Effects of Aerobic Exercise on Heart Rate Variability and C‐Reactive Protein in Middle‐Aged Adults With Normal Weight and Overweight/Obesity: A Pilot Study

ABSTRACT

Aerobic exercise (AE) can improve heart rate variability (HRV) and reduce inflammation. Whether body mass index (BMI) affects physiological responses to AE remains unclear. This pilot study aimed to compare the effects of a 16‐week AE on HRV and C‐reactive protein (CRP) in normal weight (18.5 ≤ BMI < 24) and overweight/obesity (BMI ≥ 24) middle‐aged adults. A quasi‐experimental design with purposive sampling was employed to recruit middle‐aged adults, who were categorized into normal weight (n = 26) and overweight/obesity (n = 25) groups. All participants engaged in at least moderate‐intensity AE three times per week for 16 weeks. HRV parameters and CRP were evaluated at baseline and after intervention. The results demonstrated that the overweight/obesity group experienced a significant decrease in resting heart rate (Β = −4.35, p = 0.049) but a significant increase in CRP (Β = 1.22, p = 0.045) compared to the normal weight group. Both groups exhibited similar trajectories in HRV parameters during rest, warm‐up, exercise, and cool‐down phases over the 16‐week period. However, HRV parameters associated with parasympathetic nervous system activity fluctuated more prominently from rest to exercise in the normal weight group than in the overweight/obesity group. Individuals with overweight/obesity appeared to exhibit less favorable parasympathetic adaptation during exercise. Intense physical activity was associated with inflammatory responses in these individuals. Health professionals may monitor HRV and inflammation to ensure safe exercise and guide individuals in developing customized regimens.

Trial Registration: NCT05949710.

1. Introduction

Heart rate variability (HRV), a measure of the oscillation in the intervals between consecutive heartbeats (Navarro‐Lomas et al. ²⁰²⁴), can be considered as the adaptive result in terms of heart rate caused by the sympathetic and parasympathetic nervous working collaboratively and is widely used for assessing the function of cardiac autonomic modulation (Bahameish and Stockman 2024). Notably, HRV has been identified as a valuable predictor of obesity‐related cardiovascular disease (Wiley et al. 2025). Furthermore, evidence indicates that autonomic nervous system modulation can be improved through fat mass reduction in individuals with obesity (Phoemsapthawee et al. 2019), positioning HRV as a useful lens for examining obesity‐related autonomic dysregulation.

Obesity is characterized by disruption of autonomic balance and activation of inflammatory pathways; individuals with a high body mass index (BMI) frequently show signs of inflammation (Wiley et al. 2025). One key biomarker of inflammation is C‐reactive protein (CRP) (Son et al. 2023), which has been found at significantly higher levels in individuals with overweight or obesity compared to those with a normal BMI (Su et al. 2024). Moreover, CRP is recommended as a therapeutic target for managing obesity and its associated complications (Li et al. 2020), making it a sensitive marker for detecting obesity‐induced low‐grade inflammation. Importantly, aerobic exercise (AE) training can significantly enhance parasympathetic activity (Zhang et al. 2025) and reduce CRP in individuals with obesity (Son et al. 2023), highlighting its potential as an effective intervention for mitigating inflammation associated with obesity.

AE, defined by the American College of Sports Medicine as exercise that is rhythmic, continuous, and performed using the large muscles of the body (Liguori 2021), is one of the most effective exercise modalities and can predominantly improve HRV and inflammatory status (Khalafi et al. 2025; Zhang et al. ²⁰²⁵). Most studies reported the effective AE sessions for positive health outcomes were 30‐min of moderate‐to‐vigorous intensity three times per week, with a total intervention duration of 12–24 weeks (Chang et al. 2022; Valkenborghs et al. ²⁰²⁴). A previous meta‐analysis of 21 studies concluded that AE significantly increases parasympathetic nervous system activity parameters, such as high frequency (HF), root mean square of successive RR‐intervals differences (RMSSD), standard deviation of normal‐to‐normal intervals (SDNN), percentage of adjacent NN intervals varying by more than 50 ms (pNN50), and rest of heart rate (Picard et al. 2021), while decreases sympathetic nervous system activity parameters, such as low frequency (LF) and the LF/HF ratio (Picard et al. 2021). Overall, these findings indicate that AE enhances cardiac autonomic regulation by strengthening parasympathetic activity and attenuating sympathetic influence.

