The effect of different resistance exercise training intensities on cardiovascular risk factors: a systematic review and meta-analysis

Kirsten I de Oude; Roy G Elbers; Heike Gerger; Dederieke A M Maes-Festen; Alyt Oppewal

doi:10.1093/ehjopen/oeaf093

. 2025 Aug 12;5(5):oeaf093. doi: 10.1093/ehjopen/oeaf093

The effect of different resistance exercise training intensities on cardiovascular risk factors: a systematic review and meta-analysis

Kirsten I de Oude ^1,^2,^✉,², Roy G Elbers ^3,⁴, Heike Gerger ^5,⁶, Dederieke A M Maes-Festen ^7,⁸, Alyt Oppewal ^9,¹⁰

Editor: Magnus Bäck

¹ Department of General Practice, Intellectual Disability Medicine Research, Erasmus MC, University Medical Center Rotterdam, NA 1909, P.O. Box 2040, Rotterdam, 3000 CA, The Netherlands

² Academic Collaborative Research Center Healthy Ageing and Intellectual Disabilities, NA 1909, P.O. Box 2040, Rotterdam, 3000 CA, The Netherlands

³ Department of General Practice, Intellectual Disability Medicine Research, Erasmus MC, University Medical Center Rotterdam, NA 1909, P.O. Box 2040, Rotterdam, 3000 CA, The Netherlands

⁴ Academic Collaborative Research Center Healthy Ageing and Intellectual Disabilities, NA 1909, P.O. Box 2040, Rotterdam, 3000 CA, The Netherlands

⁵ Department of General Practice, Erasmus MC, University Medical Center Rotterdam, Rotterdam, NA 1909, P.O. Box 2040, Rotterdam, 3000 CA, The Netherlands

⁶ Faculty of Psychology, Department of Clinical Psychology, Open University of the Netherlands, P.O. Box 2960, Heerlen, 6401 DL, The Netherlands

⁷ Department of General Practice, Intellectual Disability Medicine Research, Erasmus MC, University Medical Center Rotterdam, NA 1909, P.O. Box 2040, Rotterdam, 3000 CA, The Netherlands

⁸ Academic Collaborative Research Center Healthy Ageing and Intellectual Disabilities, NA 1909, P.O. Box 2040, Rotterdam, 3000 CA, The Netherlands

⁹ Department of General Practice, Intellectual Disability Medicine Research, Erasmus MC, University Medical Center Rotterdam, NA 1909, P.O. Box 2040, Rotterdam, 3000 CA, The Netherlands

¹⁰ Academic Collaborative Research Center Healthy Ageing and Intellectual Disabilities, NA 1909, P.O. Box 2040, Rotterdam, 3000 CA, The Netherlands

^✉

Corresponding author. Tel: +31 613636990Email: k.deoude@erasmusmc.nl

Conflict of interest: None declared.

Roles

Kirsten I de Oude: Conceptualization, Data curation, Formal analysis, Methodology, Project administration, Visualization, Writing - original draft

Roy G Elbers: Conceptualization, Data curation, Methodology, Supervision, Writing - review & editing

Heike Gerger: Data curation, Formal analysis, Writing - review & editing

Dederieke A M Maes-Festen: Supervision, Writing - review & editing

Alyt Oppewal: Conceptualization, Data curation, Methodology, Supervision, Writing - review & editing

Magnus Bäck: Handling Editor

PMCID: PMC12448439 PMID: 40980719

Abstract

Resistance training effectively reduces cardiovascular risk factors (CVRFs). However, the optimal training intensity remains unclear. Firstly, this systematic review investigated the effects of different resistance training intensities on glycated haemoglobin (HbA1c), systolic blood pressure (SBP), low-density lipoprotein (LDL), and waist-to-hip ratio (WHR). Secondly, we aimed to compare the effect of different resistance training intensities with each other. We identified randomized controlled trials (n = 59) investigating progressive (n = 9), low (n = 15), moderate (n = 33), and high intensity (n = 4) resistance training in adults with CVRFs. We used random-effects models to investigate the effects of each intensity on CVRFs compared to non-active controls and meta-regression analyses to investigate differences in effect between training intensities. Meta-analyses showed statistically significant effects of low to moderate certainty. Progressive intensity reduced SBP {−14.70 mm/Hg, 95% confidence interval [CI] (−16.40; −13.00)} and LDL [−0.16 mmol/L, 95% CI (−0.19; −0.13)]. High intensity reduced HbA1c [−0.81%, 95% CI (−1.52; −0.10)], low intensity LDL [−0.10 mmol/L, 95% CI (−0.16; −0.04)], and moderate intensity WHR [−0.02, 95% CI (−0.03; −0.01)] and HbA1c [−0.40%, 95% CI (−0.66; −0.14)]. Meta-regression analyses showed high intensity was significantly more effective in reducing WHR than low intensity. No significant differences were found between resistance training intensities for HbA1c, SBP, and LDL. In one study, high intensity was more effective than low intensity in reducing WHR. However, the limited number of studies investigating high and progressive intensity and the certainty of evidence limits the ability for definitive conclusions. More research is needed for clarification on the effect of different resistance training intensities on multiple CVRFs.

