Next Article in Journal
Investigating Factors Influencing the National Cancer Screening Program among Older Individuals in Republic of Korea—Data from the Korea National Health and Nutrition Examination Survey VIII
Previous Article in Journal
Quality of Life of Colorectal Cancer Survivors: Mapping the Key Indicators by Expert Consensus and Measures for Their Assessment
 
 
Search for Articles:
Title / Keyword
Author / Affiliation / Email
Journal
Article Type
 
 
Advanced Search
 
Section
Special Issue
Volume
Issue
Number
Page
 
Journals
Healthcare
Volume 12
Issue 12
10.3390/healthcare12121236
healthcare-logo
Submit to this Journal Review for this Journal Propose a Special Issue
► Article Menu

Article Menu

share Share announcement Help format_quote Cite question_answer Discuss in SciProfiles thumb_up
...
Endorse textsms
...
Comment
first_page
settings
Order Article Reprints
Font Type:
Arial Georgia Verdana
Font Size:
Aa Aa Aa
Line Spacing:
Column Width:
Background:
Systematic Review

Exercise Effects on Autonomic Nervous System Activity in Type 2 Diabetes Mellitus Patients over Time: A Meta-Regression Study

by
Jui-Kun Chiang
1,
Po-Chen Chiang
2,
Hsueh-Hsin Kao
3,
Weir-Chiang You
3,* and
Yee-Hsin Kao
4,*
1
Department of Family Medicine, Dalin Tzu Chi Hospital, Buddhist Tzu Chi Medical Foundation, No. 2, Minsheng Road, Dalin, Chiayi 622, Taiwan
2
Department of Medicine, College of Medicine, National Taiwan University, Taipei 100, Taiwan
3
Department of Radiation Oncology, Taichung Veterans General Hospital, Taichung 407, Taiwan
4
Department of Family Medicine, Tainan Municipal Hospital (Managed by Show Chwan Medical Care Corporation), 670 Chung-Te Road, Tainan 701, Taiwan
*
Authors to whom correspondence should be addressed.
Healthcare 2024, 12(12), 1236; https://doi.org/10.3390/healthcare12121236
Submission received: 15 May 2024 / Revised: 10 June 2024 / Accepted: 13 June 2024 / Published: 20 June 2024
Browse Figures
Review Reports Versions Notes

Abstract

:
Background: Diabetic autonomic neuropathy is a common complication of type 2 diabetes mellitus (T2DM), especially in patients with long-term, poorly controlled diabetes. This study investigates the effects of exercise on autonomic nervous system activity in T2DM patients over time. Methods: A literature review using MEDLINE, Embase, Cochrane Library, Scopus, and PubMed identified studies assessed via heart rate variability. Papers were categorized into three groups: immediate effects (within 60 min), short-term effects (2–3 months), and long-term effects (over 4 months). Results: Nine articles with 161 T2DM patients were included in the meta-analysis. RMSSD changes after exercise were −4.3 (p = 0.227), 8.14 (p < 0.001), and 4.17 (p = 0.002) for the immediate, short-term, and long-term groups, respectively. LF/HF ratio changes were 0.21 (p = 0.264), −3.04 (p = 0.102), and −0.05 (p = 0.006) for the respective groups. Meta-regression indicated age, male gender, and exercise duration were associated with increased RMSSD, with coefficients of 2.36 (p = 0.001), 13.76 (p = 0.008), and 1.50 (p = 0.007), respectively. Age positively correlated with the LF/HF ratio, with a coefficient of 0.049 (p = 0.048). Conclusions: Regular exercise (≥3 times per week) for over 2 months increases parasympathetic activity in T2DM patients, while sympathetic activity decreases significantly after 4 months. Further study is needed to validate these findings.

1. Introduction

In 2021, more than five million people worldwide were living with diabetes [1]. Diabetes remains a significant public health challenge, with cardiovascular disease (CVD) representing the primary burden of type 2 diabetes mellitus (T2DM) in terms of morbidity, mortality, and socioeconomic costs for individuals and societies [2].
Diabetic autonomic neuropathy (DAN), characterized by impaired function of peripheral autonomic nerves, presents a broad array of manifestations affecting various organ systems, including cardiovascular, gastrointestinal, genitourinary, sudomotor, vasomotor, and neuroendocrine systems, and is prevalent among individuals with diabetes mellitus. The prevalence of DAN rises with the duration of diabetes. It may be detected in up to 7 percent of patients at the time of diabetes diagnosis [3,4]. Cardiac autonomic neuropathy (CAN) is another serious complication of T2DM that is strongly associated with approximately a five-fold increased risk of cardiovascular mortality. Clinical correlates or risk markers for CAN include age, duration of DM, glycemic control, hypertension, dyslipidemia, and the development of other microvascular complications [5].
Various measurements are available to assess cardiac autonomic neuropathy in patients with type 2 diabetes mellitus (T2DM). However, the standard cardiovascular reflex tests remain the gold standard for the assessment of cardiac autonomic neuropathy [6]. The heart rate variability (HRV) method is a non-invasive, reliable, and pain-free measurement to assess autonomic nervous activity [7]. Given the significant divergence in study methodologies, standardized tools are evidently needed to enhance the quality of measurements in current meta-analyses. Resting HRV is influenced by both psychological factors [8] and physiological factors, including age, gender, body mass index, chronic conditions [9], heart function, and heart diseases [10]. The root mean square of successive heart beat interval differences (RMSSD) for parasympathetic activity is endorsed by the Task Force of the European Society of Cardiology and the North American Society of Pacing and Electrophysiology [9] as well as by Sequeira et al. [11] and Kobayashi et al. [12]. Additionally, the ratio between the absolute power of the high-frequency (HF) band (0.015–0.400 Hz) and the absolute power of the low-frequency (LF) band (0.040–0.150 Hz), referred to as the LF/HF ratio, has been identified as an indicator of sympathovagal balance, which indirectly reflects the degree of cardiac sympathetic nervous system activity. [13]. In our current study, we employed the LF/HF ratio, a frequency-domain measurement index, as a proxy for sympathetic activity, following the methodology outlined in previous studies by AlQatari et al. [14] and Kobayashi et al. [15].
A systematic review reported that T2DM was associated with a decrease in parasympathetic activity, as indicated by RMSSD, while findings regarding sympathetic activity, as indicated by the LF/HF ratio, were inconclusive [7]. A previous systematic review reported that exercise, encompassing aerobic exercise combined with resistance training, high-intensity interval training, and progressive resistance training, had a positive impact on cardiac autonomic function in individuals with T2DM [16]. Additionally, a previous systematic meta-analysis reported a lower RMSSD but no change in the LF/HF ratio in T2DM patients compared to healthy participants [7]. Another systemic meta-analysis reported that exercise training, especially after endurance training and supervised training, improved HRV parameters in T2DM patients [17]. However, discussion on the duration of exercise training and its impact on autonomic activity improvement in T2DM patients is limited. Therefore, the aim of the present study is to investigate the effects of exercise on autonomic nervous system activity in patients with T2DM over a specified period of time.