Evidence suggests that baseline inflammation status and BMI may influence physiological adaptations to AE, yet findings remain inconsistent. Fernandes‐Silva et al. (2017) reported that individuals with low baseline inflammation achieved greater VO_₂peak improvements after 12 weeks of AE. In contrast, both Jabbour and Iancu (2021) and Wanderley et al. (2013) suggested that individuals with higher BMI or elevated baseline inflammation, which are conditions often associated with each other, may experience more pronounced improvements in HRV following AE. However, the results of these studies may be limited by the small number of participants. Therefore, whether baseline inflammation status and BMI influence HRV and CRP improvements after exercise needs further investigation. Given this context, middle‐aged adults were chosen as the primary study population because they are at a critical stage for the onset and progression of cardiometabolic and inflammatory disorders (Tong et al. 2024), making early intervention particularly impactful. Such findings could serve as valuable references for public health promotion.

Obesity is well‐known to exert adverse effects on HRV and inflammatory status (Wiley et al. 2025). However, emerging evidence suggests that these cardiometabolic risks exist on a continuum, with overweight individuals sharing similar pathophysiological burdens to those with obesity (Moradi et al. 2023; Muthukrishnan et al. ²⁰²⁵; Tsai et al. ²⁰¹⁸). Recent systematic review and meta‐analysis indicated a linear dose‐response relationship between BMI and metabolic dysregulation, suggesting that the adverse impacts of excess adiposity begin well before the clinical threshold of obesity (Moradi et al. 2023). Accordingly, individuals with overweight and obesity were both included as the target population for recruitment in this study.

The purposes of this pilot study were to (1) compare baseline HRV and CRP between middle‐aged adults with normal weight (18.5 ≤ BMI < 24) and those with overweight or obesity (BMI ≥ 24), (2) compare the effectiveness of a 16‐week AE program in improving HRV and CRP in normal weight and overweight/obesity groups, and (3) explore the trajectory of HRV parameters over course of the 16‐week AE intervention among two groups. We hypothesized that (1) at baseline, the overweight/obesity group would show lower HRV and higher CRP than the normal‐weight group; (2) AE would improve HRV and reduce CRP, with intervention effects differing between groups; and (3) HRV would improve over time during AE, with trajectories differing between groups.

2. Methods

2.1. Study Design

This pilot study used a quasi‐experimental design with purposive sampling. Participants were categorized into two groups based on BMI: normal weight (18.5 ≤ BMI < 24) and overweight/obesity (BMI ≥ 24), with the cut‐off point defined by the Health Promotion Administration, Ministry of Health and Welfare (Ministry of Health and Welfare, Health Promotion Administration ²⁰²¹). Given the pilot nature and limited sample size, overweight and obesity were analyzed as a single group. All participants underwent a 16‐week AE intervention and engaged in three moderate‐intensity exercise sessions per week (ClinicalTrials.gov ID number: NCT05949710).

2.2. Participants

The community residents with (a) aged between 40 and 64 years and (b) had inactive habit (< 3 days of physical activity per week and < 30 min per session) were included. Residents with the following conditions were excluded: (a) Participants with underlying conditions, including stroke, acute coronary artery disease, physical disability, pregnancy, or uncontrolled hypertension (resting systolic blood pressure ≥ 180 mmHg or diastolic blood pressure ≥ 110 mmHg), (b) smoking or alcohol abuse, (c) currently being on a diet, and (d) lifestyles that may affect HRV and CRP (e.g., shift work or habit of staying up late) (Parsanathan and Jain 2020). Participants were asked to maintain their usual lifestyles and dietary habits, without any calorie restrictions or additional exercise other than the training program provided in this study.

2.3. Sample Size

An a priori sample size was estimated using G*Power (version 3.1.9.2) based on a repeated‐measures ANOVA framework (within‐between interaction) for two measurement occasions. We assumed a medium effect size (Cohen's f = 0.25), a correlation of 0.50 between repeated measures, a two‐sided α of 0.05, and 80% power. The required sample size was 34 participants. Considering a 20% attrition rate (Chang et al. 2023), the required total sample size was at least 43.

