Abstract
Sedentary behavior (SB) is a growing global health concern, particularly among bank employees, contributing to NCDs and increased mortality. While exercise and dietary modifications are recognized as effective interventions, their combined impact remains underexplored. This randomized controlled trial examined the impact of an integrated exercise and dietary counseling program on physiological biomarkers in sedentary bank employees. Forty participants (mean age: 47.55 ± 4.07 years) were randomly assigned to one of four groups: aerobic, resistance, or combined exercise (all with dietary counseling), or a control group (n = 10 each). Over the 12-week period, significant improvements (p < 0.001) were observed in pre- to post-intervention measurements of physiological markers, including Body Mass Index (BMI), Systolic Blood Pressure (SBP), Diastolic Blood Pressure (DBP), and Resting Heart Rate (RHR), among the intervention groups. The statistical analysis in MANOVA indicated a significant inter-group differences for BMI (F(3,36) = 58.554, p = 0.001, η² = 0.830), SBP (F(3,36) = 32.155, p = 0.001, η² = 0.728), DBP (F(3,36) = 27.288, p = 0.001, η² = 0.695), and RHR (F(3,36) = 37.274, p = 0.001, η² = 0.756). Post-hoc analysis revealed that all intervention groups showed statistically significant improvements (p < 0.001) in all measured biomarkers compared to the control group. Moreover, aerobic and combined exercise interventions alongside dietary counseling groups demonstrated significant improvements over other groups.
Keywords: Aerobic exercise, Resistance exercise, Combined exercise, Dietary counseling, Sedentary behavior, Physiological biomarkers
Subject terms: Physiology, Biomarkers
Introduction
Sedentary behavior (SB), defined as any waking activities characterized by sitting or reclining with an energy expenditure of ≤ 1.5 metabolic equivalents (METs)1, has become a major global public health concern2. Driven by urbanization and technological advances, SB significantly contributes to the rise of non-communicable diseases (NCDs) and premature mortality worldwide3,4. This phenomenon has far-reaching social, economic, and health implications5. Once predominantly observed in high-income countries, SB is now increasingly prevalent in low- and middle-income countries, including sub-Saharan Africa, particularly Ethiopia6,7. Prolonged sedentary time negatively affects physiological biomarkers related to body composition, blood pressure, glucose metabolism, and lipid profiles8, increases the risk of adults developing two or more chronic diseases9,10.
Non-communicable diseases are a major health challenge in low- and middle-income countries, such as Ethiopia11, account for over 73% of global deaths12, and contribute to approximately 39% of deaths in Ethiopia13. Among Ethiopian adults, 15.8% have high BP14, 19.2% are overweight and 10.3% are obese15, and the prevalence of diabetes is estimated at 2.8%16. Bank employees in Ethiopia are particularly vulnerable to NCDs such as high BP, diabetes, and related conditions due to prolonged sitting, high stress, poor diet, low health awareness, and increasing rates of obesity17–20. Across Africa, the prevalence of high BP among bank workers ranges from 12.4% to 52.4%21,22.
Physical inactivity in the banking sector is associated to increased obesity, hypertension, and diabetes23–25. Adult males, who make up the majority of the office employees in Ethiopia, are a crucial demographic that needs specific health interventions13,26. While pharmacological treatments for NCDs are common, their limitations such as poor adherence, cost barriers, and dependency have shifted attention toward lifestyle interventions27. Aerobic, resistance, and combined exercise training modalities are widely recognized for their efficacy in managing NCDs and mitigating SB-related health burdens28–30. Additionally, dietary modifications significantly improve physiological markers associated with these diseases31,32; however, dietary counseling remains underutilized in most programs33.
The main gap in existing research is the lack of comprehensive evidence on the combined effects of different exercise modalities (aerobic, resistance, and combined) alongside dietary counseling on some selected physiological biomarkers, such as BMI, resting heart rate (RHR), systolic blood pressure (SBP), and diastolic blood pressure (DBP) among sedentary bank employees. Addressing this gap through a randomized controlled trial with a factorial design enables simultaneous evaluation of multiple interventions and their interactions on key physiological biomarkers. Therefore, the main objective of this study was to examine the 12-week effects of various exercise modalities combined with dietary counseling on physiological outcomes in sedentary adult male bank employees. It was hypothesized that a 12-week intervention of aerobic, resistance, or combined exercise with dietary counseling would lead to significant improvements in physiological biomarkers, including body mass index (BMI), resting heart rate (RHR), and blood pressure (BP), compared to a control group of sedentary adults. Additionally, it was expected that aerobic and combined exercise interventions with dietary counseling would produce greater reductions in these biomarkers than resistance exercise with dietary counseling alone.
Methods and materials
Participants
This study included 40 sedentary adult men (mean age: 47.55 ± 4.07 years) recruited from inactive bank employees in Debre Markos city, Amhara regional state, Ethiopia. We informed potential participants about the study through local radio announcements and notice board postings. Ethical approval was obtained from the Addis Ababa University, College of Natural and Computational Science Institutional Review Board (CNS-IRB) committee (approval number: CNCS: 06/2017/2025). All procedures were conducted in accordance with the ethical principles of the Declaration of Helsinki, as revised in 2000. Prior to the intervention, written informed consent was obtained from all participants after they were fully informed of the study’s details and potential risks. The follow-up period for the study was from January 20, 2025, to April 20, 2025.
Eligibility criteria
Inclusion criteria were: (a) BMI between 18.5 and 29.9 kg/m² (normal weight to overweight), a range critical for investigating the impact of lifestyle interventions on health outcomes and for obesity prevention34,35; (b) volunteer to participate; and (c) adults WHO were sedentary, meaning they did not meet the recommended physical activity guidelines of 30–60 min per day (or 150 min per week) of moderate-intensity exercise, or 20–60 min per day (or 75 min per week) of vigorous-intensity exercise36. (d) To ensure the safety of participants during the intervention, we used a medical history form and the Physical Activity Readiness Questionnaire (PAR-Q) to specifically target individuals who were physically inactive. The exclusion criteria were: (a) any musculoskeletal disorders that would prevent physical exercise, (b) diabetes with a fasting blood sugar level of ≥ 126 mg/dl and high blood pressure (resting blood pressure ≥ 140/90), (c) active infection, and (d) recent myocardial infarction, surgery, or severe liver dysfunction.
Study design
This study used a 12-week randomized controlled trial with a factorial design to evaluate the effects of combined exercise and dietary counseling on physiological biomarkers in sedentary bank employees. This gold-standard design was chosen to ensure methodological rigor, reduce bias, and allow for clear causal interpretation37. The participants were randomly assigned to one of three training groups or a control group. Each of the four groups consisted of 10 participants: the aerobic exercise with dietary counseling group (AE + DC), the resistance exercise with dietary counseling group (RE + DC), the combined exercise with dietary counseling group (CE + DC), and the control group (CG). The clinical trial was prospectively registered with the Pan African Clinical Trial Registry on 09 January 2025 (Registration Number: PACTR202501649861961). Registration details can be accessed at: https://pactr.samrc.ac.za. The study followed CONSORT guidelines for rigorous and transparent reporting of clinical trials38.