Keywords: Cardiovascular risk factors, Resistance training, Blood pressure, Cholesterol, Diabetes Mellitus, Obesity

Graphical Abstract

Introduction

Cardiovascular diseases remain a global health concern, and despite preventive measures, cardiovascular diseases are still a leading cause of mortality.¹ In 2009, costs related to cardiovascular disease represented 9% of the total healthcare expenditure in the European Union.¹ According to the European Society of Cardiology (ESC) guidelines, the major cardiovascular risk factors (CVRFs) are hypercholesterolaemia, hypertension, cigarette smoking, diabetes mellitus, and obesity.¹

When managing these CVRFs, lower levels of these factors are better. For hypercholesterolaemia, the aim is to reduce low-density lipoprotein (LDL) cholesterol. A reduction in LDL of 1 mmol/L is associated with a 25% decrease in the risk of major vascular events.² For hypertension, a 5 mm/Hg reduction in systolic blood pressure (SBP) reduces the risk of major cardiovascular events by 10%.³ In adults with type 2 diabetes mellitus (DM2), a reduction of 1% in glycated haemoglobin (HbA1c) is associated with a decrease in the risk of cardiovascular disease with 5–7%.^4,5 For obesity, a healthy body composition should be achieved with a reduction in waist-to-hip ratio (WHR), which has been associated with all-cause mortality and risk of cardiovascular disease.⁶ A 0.01 increase in WHR has been associated with a 5% increase in risk of cardiovascular disease.⁶

Resistance training has been recommended as an effective intervention for reducing CVRFs.^1,7 Muscle tissue is the primary organ for glucose uptake and triglyceride disposal and therefore is important for metabolic rate.⁸ Previous studies in adults with CVRFs have shown that resistance training increases skeletal muscle mass, which led to improvements in glycaemic control, insulin sensitivity, blood pressure, body composition, and lipid profile.^8–10 These findings emphasize the importance of resistance training in the management of CVRFs.

Although previous systematic reviews showed the importance of resistance training on physiological and metabolic parameters in adults with CVRFs,^10–15 there is still a lot of variability in the training intensities used in training protocols. To increase muscle mass with resistance training, the American College of Sports Medicine (ACSM) guidelines recommend training all large muscle groups at an intensity of 70–80% of the one repetition maximum (1RM), two to three times per week. However, for special populations such as adults with CVRFs, the recommended intensities range between 40–50% of 1RM for older adults with hypertension and 70–85% of 1RM for adults with DM2 or hypercholesterolaemia.⁷ These different recommendations might explain the variability in training intensities used in studies. Furthermore, multimorbidity is highly prevalent in older adults who are at high risk for cardiovascular diseases,¹ which can make it difficult for clinicians to select the best intensity. This indicates the need for more clarity on the effectiveness of different resistance training intensities.

The effect of resistance training on individual CVRFs has been extensively investigated. Previous reviews investigating the effect of resistance training on CVRFs all found positive results. However, these reviews did not provide a comprehensive overview regarding different resistance training intensities for adults with multiple CVRFs. Three previous reviews^16–18 have investigated the effect of different resistance training intensities. However, one focused only on SBP in older adults,¹⁷ and the other two focused only on adults with DM2.^16,18 One review investigated the effect of the duration of resistance training on multiple CVRFs.¹⁹ Other reviews^20–23 investigated the effect of resistance training on CVRFs in general and did not differentiate between different intensities. Therefore, it is still unknown if there is one resistance training intensity that can be effective in reducing all the above-mentioned CVRFs and, if so, which intensity is the most effective.