2. Materials and Methods

2.1. Study Design

A systematic review and meta-analyses were conducted to identify studies examining the effects of exercise on autonomic nervous system activity in patients with type 2 diabetes mellitus over time. The Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines were followed [18]. The study protocol was reviewed and approved by the Research Ethics Committee of the Buddhist Dalin Tzu Chi Hospital in Taiwan (No. B11301022). The study was registered with PROSPERO(CRD42024552655).

2.2. Search Strategy

A wide search of the literature was conducted for studies indexed on MEDLINE, Embase, Cochrane Library, Scopus, and PubMed from their inception to 19 April 2024 in English (Figure 1). In our current study, we included clinical trials, case-controlled studies, and observational studies while excluding case-reported studies, poster articles, retrospective studies, systematic reviews, and meta-analysis studies. We utilized terms like “exercise”, including variations such as “run*”, “walk*”, “jog*”, “treadmill*”, “tread mill*”, and “racewalk*”. We searched for these terms within the title, abstract, and keywords. We systematically searched Ovid Medline, Embase, Cochrane Library, PubMed, and Scopus (Google Scholar) for relevant articles.

2.3. Study Selection

We applied the PICOS (participants, interventions, comparisons, outcomes, and study design) model to define the research question. The inclusion criteria were as follows: (1) patients with T2DM, (2) receiving regular exercise, and (3) studies in which the methods used to assess parasympathetic activity (such as RMSSD) and evaluate sympathetic activity (such as the LF/HF ratio) were presented as mean ± SD during the data extraction process. Studies were excluded if the data were ambiguous, no data after exercise were provided, or communication with the corresponding authors was not possible. The extracted data were verified by two independent reviewers (Y.-H.K. and J.-K.C.), which were further revalidated by H.-H.K. Any disagreements between the reviewers were resolved through consultation with a statistician. Subsequently, these two authors further screened the papers and selected nine for analysis.

2.4. Data Extraction

The following data from the included studies were recorded: author, year of publication, sample size, age (years), gender (percentage of women), presence of type 2 diabetes mellitus, and the values of parasympathetic activity (such as RMSSD) and sympathetic activity (such as the LF/HF ratio), which were presented as mean ± SD. The data extraction was independently conducted by two independent reviewers (Y.-H.K. and J.-K.C.). A standardized form for data extraction is provided in Supplementary Table S1.

2.5. Methodological Quality of Included Studies

After obtaining the eligible articles, data extraction and methodological quality assessment were carried out by two independent reviewers (Y.-H.K. and J.-K.C.). Methodological quality assessment was evaluated using the Downs and Black checklist [19]. This tool consists of 27 items, including five subscales, which are as follows: reporting, external validity, internal validity (study bias and confounding), selection bias, and study power. Poor quality is considered when a score of 14 or less is achieved, fair quality between 15 and 19, good quality between 20 and 25, and excellent quality when the score is higher or equal to 26 [20].

2.6. Data Collection and Analysis

The data were extracted into a standardized form by these two authors and then extracted into summary of findings tables. The authors were contacted to seek clarification on any ambiguous data regarding the methods used to assess parasympathetic activity, such as RMSSD, and evaluate sympathetic activity, such as detecting the LF/HF ratio, during the data extraction process. The studies, published between 2003 and 2024, included five randomized designs [21,22,23,24,25].

2.7. Data Synthesis and Publication Bias Check

After extracting and critically appraising the data, the included papers were analyzed using narrative synthesis. To guide the narrative synthesis process, we consulted the flowchart by Rodgers et al. [26], which offers guidance on synthesizing data, identifying patterns, assessing the strength of these patterns, and drawing conclusions based on them. To identify potential publication bias, we performed a funnel plot analysis. Egger’s test was particularly used to assess the symmetry of the funnel plot for detecting publication bias. The articles were screened, and discrepancies were resolved by two independent reviewers (Y.-H.K. and J.-K.C.). J.-K.C. also served as the statistician for the current study.

2.8. Statistical Analysis

The meta-analysis utilized the Knapp and Hartung adjustments to compute the weighted average of the studies, comparing pre- and post-exercise measurements across various intervals. The pooled summary effect was illustrated in a forest plot. Heterogeneity among the collected studies was assessed using the chi-square Q test and the I2 statistics. In cases of substantial heterogeneity, random-effects models were applied. Subgroup analyses for mean differences were conducted to explore heterogeneity, and meta-regression was employed to identify significant moderators.
To ensure the analysis’s quality, basic model fitting techniques, including goodness-of-fit (GOF) assessment and regression diagnostics, were applied in the meta-regression analysis for mean differences. The coefficient of determination, R2, was reported to evaluate the GOF of the fitted linear meta-regression model. Additionally, statistical tools for regression diagnostics were used to examine the data. The publication bias, residual analysis, and identification of influential studies were examined. Trial sequential analysis (TSA) was employed to determine if the sample size was adequate, relying on a type I error rate of 5% and a power of 90%. This method delineates boundaries for benefit, harm, and the inner wedge. Additionally, it evaluates overall efficacy through cumulative z-scores [27].
All statistical calculations were performed using R statistical software, version 4.2.3 (R Foundation for Statistical Computing, Vienna, Austria). A two-sided p-value ≤ 0.05 was considered statistically significant.