Fifty-five sedentary adults were screened; 7 were excluded for not meeting the inclusion criteria, resulting in 48 eligible participants. The required sample size was calculated using G*Power software (version 3.1.9.7; Heinrich-Heine-Universität Düsseldorf, Germany), based on prior research conducted by39. The sample size calculation was based on a Cohen’s f effect size of 0.442, corresponding to an expected mean difference of 9.3 mg/dL in LDL-C levels between groups. Assuming a two-sided alpha level of 0.05 and a statistical power (1–β) of 80%, the analysis indicated that 28 participants would be required. To account for a projected 30% dropout rate, the target sample size was increased to 40 participants. These 40 participants were selected from a pool of 48 eligible individuals (Fig. 1).
Fig. 1.
Participant flow chart BP = blood pressure, AE + DC: aerobics exercise with dietary counseling, RE + DC: resistance exercise with dietary counseling, CE + DC: combined exercise with dietary counseling.
To minimize potential bias, trained research personnel oversaw the participant randomization and intervention assignment. Given the study’s small sample size and the need for balanced baseline characteristics, a stratified randomization approach was employed. Participants were stratified by age and Body Mass Index (BMI) categories to ensure equitable group distribution and improve internal validity. Within each stratum, participants were randomly allocated to one of the four study groups in a 1:1:1:1 ratio using a sealed-envelope lottery method. To further minimize bias, blinding procedures were implemented where feasible. In particular, outcome assessors were blinded to group allocation to reduce the risk of observer bias during data collection and outcome evaluation.
Measurement of study variables
Measurement of BMI
The body mass index was calculated by dividing the body weight in kilograms by the height in meters squared (kg/m2)40, using a standard stadiometer (Height & Weight Scale ZT-160 – NSL). Participants were directed to remove their shoes and wear minimal clothing, during weight measurements to ensure accuracy41.
Measurement of blood pressure (BP) and resting heart rate (RHR)
Blood pressure, including both SBP and DBP, as well as RHR, was measured simultaneously using a validated automated oscillometric device (Rossmax Medical, Cincinnati, USA)42. Qualified clinical staff with experience in BP assessment ensured proper technique. The monitor was calibrated before each measurement to maintain accuracy and consistency. Prior to each measurement, the automated oscillometric blood pressure monitor was calibrated to guarantee accurate and consistent readings. To standardize conditions, all measurements were taken between 9:00 a.m. and 12:00 p.m. on the same day, following 5 to 10-minute rest period43. They were also instructed to abstain from caffeine, alcohol, and exercise for at least approximately 30 min to several hours before measurement to ensure accuracy44. An appropriately sized cuff was placed on the participant’s left upper arm while they remained relaxed and motionless on the examination table. After recording standard brachial blood pressure, the cuff was reinflated to sub-diastolic pressure to capture volumetric waveforms for five seconds. Participants were instructed to remain still and keep their arm relaxed during the procedure. Two readings were taken for each participant, and the average was used for analysis.
Interventions
Exercise interventions
The exercise intervention program followed the American College of Sports Medicine (ACSM’s) exercise testing and prescription recommendations45. Except for the non-exercise control group, participants trained for 60 min per session, including 10–15 min of warm-up and dynamic stretching, 45–50 min of main exercises, and 10–15 min of cooldown and static stretching29. The training load progressively increased, adjusting intensity, sets, and repetitions. All training sessions were overseen by qualified health fitness professionals and exercise physiologists, who ensured proper execution, provided constructive feedback, and offered motivation to participants. Participants were randomly assigned to one of four groups: an aerobic exercise with dietary counseling (AE + DC) group, a resistance exercise with dietary counseling (RE + DC) group, a combined exercise with dietary counseling (CE + DC) group, or a control group (CG). All intervention groups completed a 12-week training program consisting of three sessions per week, for a total of 36 sessions. These sessions were held at the Debre Markos University gymnasium. Participant compliance was monitored by tracking attendance. Only individuals WHO attended at least 80% of the scheduled sessions (≥ 29 out of 36) were included in the final analysis46.
Aerobic exercise intervention
The aerobic exercise intervention group participated in training sessions three times per week, each lasting 60 min. These sessions utilized treadmills (Cybex 530 T Pro plus USA), recumbent bicycles (Biodex LBC, Biodex Inc., New York, NY, USA), and elliptical cross-trainers (Cybex)46,47. Training intensity commenced at 50–70% of maximal heart rate (HRmax) for the first six weeks, subsequently increasing to 70–85% for the remaining six weeks. Participants wore the Polar H7 heart rate monitor (Polar Electro, Kempele, Finland) during each exercise session to record maximum heart rate. The device, placed on the sternum via a flexible plastic sensor (2.4 × 27.9 cm), samples at 1000 Hz and shows high agreement with ECG across exercise modalities48. Exercise intensity was maintained below 85% of maximum heart rate (MHR), which was estimated using the Gellish et al. formula due to the wide age range of participants49. Each session adhered to a circuit training format, incorporating 15–20 min segments per machine, interspersed with 1–2 min rest periods between sets.
Resistance exercise intervention
The resistance exercise intervention group’s protocol involved 9 distinct exercises: leg press, hamstring curl, quadriceps extension, chest press, lat pulldown, shoulder press, biceps curl, triceps extension, and abdominal crunch. These sessions were conducted 3 times per week, each lasting 60 min46,47. Each workout comprised 3 sets of 8–12 repetitions, performed at an intensity of 50–80% of participants’ one-repetition maximum (1RM). The training followed a circuit format, which included 15–20 s intervals between exercises and 1–2 min rest periods between sets.
Combined exercise intervention
The combination exercise (CE) intervention group completed sessions comprising approximately 23–25 min of aerobic exercise and 23–25 min of resistance exercise, for a total of 45–50 min of main exercise. Each session also incorporated a total of 10–15 min for both warm-up and cooldown periods combined46,47, resulting in an overall session duration of approximately 60 min. Participants adhered to the same intensity and general protocol as the individual aerobic and resistance training groups previously described. Specifically, the resistance training component was modified to include 6 exercises instead of 9 (excluding leg press, lat pulldown, and shoulder press), and 2 sets instead of 3. The exercise order was standardized, with most participants performing resistance exercise prior to aerobic exercise to minimize fatigue and preserve strength performance, ensuring proper form and training intensity45,50. The details of the general exercise intervention approach were outlined in Table 1.
Table 1.