Therefore, the primary aim of this study was to investigate the effect of low (<60% 1RM), moderate (60–80% 1RM), high (>80% 1RM), and progressive (50–100% 1RM) intensity resistance training on HbA1c, SBP, LDL, and WHR in adults who are at higher risk for cardiovascular diseases. The secondary aim was to compare the effects of different training intensities on CVRFs with each other. This review will therefore summarize the effects of different resistance training intensities on HbA1c, SBP, LDL, and WHR and give recommendations for clinical practice.

Methods

This systematic review is reported according to the PRISMA guidelines (see Supplementary material online, Appendix S1).²⁴ The protocol is registered in the International Prospective Register of Systematic Reviews (PROSPERO; CRD42022348929).

Study selection and eligibility criteria

For this review, we included randomized or cluster randomized controlled trials (RCTs). There were no restrictions for year of publication. We excluded reports of trials that could not be adequately translated by the research team.

Participants

The participants in the trials had to be 18 years or older and diagnosed with DM2, hypertension, hypercholesterolaemia, obesity, and/or metabolic syndrome defined as the combination of abdominal obesity, insulin resistance, hypertension, and hypercholesterolaemia.²⁵ Because thresholds and definitions for CVRF have changed over time and differ between published guidelines,^1,26,27 we used the thresholds and definitions applied by the investigators of each trial.

Intervention

The trials had to compare different resistance training interventions with each other or with a non-active control group or usual care. We defined non-active as no additional intervention that would increase the physical activity of participants throughout the study. Usual care had to be started prior to the trial. Usual care could, for example, include lifestyle recommendations or pharmaceutical interventions. We included trials that used conventional resistance training modalities; trials that used interval training with resistance were excluded. Trials that investigated combined interventions, such as resistance training and diet or resistance training and aerobic training, were excluded. Furthermore, the intensity of the resistance training had to be characterized as low (<60% of 1RM), moderate (60–80% of 1RM), high (>80% of 1RM), or progressive (50–100%). Trials that did not report clearly on the intensity used (as in reporting the % 1RM or the number of repetitions) were excluded. Finally, the duration of the exercise programme (minimum of 8 weeks) and frequency (minimum of two training sessions with a maximum of four per week) had to meet the ACSM recommendations.⁷

Outcomes

The trials had to report one of the following outcomes: HbA1c, SBP, LDL, or WHR. We selected HbA1c as it is a reliable measurement and is recommended by the American Diabetes Association for diagnosing DM2.²⁸ For hypertension, we selected SBP as it is shown to be related to cardiovascular diseases.²⁷ For hypercholesterolaemia, LDL was chosen because in primary care pharmaceutical interventions focus on the regulation of LDL as it is associated with CVD.²⁹ Finally, the primary outcome for obesity was WHR as it is the best predictive measurement of obesity for CVRF.³⁰ Glycated haemoglobin was reported in all included articles as %; therefore, we used this unit as reference for HbA1c to ensure accuracy with the source data. When LDL was reported as mg/dL we, converted it to mmol/L LDL.³¹

Search strategy and selection process

In collaboration with the medical library of Erasmus MC, University Medical Center Rotterdam, we developed a search strategy using a combination of relevant keywords and Medical Subject Headings (MeSH) for resistance training, CVRF, and study design. The search was conducted on 29 November 2019 and updated on 11 November 2023, in Embase, MEDLINE Ovid, SPORTDiscus, and the Cochrane Central Register of Controlled Trials (CENTRAL). The search strategy is provided in Supplementary material online, Appendix S2. Each record has been assessed by two reviewers independently. All records were assessed by K.I.d.O. as the first reviewer and by R.G.E. or S.B. as the second reviewers. Screening of titles and abstract was done using the Rayyan platform. The full-text reports of potentially eligible studies were obtained, which were assessed based on the predefined eligibility criteria. Any discrepancies were resolved through consensus discussion or consultation with a third reviewer. Reference lists of included reports and relevant systematic reviews were hand searched in addition to the electronical database search to ensure completeness of identified studies.

Data extraction

We used Google Forms (Google, Dublin, Ireland) to extract study characteristics (i.e. first author, year of publication, and study design), participant characteristics (i.e. sample size, age, sex, and population), details of the intervention (i.e. intensity, duration, frequency, type of and intervention), and outcome measures related to CVRFs (i.e. HbA1c (%), SBP (mmHg), LDL (mmol/L), and WHR).