3. Results

We identified 1307 papers in the Ovid Medline database, 905 papers in the Embase database, 301 papers in the Cochrane Library database, 603 papers in the Scopus database, and 218 papers in the PubMed database. In total, we found 3334 papers. Among these, 1258 studies were excluded due to duplication, and 606 studies were excluded for not meeting the PICO criteria. Subsequently, we included 140 papers that specifically addressed T2DM. Additionally, 131 full-text articles were excluded because they did not meet the criteria for measuring autonomic nervous system activity, such as the presentation of median values or logarithmic values of the LF/HF ratio or RMSSD. Finally, nine studies involving 161 T2DM patients were included for meta-analysis. The methodological quality of these studies was evaluated using the Downs and Black quality assessment method, and all articles were classified as fair. These nine studies provided data on 161 T2DM patients (mean age, 54.97 years; 39.6% women), and details of these nine studies are presented in Table 1. These articles comprised both experimental and control groups, incorporating various exercise modalities such as aerobic exercise, resistance exercise, cycling, and self-paced walking on a treadmill. For the influence of exercise duration on T2DM, we classified these nine studies into three groups: immediate effects of exercise within 60 min, short-term effects spanning 2–3 months, and long-term effects exceeding 4 months. Four studies, comprising nine subgroups, were categorized under the immediate group [21,22,28,29]; two studies, with four subgroups, were classified under the short-term group [23,24]; and three studies, representing four subgroups, were allocated to the long-term group [25,30,31].
We observed that the mean difference in parasympathetic activity after exercise, as indicated by RMSSD, compared to pre-exercise levels, was −4.3 (95% confidence interval [CI]: −12.67–4.07, p = 0.227), 8.14 (95% CI: 5.23–11.06, p < 0.001), and 4.17 (95% CI: 1.58–6.76, p = 0.002) in the immediate (within 60 min), short-term (2–3 months), and long-term (4 or more months) groups, respectively (Figure 2). Similarly, the mean difference in sympathetic activity after exercise, represented by the LF/HF ratio, compared to pre-exercise levels, was 0.21 (95% CI: −0.21–0.64, p = 0.264), −3.04 (95% CI: −7.70–1.62, p = 0.102), and −0.05 (95% CI: −0.10–−0.01, p = 0.006) in the immediate, short-term, and long-term groups, respectively (Figure 3).
In our present study, we observed that the types of exercise in the short-term group included aerobic exercise (one subgroup), resistance training (one subgroup), or a combination of both (two subgroups). For the long-term group, the types of exercise comprised endurance training (one subgroup), walking training (one subgroup), and aerobic exercise (two subgroups). In the immediate-term group, the types of exercise included walking on a treadmill (one subgroup), table tennis (one subgroup), yoga (one subgroup), a maximal exercise test (two subgroups), moderate-intensity continuous exercise (MICE) (two subgroups), and acute high-intensity interval exercise (HIIE) (two subgroups).
Finally, as illustrated in Table 2, we conducted a mixed-effects linear meta-regression analysis using data from these nine studies to identify predictors for RMSSD and the LF/HF ratio. The meta-regression model indicated that age, male gender, and duration of exercise were associated with increased RMSSD after exercise. The estimated coefficients for these factors were 2.36 (95% CI: 1.01–3.72, p = 0.001), 13.76 (95% CI: 3.59–23.94, p = 0.008), and 1.50 (95% CI: 0.41–2.59, p = 0.007), respectively. Egger’s test did not detect funnel plot asymmetry for RMSSD (p = 0.489). Additionally, an R-square value of 0.836 indicated an excellent fit. The meta-regression model revealed that age was significantly associated with an increased LF/HF ratio after exercise, with an estimated coefficient of 0.05 (95% CI: 0.001–0.098, p = 0.048). Eggers’ test does not indicate the presence of funnel plot asymmetry for the LF/HF ratio (p = 0.250). However, the R-squared value was 0.093 (Figure 4). In the post-hoc analysis using trial sequential analysis, the cumulative Z-line crossed the boundary for the required sample size at the 95% confidence level for both RMSSD and the LF/HF ratio. Thus, it seems that the amount of data gathered in this study should be sufficient to explore this topic adequately. In the current TSA, we set alpha (type I error) at 0.05 and beta (type II error) at 0.1 (power at 0.9). Additionally, Tau2 was obtained at 0.10 for LF/HF and 0.57 for RMSSD (Figure 5). Table 3 contains details of the types of exercise used in each study and group, emphasizing the differences between the exercise methods and their potential influence on autonomic nervous system activity.
We further analyzed the data after excluding the immediate group and observed that the pooling RMSSD and LF/HF ratio after exercise, compared to pre-exercise levels, was 5.92 (95% CI: 3.98–7.86, p < 0.001) and −1.34 (95% CI: −3.14–0.46, p = 0.123), respectively. The trial sequential analysis (TSA)-adjusted 95% CI for the LF/HF ratio was −0.43 to 0.08. In the post-hoc analysis using TSA for the LF/HF ratio, the cumulative Z-line did not cross the boundary for benefit and fell within the futility boundary. Therefore, further studies on the benefits of exercise duration exceeding two months in T2DM patients might not be necessary for the LF/HF ratio. For RMSSD, the TSA-adjusted 95% CI was 3.98 to 7.86, and the cumulative Z-line crossed the trial monitoring boundary for benefit. However, this analysis for RMSSD did not reach the ideal sample size. Consequently, further large-scale studies on the benefits of exercise duration exceeding two months in T2DM patients are warranted for RMSSD.