Training protocol details.
| Week/s | Intensity | Duration | ||||||
|---|---|---|---|---|---|---|---|---|
| AE(HRmax) | RE(1RM) | CE | AE (minutes) |
RE (3 sets) |
CE | |||
| AE | RE | AE | RE | |||||
| Week 1 & 2 | 50 to 55% | 50 to 55% | 50 to 55% | 50 to 55% | 45 | 8 to 12 | 23 | 8 to 12 |
| Week 3 & 4 | 55 to 60% | 55 to 60% | 55 to 60% | 55 to 60% | 45 | 8 to 12 | 23 | 8 to 12 |
| Week 5 & 6 | 60 to 65% | 60 to 65% | 60 to 65% | 60 to 65% | 45 | 8 to 12 | 23 | 8 to 12 |
| Week 7 & 8 | 65 to 70% | 6 5 to 70% | 65 to 70% | 6 5 to 70% | 50 | 8 to 12 | 25 | 8 to 12 |
| Week 9 & 10 | 70 to 75% | 70 to 75% | 70 to 75% | 70 to 75% | 50 | 8 to 12 | 25 | 8 to 12 |
| Week 11 & 12 | 75 to 85% | 75 to 80% | 75 to 85% | 75 to 80% | 50 | 8 to 12 | 25 | 8 to 12 |
Dietary counseling
Before the dietary counseling intervention began, all participants, including those in the control group, completed Food Frequency Questionnaires (FFQs) on three random days (fasting, non-fasting, and weekend days) at both baseline and post-intervention to assess their dietary habits. These assessments revealed a high intake of unhealthy foods across the entire study population at baseline, including high-glycemic index foods, animal-based products, alcohol, sugar, salt, fatty foods, and caffeine, along with a low intake of vegetables, fruits, cereals, and water. Only the intervention groups received the same standardized dietary counseling based on the DASH guidelines46,47,51, delivered by trained dietitians in 30-minute sessions three times per week. This standardization ensured a consistent dietary effect across intervention groups, allowing any differences in outcomes to be attributed primarily to the exercise intervention. The control group did not receive any dietary counseling; their dietary habits were monitored solely for comparative analysis, enabling us to isolate the effects of exercise and dietary counseling interventions on physiological biomarkers and dietary behavior.
Statistical analysis
All statistical analyses were conducted using SPSS version 27.0 (SPSS Inc., Chicago, IL, USA), with the significance level set at p < 0.05. Both descriptive statistics (means and standard deviations) and inferential statistics were employed. Prior to conducting a Multivariate Analysis of Variance (MANOVA), key assumptions were tested: multivariate normality was assessed using the Shapiro-Wilk test; homogeneity of variance-covariance matrices was evaluated with Box’s M test; and multicollinearity was examined through correlation matrices and variance inflation factors (VIFs). Paired-sample t-tests were used to compare pre- and post-intervention means within each group. MANOVA was then performed to determine significant differences between the intervention and control groups, followed by Bonferroni post-hoc tests to identify specific group differences.
Results
Characteristics of study participants
Table 2 summarizes the data’s descriptive characteristics at baseline, along with the normality test results. All 40 adult male participants completed the study program successfully and each group was assigned 10 subjects: AE + DC, RE + DC, CE + DC and the control group. There were no significant differences between groups at baseline in BMI, SBP, DBP, and RHR. A Shapiro-Wilk test confirmed normal data distribution and Box’s M test was not significant (p > 0.05), indicating that the assumption of homogeneity of variance-covariance matrices was met.
Table 2.
Baseline data and normality test.
| Variables | Type of groups | Mean (SD) | Normality test | |
|---|---|---|---|---|
| (Shapiro-wilk test) | ||||
| Statistics | P-value | |||
| Age, Years | AE + DC group | 48.00 ± 4.14 | 0.91 | 0.281 |
| RE + DC group | 47.20 ± 4.34 | 0.893 | 0.184 | |
| CE + DC group | 47.60 ± 3.86 | 0.908 | 0.269 | |
| Control group | 47.4 0 ± 4.53 | 0.917 | 0.333 | |
| BMI, kg/m2 | AE + DC group | 25.11 ± 1.60 | 0.886 | 0.153 |
| RE + DC group | 25.00 ± 1.70 | 0.88 | 0.132 | |
| CE + DC group | 25.10 ± 1.52 | 0.929 | 0.441 | |
| Control group | 25.30 ± 1.34 | 0.932 | 0.466 | |
| SBP, mmHg | AE + DC group | 123.70 ± 7.09 | 0.851 | 0.06 |
| RE + DC group | 123.40 ± 6.54 | 0.855 | 0.067 | |
| CE + DC group | 123.80 ± 5.47 | 0.859 | 0.075 | |
| Control group | 123.10 ± 7.13 | 0.863 | 0.082 | |
| DBP, mmHg | AE + DC group | 82.40 ± 4.86 | 0.89 | 0.171 |
| RE + DC group | 82.00 ± 4.55 | 0.859 | 0.074 | |
| CE + DC group | 82.30 ± 3.97 | 0.928 | 0.43 | |
| Control group | 82.70 ± 4.08 | 0.938 | 0.531 | |
| RHR, bpm | AE + DC group | 83.30 ± 4.85 | 0.881 | 0.134 |
| RE + DC group | 83.10 ± 4.86 | 0.981 | 0.969 | |
| CE + DC group | 83.80 ± 4.94 | 0.937 | 0.522 | |
| Control group | 83.00 ± 3.89 | 0.923 | 0.380 | |
BMI = body mass index, SBP = systolic blood pressure, DBP = diastolic blood pressure, RHR = resting heart rate, MD = mean difference, SD = standard deviation, AE + DC = aerobic exercise with dietary counseling, RE + DC = resistance exercise with dietary counseling, CE + DC = combined exercise with dietary counseling.
At baseline, the average ages of participants were AE + DC (48.00 ± 4.14), RE + DC (47.20 ± 4.34), CE + DC (47.60 ± 3.86), and CG (47.40 ± 4.53). BMI values were similar across all groups: AE + DC (25.11 ± 1.60), RE + DC (25.00 ± 1.70), CE + DC (25.10 ± 1.52), and CG (25.30 ± 1.34). SBP values were similar across all groups: AE + DC (123.70 ± 7.09), RE + DC (123.40 ± 6.54), CE + DC (123.80 ± 5.47), and CG (123.10 ± 7.13). DBP levels were comparable across all groups: AE + DC (82.40 ± 4.86), RE + DC (82.00 ± 4.55), CE + DC (82.30 ± 3.97), and CG (82.70 ± 4.08). Similarly, RHR values were comparable: AE + DC (83.30 ± 4.85), RE + DC (83.10 ± 4.86), CE + DC (83.80 ± 4.94), and CG (83.00 ± 3.89). Overall, the participants’ average age, BMI, SBP, DBP, and RHR were comparable across all groups. This suggests effective randomization, with no baseline impacts on the intervention.