The post-intervention means and standard deviations (SDs) from the intervention and control groups were extracted. If other statistical values were reported, we calculated the mean and SD using the available values.³² If both intention-to-treat analysis and per protocol analysis data were reported, only the data from the intention-to-treat analysis was extracted. Data extraction was done in duplicate, with the first author (K.I.d.O.) extracting the data for all included studies and R.G.E., H.G., A.O., and S.B. serving as the second reviewers. Any discrepancies were resolved through consensus discussion or consultation with a third reviewer.

Risk of bias

The risk of bias assessment was conducted using the revised Cochrane risk of bias tool (RoB 2).³³ For every domain of the tool, risk of bias was categorized into low risk (+), some concerns (±), or high risk (−). Two independent reviewers assessed the risk of bias on each domain for each outcome separately. All risk of bias assessments were completed by the first author (K.I.d.O.) and R.G.E., H.G., A.O., S.B., and L.K. served as the second reviewers. Any discrepancies were resolved through consensus discussion or consultation with a third reviewer.

Certainty of evidence

To determine the certainty of evidence for each outcome, we used the Grading of Recommendations Assessment, Development and Evaluation (GRADE) framework. We assessed our results in four domains: risk of bias, inconsistency, indirectness, and imprecision. The certainty of evidence for each outcome was rated as high, moderate, low, or very low.³⁴ For the assessments, we used the GRADEpro Guideline Development Tool (McMaster University and Evidence Prime, 2024).

Data analysis

Initially, we planned to conduct a network meta-analysis to compare the effect of different resistance training intensities. This approach would have allowed for the simultaneous comparison of multiple intensities, incorporating both direct and indirect evidence. However, during the data collection, we noticed a scarcity of multi-arm studies, which are needed for a network meta-analysis. Therefore, we performed pairwise meta-analyses and meta-regression analyses instead.

We used random-effects meta-analyses to analyse the effect estimates across studies, using a mean difference (MD). We analysed the effect estimates for each CVRF outcome and resistance training intensity. Statistical heterogeneity between studies for each analysis was assessed using I² statistics and τ², where heterogeneity was classified as low (I² < 25%), moderate (I² > 50%), and high (I² > 75%).³⁵

We detected outliers by checking the forest plots of each meta-analysis regarding lack of overlap between pooled 95% confidence intervals (95% CIs) and 95% CI of individual studies. Additionally, we used the leave-one-out method to check for the influence of individual study results on the overall effect size.³⁶ We checked the reports of outlier studies for possible mistakes in data extraction or methodological explanations for extreme values. Sensitivity analyses were performed excluding studies considered at high risk of bias, with baseline differences or based on the type of intervention (homebased programmes or elastic band training). We presented results from the meta-analyses in a forest plot with the MD as the effect size with 95% CI. In case of substantial heterogeneity (I² > 75%), we did not present pooled effect estimates. Additionally, we conducted meta-regression analyses to compare the effect of each training intensity on the CVRFs separately.

All statistical analyses were performed using R statistical software (v4.1.2; R Core Team, 2021) using the packages ‘meta’³⁷ for meta-analyses, ‘forestplot’³⁸ to plot the results, and ‘metafor’³⁹ for meta-regression analyses.

Results

Study selection

Figure 1 presents the study selection procedure. The search strategy identified 8870 records after duplicate removal. Following title and abstract screening, 234 reports were selected for full-text assessment. Of these, two reports could not be retrieved, one report was requested for full text with the author but was not received, 25 reports were conference abstracts, and 21 were trial registrations. Finally, 185 full-text reports were assessed, of which127 reports did not meet the inclusion criteria. These reports are presented in Supplementary material online, Appendix S3, with reason for exclusion. From reference screening, one additional report was included, which resulted in a total of 59 included studies.

Figure 1. PRISMA flowchart, Adapted from: Page MJ, McKenzie JE, Bossuyt PM, Boutron I, Hoffmann TC, Mulrow CD, et al. The PRISMA 2020 statement: an updated guideline for reporting systematic reviews. BMJ 2021;372:n71, distributed under the terms of the Creative Commons Attribution License CC BY 4.0. — PRISMA flowchart. Adopted from Page *et al*. (2021),⁴⁰ distributed under the terms of the Creative Commons Attribution License CC BY 4.0.

