.10
	K-E2	−0.02 **	−0.04	0
	K1-E3	−0.05 **	−0.06	−0.03
	K2-E3	−0.03 **	−0.05	−0.01
HDL	K-E1	−0.23 **	−0.27	−0.19
	K-E2	−0.18 **	−0.22	−0.14
	K-E3	−0.13 **	−0.17	−0.09
	K-E2	0.05 **	0.02	0.09
	E1-E3	0.11 **	0.07	0.14
	E2-E3	0.05 **	0.01	0.09
LDL	K-E1	0.24 **	0.21	0.27
	K-E2	0.19 **	0.17	0.22
	K-E3	0.21 **	0.18	0.24
	E1-E2	−0.05 **	−0.08	−0.02
	E1-E3	−0.03 *	−0.06	0
TC	K-E1	0.43 **	0.40	0.47
	K-E2	0.33 **	0.29	0.37
	K-E3	0.37 **	0.33	0.40
	K-E2	−0.10 **	−0.14	−0.07
	E1-E3	−0.07 **	−0.10	−0.03

* p < 0.05; ** p < 0.01; K—control group; E1—mix aerobics; E2—kickbox; E3—step aerobics; WC—waist circumference; MM%—muscle mass percentage; TSF-AB—skinfold thickness (abdomen); TG—triglycerides; HDL—high-density lipoprotein; LDL—low-density lipoprotein; TC—total cholesterol.

).

The effect of measurement, i.e., the passage of time, when controlling for the impact of training is statistically significant with a significance threshold of 1% (p ≤ 0.006 < 0.01) for body weight, waist circumference, muscle percentage, and abdominal skinfold, and with a significance threshold of 5% for all other variables (p ≤ 0.045 < 0.05). The effect of time when controlling for the effects of different training programs explains the highest variability for waist circumference (10.8%) and muscle percentage (14.6%). For other body characteristic variables, this percentage is below 10%. For the scores of triglycerides, HDL, LDL, and cholesterol, this effect explains 92.5%, 80%, 93.4%, and 96.5% of the variability, respectively.

The interaction effect (joint simultaneous influence) of group membership and measurement is statistically significant with a significance threshold of 10% only for muscle percentage (p = 0.07). This interaction explains 6% of the variability in muscle percentage. The interaction of group and measurement on other variables is not statistically significant (p > 0.1). The percentage of variability in all other body characteristic variables explained by this interaction is less than 5%. For the scores of triglycerides, HDL, LDL, and cholesterol, the interaction effect of group membership and measurement explains 82.5%, 58%, 82.4%, and 90% of the variability, respectively.

Tukey’s post hoc test showed statistically significant differences in the effects between the groups, control and step aerobics (p = 0.045), and control and mix aerobics (p = 0.028) for the variable muscle percentage. The effects of the training programs in the mix aerobics, kickboxing, and step aerobics groups did not significantly differ from each other.

The effect of each group (mix aerobics, kickboxing, and step aerobics) on waist circumference was statistically significantly higher compared to the effect of the control group (p ≤ 0.006 < 0.05), but the effects between these groups did not significantly differ (p ≥ 0.510 > 0.05).

The effect of each group (mix aerobics, kickboxing, and step aerobics) on triglycerides was statistically significantly higher compared to the effect of the control group (p < 0.001 < 0.05). The effect of kickboxing was significantly greater than the effect of step aerobics (p = 0.003). The effect of mix aerobics was significantly greater compared to the effects of both kickboxing (p = 0.045) and step aerobics (p < 0.001).

The effect of each group (mix aerobics, kickboxing, and step aerobics) on HDL was statistically significantly higher compared to the effect of the control group (p = 0.001). The effect of kickboxing was significantly greater than the effect of step aerobics (p = 0.003). The effect of mix aerobics was significantly greater compared to the effects of both kickboxing (p = 0.002) and step aerobics (p = 0.001).

The effect of each group (mix aerobics, kickboxing, and step aerobics) on LDL was statistically significantly higher compared to the effect of the control group (p = 0.001). The effects of kickboxing and step aerobics did not significantly differ (p = 0.299). The effect of mix aerobics was significantly greater compared to the effects of both kickboxing (p = 0.001) and step aerobics (p = 0.037).