Results of paired t-tests comparing pre- and post-intervention biomarker changes
Table 3 presents paired t-test results comparing intragroup changes in BMI, SBP, DBP, and RHR after the intervention. In the AE + DC group, BMI [t (9) = −16.54, MD = −4.91 kg/m², p < 0.001], SBP [t (9) = −12.59, MD = −18.40 mmHg, p < 0.001], DBP [t (9) = −12.66, MD = −12.20 mmHg, p < 0.001], and RHR [t (9) = −15.10, MD = −14.20 bpm, p < 0.001] were significantly decreased. In the RE + DC group, there were significantly decreased BMI [t (9) = −15.06, MD = −2.30 kg/m², p < 0.001], SBP [t (9) = −15.90, MD = −9.90 mmHg, p < 0.001], DBP [t (9) = −9.24, MD = −6.50 mmHg, p < 0.001], and RHR [t (9) = −10.47, MD = −8.80 bpm, p < 0.001]. In the CE + DC group, BMI [t (9) = −20.98, MD = −5.65 kg/m², p < 0.001], SBP [t (9) = −23.78, MD = −19.50 mmHg, p < 0.001], and DBP [t (9) = −16.83, MD = −12.30 mmHg, p < 0.001] were significantly decreased. In contrast, the control group (CG) BMI [t (9) = 1.92, MD = 0.40 kg/m², p = 0.087]; SBP [t (9) = 1.43, MD = 2.00 mmHg, p = 0.186]; DBP [t (9) = 1.00, MD = 0.60 mmHg, p = 0.343]; and RHR [t (9) = 1.69, MD = 1.20 bpm, p = 0.126] did not show statistically significant changes. All intervention groups showed statistically significant improvements (p < 0.001), while the control group showed no statistically significant changes.
Table 3.
Comparison of pretest and posttest mean differences using a paired sample t-test.
| Variables | Types of group | 95% Confidence Interval of the Difference |
||||||
|---|---|---|---|---|---|---|---|---|
| MD | Std. deviation | Lower | Upper | t | df | P value | ||
| BMI, kg/m2 | AE + DC group | −4.91 | 0.94 | −5.58 | −4.24 | −16.54 | 9 | < 0.001 |
| RE + DC group | −2.30 | 0.48 | −2.65 | −1.95 | −15.06 | 9 | < 0.001 | |
| CE + DC group | −5.65 | 0.85 | −6.26 | −5.04 | −20.98 | 9 | < 0.001 | |
| Control group | 0.40 | 0.66 | −0.07 | 0.87 | 1.92 | 9 | 0.087 | |
| SBP, mmHg | AE + DC group | −18.40 | 4.62 | −21.71 | −15.09 | −12.59 | 9 | < 0.001 |
| RE + DC group | −9.90 | 1.97 | −11.31 | −8.49 | −15.90 | 9 | < 0.001 | |
| CE + DC group | −19.50 | 2.59 | −21.36 | −17.65 | −23.78 | 9 | < 0.001 | |
| Control group | 2.00 | 4.42 | −1.16 | 5.16 | 1.43 | 9 | 0.186 | |
| DBP, mmHg | AE + DC group | −12.20 | 3.08 | −14.38 | −10.02 | −12.66 | 9 | < 0.001 |
| RE + DC group | −6.50 | 2.22 | −8.09 | −4.91 | −9.24 | 9 | < 0.001 | |
| CE + DC group | −12.30 | 2.31 | −13.95 | −10.6 | −16.83 | 9 | < 0.001 | |
| Control group | 0.60 | 1.90 | −0.76 | 1.96 | 1.00 | 9 | 0.343 | |
| RHR, bpm | AE + DC group | −14.20 | 2.97 | −16.33 | −12.07 | −15.10 | 9 | < 0.001 |
| RE + DC group | −8.80 | 2.66 | −10.70 | −6.90 | −10.47 | 9 | < 0.001 | |
| CE + DC group | −14.60 | 2.50 | −16.39 | −12.80 | −18.44 | 9 | < 0.001 | |
| Control group | 1.20 | 2.25 | −0.41 | 2.81 | 1.69 | 9 | 0.126 | |
BMI = body mass index, SBP = systolic blood pressure, DBP = diastolic blood pressure, RHR = resting heart rate, MD = mean difference, AE + DC = aerobic exercise with dietary counseling, RE + DC = resistance exercise with dietary counseling, CE + DC = combined exercise with dietary counseling.
Comparison of BMI, SBP, DBP, and RHR using MANOVA in sedentary adults
Table 4 showed that the primary objective of this study was to determine the most effective intervention modalities for enhancing key study variables, including BMI, SBP, DBP, and RHR. To address this, a multivariate analysis of variance (MANOVA) was conducted, followed by Bonferroni-corrected post-hoc tests, to ascertain the differential impact of each training intervention. The MANOVA results revealed significant multivariate differences among the intervention and control groups across all measured variables: BMI F (3, 36) = 58.554, p < 0.001, η² = 0.830; SBP F (3, 36) = 32.155, p < 0.001, η² = 0.728; DBP F (3, 36) = 27.288, p < 0.001, η² = 0.695; and RHR F (3, 36) = 37.274, p < 0.001, η² = 0.756. The post-hoc Bonferroni tests (detailed in Table 4) provided more specific insights into the effectiveness of each group: All three intervention groups (AE + DC, RE + DC, and CE + DC) Showed statistically significant reductions in BMI, SBP, DBP, and RHR compared with the control group (p < 0.001).
Table 4.
MANOVA multiple group comparison of BMI, SBP, DBP, and RHR among sedentary adult men.
| Variables | Between-subjects effects | Pairwise comparison | |||||||
|---|---|---|---|---|---|---|---|---|---|
| F | P- value | η2 | Treatment group | MD | Std. Error | P-value | 95% CI | ||
| (I-J) | Lower bound | Upper bound | |||||||
| BMI | 58.55 | < 0.001 | 0.830 | AE + DC - CG | −5.50 | 0.52 | < 0.001 | −6.96 | −4.04 |
| RE + DC - CG | −3.00 | 0.52 | < 0.001 | −4.46 | −1.54 | ||||
| CE + DC - CG | −6.25 | 0.52 | < 0.001 | −7.71 | −4.79 | ||||
| AE - RE | −2.50 | 0.52 | < 0.001 | −3.96 | −1.04 | ||||
| CE - AE | −0.75 | 0.52 | 0.956 | −2.21 | 0.71 | ||||
| CE - RE | −3.25 | 0.52 | < 0.001 | −4.71 | −1.79 | ||||
| SBP | 32.155 | < 0.001 | 0.728 | AE + DC - CG | −19.80 | 2.40 | < 0.001 | −26.50 | −13.10 |
| RE + DC - CG | −11.60 | 2.40 | < 0.001 | −18.30 | −4.90 | ||||
| CE + DC - CG | −20.80 | 2.40 | < 0.001 | −27.50 | −14.10 | ||||
| AE - RE | −8.20 | 2.40 | 0.010 | −14.90 | 1.50 | ||||
| CE - AE | −1.00 | 2.40 | 1.000 | −7.70 | 5.70 | ||||
| CE - RE | −9.20 | 2.40 | 0.003 | −15.90 | −2.50 | ||||
| DBP | 27.288 | < 0.001 | 0.695 | AE + DC - CG | −13.10 | 1.69 | < 0.001 | −17.82 | −8.38 |
| RE + DC - CG | −7.80 | 1.69 | < 0.001 | −12.52 | −3.08 | ||||
| CE + DC - CG | −13.30 | 1.69 | < 0.001 | −18.02 | −8.58 | ||||
| AE - RE | −5.30 | 1.69 | 0.020 | −10.02 | −0.58 | ||||
| CE - AE | −0.20 | 1.69 | 1.000 | −4.92 | 4.52 | ||||
| CE - RE | −5.50 | 1.69 | 0.015 | −10.22 | −0.78 | ||||
| RHR | 37.274 | < 0.001 | 0.756 | AE + DC - CG | −15.10 | 1.64 | < 0.001 | −19.69 | −10. 51 |
| RE + DC - CG | −9.90 | 1.64 | < 0,001 | −14.49 | −5.31 | ||||
| CE + DC - CG | −15.00 | 1.64 | < 0.001 | −19.59 | −10.41 | ||||
| AE - RE | −5.20 | 1.64 | 0.019 | −9.79 | −0.61 | ||||
| CE - AE | 0.10 | 1.64 | 1.000 | −4.49 | 4.69 | ||||
| CE - RE | −5.10 | 1.64 | 0.022 | −9.69 | −0.51 | ||||
BMI = body mass index, SBP = systolic blood pressure, DBP = diastolic blood pressure, RHR = resting heart rate, MD = mean difference, SE = standard error, CI = Confidence Interval, AE + DC = aerobic exercise with dietary counseling, RE + DC = resistance exercise with dietary counseling, CE + DC = combined exercise with dietary counseling, CG = control group.