Characteristics of included studies

The characteristics of the included studies are presented in Supplementary material online, Appendix S4. The included studies were conducted in Asia (n = 33), North America (n = 10), South America (n = 9), Europe (n = 3), Oceania (n = 2), and Africa (n = 2). A total of 1862 adults with an average age ranging from 21 to 87 years were investigated. Two studies did not report sex distribution, 24 studies included only woman, 14 studies included only men, and 19 studies included both. The duration of the interventions ranged between 8 and 52 weeks, with an average of three^2–4 sessions per week. Fifteen studies^41–55 compared low intensity resistance training vs. a non-active control group, 34 studies^41,56–88 compared moderate intensity vs. a non-active control group, four studies^41,89–91 compared high intensity vs. a non-active control group, and nine studies^57,92–99 compared progressive intensity vs. a non-active control group.

Risk of bias assessment

A summary of the risk of bias assessments is reported in the forest plot for each outcome.

A total of 110 outcomes were assessed for risk of bias. Overall, 76 outcomes had some concerns of risk of bias, 31 had high risk of bias, and four had low risk of bias. The concerns are primarily due to bias within the randomization process (n = 85), bias due to missing outcome data (n = 57), and bias due to selectively reported results (n = 91).

Glycated haemoglobin

Figure 2 presents the results of our meta-analysis for HbA1c. A total of 16 studies with 675 adults (54.2% male) reported HbA1c as a study outcome, of these 14 studies included adults with DM2. The average age ranged between 44 and 68 years. Of these 16 studies, two studies investigated low intensity resistance training, nine studies moderate intensity resistance training, two studies high intensity resistance training, and three studies progressive resistance training.

For all outcomes, lower values indicate improvement. Therefore, negative MDs indicate superiority of the intervention over control in all analyses. Our meta-analyses showed statistically significant pooled effects of −0.40% HbA1c [95% CI (−0.66; −0.14)] for moderate intensity resistance training as compared to non-active control and of −0.81% HbA1c [95% CI (−1.52; −0.10)] for high intensity resistance training compared to non-active control. The statistical heterogeneity for low and progressive intensity resistance training was high; therefore, we did not report pooled effect estimates. The MDs for low intensity resistance training ranged from −2.02 to 0.30% HbA1c and for progressive intensity resistance training from −1.82 to 0.20% HbA1c.

Our meta-regression model (I² = 81.87%; τ² = 0.40) showed no statistical differences in effect on HbA1c between training intensities. All outputs of our meta-regression analyses are presented in Supplementary material online, Appendix S5.

Sensitivity analyses

We detected three outliers.^45,76,97 In the study of Oliveira et al., we discovered baseline differences for HbA1c between intervention and control groups. However, excluding this study did not change the heterogeneity or pooled effect estimate.

We found high heterogeneity for low (I² = 93%; τ² = 2.51) and progressive intensity resistance training (I² = 88%; τ² = 0.86). Due to the lack of studies for low intensity resistance training (n = 2), we could not conduct sensitivity analysis for this intensity. For progressive intensity, we excluded the study by Plotnikoff et al. based on the type of intervention. This did not result in a decrease of the heterogeneity or a change in the pooled effect estimate.

Excluding the study by Plotnikoff et al. from the meta-regression analysis decreased the heterogeneity (I² = 77.18%; τ² = 0.32), but still no statistical differences between training intensities was found.

Systolic blood pressure

Figure 3 presents the results for SBP. A total of 34 studies with 1143 adults (41.9% male) reported SBP as a study outcome; only 17 of these studies included adults with hypertension or metabolic syndrome. The average age ranged between 30 and 72 years. Of these studies, seven studies investigated low intensity resistance training, 18 studies moderate intensity resistance training, two studies high intensity resistance training, and seven studies investigated progressive resistance training.

High intensity resistance training showed a non-statistically significant pooled effect of −1.49 mmHg [95% CI (−6.59; 3.61)] compared to non-active control. Progressive intensity resistance training showed a statistically significant pooled effect of −14.70 mmHg [95% CI (−16.40; −13.00)]. The heterogeneity for low and moderate intensity resistance training was high; therefore, we do not report pooled effect estimates. The MDs for low intensity resistance training ranged from −20.00 to 6.00 mmHg, and for moderate intensity resistance training from −20.46 to 0.80 mmHg.

Our meta-regression model (I² = 93.40%; τ² = 38.76) showed no statistical differences in effect on SBP between training intensities.