The effect of each group (mix aerobics, kickboxing, and step aerobics) on cholesterol was statistically significantly higher compared to the effect of the control group (p = 0.001). The effects of kickboxing and step aerobics did not significantly differ (p = 0.055). The effect of mix aerobics was significantly greater compared to the effects of both kickboxing and step aerobics (p = 0.001).

When the effect of measurement is not controlled, ANOVA shows no statistically significant difference in values for different groups of participants for all variables except triglycerides in the initial measurement (F ≤ 2.017, p ≥ 0.122 > 0.1). Therefore, all participants, regardless of whether they underwent any training, have statistically equal scores for the research variables in the initial measurement. It is notable that in the initial measurement, the triglyceride score for participants in the mix aerobics group was significantly higher compared to the control group participants (p = 0.004). This, however, further emphasizes the effect of that training.

In the final measurement, the training programs resulted in no significant differences between groups for body weight (F = 1.088, p = 0.362), body mass index (F = 1.295, p = 0.285), and skinfold of the arm (F = 1.226, p = 0.308). For the skinfold of the thigh, a statistically significant difference in values between at least two groups occurs, but only when the error probability is 10% (F = 2.219, p = 0.096), so the significance of the difference cannot be reliably asserted in this case. When the error probability is 5%, a significant difference in scores between at least two groups occurs for body fat percentage (F = 2.891, p = 0.043) and abdominal skinfold (F = 3.179, p = 0.031). A statistically significant difference in values between at least two groups can reliably be asserted for waist circumference (F = 8.876, p = 0.01) and muscle percentage (F = 2.891, p = 0.002).

4. Discussion

The objective of this study was to investigate the impact of various group exercise programs on anthropometric characteristics, body composition, and lipid status in young women. All three experimental groups had statistically significant increases in key health indices, demonstrating the efficacy of structured aerobic exercise. These findings are consistent with prior research that has confirmed the importance of physical activity in improving cardiovascular health, lipid profiles, and overall physical fitness [46].

All training sessions lasted 45 min, with exercise intensity ranging from 60% to 85% of maximal heart rate, which allowed for adequate stimulation of body systems without the risk of overtraining. After the program implementation, a reduction in body weight, waist circumference, body fat percentage, LDL, total cholesterol, and triglycerides was recorded, while muscle mass and HDL increased simultaneously. Statistically significant reductions were observed in all skinfolds, as well as in BMI, which also showed a decrease in the final measurement compared to the initial state, further confirming the effectiveness of physical activity in the prevention and treatment of metabolic disorders and the preservation of muscle mass, which is particularly important for young women. Given that the participants in the control group were not involved in physical activity during the study, it was not expected that any significant changes would occur in the measured parameters, further validating the efficacy of the tested programs in inducing positive changes.

The results of this study showed significant changes in anthropometric parameters in participants who participated in different group fitness programs. In all experimental groups, body weight and waist circumference decreased, with the most significant changes observed in the mix aerobics group (−6.53% for body weight and −9.00% for waist circumference), followed by the kickboxing aerobics group (−5.99% for body weight and −8.09% for waist circumference), while the smallest changes were noted in the step aerobics group (−5.81% for body weight and −6.76% for waist circumference). Similar findings were reported by Širić et al. [47], who emphasized that aerobic training leads to significant reductions in body weight and waist circumference in women of various age groups. The results of our study are also consistent with the studies of Stojiljković et al. [48] and Obrovac [49], which confirmed the effectiveness of various forms of aerobic training in reducing body weight in women. Studies by Pantelic et al. [50] and Spirtovic et al. [30] showed that programmed aerobic training leads to a reduction in waist circumference in women, further supporting the findings of this study.