Further comparisons among the intervention groups showed that AE + DC and CE + DC were the most statistically significant in improving BMI, SBP, DBP, and RHR compared to RE + DC. The AE + DC group showed the most significant reductions compared to the RE + DC group in.
BMI: MD = − 2.50 ± 0.52 kg/m², p < 0.001; SBP: MD = − 8.20 ± 2.40 mmHg, p = 0.010; DBP: MD = − 5.30 ± 1.69 mmHg, p = 0.020; and RHR: MD = − 5.20 ± 1.64 bpm, p = 0.019. The CE + DC group revealed comparable effects to AE + DC across all variables, with no significant differences: BMI: MD = − 0.75 ± 0.52 52 kg/m², p = 0.956, SBP: MD = − 1.00 ± 2.40 mmHg, p = 1.000, DBP: MD = − 0.20 ± 1.69 mmHg, p = 1.000, and RHR: MD = 0.10 ± 1.64 bpm, p = 1.000, However, CE + DC was statistically significantly more effective than RE + DC in reducing: BMI: MD = − 3.25 ± 0.52 52 kg/m², p < 0.001; SBP: MD = − 9.20 ± 2.40 mmHg, p = 0.003; DBP: MD = − 5.50 ± 1.69 mmHg, p = 0.015; and RHR: MD = − 5.10 ± 1.64 bpm, p = 0.022. Overall, the AE + DC and CE + DC groups were the most effective interventions for improving BMI, SBP, DBP, and RHR compared to the RE + DC and control groups as indicated in (Fig. 2).
Fig. 2.
Within-group and between-group effects of aerobic, resistance, and combined exercise interventions, alongside dietary counseling, on BMI, SBP, DBP, and RHR in sedentary adult males a) b) c) d).
Discussion
This study examined the effects of exercise interventions combined with dietary counseling on BMI, SBP, DBP, and RHR in sedentary male bank employees. As shown in Table 3, all three intervention groups (AE + DC, RE + DC, and CE + DC) demonstrated significant intragroup reductions in BMI, SBP, DBP, and RHR (p < 0.001), while the control group showed no significant changes in these parameters. Furthermore, our MANOVA and post-hoc Bonferroni tests (Table 4) confirmed that all three intervention groups revealed significant reductions in these variables when compared to the control group (p < 0.001). Our findings, consistent with previous studies, indicate that aerobic exercise alone significantly reduced SBP and DBP52 and BMI and RHR53. However, it is important to note that some studies, such as54, have reported no significant reductions in SBP, DBP, or RHR after aerobic interventions, which contrasts with the significant improvements observed in the present study. In the present study, the RE + DC group also showed significant reductions in all measured variables of BMI, SBP, DBP, and RHR. These findings align with earlier studies demonstrating that resistance exercise contributes to reductions in SBP, DBP, RHR55,56 and BMI57. Conversely, some studies by58,59 reported no significant changes in SBP, DBP, or RHR, respectively, in resistance exercise groups, which differs from the significant reductions we observed in the present study. The CE + DC group demonstrated significant reductions across all measured variables, including BMI, SBP, DBP, and RHR. These findings are consistent with previous studies on BMI29,40,60, and also align with research on SBP, DBP, and RHR SBP, DBP and RHR28,61,62. Contrary to this, some studies63,64; have reported no significant reductions in SBP and DBP, and another study56 found no significant reductions in BMI after regular exercise interventions.
Post-hoc Bonferroni tests revealed that both AE + DC and CE + DC were the most effective interventions for improving BMI, SBP, DBP, and RHR when compared to the RE + DC group. Furthermore, no significant differences were observed between the AE + DC and CE + DC groups across these variables. This finding aligns with previous studies65, which reported that both combined and aerobic training significantly reduced BMI, with no significant difference observed between these two modalities. Similarly66, cardiovascular disease risk profiles in overweight adults, with no significant difference between aerobic and combined exercise outcomes. A meta-analysis by67 further supports these observations, indicating that combined training significantly improved BMI, SBP, and DBP compared to resistance training alone, while no significant differences observed in RHR. Additionally47,68, found that both aerobic and combined training significantly reduced resting heart rate compared to resistance and control groups. However, some studies present contradictory findings such as40,, observed a more significant reduction in BMI in the combined exercise group compared to both aerobic and resistance training groups. Similarly, research by28,29,46,62, indicated that while all interventions reduced BMI, SBP, DBP, and RHR, combined exercise yielded more significant reductions than aerobic or resistance training alone. Conversely30, reported that combined and resistance exercises reduced SBP more than aerobic exercises but had no effect on DBP. In contrast69, found no statistically significant difference in SBP and DBP among aerobic, resistance, and combined exercise intervention groups, although aerobic exercise was superior to resistance exercise regarding BMI. This study suggested that exercise interventions combined with dietary counseling significantly improved BMI, blood pressure, and resting heart rate in sedentary males. Aerobic and combined exercises were more effective than resistance exercise alone, with no significant difference between aerobic and combined modalities. However, some studies showed inconsistent results regarding the extent to which these interventions improved the measured outcomes. These inconsistencies may be due to differences in participant characteristics, intervention duration, and adherence levels, which influenced the response to the interventions. Overall, combined exercise and dietary counseling lifestyle interventions are important for improving physiological biomarker outcomes.
Limitations of the study
Several limitations should be considered when interpreting the results of this study. First, the sample consisted exclusively of sedentary male bank employees from a single city, which limits the generalizability of the findings to females, other age groups, occupations, and diverse cultural contexts. Second, the intervention duration was relatively short, spanning only 12 weeks. While this period was sufficient to observe significant improvements in physiological biomarkers, the study did not evaluate the long-term sustainability of these effects. Third, potential confounding factors such as genetic predispositions and psychosocial stress were not controlled for, which may have influenced the physiological outcomes measured. Future research should aim to include a more diverse participant population, extend the intervention period to assess long-term impacts, and incorporate controls for genetic and psychosocial variables to enhance the external validity and applicability of the findings.