4. Discussion

In the present meta-analysis, we observed that parasympathetic activity, as indicated by RMSSD, decreased immediately following exercise (within 60 min) but increased over the short term (2–3 months) and long term (4 months or more) with regular exercise (≥3 times per week) in patients with T2DM. However, the decrease in sympathetic activity after exercise, as indicated by the LF/HF ratio, was significant only in the long-term exercise group (4 months or more).
A prior study suggested that exercise therapy may improve HRV in patients with myocardial infarction, chronic heart failure, and those undergoing revascularization by increasing vagal tone and decreasing sympathetic activity. One hypothesis is that a shift toward greater vagal modulation, possibly mediated by angiotensin II and nitric oxide, may positively affect the prognosis of these individuals [32]. However, in the current study, sympathetic activity, as indicated by the LF/HF ratio, did not decrease in the immediate and short-term exercise groups but significantly decreased in the long-term group (exercise duration ≥4 months in individuals with T2DM). A previous study reported that exercise training could enhance parasympathetic activity, subsequently reducing the risk of lethal arrhythmias. The mechanism may involve the mediation of angiotensin II and nitric oxide in the effect of exercise on improving parasympathetic activity [32]. A previous study reported that regular exercise, particularly endurance training over a period of about three months, increased sympathetic and parasympathetic activity, as indicated by LF and HF measurements, in individuals with T2DM who had no or early CAN. However, this benefit was not observed in individuals with T2DM who had definite or severe CAN [33]. This may be due to a high genetic risk in this subpopulation, influenced significantly by gene–environment interactions, where intense physical activity is associated with an increased risk of cardiovascular outcomes [34].
A previous systematic meta-analysis reported that patients with type 2 diabetes mellitus (T2DM) had a lower RMSSD but no change in the LF/HF ratio compared to healthy participants [7]. Another systematic meta-analysis found that exercise training, especially endurance training and supervised training, could increase RMSSD and decrease the LF/HF ratio in T2DM patients [17]. However, the study by Picard et al. had a small number of participants and did not find a significant association between the duration of exercise and improvements in HRV. In the current study, parasympathetic activity, as indicated by RMSSD, increased after more than 2 months of regular exercise. Additionally, sympathetic activity, as indicated by the LF/HF ratio, significantly decreased after more than 4 months of regular exercise among individuals with T2DM.
The benefits of exercise training may indeed vary depending on the characteristics of the patients. A separate systematic review indicated that exercise effects were influenced by age (age <50), male gender, and individuals with T2DM, who appeared to experience greater benefits [35]. However, another systematic review found that age and gender were not associated with improvements in HRV parameters in T2DM patients [17]. In the current study, we observed a significant positive association between male gender, age, and duration of exercise and a decrease in parasympathetic activity in individuals with T2DM. TSA was conducted in the current study. We set alpha (type I error) at 0.05 and beta (type II error) at 0.1 (power 0.9). The number of collected studies exceeded the required information size [36], suggesting that the amount of data gathered should be sufficient to explore this topic adequately. Thus, it seems that the data collected in this study should be sufficient to explore this topic comprehensively.
There are several limitations to the current study. Firstly, we acknowledge the inherent limitations of all meta-analyses [37], including the constraints and biases present in the individual studies analyzed. Because the studies we collected followed the guidelines of the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA), selection bias might be limited. However, a potential limitation of the current study is that we did not use search terms related to physical activity, physical training, tai chi, or other exercises. Secondly, we conducted the meta-analyses solely on published articles, thereby potentially exposing them to publication bias. However, the use of broader keywords in our search strategy likely reduced the number of missing studies. Additionally, the included studies were homogeneous according to funnel plots, and the populations investigated in the current study appeared to be equally distributed around the world. Thirdly, there is substantial methodological variation in the literature regarding the responses of heart rate variability (HRV) to exercise, including exercise protocols and HRV analysis techniques. This warrants further research to standardize methods and ensure consistency in exercise protocols. Lastly, the low R-squared value of 0.093 for the LF/HF ratio in the current meta-regression study suggests that the sample size might have been insufficient. Further studies are warranted to elucidate these findings.

5. Conclusions

In the current meta-analysis, we found that parasympathetic activity, as indicated by RMSSD, decreased immediately following exercise but increased after regular exercise (≥3 times per week) for more than 2 months in patients with T2DM. However, the decrease in sympathetic activity following exercise, as evidenced by the LF/HF ratio, became significant after engaging in exercise for 4 months or longer. In the post-hoc analysis using the TSA, the cumulative Z-lines finally did not cross the boundary for benefit and fell in the futility boundary for both RMSSD and the LF/HF ratio. Further study is needed to validate these findings.
In the current meta-regression study, we found that age, male gender, and duration of exercise were associated with increased RMSSD after exercise. The meta-regression model revealed a significantly positive association between age and the LF/HF ratio after exercise.

Supplementary Materials

The following supporting information can be downloaded at: https://www.mdpi.com/article/10.3390/healthcare12121236/s1, Table S1: data extraction.

Author Contributions

Conceptualization, J.-K.C. and Y.-H.K.; methodology, J.-K.C.; validation, Y.-H.K.; formal analysis, J.-K.C. and H.-H.K.; investigation, P.-C.C. and W.-C.Y.; data curation, Y.-H.K.; writing—original draft preparation, J.-K.C. and Y.-H.K.; writing—review and editing, W.-C.Y. and Y.-H.K.; visualization, W.-C.Y. All authors have read and agreed to the published version of the manuscript.

Funding

This research received no external funding.

Institutional Review Board Statement

The study protocol was reviewed and approved by the Research Ethics Committee of the Buddhist Dalin Tzu Chi Hospital in Taiwan (No. B11301022, 13 March 2024).

Informed Consent Statement

Not applicable.

Data Availability Statement

No new data were created or analyzed in this study.

Conflicts of Interest

The authors declare no conflicts of interest.