Regarding skinfolds, significant differences were observed in the final measurement compared to the initial measurement in all three groups. In the group practicing mix aerobics, the thigh skinfold decreased by −15.74%, the upper arm skinfold by −26.42%, and the abdominal skinfold by −26.44%. In the group practicing kickboxing aerobics, the following changes were recorded: the thigh skinfold decreased by −14.48%, the upper arm skinfold by −26.50%, and the abdominal skinfold by −20.53%. The group practicing step aerobics showed the following results: the thigh skinfold decreased by −13.82%, the upper arm skinfold by −22.04%, and the abdominal skinfold by −21.34%. These results clearly indicate the effectiveness of all these aerobic programs in reducing subcutaneous fat tissue. The results of our research align with the findings of Hrgetić et al. [51], who also emphasized the importance of aerobic exercises in reducing subcutaneous fat, where the upper arm skinfold decreased by −20.21%, and the abdominal skinfold decreased by −15.70%, confirming the positive effects of the applied aerobic programs. Differences among the groups can be explained by varying exercise intensity and focus—while the mix and kickboxing aerobics programs included high-intensity segments, step aerobics relied more on moderate intensity and movement coordination.

Body composition analysis showed significant changes in reducing body fat percentage and increasing muscle mass in all groups. The greatest reduction in body fat percentage was recorded in the mix aerobics group (−11.58%), followed by the kickboxing aerobics group (−9.60%), and the smallest in the step aerobics group (−7.47%). Furthermore, in these same groups, significant improvements were observed in the body mass index (BMI), where BMI decreased by −6.47% in the mix group, −5.92% in the kickboxing group, and −5.74% in the step group, while muscle mass percentage after the experimental program showed the highest values in the mix aerobics group (+18.27%), followed by the kickboxing aerobics group (+16.85%), and the smallest in the step aerobics group (+11.57%). All of this indicates the positive effects of these programs in reducing BMI and improving overall body composition. Similar findings were confirmed in the study by Špirtović et al. [30], which showed that such forms of aerobic training can have a positive effect on body composition in young women. Kyröläinen et al. [52] also showed that high-intensity aerobic training can result in greater reductions in body fat percentage compared to moderate-intensity training. Exercise, particularly aerobic training, effectively reduces visceral fat and improves body composition in individuals with excess body weight or obesity, which can significantly improve their cardiometabolic health [53]. Davis et al. [54] determined that all forms of exercise are more effective than inactivity, with aerobic training contributing the most to improving fitness and reducing body weight, while low-load training has the greatest effect on reducing body fat in obese women. Our results further confirm these findings, highlighting the superior effects of high-intensity aerobic training (mix and kickboxing aerobics) over step aerobics, which proved more effective in improving coordination and endurance than in reducing body fat percentage.

Regarding lipid profile, the results show significant positive changes in reducing triglycerides, total cholesterol, and LDL cholesterol, while simultaneously increasing HDL cholesterol. The greatest reduction in triglycerides was recorded in the mix aerobics group (−26.27%), followed by the kickboxing aerobics group (−21.29%), while the smallest reduction was observed in the step aerobics group (−15.48%). The reduction in total cholesterol was most pronounced in the mix aerobics group (−18.12%), step aerobics group (−15.32%), and least in the kickboxing aerobics group (−14.33%). A reduction in LDL was also noted in the mix aerobics group (−17.86%), step aerobics group (−15.99%), and least in the kickboxing aerobics group (−14.97%). The positive impact of these programs was also reflected in HDL, where the mix aerobics group increased by (+25.11%), the kickboxing aerobics group by (+21.79%), and the step aerobics group by (+16.84%). These results are consistent with studies by Chavarrias et al. [55], Kyröläinen et al. [52], and Devries et al. [56], which confirmed the positive impact of aerobic exercises on lipid profile, particularly through increasing HDL and reducing LDL cholesterol.