Conclusion
This study showed that aerobic, resistance, and combined exercise, along with dietary counseling, all led to statistically significant improvements in BMI, SBP, DBP, and RHR in sedentary adults, while the control group did not show any changes. Overall, both aerobic and combined exercise interventions were the most effective, resulting in a significant reduction in these physiological biomarker outcomes compared to resistance exercise alone. Importantly, there were no significant differences in the effectiveness of aerobic and combined exercise for improvements in these important health markers. These findings suggest that sedentary adults should engage in structured exercise programs, particularly aerobic and combined training, alongside dietary counseling, to reduce health risks associated with sedentary lifestyles.
Acknowledgements
The authors gratefully acknowledge Addis Ababa University for providing financial support for this research. We also thank the gym management and the head of the sports academy at Debre Markos University for their generous support in allowing the gym to be used free of charge throughout the intervention period. We are especially grateful to Mr. Ayenew Negesse, Dr. Zewudu Wondifraw, and Dr. Esikeziaw Agedew for their dedicated dietary counseling during the 12-week intervention. Finally, we extend our sincere appreciation to Debre Markos Referral Hospital and all the study participants, whose contributions were essential to the successful completion of this research.
Author contributions
Abraham Abebe was responsible for conceptualizing, data curation, formal analysis, investigation, methodology, writing the original draft, and reviewing and editing the manuscript. Dr. Alemmebrat Kiflu was responsible for conceptualizing, data curation, formal analysis, investigation, methodology, supervision, reviewing and editing. Dr. Zeru Bekele was responsible for conceptualizing, data curation, formal analysis, investigation, methodology, supervision, reviewing and editing. All authors have read and approved the final manuscript.
Funding
This study forms part of the first author’s Ph.D. thesis in Exercise Physiology at the Department of Sports Science and Physical Education, Addis Ababa University. It was conducted as a partial fulfillment of the requirements for the Ph.D. degree and was financially supported by Addis Ababa University’s doctoral funding program. The authors received financial support for the research and manuscript preparation; however, publication fees were not covered.
Data availability
The datasets generated and/or analyzed during this study are available from the corresponding author upon reasonable request.
Declarations
Ethics approval and consent to participate
Informed consent was obtained from all participants, and the study adhered to relevant guidelines and regulations. Ethical approval, including the consent form, was granted by the Addis Ababa University College of Natural and Computational Sciences Institutional Review Board (CNC-IRB, Code: 06/2017/2025). Before the trial, participants were informed about the intervention and potential risks and provided written consent.
Consent for publication
Not applicable.
Competing interests
The authors declare no competing interests.
Footnotes
Publisher’s note
Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
References
- 1.Tremblay, M. S. et al. Sedentary behavior research network (SBRN)–terminology consensus project process and outcome. Int. J. Behav. Nutr. Phys. Activity. 14, 1–17 (2017). [DOI] [PMC free article] [PubMed] [Google Scholar]
- 2.Yang, Z. et al. Public health concern on sedentary behavior and cardiovascular disease: A bibliometric analysis of literature from 1990 to 2022. Med. (Kaunas), 58(12), 1764 (2022). [DOI] [PMC free article] [PubMed]
- 3.Stappers, N. E. H. et al. Effects of major urban redesign on sedentary behavior, physical activity, active transport and health-related quality of life in adults. BMC Public. Health. 23 (1), 1157 (2023). [DOI] [PMC free article] [PubMed] [Google Scholar]
- 4.Wu, J. et al. Sedentary behavior patterns and the risk of non-communicable diseases and all-cause mortality: A systematic review and meta-analysis. Int. J. Nurs. Stud.146, 104563 (2023). [DOI] [PubMed] [Google Scholar]
- 5.López-Valenciano, A. et al. Changes in sedentary behaviour in European union adults between 2002 and 2017. BMC Public. Health. 20 (1), 1206 (2020). [DOI] [PMC free article] [PubMed] [Google Scholar]
- 6.Motuma, A. et al. Sedentary behavior and associated factors among working adults in Eastern Ethiopia. Front. Public. Health. 9, 693176 (2021). [DOI] [PMC free article] [PubMed] [Google Scholar]
- 7.Enyew, A. et al. Prevalence and associated factors of physical inactivity among adult diabetes mellitus patients in Felege Hiwot referral hospital, Bahir dar, Northwest Ethiopia. Sci. Rep.13 (1), 118 (2023). [DOI] [PMC free article] [PubMed] [Google Scholar]
- 8.Hadgraft, N. T. et al. Effects of sedentary behaviour interventions on biomarkers of cardiometabolic risk in adults: systematic review with meta-analyses. Br. J. Sports Med.55 (3), 144–154 (2021). [DOI] [PMC free article] [PubMed] [Google Scholar]
- 9.Dieterich, A. V. et al. Reducing sedentary behaviour and physical inactivity in the workplace: protocol for a review of systematic reviews. BMJ Open. Sport Exerc. Med.6 (1), e000909 (2020). [DOI] [PMC free article] [PubMed] [Google Scholar]
- 10.WHO. Global Report on Hypertension: the Race against a Silent Killer (World Health Organization, 2023).
- 11.Abdelmenan, S. et al. Prevalence of Self-Reported chronic Non-Communicable diseases among adults in addis health and demographic surveillance system (Addis-HDSS), addis ababa, Ethiopia. Ethiop. J. Health Sci., 34(2), 127–137 (2024). [DOI] [PMC free article] [PubMed]
- 12.Lauber, K. et al. Non-communicable disease governance in the era of the sustainable development goals: a qualitative analysis of food industry framing in WHO consultations. Globalization Health. 16, 1–15 (2020). [DOI] [PMC free article] [PubMed] [Google Scholar]
- 13.Girum, T. et al. The burden of noncommunicable diseases in ethiopia, 2000–2016: analysis of evidence from global burden of disease study 2016 and global health estimates 2016. Int. J. Chronic Dis.2020 (1), 3679528 (2020). [DOI] [PMC free article] [PubMed] [Google Scholar]
- 14.Gebreyes, Y. F. et al. Prevalence of high bloodpressure, hyperglycemia, dyslipidemia, metabolic syndrome and their determinants in ethiopia: evidences from the National NCDs STEPS survey, 2015. PLoS One. 13 (5), pe0194819 (2018). [DOI] [PMC free article] [PubMed] [Google Scholar]
- 15.Tesfay, F. H. et al. The magnitude of NCD risk factors in ethiopia: Meta-Analysis and systematic review of evidence. Int. J. Environ. Res. Public. Health, 19(9), 5316 (2022). [DOI] [PMC free article] [PubMed]
- 16.Koye, D. N. et al. Mapping national, regional and local prevalence of hypertension and diabetes in Ethiopia using Geospatial analysis. BMJ Open.12 (12), e065318 (2022). [DOI] [PMC free article] [PubMed] [Google Scholar]
- 17.Dejenie, M., Kerie, S. & Reba, K. Undiagnosed hypertension and associated factors among bank workers in Bahir Dar city, northwest, ethiopia, 2020. A cross-sectional study. PloS One. 16 (5), e0252298 (2021). [DOI] [PMC free article] [PubMed] [Google Scholar]
- 18.Razibi, K. et al. Prevalence and risk factors of hypertension among bank employees in Dhaka City of Bangladesh. Cogent Public. Health. 10 (1), 2178054 (2023). [Google Scholar]
- 19.Cinquenta, A. et al. Lifestyle and eating habits of bank employees. J. Health NPEPS, 8(1), e10925 (2023).