2.4. Data Collection, Procedure, and Settings

Recruitment and implementation were conducted from September 2023 to January 2024. The participants were approached online by posting advertisements on Facebook. The residents who were interested in participating in this study carefully screened on the basis of the inclusion criteria. After explained the research purpose and process to participants, informed consent and completed questionnaires on demographic characteristics obtained from the participants. The participants then invited to undergo baseline measurements on another morning. HRV parameters obtained from a standardized 5‐min quiet rest recording, along with blood samples and body composition, were measured 1 week before the 16‐week exercise intervention (T₀) and 1 week after completion of the 16‐week exercise intervention (T₁). All data collection procedures and interventions were conducted at community centers.

The AE intervention sessions were conducted on three nonconsecutive weekdays. During each supervised session, the participants were asked to first wear an elastic band with an electrocardiogram (ECG) electrode sensor on their xiphoid process and remain in a seated position at rest for at least 5 min for HRV measurement before they started their exercise training. During the exercise session, heart rate and HRV were monitored continuously, and HRV parameters were derived at 30‐second intervals.

2.5. Intervention

The AE program was delivered as an instructor‐led, music‐based group aerobic dance performed without a step platform. Sessions incorporated choreographed step‐pattern movements (e.g., march, step touch, lunge, V‐step, box step, twist, knee up, scoop, and scissors) combined with coordinated arm movements. The movements and session structure were consistent across the intervention, while the sequences and combinations of movements varied between sessions.

The participants received AE three times per week for 16 weeks. Each exercise session started with 10 min of warm‐up with background music playing at 120–130 bpm in order to facilitate attainment of at least 50% of maximum heart rate (HR_max; Berge et al. ²⁰²¹). The main AE training performed for 30 min at approximately 140 bpm to achieve at least moderate intensity, represented by a heart rate reserve (HRR) of 40%–59% (Liguori 2021). HRR is calculated as [(HR_max – HR_rest) × % intensity] + HR_rest, where HR_max is calculated by subtracting participants’ age from 220 (Liguori 2021). After the main exercise, a 10‐min of cool‐down phase designed at 90–100 bpm to achieve approximately 50% of HR_max (Berge et al. 2021).

The intervener is a certified physical fitness class C fitness instructor and Zumba Basic 1 instructor with more than 10 years of experience teaching physical fitness. The exercise prescription designed after a consensus between the first author and intervener based on the health conditions of the participants.

2.6. Measures

2.6.1. HRV Analyzer

Resting HRV was measured for all participants at baseline and at the end of the intervention. Besides, HRV was additionally measured during each exercise session in order to understand the dynamic HRV changes across the rest, warm‐up, main exercise, and cool‐down phases. The participants were asked to wear the ECG electrode sensor throughout the exercise session. Both time‐ and frequency‐domains were analyzed. HRV was measured every 30 s during each exercise session. The HRV parameters recorded were LF, HF, LF/HF, RMSSD, SDNN, pNN50, and heart rate. Mean HRV parameter values were calculated for the 10‐min warm‐up, 30‐min main exercise, and 10‐min cool‐down phases.

2.6.2. Blood Sample

Venous blood samples were collected in the morning 1 week before and 1 week after the 16‐week intervention, after an overnight fast of at least 8 h. The samples were centrifuged at 3000 rpm for 10 min at 4°C to obtain serum. Serum hs‐CRP was measured using a high‐sensitivity immunoturbidimetric assay.

2.6.3. Body Composition Analyzer

Body fat, and visceral fat were measured using a body composition analyzer (ACCUNIQ BC300, SELVAS Healthcare, Seoul, Republic of Korea), which had undergone rigorous validation (Yang et al. 2018). Participants were instructed to fast for 8 h before measurement. They were asked to remove their socks, shoes, and any metal objects, stand on the machine, and hold its handle with electrodes during measurement. Body weight and height were measured using the same analyzer, and BMI was calculated as weight (kg) divided by height squared (m²) (Chang et al. 2024).

2.6.4. Questionnaire for Demographic Background and Clinical Characteristics

The demographic characteristics included age, sex, education level, marital status, sleeping duration, and sedentary time. The clinical characteristics included a survey of whether participants underlying had chronic diseases of hypertension or diabetes mellitus.