References

  1. Collaborators, G.B.D.D. Global, regional, and national burden of diabetes from 1990 to 2021, with projections of prevalence to 2050: A systematic analysis for the Global Burden of Disease Study 2021. Lancet 2023, 402, 203–234. [Google Scholar]
  2. Bonora, E.; Cigolini, M. DPP-4 inhibitors and cardiovascular disease in type 2 diabetes mellitus. Expectations, observations and perspectives. Nutr. Metab Cardiovasc. Dis. 2016, 26, 273–284. [Google Scholar] [CrossRef] [PubMed]
  3. Vinik, A.I.; Freeman, R.; Erbas, T. Diabetic autonomic neuropathy. Semin. Neurol. 2003, 23, 365–372. [Google Scholar] [CrossRef] [PubMed]
  4. Kempler, P.; Tesfaye, S.; Chaturvedi, N.; Stevens, L.K.; Webb, D.J.; Eaton, S.; Kerenyi, Z.; Tamas, G.; Ward, J.D.; Fuller, J.H.; et al. Autonomic neuropathy is associated with increased cardiovascular risk factors: The Eurodiab Iddm Complications Study. Diabet. Med. 2002, 19, 900–909. [Google Scholar] [CrossRef] [PubMed]
  5. Serhiyenko, V.A.; Serhiyenko, A.A. Cardiac autonomic neuropathy: Risk factors, diagnosis and treatment. World J. Diabetes 2018, 9, 1–24. [Google Scholar] [CrossRef] [PubMed]
  6. Ewing, D.J.; Martyn, C.N.; Young, R.J.; Clarke, B.F. The value of cardiovascular autonomic function tests: 10 years experience in diabetes. Diabetes Care 1985, 8, 491–498. [Google Scholar] [CrossRef] [PubMed]
  7. Benichou, T.; Pereira, B.; Mermillod, M.; Tauveron, I.; Pfabigan, D.; Maqdasy, S.; Dutheil, F. Heart rate variability in type 2 diabetes mellitus: A systematic review and meta-analysis. PLoS ONE 2018, 13, e0195166. [Google Scholar] [CrossRef] [PubMed]
  8. McCraty, R.; Atkinson, M.; Tiller, W.A.; Rein, G.; Watkins, A.D. The effects of emotions on short-term power spectrum analysis of heart rate variability. Am. J. Cardiol. 1995, 76, 1089–1093. [Google Scholar] [CrossRef]
  9. Camm, A.J.; Malik, M.; Bigger, J.T.; Breithardt, G.; Cerutti, S.; Cohen, R.J.; Singer, D.H. Heart rate variability: Standards of measurement, physiological interpretation and clinical use. Task Force of the European Society of Cardiology and the North American Society of Pacing and Electrophysiology. Circulation 1996, 93, 1043–1065. [Google Scholar]
  10. Bigger, J.T., Jr.; Fleiss, J.L.; Steinman, R.C.; Rolnitzky, L.M.; Kleiger, R.E.; Rottman, J.N. Frequency domain measures of heart period variability and mortality after myocardial infarction. Circulation 1992, 85, 164–171. [Google Scholar] [CrossRef]
  11. Sequeira, V.C.C.; Bandeira, P.M.; Azevedo, J.C.M. Heart rate variability in adults with obstructive sleep apnea: A systematic review. Sleep Sci. 2019, 12, 214–221. [Google Scholar] [CrossRef] [PubMed]
  12. Kobayashi, H.; Ishibashi, K.; Noguchi, H. Heart rate variability; an index for monitoring and analyzing human autonomic activities. Appl. Human Sci. 1999, 18, 53–59. [Google Scholar] [CrossRef] [PubMed]
  13. Billman, G.E. The LF/HF ratio does not accurately measure cardiac sympatho-vagal balance. Front. Physiol. 2013, 4, 26. [Google Scholar] [CrossRef] [PubMed]
  14. AlQatari, A.A.; Alturki, J.A.; Abdulali, K.A.; Alhumud, D.A.; Alibrahim, M.A.; Alarab, Y.A.; Salem, A.M.; Yar, T.; Alqurashi, Y.D.; Alsunni, A.A.; et al. Changes in Heart Rate Variability and Baroreflex Sensitivity During Daytime Naps. Nat. Sci. Sleep 2020, 12, 661–669. [Google Scholar] [CrossRef] [PubMed]
  15. Kobayashi, H.; Song, C.; Ikei, H.; Park, B.J.; Lee, J.; Kagawa, T.; Miyazaki, Y. Forest Walking Affects Autonomic Nervous Activity: A Population-Based Study. Front. Public Health 2018, 6, 278. [Google Scholar] [CrossRef] [PubMed]
  16. Hamasaki, H. The Effect of Exercise on Cardiovascular Autonomic Nervous Function in Patients with Diabetes: A Systematic Review. Healthcare 2023, 11, 2668. [Google Scholar] [CrossRef]
  17. Picard, M.; Tauveron, I.; Magdasy, S.; Benichou, T.; Bagheri, R.; Ugbolue, U.C.; Navel, V.; Dutheil, F. Effect of exercise training on heart rate variability in type 2 diabetes mellitus patients: A systematic review and meta-analysis. PLoS ONE 2021, 16, e0251863. [Google Scholar] [CrossRef] [PubMed]
  18. Page, M.J.; McKenzie, J.E.; Bossuyt, P.M.; Boutron, I.; Hoffmann, T.C.; Mulrow, C.D.; Shamseer, L.; Tetzlaff, J.M.; Akl, E.A.; Brennan, S.E.; et al. The PRISMA 2020 statement: An updated guideline for reporting systematic reviews. BMJ 2021, 372, n71. [Google Scholar] [CrossRef] [PubMed]
  19. Downs, S.H.; Black, N. The feasibility of creating a checklist for the assessment of the methodological quality both of randomised and non-randomised studies of health care interventions. J. Epidemiol. Community Health 1998, 52, 377–384. [Google Scholar] [CrossRef]
  20. Deeks, J.J.; Dinnes, J.; D’Amico, R.; Sowden, A.J.; Sakarovitch, C.; Song, F.; Petticrew, M.; Altman, D.G. Evaluating non-randomised intervention studies. Health Technol. Assess. 2003, 7, 1–173. [Google Scholar] [CrossRef]
  21. Maroco, J.L.; Arrais, I.; Silvestre, T.; Pinto, M.; Laranjo, S.; Magalhaes, J.; Santa-Clara, H.; Fernhall, B.; Melo, X. Post-acute exercise cardiovagal modulation in older male adults with and without type 2 diabetes. Eur. J. Appl. Physiol. 2024, 124, 1475–1486. [Google Scholar] [CrossRef] [PubMed]
  22. Bhati, P.; Moiz, J.A.; Naqvi, I.H.; Hussain, M.E. Diagnostic performance of resting and post-exercise heart rate variability for detecting cardiac autonomic neuropathy in type 2 diabetes mellitus. Auton. Neurosci. 2019, 219, 53–65. [Google Scholar] [CrossRef] [PubMed]
  23. Piralaiy, E.; Siahkuhian, M.; Nikookheslat, S.D.; Pescatello, L.S.; Sheikhalizadeh, M.; Khani, M. Cardiac Autonomic Modulation in Response to Three Types of Exercise in Patients with Type 2 Diabetic Neuropathy. J. Diabetes Metab. Disord. 2021, 20, 1469–1478. [Google Scholar] [CrossRef] [PubMed]
  24. Kang, S.J.; Ko, K.J.; Baek, U.H. Effects of 12 weeks combined aerobic and resistance exercise on heart rate variability in type 2 diabetes mellitus patients. J. Phys. Ther. Sci. 2016, 28, 2088–2093. [Google Scholar] [CrossRef] [PubMed]