- 20.Moloro, A. H., Seid, A. A. & Jaleta, F. Y. A systematic review and meta-analysis protocol on hypertension prevalence and associated factors among bank workers in Africa. SAGE Open. Med.11, 20503121231172001 (2023). [DOI] [PMC free article] [PubMed] [Google Scholar]
- 21.Shitu, K. & Kassie, A. Behavioral and sociodemographic determinants of hypertension and its burden among bank employees in metropolitan cities of Amhara regional state, Ethiopia. Int. J. Hypertens.2021 (1), 6616473 (2021). [DOI] [PMC free article] [PubMed] [Google Scholar]
- 22.Al-Batanony, M. A. et al. Prevalence of and factors associated with hypertension among bank employees: A Cross-Sectional study in Saudi Arabia. Healthc. (Basel), 13(2). (2025). [DOI] [PMC free article] [PubMed]
- 23.Nketiah, G. B. et al. Physical inactivity among corporate bank workers in accra, ghana: implications for health promotion. Plos One. 18 (5), e0277994 (2023). [DOI] [PMC free article] [PubMed] [Google Scholar]
- 24.Aderibigbe, S. et al. Knowledge and practice of sedentary lifestyle among bankers in abuja, North-Central Ngeria. Res. J. Health Sci.5 (3), 167–174 (2017). [Google Scholar]
- 25.Schauer, M. et al. The association of physical activity level with micronutrient and health status of Austrian bank employees. Nutrients15 (23), 4884 (2023). [DOI] [PMC free article] [PubMed] [Google Scholar]
- 26.Kebede, S. A., Weldesenbet, A. B. & Tusa, B. S. Spatial distribution and factors associated with risky health behavior among adult males aged 15–59 years in ethiopia: generalized structural equation modeling. Front. Psychiatry. 13, 688336 (2022). [DOI] [PMC free article] [PubMed] [Google Scholar]
- 27.Döding, R., et al., Evidence gaps in conservative non-pharmacological interventions and guideline implementation for high-burden non-communicable diseases: protocol for an overview of reviews. BMJ open sport & exercise medicine, 2024. 10(4): p. e002032. [DOI] [PMC free article] [PubMed]
- 28.Alemayehu, A. & Teferi, G. Effectiveness of aerobic, resistance, and combined training for hypertensive patients: A randomized controlled trial. Ethiop. J. Health Sci.33 (6), 1063–1074 (2023). [DOI] [PMC free article] [PubMed] [Google Scholar]
- 29.Ambelu, T. & Teferi, G. The impact of exercise modalities on blood glucose, blood pressure and body composition in patients with type 2 diabetes mellitus. BMC Sports Science, Medicine and Rehabilitation, 15(1): p. 153. (2023). [DOI] [PMC free article] [PubMed]
- 30.Mengistu, F. A. & Lake, Y. A. Impact of aerobic, resistance, and combined training on cardiometabolic healthrelated indicators in inactive middle-aged men with excess body weight and obesity. Front. Physiol.16, 1519180 (2025). [DOI] [PMC free article] [PubMed] [Google Scholar]
- 31.Ayoub, Al-Jawaldeh Marwa M. S., Abbass (2022) Unhealthy Dietary Habits and Obesity: The Major Risk Factors Beyond Non-Communicable Diseases in the Eastern Mediterranean Region Frontiers in Nutrition 910.3389/fnut.2022.817808 [DOI] [PMC free article] [PubMed]
- 32.Wondimagegn Paulos, Kumma Eskindir, Loha (2023) Dietary patterns and their association with cardiovascular risk factors in Ethiopia: A community-based cross-sectional study Frontiers in Nutrition 1010.3389/fnut.2023.1074296 [DOI] [PMC free article] [PubMed]
- 33.Endris, B. S. et al. Barriers and facilitators to the implementation of nutrition interventions at primary health care units of ethiopia: A consolidated framework for implementation research. Matern Child. Nutr.19 (1), e13433 (2023). [DOI] [PMC free article] [PubMed] [Google Scholar]
- 34.Rotunda, W. et al. Weight loss in Short-Term interventions for physical activity and nutrition among adults with overweight or obesity: A systematic review and Meta-Analysis. Prev. Chronic Dis.21, E21 (2024). [DOI] [PMC free article] [PubMed] [Google Scholar]
- 35.Yari-Boroujeni, R. et al. A pragmatic multi-setting healthy lifestyle intervention to improve BMI status in a middle-income population: A potential strategy for individuals at risk. Health Promot Perspect.14 (4), 369–379 (2024). [DOI] [PMC free article] [PubMed] [Google Scholar]
- 36.Liguori, G. & Medicine, A. C. S. ACSM’s guidelines for exercise testing and prescription (Lippincott williams & wilkins, 2020).
- 37.Shiely, F. et al. Registry-based randomised controlled trials: conduct, advantages and challenges—a systematic review. Trials25 (1), 375 (2024). [DOI] [PMC free article] [PubMed] [Google Scholar]
- 38.Farrell, A. On behalf of the, Improving transparency in clinical trial reporting. PLoS Med.22 (4), e1004588 (2025). [DOI] [PMC free article] [PubMed] [Google Scholar]
- 39.Amare, F. et al. Effects of aerobic, resistance, and combined exercise training on body fat and glucolipid metabolism in inactive middle-aged adults with overweight or obesity: a randomized trial. BMC Sports Sci. Med. Rehabilitation. 16 (1), 1–10 (2024). [DOI] [PMC free article] [PubMed] [Google Scholar]
- 40.Kumari, A. et al. Effect of combined aerobic and resistance training exercise on Vo2 max and BMI in overweight collegiate population a randomized controlled trial. J. Bodyw. Mov. Ther.42, 221–226 (2025). [DOI] [PubMed] [Google Scholar]
- 41.Sabbahi, A. et al. Improvements in cardiometabolic risk markers, aerobic fitness, and functional performance following a physical therapy weight loss program. Physiother. Theory Pract.34 (1), 13–21 (2018). [DOI] [PubMed] [Google Scholar]
- 42.Shabani, A. et al. The effect of concurrent endurance and resistance training on cardio-respiratory capacity and cardiovascular risk markers among sedentary overweight or obese post-menopausal women. J. Nurs. Midwifery Sci.5 (4), 123–129 (2018). [Google Scholar]
- 43.Sun, F. et al. Effect of eight-week high-intensity interval training versus moderate-intensity continuous training programme on body composition, cardiometabolic risk factors in sedentary adolescents. Front. Physiol.15, 1450341 (2024). [DOI] [PMC free article] [PubMed] [Google Scholar]
- 44.Diaz, K. M. et al. Breaking up prolonged sedentary behavior to improve cardiometabolic health (BREAK2): protocol for a dose-finding adaptive randomization trial. BMC Public. Health. 25 (1), p1929 (2025). [DOI] [PMC free article] [PubMed] [Google Scholar]
- 45.Bayles, M. P. ACSM’s exercise testing and prescription (Lippincott williams & wilkins, 2023).