2.7. Data Analysis

SPSS version 24.0 (IBM, Corp. Released 2016. IBM SPSS Statistics for Windows, Version 24.0. Armonk, NY: IBM Corp.) was used for data analysis. The clinical characteristics and demographic data of the participants presented as the mean (standard deviation) or percentage by using descriptive statistics. Weekly group means for each HRV parameter across exercise phases were computed by averaging values across the three exercise sessions per week to describe HRV trajectories during the 16‐week AE intervention. Mann‐Whitney U test or χ² tests were used to compare the differences between the groups. Within‐group changes in outcomes from T₀ to T₁ were additionally examined using Wilcoxon signed‐rank tests. p values < 0.05 considered statistically significant.

Adherence is the most crucial factor influencing the targeted effect of exercise (Dessie et al. 2021). The adherence rate determined as the ratio of the number of sessions attended to the total number of sessions. The adherence to targeted intensity was evaluated as the ratio of the number of sessions able to perform moderate or vigorous intensity exercise to the total number of sessions.

Linear mixed‐effects models (LMMs) were used to examine group‐by‐time interaction effects, with time specified as a repeated factor and a compound symmetry covariance structure. Exercise adherence was included as a covariate because it may influence intervention effects (Dessie et al. 2021). All analyses were performed using all available observations in the LMMs, with no imputation for missing data; participants contributed data for the time points with observed measurements.

2.8. Ethical Considerations

The ethical approval application approved by a Human Research Ethics Committee (Number: NCKU HREC‐E‐111‐587‐2). The eligible residents were provided written informed consent before data collection. The participants were free to withdraw from the study at any time, but their collected data remained anonymous in the data analysis.

3. Results

3.1. Demographic Characteristics of Participants

A total of 55 community residents were initially approached, four of whom declined participation. In total, 51 participants were recruited, including 26 with normal weight and 25 with overweight or obesity. After the 16‐week intervention, three participants from the normal weight group and two from the overweight/obesity group dropped out because of discomfort or loss of interest, yielding an attrition rate of 9.8% (Figure 1). Table 1 presents the demographic characteristics of participants in both groups. No significant differences in demographic characteristics were observed between the groups. Exercise adherence rates were 79.21% and 72.67% in the normal weight and overweight/obesity groups, respectively, whereas the rates of adherence to the targeted intensity (at least moderate level) were 96.85% and 99.32%, respectively. No significant difference in exercise adherence (Z = − 1.021, p = 0.307) or adherence to the targeted intensity (Z = − 0.354, p = 0.723) was noted between the two groups. Up to 88.8% of participants in the normal weight group and 84.5% in the overweight/obesity group reached vigorous intensity. None of the participants experienced exercise‐related injuries.

Figure 1.

The flow chart of recruiting process for the participants.

Table 1.

Demographic characteristics of participants in the normal weight and the overweight/obesity groups (N = 51).

Variables	Normal weight 18.5 ≤ BMI < 24 (n = 26)		Overweight/obesity BMI ≥ 24 (n = 25)		χ2	Z	p
	n	%	n	%
Sex					0.002		0.680
Male	2	7.69	2	8.00
Female	24	92.31	23	92.00
Age (years)/mean (SD)	52.62 (5.45)		52.16 (6.73)			−0.75a	0.455
Education					0.695		0.465
≧ College	23	88.46	20	80.00
< College	3	11.54	5	20.00
Marital status					0.784		0.523
Unmarried	8	30.76	5	20.00
Married	18	69.24	20	80.00
Sleep time (hr)/mean (SD)	6.90 (0.93)		6.60 (0.79)			−1.30 a	0.193
Sedentary time (h)/mean (SD)	5.62 (2.62)		6.80 (2.85)			−1.42 a	0.155
Underlying with HTN					0.695		0.465
Yes	3	11.54	5	20.00
No	23	88.46	20	80.00
Underlying with DM					0.003		0.959
Yes	3	11.54	3	12.00
No	23	88.46	22	88.00

Abbreviations: BMI, body mass index; DM, diabetes mellitus; HTN, hypertension; SD, standard deviation.