Sensitivity analyses

We checked outliers^53,78,89 for any mistakes in data extraction. We found high heterogeneity for low (I² = 98%; τ² = 75.14), moderate (I² = 86%; τ² = 31.16), and progressive intensity resistance training (I² = 93%; τ² = 29.87). Sensitivity analyses did not provide any explanations for low and moderate intensity.

For progressive intensity, we excluded the studies by Plotnikoff et al., Son et al., Son., and Gao et al. based on the type of intervention, which decreased the heterogeneity (I² = 1%; τ² = < 0.001) and increased the pooled effect estimate from −7.62 [95% CI (−12.02; −3.22)] to −14.70 mmHg [95% CI (−16.40; −13.00)].

After excluding the above-mentioned studies in the meta-regression analysis, heterogeneity did not change. However, the estimate for progressive intensity resistance training increased from 0.45 [95% CI (−6.78; 7.68)] to −5.61 mmHg [95% CI (−14.90; 3.68)], but still no statistical differences were found between training intensities.

Low-density lipoprotein

Figure 4 presents the results for LDL. A total of 41 studies with 1324 adults (32.8% male) reported LDL as a study outcome, and eight studies only included adults with hypercholesterolaemia or metabolic syndrome. The average age ranged between 23 and 75 years. Of these 41 studies, 11 studies investigated low intensity resistance training, 25 studies moderate intensity training, three studies high intensity resistance training, and four studies progressive intensity resistance training.

The meta-analyses showed a significant pooled effect for low intensity resistance training of −0.10 mmol/L [95% CI (−0.16; −0.04)] and progressive intensity resistance training of −0.16 mmol/L [95% CI (−0.19; −0.13)] as compared to non-active control. The heterogeneity for moderate and high intensity resistance training was high; therefore, we did not report pooled effect estimates. The MDs for moderate intensity resistance training ranged from −1.65 to 0.44 mmol/L, and for high intensity resistance training from −0.81 to 0.02 mmol/L.

The meta-regression model (I² = 94.29%; τ² = 0.11) showed no statistical differences in effect on LDL between training intensities.

Sensitivity analyses

We found high heterogeneity for the effect of resistance training on LDL for moderate (I² = 94%; τ² = 0.16) and high intensity resistance training (I² = 79%; τ² = 0.12). Excluding Tomeleri et al. (highly deviant MD) and studies at high risk of bias^{41,61,65,67,78,87,88} in the sensitivity analysis decreased the heterogeneity for moderate intensity resistance training (I² = 80%; τ² = 0.04). For high intensity resistance training, we could not do sensitivity analysis due to the small number of studies included (n = 3).

After excluding the above-mentioned studies for moderate intensity resistance training in the meta-regression analysis, we found a decrease in heterogeneity (I² = 68.48%; τ² = −5.47); however, still no statistical differences were found between training intensities.

Waist-to-hip ratio

Figure 5 presents the results for WHR. A total of 16 studies with 426 adults (43.19% male) reported WHR as a study outcome, and 11 studies only included adults who were obese. The average age ranged between 21 and 75 years. Of these studies, three studies investigated low intensity resistance training, 10 studies moderate intensity training, one study high intensity resistance training, and three studies progressive intensity resistance training.

The meta-analysis showed a significant pooled effect for moderate intensity resistance training of −0.02 [95% CI (−0.03; −0.01)] and for progressive intensity resistance training of −0.06 [95% CI (−0.10; −0.02)] compared to non-active control. A non-significant pooled effect estimate was found for low intensity resistance training of 0.01 [95% CI (−0.04; 0.05)]. High intensity resistance training was investigated by only one study showing a MD in WHR of −0.09 [95% CI (−0.10; −0.08)].

The meta-regression model (I² = 68,10%; τ² = 51.08) showed that there was a statistical difference in effect estimates between low and high intensity resistance training and between low and progressive intensity resistance training. With high and progressive being more effective compared to low intensity resistance training.

Sensitivity analyses

We found two outliers^72,76 for moderate intensity resistance training in our meta-analysis. For Oliveira et al., we did not find an explanation for the larger MD found in this study. The mean value for WHR in the control group in the study of Kolahdouzi et al. increased between baseline and post-intervention, resulting in a larger MD between groups.

We found high heterogeneity for progressive intensity resistance training (I² = 70%; τ² = 0.001). However, we could not find any explanation for the observed heterogeneity.