- 46.Brellenthin, A. G. et al. Comparison of the cardiovascular benefits of resistance, aerobic, and combined exercise (CardioRACE): rationale, design, and methods. Am. Heart J.217, 101–111 (2019). [DOI] [PMC free article] [PubMed] [Google Scholar]
- 47.Schroeder, E. C. et al. Comparative effectiveness of aerobic, resistance, and combined training on cardiovascular disease risk factors: A randomized controlled trial. PloS One. 14 (1), e0210292 (2019). [DOI] [PMC free article] [PubMed] [Google Scholar]
- 48.Hernandez-Vicente, A. et al. Validity of the Polar H7 heart rate sensor for heart rate variability analysis during exercise in different age, body composition and fitness level groups. Sens. (Basel), 21(3), 902 (2021). [DOI] [PMC free article] [PubMed]
- 49.Gellish, R. L. et al. Longitudinal modeling of the relationship between age and maximal heart rate. Med. Sci. Sports Exerc.39 (5), 822–829 (2007). [DOI] [PubMed] [Google Scholar]
- 50.Khalafi, M. et al. The Effects of Concurrent Training Versus Aerobic or Resistance Training Alone on Body Composition in Middle-Aged and Older Adults: A Systematic Review and Meta-Analysis. Healthcare (Basel), 13(7). (2025). [DOI] [PMC free article] [PubMed]
- 51.Derkach, A. et al. Effects of dietary sodium on metabolites: the dietary approaches to stop hypertension (DASH)–Sodium feeding Study1. Am. J. Clin. Nutr.106 (4), 1131–1141 (2017). [DOI] [PMC free article] [PubMed] [Google Scholar]
- 52.Doulatyari, P. K., Ghahramani, M. & Mozaffari, K. Investigating the effect of aerobic and resistance training on insulin resistance and some cardiovascular disease risk factors in type 2 diabetes mellitus patients: A systematic review. J. Clin. Res. Paramedical Sci., 12(1), e134510 (2023).
- 53.Monda, V. et al. Aerobic exercise and metabolic syndrome: The role of sympathetic activity and the redox system. Diabetes, Metabolic Syndrome and Obesity, : pp. 2433–2442. (2020). [DOI] [PMC free article] [PubMed]
- 54.Akwa, L. G. et al. Lipid profile, cardiorespiratory function and quality of life of postmenopausal women improves with aerobic exercise. J. Hum. Sport Exerc.12 (3), 698–709 (2017). [Google Scholar]
- 55.Hakimi, M. et al. Investigation and comparison of the effects of eight weeks of resistance and endurance training with vitamin D3 supplementation on blood pressure, resting heart rate, and body composition in obese hypertensive middle-aged men. J. Clin. Res. Paramedical Sci., 7(1), e79971 (2018).
- 56.Guo, L. & Wang, C. The effect of exercise on cardiovascular disease risk factors in sedentary population: a systematic review and meta-analysis. Front. Public. Health. 13, 1470947 (2025). [DOI] [PMC free article] [PubMed] [Google Scholar]
- 57.Said, M. A., Alibrahim, M. & Kotb, M. Resistance Training, or their Combination as a Means To Fight against Excess Weight and Metabolic Syndrome in Obese Students—Which Is the Most Effective Modality? A Randomized Controlled Trial (Applied Physiology, Nutrition, and Metabolism, 2021). Ahmed ;, Aerobic Training. [DOI] [PubMed]
- 58.Carvalho, C. J. et al. Aerobic and resistance exercise in patients with resistant hypertension. Revista Brasileira De Med. Do Esporte. 25 (2), 107–111 (2019). [Google Scholar]
- 59.Ramezani, S. et al. The effect of muscle endurance training on blood pressure, resting heart rate and Endothelin-1 levels in inactive men. J. Vessels Circulation. 2 (1), 9–16 (2021). [Google Scholar]
- 60.Akkurt, M., Ökmen, M. Ş. & Polat, M. Effects of eight-week aerobic exercises combined with resistance training on cardiovascular risk factors in women. Biomedical Hum. Kinetics. 15 (1), 1–8 (2023). [Google Scholar]
- 61.Xi, H. et al. Effect of combined aerobic and resistance exercise on blood pressure in postmenopausal women: A systematic review and meta-analysis of randomized controlled trials. Exp. Gerontol.155, 111560 (2021). [DOI] [PubMed] [Google Scholar]
- 62.Mondal, S. et al. Effects of aerobic and resistance exercises on selected physiological biochemical and anthropometric variables among type 2 diabetic patients in dilla, Ethiopia. Indian J. Public. Health Res. Dev.12 (3), 229–237 (2021). [Google Scholar]
- 63.Dianatinasab, A. et al. The effects of aerobic, resistance, and combined exercises on the plasma Irisin levels, HOMA-IR, and lipid profiles in women with metabolic syndrome: A randomized controlled trial. J. Exerc. Sci. Fit.18 (3), 168–176 (2020). [DOI] [PMC free article] [PubMed] [Google Scholar]
- 64.Versic, S. et al. Differential effects of Resistance- and Endurance-Based exercise programs on muscular fitness, body composition, and cardiovascular variables in young adult women: contextualizing the efficacy of Self-Selected exercise modalities. Med. (Kaunas), 57(7), 654 (2021). [DOI] [PMC free article] [PubMed]
- 65.Khalafi, M. et al. Combined versus independent effects of exercise training and intermittent fasting on body composition and cardiometabolic health in adults: a systematic review and meta-analysis. Nutr. J.23 (1), 7 (2024). [DOI] [PMC free article] [PubMed] [Google Scholar]
- 66.Lee, D. et al. Aerobic, resistance, or combined exercise training and cardiovascular risk profile in overweight or obese adults: the cardiorace trial. Eur. Heart J., 43(13), 1127–1142 (2024). [DOI] [PMC free article] [PubMed]
- 67.Al-Mhanna, S. B. et al. Effects of combined aerobic and resistance training on glycemic control, blood pressure, inflammation, cardiorespiratory fitness and quality of life in patients with type 2 diabetes and overweight/obesity: a systematic review and meta-analysis. PeerJ12, e17525 (2024). [DOI] [PMC free article] [PubMed] [Google Scholar]
- 68.Verma, M. Comparative study of the effects of aerobic, resistance, and concurrent training on resting heart rate in college men international. J. Med. Sciences(ISSN. 4 (06), 2692–5206 (2024). [Google Scholar]
- 69.Liang, M. et al. Effects of aerobic, resistance, and combined exercise on metabolic syndrome parameters and cardiovascular risk factors: a systematic review and network meta-analysis. RCM22 (4), 1523–1533 (2021). [DOI] [PubMed] [Google Scholar]
Associated Data
This section collects any data citations, data availability statements, or supplementary materials included in this article.
Data Availability Statement
The datasets generated and/or analyzed during this study are available from the corresponding author upon reasonable request.