^a Mann–Whitney U test.

3.2. Baseline Outcome Variables Between Groups

Table 2 presents the baseline and post‐intervention values for body composition, HRV, and the inflammatory biomarker (CRP) for the normal weight and the overweight/obesity groups. The overweight/obesity group had a higher body weight (Z = −5.43, p < 0.001), BMI (Z = −6.11, p < 0.001), body fat (Z = −5.09, p < 0.001), visceral fat (Z = −5.51, p < 0.001), and CRP (Z = −2.16, p = 0.031) than did the normal weight group.

Table 2.

Baseline and post‐intervention values for body composition, heart rate variability, and an inflammatory biomarker in the normal weight and the overweight/obesity groups (N = 51).

Variables	Normal weight 18.5 ≤ BMI < 24 (n = 26)				Overweight/obesity BMI ≥ 24 (n = 25)				Between‐group difference at baseline
	pre		post		pre		post		Z a	p
	mean	SD	mean	SD	mean	SD	mean	SD
Body composition
Body weight (kg)	54.30	6.63	54.20	6.89	73.42	11.18	74.68	11.63	−5.43	< 0.001
BMI (kg/m2)	21.31	1.43	21.26	1.42	28.65	3.67	29.04	3.86	−6.11	< 0.001
Body fat (%)	27.55	3.80	27.08	3.59	35.43	4.96	36.36	4.67	−5.09	< 0.001
visceral fat (cm2)	57.46	21.48	55.92	22.02	117.56	38.99	127.50	41.64	−5.51	< 0.001
Heart rate variability
LF (ms²)	254.65	311.20	312.62	346.79	175.10	141.72	234.36	286.49	−1.28	0.200
HF (ms²)	121.97	124.53	147.64	149.34	127.20	159.71	137.25	215.28	−0.97	0.332
LF/HF	2.65	2.52	3.43	3.57	3.13	3.61	2.89	2.56	−0.60	0.546
RMSSD (ms)	23.75	13.17	25.92	13.28	21.28	13.02	22.69	15.03	−0.80	0.423
SDNN (ms)	38.60	18.48	40.76	17.57	35.62	18.94	38.79	18.90	−0.40	0.692
pNN50 (%)	5.15	9.60	6.73	9.84	5.04	9.53	6.27	11.63	−0.33	0.744
HRrest (bpm)	71.15	11.02	71.63	10.94	72.08	8.72	68.64	6.70	−0.37	0.713
Inflammatory biomarker
CRP (mg/L)	1.20	1.18	1.09	1.20	2.36	1.88	3.08	2.72	−2.16	0.031

Abbreviations: BMI, body mass index; CRP, C‐reactive protein; HF, high‐frequency; HR_rest, resting heart rate; LF, low‐frequency; pNN50, proportion derived by dividing NN50 by the total number of NN intervals; RMSSD, root mean square of successive R‐R interval differences; SD, standard deviation; SDNN, standard deviation of normal to normal interval.

^a Between‐group differences at baseline (pre‐exercise).

3.3. Comparison of Outcome Variables Between Groups After the 16‐Week AE Intervention

Table 3 presents a comparison of the effects of exercise on changes in HRV and inflammatory biomarkers (CRP) between participants in the normal weight group and the overweight/obesity group over a 16‐week period. Participants in the overweight/obesity group showed a significant decrease in resting heart rate compared to those in the normal weight group after 16 weeks (Β = −4.35, p = 0.049). However, the CRP was significantly higher in the overweight/obesity group than in the normal weight group (Β = 1.22, p = 0.045).

Table 3.

Comparison of the effects of exercise on changes in HRV and an inflammatory biomarker between the normal weight and the overweight/obesity groups over 16‐week period (N = 51).