For low intensity resistance training, we conducted a sensitivity analysis based on the type of intervention, excluding Rashidi et al. Excluding this study explained all heterogeneity for low intensity resistance training. The pooled effect estimate changed from 0.01 [95% CI (−0.04; 0.05)] to −0.01 [95% CI (−0.05; 0.03)].

Excluding the study of Rashidi et al. in our meta-regression analysis increased the effect estimate of low intensity resistance training, resulting in a non-significant difference between low and progressive intensity resistance training. The effect estimate of high intensity resistance training remained significantly higher than low intensity resistance training. No change in heterogeneity of the regression model was found.

Certainty of evidence

The certainty of evidence is presented in Table 1. For all resistance training intensities, the certainty of evidence was downgraded due to serious (moderate and progressive intensity) and very serious (low and high intensity) concerns for risk of bias. Subsequently, evidence for low, moderate, and progressive intensity resistance training was downgraded due to serious concerns because of inconsistency in the study results, and evidence for low and high intensity resistance training was downgraded for serious concerns because of imprecision in the study results. Resulting in an overall very low certainty of evidence for low and high intensity resistance training, low certainty for moderate intensity resistance training, and low to moderate certainty for progressive intensity resistance training.

Table 1.

GRADE evidence profile

Certainty assessment							Number of patients		Pooled effect MD [95% CI]	Range of MD [95% CI] (individual studies)	Certainty ⨁⨁⨁⨁
Outcome	n studies	Risk of bias	Inconsistency	Indirectness	Imprecision	Other factors	I	C	Pooled effect MD [95% CI]	Range of MD [95% CI] (individual studies)	Certainty ⨁⨁⨁⨁
Low intensity
HbA1c	2	Very serious^a	Serious^b	Not serious^c	Serious^d	None	34	32		0.30 [−0.22; 0.82] to −2.02 [−3.10; −0.94]	⨁ Very low
SBP	7	Very serious^a	Serious^b	Not serious	Not serious	None	161	125		−20.00 [−21.02; −18.98] to 6.00 [−3.29; 15.29]	⨁ Very low
LDL	11	Serious^e	Not serious	Not serious	Not serious	None	137	137	−0.10 [−0.16; −0.04]		⨁⨁⨁ Moderate
WHR	3	Serious^e	Not serious	Not serious	Serious^d	None	33	33	0.01 [−0.04; 0.05]		⨁⨁ Low
Moderate intensity
HbA1c	9	Serious^e	Not serious	Not serious	Not serious	None	199	198	−0.40 [−0.66; −0.14]		⨁⨁⨁ Moderate
SBP	18	Serious^e	Serious^b	Not serious	Not serious	None	226	218		−20.46 [−30.79; −10.13] to 0.80 [−12.32; 13.92]	⨁⨁ Low
LDL	25	Serious^e	Serious^b	Not serious	Not serious	None	407	402		−1.65 [−1.92; −1.38] to 0.44 [−0.07; 0.94]	⨁⨁ Low
WHR	10	Serious^e	Serious^b	Not serious	Not serious	None	103	105	−0.02 [−0.03; −0.01]		⨁⨁ Low
High intensity
HbA1c	2	Very serious^a	Not serious	Not serious	Not serious	None	43	43	−1.20 [−1.86; −0.54]		⨁⨁ Low
SBP	2	Very serious^a	Not serious	Not serious^f	Serious^d	None	43	43	−1.49 [−6.59; 3.61]		⨁ Very low
LDL	3	Very serious^a	Serious^b	Not serious	Serious^d	None	54	54		−0.81 [−1.14; −0.48] to 0.02 [−0.44; 0.48]	⨁ Very low
WHR	1	Very serious^a	Not serious	Not serious	Not serious	None	15	15	−0.09 [−0.10; −0.08]		⨁⨁ Low
Progressive intensity
HbA1c	4	Serious^e	Serious^b	Not serious	Not serious^c	None	66	62		−1.82 [−2.57; −1.07] to 0.20 [−0.41; 0.81]	⨁⨁ Low
SBP	8	Serious^e	Not serious^g	Not serious^c	Not serious	None	119	112	−14.70 [−16.40; −13.00]		⨁⨁⨁ Moderate
LDL	4	Serious^e	Not serious	Not serious	Not serious	None	81	75	−0.16 [−0.19; −0.13]		⨁⨁⨁ Moderate
WHR	3	Serious^e	Serious^h	Not serious	Not serious	None	49	43		−0.10 [−0.16; −0.04] to −0.03 [−0.05; −0.01]	⨁⨁ Low

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^aMost information is from studies at high risk of bias.