  25. Loimaala, A.; Huikuri, H.V.; Koobi, T.; Rinne, M.; Nenonen, A.; Vuori, I. Exercise training improves baroreflex sensitivity in type 2 diabetes. Diabetes 2003, 52, 1837–1842. [Google Scholar] [CrossRef] [PubMed]
  26. Rodgers, M.; Sowden, A.; Petticrew, M.; Arai, L.; Roberts, H.; Britten, N.; Popay, J. Testing methodological guidance on the conduct of narrative synthesis in systematic reviews: Effectiveness of interventions to promote smoke alarm ownership and function. Evaluation 2009, 15, 49–73. [Google Scholar] [CrossRef]
  27. Wetterslev, J.; Jakobsen, J.C.; Gluud, C. Trial sequential analysis in systematic reviews with meta-analysis. BMC Med. Res. Methodol. 2017, 17, 39. [Google Scholar] [CrossRef] [PubMed]
  28. Colberg, S.R.; Grieco, C.R.; Somma, C.T. Exercise effects on postprandial glycemia, mood, and sympathovagal balance in type 2 diabetes. J. Am. Med. Dir. Assoc. 2014, 15, 261–266. [Google Scholar] [CrossRef] [PubMed]
  29. Grieco, C.R.; Colberg, S.R.; Somma, C.T.; Thompson, A.G.; Vinik, A.I. Acute effect of breathing exercises on heart rate variability in type 2 diabetes: A pilot study. J. Altern. Complement Med. 2014, 20, 642–648. [Google Scholar] [CrossRef]
  30. Figueroa, A.; Baynard, T.; Fernhall, B.; Carhart, R.; Kanaley, J.A. Endurance training improves post-exercise cardiac autonomic modulation in obese women with and without type 2 diabetes. Eur. J. Appl. Physiol. 2007, 100, 437–444. [Google Scholar] [CrossRef]
  31. Pagkalos, M.; Koutlianos, N.; Kouidi, E.; Pagkalos, E.; Mandroukas, K.; Deligiannis, A. Heart rate variability modifications following exercise training in type 2 diabetic patients with definite cardiac autonomic neuropathy. Br. J. Sports Med. 2008, 42, 47–54. [Google Scholar] [CrossRef]
  32. Routledgecurdle, J.A.; Bacon, S.L. Improvements in heart rate variability with exercise therapy. Can J. Cardiol. 2010, 26, 303–312. [Google Scholar] [CrossRef] [PubMed]
  33. Howorka, K.; Pumprla, J.; Haber, P.; Koller-Strametz, J.; Mondrzyk, J.; Schabmann, A. Effects of physical training on heart rate variability in diabetic patients with various degrees of cardiovascular autonomic neuropathy. Cardiovasc. Res. 1997, 34, 206–214. [Google Scholar] [CrossRef] [PubMed]
  34. Lee, C.L.; Yamada, T.; Liu, W.J.; Hara, K.; Yanagimoto, S.; Hiraike, Y. Interaction between type 2 diabetes polygenic risk and physical activity on cardiovascular outcomes. Eur. J. Prev. Cardiol. 2024. [Google Scholar] [CrossRef] [PubMed]
  35. Lin, X.; Zhang, X.; Guo, J.; Roberts, C.K.; McKenzie, S.; Wu, W.C.; Liu, S.; Song, Y. Effects of Exercise Training on Cardiorespiratory Fitness and Biomarkers of Cardiometabolic Health: A Systematic Review and Meta-Analysis of Randomized Controlled Trials. J. Am. Heart Assoc. 2015, 4, e002014. [Google Scholar] [CrossRef] [PubMed]
  36. Kang, H. Trial sequential analysis: Novel approach for meta-analysis. Anesth. Pain Med. 2021, 16, 138–150. [Google Scholar] [CrossRef]
  37. LeLorier, J.; Gregoire, G.; Benhaddad, A.; Lapierre, J.; Derderian, F. Discrepancies between meta-analyses and subsequent large randomized, controlled trials. N. Engl. J. Med. 1997, 337, 536–542. [Google Scholar] [CrossRef]
Healthcare 12 01236 g001
Figure 1. PRISMA flow diagram of the study selection. * Each database along with the corresponding numbers of records identified.
Figure 1. PRISMA flow diagram of the study selection. * Each database along with the corresponding numbers of records identified.
Healthcare 12 01236 g001
Healthcare 12 01236 g002
Figure 2. Summary of the meta-analysis on the effect of training exercises on RMSSD in T2DM [22,23,24,28,29,31].
Figure 2. Summary of the meta-analysis on the effect of training exercises on RMSSD in T2DM [22,23,24,28,29,31].
Healthcare 12 01236 g002
Healthcare 12 01236 g003
Figure 3. Summary of meta-analysis on the effect of training exercise on the LF/HF ratio in T2DM [21,22,23,24,25,28,30,31].
Figure 3. Summary of meta-analysis on the effect of training exercise on the LF/HF ratio in T2DM [21,22,23,24,25,28,30,31].
Healthcare 12 01236 g003
Healthcare 12 01236 g004
Figure 4. The funnel plots for (a) RMSSD and (b) LF/HF ratio. Each included study is represented as a black dot.
Figure 4. The funnel plots for (a) RMSSD and (b) LF/HF ratio. Each included study is represented as a black dot.
Healthcare 12 01236 g004
Healthcare 12 01236 g005aHealthcare 12 01236 g005b
Figure 5. Trial sequential analysis for (a) RMSSD and (b) LF/HF ratio.
Figure 5. Trial sequential analysis for (a) RMSSD and (b) LF/HF ratio.
Healthcare 12 01236 g005aHealthcare 12 01236 g005b
Table 1. Characteristics of studies included in this systematic review.
Table 1. Characteristics of studies included in this systematic review.
PublicationKinds of ExerciseHealth StatusesN, Age (Years Old)Sympathetic Activity, Measured by the LF/HF RatioParasympathetic Activity, Measured by the RMSSD
Colberg, 2014 [28]Walk on a treadmillUncomplicated T2DMN = 12, 58.7 ± 2.4Pre-exercise: 2.9 ± 3.3
Immediate post-exercise: 2.6 ± 3.2		Pre-exercise: 1.4 ± 0.1
Immediate post-exercise: 1.3 ± 1.0
Table tennisUncomplicated T2DMN = 12, 58.7 ± 2.4Pre-exercise: 2.4 ± 3.5
Immediate post-exercise: 2.8 ± 4.7		Pre-exercise: 1.4 ± 0.1
Immediate post-exercise: 1.3 ± 0.1
Marôco, 2023 [21]HIIE 10minT2DMN = 12, 67 ± 8Pre-exercise: 3.2 ± 0.4
Immediate post-exercise: 3.2 ± 0.5		Not available
HIIE 60minT2DMN = 12, 67 ± 8Pre-exercise: 3.2 ± 0.4
Immediate post-exercise: 3.1 ± 0.4		Not available
MICE 10minT2DMN = 12, 67 ± 8Pre-exercise: 3.3 ± 0.3
Immediate post-exercise: 3.7 ± 0.3		Not available
MICE 60minT2DMN = 12, 67 ± 8Pre-exercise: 3.3 ± 0.3
Immediate post-exercise: 4.3 ± 0.5		Not available
Bhati, 2019 [23]A maximal
exercise test		T2DM with CANN = 27, 51.7 ± 6.1Pre-exercise: 1.5 ± 0.7
Immediate post-exercise: 1.4 ± 0.6		Pre-exercise: 24.6 ± 11.2
Immediate post-exercise: 10.7 ± 4.2
A maximal
exercise test		T2DM without CANN = 15, 50.2 ± 6.4Pre-exercise: 1.7 ± 1.3
Immediate post-exercise: 1.2 ± 1.8		Pre-exercise: 30.7 ± 15.6