Variables	Estimate	Standard Error	95% CI		t	p
			Lower	Upper
HRV parameters
LF/HF
Intercept	1.93	1.66	−1.40	5.25	1.16	0.251
Adherence	1.31	2.10	−2.90	5.51	0.62	0.536
Group	0.42	0.91	−1.39	2.24	0.46	0.645
Time	0.29	0.74	−1.18	1.77	0.40	0.692
Group × Time	−0.95	1.03	−3.01	1.11	−0.93	0.359
RMSSD (ms)
Intercept	24.01	7.73	8.51	39.51	3.11	0.003
Adherence	−2.51	9.91	−22.40	17.39	−0.25	0.801
Group	3.52	3.91	−4.26	11.31	0.90	0.370
Time	−0.36	2.32	−5.04	4.31	−0.16	0.876
Group × Time	−1.24	3.24	−7.76	5.28	−0.38	0.704
SDNN (ms)
Intercept	46.09	10.60	24.84	67.35	4.35	< 0.001
Adherence	−10.34	13.65	−37.74	17.06	−0.76	0.452
Group	2.07	5.19	−8.30	12.44	0.40	0.692
Time	−2.04	2.53	−7.13	3.04	0.81	0.423
Group × Time	1.37	3.53	−5.74	8.48	0.39	0.699
pNN50 (%)
Intercept	8.48	5.76	−2.97	20.12	1.49	0.142
Adherence	−3.59	7.38	−18.40	11.22	−0.49	0.629
Group	0.82	2.92	−4.99	6.63	0.28	0.781
Time	−0.72	1.76	−4.26	2.82	−0.41	0.685
Group × Time	−0.65	2.46	−5.59	4.26	−0.26	0.793
HR rest (bpm)
Intercept	70.09	5.60	58.86	81.32	12.52	< 0.001
Adherence	−1.55	7.19	−15.99	12.89	−0.22	0.830
Group	3.62	2.79	−1.95	9.19	1.30	0.199
Time	3.04	1.54	−0.06	6.14	1.97	0.054
Group × Time	−4.35	2.15	−8.68	−0.02	−2.02	0.049
Inflammatory biomarker
CRP (mg/L)
Intercept	5.16	1.03	3.09	7.24	5.01	< 0.001
Adherence	−2.93	1.35	−5.65	−0.21	−2.17	0.036
Group	−1.93	0.55	−2.49	−3.03	−3.48	0.001
Time	−0.86	0.43	−1.73	0.01	−2.00	0.052
Group × Time	1.22	0.59	0.03	2.42	2.06	0.045

Note: Participants in the normal weight group are set as reference.

Abbreviations: CRP, C‐reactive protein; CI, confidence interval; HF, high‐frequency; HR_rest, resting heart rate; HRV, heart rate variability; LF, low‐frequency; pNN50, proportion derived by dividing NN50 by the total number of NN intervals; RMSSD, root mean square of successive R‐R interval differences; SDNN, standard deviation of normal to normal interval.

3.4. Trajectory of Change in HRV Parameters During 16 Weeks of AE

Trends for resting, warm‐up, main exercise, and cool‐down phases over the 16‐week AE program showed a similar trajectory for the normal weight and overweight/obesity groups (Figure 2a–g). In both groups, the values of LF, HF, RMSSD, SDNN, and pNN50 were the highest at rest, decreased during the warm‐up phase, and reached their lowest during the main exercise phase. These values then increased during the cool‐down phase. However, the normal weight group consistently had higher LF, HF, RMSSD, and pNN50 values than did the overweight/obesity group. These parameters fluctuated more prominently in the normal weight group than in the overweight/obesity group. The LF/HF ratio slightly increased during the warm‐up phase, decreased during the main exercise phase, and then increased during the cool‐down phase in both the normal weight and overweight/obesity groups.

Figure 2.

The descriptive trajectories of HRV parameters across rest, warm‐up, main exercise, and cool‐down phases during exercise sessions over the 16‐week AE program. (a) LF; (b) HF; (c) LF/HF; (d) RMSSD; (e) SDNN; (f) pNN50; (g) heart rate. Values represent weekly group means averaged across the three sessions per week. HF, high‐frequency; LF, low‐frequency; pNN50, percentage of adjacent NN intervals varying by more than 50 ms; RMSSD, root mean square of successive RR‐intervals differences; SDNN, standard deviation of normal‐to‐normal intervals.