Our results align with findings from Haxhi et al. [20] and Mei et al. [21], who confirmed that exercise affects the regulation of triglyceridemia in healthy individuals. Increased physical activity contributes to the improvement of health indicators, such as reduced blood pressure, decreased insulin resistance, and normalization of lipid profile [21,57], as confirmed by our results regarding lipid profile. Furthermore, Zaer Ghodsi et al. [58] showed that high-intensity aerobic training can have significant effects on reducing LDL cholesterol and total cholesterol, which is also in line with the results of our study, while Dandanell et al. [59] highlighted that spinning exercises, which are similar in intensity to kickboxing aerobics, can lead to greater energy expenditure, positively affecting lipid profile improvement. Yamaner et al. [60] pointed out that a six-week aerobic exercise program significantly improved lipid profiles in sedentary women, increasing HDL by 15.8% and reducing LDL by 15.7%, indicating the potential of aerobic activities such as spinning to reduce the risk of cardiovascular diseases. Our results further confirm these findings, indicating that high-intensity aerobic exercises, such as kickboxing and mix aerobics, may have superior effects on reducing triglyceride levels compared to lower-intensity training, such as step aerobics. Higher-intensity training (70–85% maximal heart rate) proved more effective for reducing body fat and improving lipid profile, while moderate-intensity training (60–75%) also had significant benefits, especially in individuals with lower physical activity levels. Aerobic exercise particularly improves lipoprotein–lipid profile, cardiorespiratory fitness, and body composition in young women [8,21,61,62]. In addition to significantly reducing triglycerides, LDL cholesterol, and total cholesterol, while simultaneously increasing HDL cholesterol, the improvement in lipid metabolism indicates the positive effect of these programs on the metabolic state of participants.

Long-term physical activity maintenance is crucial for achieving lasting benefits, with the combination of aerobic exercises and strength training further contributing to the preservation of muscle mass and functional strength. These findings align with research by Spiering et al. [63], who emphasized that performance adaptations to endurance and strength training are relatively well-maintained in the general population, despite significant reductions in training frequency (up to 66%) and volume (33–66%), if adequate training intensity is maintained.

4.1. Strengths of the Study

This study benefits from a randomized controlled design, a relatively large sample size for an exercise intervention in this demographic, and comprehensive tracking of multiple health parameters, including anthropometric indices, body composition, and lipid profile biomarkers.

The use of three distinct aerobic modalities allows for a comparative analysis of their relative efficacy, an approach that is rarely explored in similar studies. Training intensity was rigorously monitored and personalized, increasing interval validity. Furthermore, the 12-week duration proved sufficient to detect statistically significant changes across a broad range of outcomes.

4.2. Limitations of the Study

Despite the robust design, several limitations should be acknowledged. First, the 12-week duration may not reflect the long-term sustainability of the observed improvements. Second, the study sample included only young adult women, limiting the generalizability across sexes and age groups. Third, while participants were instructed to maintain their usual diet, no nutritional tracking was conducted, which may have influenced body composition and lipid outcomes. Fourth, although stable body weight was required as an inclusion criterion, it was assessed through self-report at baseline. This approach may have introduced bias or inaccuracies, which could partly explain the statistically significant weight gain observed in the control group over the 12-week period. Such changes are not unexpected in sedentary populations and may result from unmonitored shifts in behavior, such as decreased incidental activity or increased caloric intake. Fifth, although the International Physical Activity Questionnaire (IPAQ) was used to screen participants and exclude those with high activity levels, baseline IPAQ scores were not statistically compared between groups. This may represent a potential confounding factor, as small pre-existing differences in habitual physical activity could have influenced the outcomes. Future studies should include objective or standardized assessments of physical activity as part of the baseline comparison. Lastly, point-intervention follow-up data were not collected, making it difficult to assess the persistence of the effects over time.

Future research should incorporate longer intervention and follow-up periods, objective dietary tracking, and a more diverse population. Additionally, comparative trials involving combined aerobic and resistance training versus aerobic-only interventions could yield valuable insights for optimizing exercise prescriptions aimed at metabolic health.

5. Conclusions

The present study provides strong evidence that various group fitness programs, particularly those involving higher-intensity aerobic exercises such as mix and kickboxing aerobics, significantly improve anthropometric measures, body composition, and lipid profiles in overweight young women. These high-intensity formats demonstrated superior results in reducing body fat and improving cardiovascular health indicators. Furthermore, all programs contributed to increases in muscle mass, reinforcing the benefits of structured group fitness activities for enhancing overall health, physical fitness, and well-being in this population.

While the findings are promising, they should be interpreted within the study’s limitations, including its duration and participants’ demographics. Nevertheless, these results support the integration of targeted group fitness interventions into public health and clinical strategies aimed at young adult populations.