Immediate post-exercise: 19.6 ± 11.3
Grieco, 2014 [29]YogaT2DMN = 12, 54.9 ± 7.4Not availablePre-exercise: 1.5 ± 0.4
Immediate post-exercise: 1.5 ± 0.1
Piralaiy, 2021 [23]Aerobic
training
(25–45 min per day, 3–5 times per week for 12 weeks)		T2DMN = 11, 55.2 ± 8.2Pre-exercise: 3.3 ± 1.8
Short-term post-exercise: 1.2 ± 1.6		Pre-exercise: 14.5 ± 5.0
Short-term post-exercise: 24.1 ± 4.0
Resistant
training
(25–45 min per day, 3–5 times per week for 12 weeks)		T2DMN = 11, 55.2 ± 8.2Pre-exercise: 6.1 ± 5.3
Short-term post-exercise: 1.0 ± 0.6		Pre-exercise: 13.7 ± 5.8
Short-term post-exercise: 25.7 ± 12.1
Combination aerobic and resistance training
(25–45 min per day, 3–5 times per week for 12 weeks)		T2DMN = 11, 55.2 ± 8.2Pre-exercise: 7.9 ± 6.1
Short-term post-exercise: 1.3 ± 0.9		Pre-exercise: 20.7 ± 17.4
Short-term post-exercise: 30.4 ± 15.9
Kang, 2016 [24]Combination aerobic and resistance training for 60 min per day, three times per week for 12 weeksT2DMN = 8, 56.0 ± 7.4Pre-exercise: 1.12 ± 0.3
Short-term post-exercise: 1.1 ± 0.2		Pre-exercise: 17.9 ± 5.4
Short-term post-exercise: 19.9 ± 6.8
Loimaala, 2003 [25]Endurance training twice a week and supervised muscle strength training twice a week for 12 monthsT2DMN = 24, 53.6 ± 6.2Pre-exercise: 0.32 ± 0.16
Long-term post-exercise: 0.39 ± 0.24		Not available
Figueroa, 2007 [30]16 weeks of walking trainingT2DMN = 8, 50.0 ± 1.0Pre-exercise: 1.01 ± 0.06
Long-term post-exercise: 0.93 ± 0.05		Not available
Pagkalos, 2008 [31]An aerobic exercise training program three times a week for 6 monthsT2DM with CANN = 17, 56.2 ± 5.8Pre-exercise: 5.0 ± 2.0
Long-term post-exercise: 4.4 ± 1.6		Pre-exercise: 13.4 ± 4.0
Long-term post-exercise: 18.1 ± 5.2
An aerobic exercise training program three times a week for 6 monthsT2DM without CANN = 15, 55.8 ± 5.6Pre-exercise: 6.1 ± 3.3
Long-term post-exercise: 5.2 ± 2.4		Pre-exercise: 19.7 ± 5.4
Long-term post-exercise: 22.7 ± 7.4
In the present study, we categorized these articles into three groups: immediate effects of exercise within 60 min, short-term effects spanning 2–3 months, and long-term effects exceeding 4 months. The order of suggestion was based on the interval from baseline to post-exercise, with immediate (9 subgroups), short-term (4 subgroups), and long-term (4 subgroups) effects. Abbreviation: CAN, cardiac autonomic neuropathy; LF/HF, the ratio between the absolute power of the high-frequency (HF) band (0.015–0.400 Hz) and the absolute power of the low-frequency (LF) band (0.040–0.150 Hz); HIIE, high-intensity interval exercise (consisted of 1 min exercise bouts at 90% of VO2 Reserve, alternated with 1 min active recovery bouts at 60% of VO2 Reserve (1:1 ratio); MICE, moderate continuous exercise (protocol intensity was set at 60% of VO2 Reserve, and the duration was adjusted for each participant to achieve the targeted energy expenditure) [21]; RMSSD, the root mean square of successive heartbeat interval differences.
Table 2. The significant factors associated with RMSSD and the LF/HF ratio by linear meta-regression.
Table 2. The significant factors associated with RMSSD and the LF/HF ratio by linear meta-regression.
OutcomeVariablesEstimate (95% C.I.)S.E.z Valuep Value
RMSSD
Mean age in years2.36 (1.01–3.72)0.683.430.001
Male (%)13.76 (3.59–23.94)5.192.650.008
The duration of exercise in months1.50 (0.41–2.59)0.562.690.007
Intercept−140.5 (−218.6–62.3)39.89−3.52<0.001
LF/HF ratio
Mean age in years0.05 (0.001–0.098)0.021.980.048
Intercept−2.99 (−5.86–−0.119)1.47−2.040.041
Abbreviations: LF/HF, the ratio between the absolute power of the high-frequency (HF) band (0.015–0.400 Hz) and the absolute power of the low-frequency (LF) band (0.040–0.150 Hz); RMSSD, the root mean square of successive heart beat interval differences.
Table 3. The summary of different groups by immediate, short-term, and long-term effects of exercise on autonomic nervous system activity.
Table 3. The summary of different groups by immediate, short-term, and long-term effects of exercise on autonomic nervous system activity.
The GroupsStudyTypes of ExercisesHRV MeasurementInfluence of Autonomic Nervous System Activity after Exercise
Immediate (exercise within 60 min)
Marôco, 2023 [21]MICE and HIIELF/HF ratioMild increase in the LF/HF ratio in MICE
Bhati, 2019 [22]A maximal
exercise test		RMSSD and LF/HF ratioDecrease in both RMSSD and LF/HF ratio
Colberg, 2014 [28]Walk on a treadmill and play table tennisRMSSD and LF/HF ratioThe RMSSD and LF/HF ratio decrease during treadmill walking, while the LF/HF ratio increases and the RMSSD decreases during table tennis
Grieco, 2014 [29]YogaRMSSDNo change
Short-term (exercise between 2–3 months)
Piralaiy, 2021 [23]Aerobic training, resistance training, and combinationRMSSD and LF/HF ratioIncrease in RMSSD and decrease in LF/HF ratio
Kang, 2016 [24]Combination aerobic and resistance trainingRMSSD and LF/HF ratioIncrease in RMSSD and no change in LF/HF ratio
Long-term (exercise exceeding 4 months)
Loimaala, 2003 [25]Endurance trainingLF/HF ratioIncrease in LF/HF ratio
Figueroa, 2007 [30]Walking trainingLF/HF ratioDecrease in LF/HF ratio
Pagkalos, 2008 [31]An aerobic exercise training programRMSSD and LF/HF ratioIncrease in RMSSD and decrease in LF/HF ratio
Abbreviation: HIIE, high-intensity interval exercise (consisted of 1 min exercise bouts at 90% of VO2 Reserve, alternated with 1 min active recovery bouts at 60% of VO2 Reserve (1:1 ratio); MICE, moderate continuous exercise (protocol intensity was set at 60% of VO2 Reserve, and the duration was adjusted for each participant to achieve the targeted energy expenditure) [21].
Disclaimer/Publisher’s Note: The statements, opinions and data contained in all publications are solely those of the individual author(s) and contributor(s) and not of MDPI and/or the editor(s). MDPI and/or the editor(s) disclaim responsibility for any injury to people or property resulting from any ideas, methods, instructions or products referred to in the content.