4. Discussion

To the best of our knowledge, this study is the first to compare the effects of a 16‐week AE program on HRV and CRP between community middle‐aged adults with normal weight and those with overweight/obesity. We expected lower HRV and higher CRP at baseline in the overweight/obesity group and anticipated improvements after AE, with group differences in intervention effects and HRV trajectories. The results partially supported these expectations. Baseline CRP was higher and resting heart rate decreased more in the overweight/obesity group, but CRP increased after AE. HRV trajectories across rest, warm‐up, main exercise, and cool‐down were largely similar between groups. However, parasympathetic‐related indices fluctuated more from rest to exercise in the normal weight group.

The overweight/obesity group experienced a greater reduction in resting heart rate than the normal weight group after the 16‐week AE program, which is consistent with previous studies reporting that participants with higher baseline BMI or inflammatory status showed greater improvements after AE (Jabbour and Iancu 2021; Wanderley et al. ²⁰¹³). Limited evidence suggests that individuals with overweight or obesity often have greater baseline sympathetic activation and more pronounced sympathovagal imbalance, which may result in larger improvements in autonomic regulation after exercise training (Notarius and Floras 2021; Zhang et al. ²⁰²⁵). This mechanism could explain the greater reduction in resting heart rate observed in the overweight/obesity group in the present study. Given that resting heart rate is an optimal biomarker of fitness level, cardiovascular health (Gonzales et al. 2023), and autonomic nervous system function (Sigrist et al. 2021), our findings suggest that individuals with overweight or obesity can improve these parameters within 16 weeks of AE, underscoring the importance of regular physical activity in this population.

In the present study, participants with overweight or obesity showed an increase in CRP after the 16‐week AE intervention compared with those with normal weight. Prior studies suggest that reductions in CRP are more pronounced when exercise is accompanied by weight loss (Son et al. 2023; Sturgeon et al. ²⁰²³). In our data, body weight and body fat showed small numerical changes in both groups; however, no statistically significant within‐group differences from T₀ to T₁ were observed. Therefore, the CRP pattern should not be attributed to adiposity changes alone. Although the between‐group difference in CRP change was statistically significant, the small sample size limited the precision of the estimate. Given that obesity is associated with autonomic imbalance and chronic low‐grade inflammation (Wiley et al. 2025), individuals with overweight or obesity may have a heightened inflammatory milieu at baseline. Exercise is a physiological stressor and may transiently amplify inflammatory responses in some individuals (Andarianto et al. 2022; Maaloul et al. ²⁰²³). However, such transient CRP elevations have mainly been reported after acute exercise and are generally expected to subside within approximately 24–48 h (Cerqueira et al. 2020). Therefore, given that post‐intervention blood samples (T₁) in this study were collected 1 week after completion of the intervention, the observed CRP increase in the overweight/obesity group may reflect a differential inflammatory adaptation to AE, highlighting the potential role of weight status in training‐related inflammatory responses.

Numerous studies have demonstrated that at least 12 weeks of moderate‐intensity AE can effectively improve body composition (Chang et al. 2023; Chang et al. ²⁰²²). However, in the present study, no significant change in body weight or adiposity was observed in the normal weight and the overweight/obesity groups. A possible explanation is that changes in body composition depend on overall energy balance, and dietary intake was not monitored in the present study. Participants may have increased caloric intake after exercise as a compensatory response, which could attenuate the expected improvements in body composition. Although an average of 85.96% of the participants reached vigorous intensity during each session, the expected improvements in body composition were not observed. A plausible explanation is that moderate‐intensity endurance exercise primarily relies on fat oxidation for energy, whereas vigorous‐intensity exercise relies more on carbohydrate metabolism (Noakes et al. 2023). This may also help explain why the CRP increased among the overweight/obesity group. Their higher body weight combined with 16 weeks of exercise and a previously inactive lifestyle may have exacerbated physiological stress, contributing to increased inflammation (Noushad et al. 2021). Thus, maintaining moderate intensity may be advisable for individuals with overweight or obesity to avoid placing excessive stress on the body. Further research is needed to validate these findings.

In the present study, we measured HRV parameters during each exercise session over the 16‐week intervention, including the resting, 10‐min warm‐up, 30‐min main exercise, and 10‐min cool‐down phases. Both the normal weight and overweight/obesity groups exhibited similar trajectory changes across phases. Although the LMM results did not reveal significant differences in the changes in HRV parameters between the two groups from T₀ to T₁, variations in HF, RMSSD, and pNN50, which are markers of parasympathetic activity, were more pronounced in the normal weight group. Notably, HRV fluctuations were greater in the normal weight group, indicating higher short‐term HRV and stronger autonomic nervous system activity in this group (Dias et al. 2022). Higher pNN50 values in this group further supported this observation (Jian et al. 2022). These findings indicate that individuals with normal weight maintain greater HRV adaptability throughout different exercise phases than in overweight/obesity groups. Therefore, exercise programs should be tailored to different BMI categories, with a particular emphasis on personalized exercise prescriptions for individuals with overweight or obesity.

4.1. Study Limitations

Our study measured HRV at baseline and post‐intervention and also recorded HRV parameters during each exercise session across the 16‐week program, allowing us to descriptively depict HRV trajectories over the intervention period. However, some limitations should be acknowledged. First, due to the relatively small sample size, participants with overweight and obesity were combined into a single group, which should be considered a limitation. Although no statistically significant baseline differences in HRV parameters or CRP were observed between the overweight and obesity subgroups, the small sample size limited statistical power to detect meaningful subgroup differences. Future studies should recruit larger samples and analyze overweight and obesity separately to better determine the effects of exercise on HRV and inflammatory outcomes across weight categories. Second, although the study recruited participants online from eight administrative districts, all participants were from a single city, which limits the generalizability of the findings. Third, habitual diet and other lifestyle behaviors were not objectively monitored during the intervention. Although participants were instructed to maintain their usual routines, we cannot rule out exercise‐related compensatory changes, such as increased energy intake or changes in sleep and stress, which may have confounded HRV outcomes. Finally, because multiple outcomes were tested without multiplicity adjustment, the risk of type I error is increased; therefore, the findings should be interpreted cautiously.

4.2. Implication for Nursing Practice

As exercise is a commonly recommended health‐promotion strategy in community settings, our exploratory findings suggest that adults with overweight or obesity may show less favorable autonomic adaptation during exercise, reflected by smaller rest‐to‐exercise HRV fluctuations. Therefore, healthcare professionals may consider closer monitoring of exercise responses, such as heart rate and perceived exertion, and individualizing the exercise dose accordingly. Given the observed increase in CRP in this group after the intervention, initiating AE at a moderate intensity and progressing gradually may be reasonable as a cautious approach to minimize excessive physiological stress and potential inflammatory responses.

5. Conclusion

Community residents with overweight or obesity had higher baseline CRP than did those with normal weight. After 16 weeks of AE, participants with overweight/obesity exhibited greater reductions in resting heart rate but significant increases in CRP than did those with normal weight. Both the normal weight and overweight/obesity groups followed similar HRV trajectories during rest and exercise phases. However, LF, HF, RMSSD, and pNN50 fluctuated more prominently between rest and exercise phases in the normal weight group. Our findings indicate different responses between community residents with normal weight and those with overweight or obesity regarding inflammatory status, resting heart rate, and HRV parameters during the 16‐week AE intervention. Individuals with overweight or obesity appeared to exhibit less favorable parasympathetic adaptation during exercise, and exercise exposure may be related to inflammatory responses in this group. Therefore, closer monitoring and individualized exercise planning may be warranted, particularly in individuals with overweight or obesity.

Author Contributions

Yu‐Hsuan Chang conceived and designed the study, supervised data collection and statistical analysis, contributed to data interpretation, drafted the manuscript, and revised it for important intellectual content. Shiow‐Ching Shun conceived and designed the study, contributed to data interpretation, and revised the manuscript for important intellectual content. Wei‐Li Hsu contributed to the study design, participated in data interpretation, and critically reviewed the manuscript. Kay L.H. Wu contributed to data interpretation and critically reviewed the manuscript.

Ethics Statement

This study was approved by National Cheng Kung University Human Research Ethics Committee in Taiwan (Number: NCKU HREC‐E‐111‐587‐2) and registered at ClinicalTrials.gov (NCT05949710).

Consent

All subjects have been informed and have signed the inform consent before their inclusion in the study.

Conflicts of Interest

The authors declare no conflicts of interest.

Data Availability Statement

The data that support the findings of this study are available on request from the corresponding author. The data are not publicly available due to privacy or ethical restrictions.