Share and Cite

MDPI and ACS Style

Chiang, J.-K.; Chiang, P.-C.; Kao, H.-H.; You, W.-C.; Kao, Y.-H. Exercise Effects on Autonomic Nervous System Activity in Type 2 Diabetes Mellitus Patients over Time: A Meta-Regression Study. Healthcare 2024, 12, 1236. https://doi.org/10.3390/healthcare12121236

AMA Style

Chiang J-K, Chiang P-C, Kao H-H, You W-C, Kao Y-H. Exercise Effects on Autonomic Nervous System Activity in Type 2 Diabetes Mellitus Patients over Time: A Meta-Regression Study. Healthcare. 2024; 12(12):1236. https://doi.org/10.3390/healthcare12121236

Chicago/Turabian Style

Chiang, Jui-Kun, Po-Chen Chiang, Hsueh-Hsin Kao, Weir-Chiang You, and Yee-Hsin Kao. 2024. "Exercise Effects on Autonomic Nervous System Activity in Type 2 Diabetes Mellitus Patients over Time: A Meta-Regression Study" Healthcare 12, no. 12: 1236. https://doi.org/10.3390/healthcare12121236

Note that from the first issue of 2016, this journal uses article numbers instead of page numbers. See further details here.

Article Metrics

Back to TopTop