^bHigh heterogeneity and significant.

^cDifferent types of intervention.

^dConfidence interval includes no effect.

^eMost information is from studies at moderate risk of bias.

^fOne study had a population without hypertension.

^gHeterogeneity explained by subgroup analysis for the type of intervention.

^hResults are not consistent.

Discussion

The aim of this systematic review was to summarize the effects of different resistance training intensities on multiple CVRFs. We aimed to give an overview of the evidence to give clinical recommendations for the use of resistance training in adults with multiple CVRFs. This systematic review presents data from 59 trials investigating the effect of resistance training on CVRFs. To our knowledge, there has not previously been such a comprehensive review on the effect of different resistance training intensities on multiple CVRFs.

Our meta-regression analyses showed no statistically significant differences between the effect of different training intensities on HbA1c, SBP, and LDL. Our results did show a statistically significant difference between low and high intensity resistance training on WHR. The meta-regression models showed bigger effect estimates with higher training intensities. These findings show indications that a higher training intensity has a bigger effect on CVRFs. However, overall, the number of studies that investigated high (n = 4) and progressive (n = 9) intensity resistance training in this review was small. This could explain why we did not find statistical differences between training intensities, except for the effect of low vs. high intensity resistance training on WHR.

For HbA1c, our meta-analysis showed a positive significant pooled effect estimate of −0.40% for moderate intensity and −0.81% for high intensity. The systematic reviews by Fan et al. (−0.49% HbA1c) and Liu et al. (−0.61% HbA1c) found greater reductions on HbA1c for high intensity resistance training (75–100% 1RM) than for low−moderate intensity. However, these reviews categorized studies that used progressive intensity as high intensity and could therefore not differentiate between these intensities. Costa et al. conducted a subgroup analysis based on training intensity and found a positive effect on LDL of −7.70 mg/dL for studies that used a progressive training protocol. This is similar to our results where we found a positive pooled effect of progressive intensity on LDL of −0.16 mmol/L (−6.19 mg/dL).

For WHR, our meta-analysis showed a significant reduction in WHR for moderate intensity of −0.02 and a non-significant increase in WHR for low intensity resistance training of 0.01. Meta-regression analysis showed that high intensity resistance training reduced WHR significantly more compared to low intensity. However, the effect of high intensity resistance training on WHR was only investigated in one study. Previous reviews found similar results. Fan et al. found non-significant effect sizes of 0.01 for WHR for high intensity training and of −0.02 for low–moderate intensity training in adults with DM2. Lopez et al. found no association between whole body fat mass and training intensity in adults who were overweight or obese.

The results are of moderate and low certainty of evidence, mostly due to risk of bias and inconsistency of the results. We found substantial between-study heterogeneity in most of our results, indicating that there is high variability between studies. The inclusion of studies with a variety of participant populations and intervention characteristics such as duration and supervision could explain this variability. Furthermore, although only RCTs were included in this review, our risk of bias assessment showed concerns due to bias within the randomization process, missing outcome data, and reported results.

Strengths and limitations

Our systematic review and meta-analysis have several strengths. We used two analytical approaches to compare the effects of different training intensities on CVRFs. First, we conducted meta-analyses according to training intensities for each CVRF. Second, we conducted meta-regression analyses to statistically compare the effects of different training intensities. Furthermore, subgroup analyses were conducted to explain heterogeneity and inconsistencies in the results. Finally, we included studies from different parts of the world, which contribute to the generalizability of our results. We did exclude studies because we were not able to translate the reports adequately (n = 12). However, given the number of included studies, we consider the risk of missing relevant studies to be small.

This review was conducted according to a predefined protocol. However, due to the scarcity of multi-arm studies it was not possible to conduct a network meta-analysis. Therefore, we deviated from our protocol regarding the conducted analyses. This limits the possibility to rank the training intensities and affects the certainty of evidence based on indirectness.

For our pairwise meta-analysis, we used the mean post-intervention scores. This method does not correct for mean baseline scores, which may have resulted in large inter-study effect size differences and imprecision of our results. We tried to account for baseline differences in sensitivity analyses by excluding outlier studies with baseline differences between study groups.

Another limitation is that WHR was the only anthropometric outcome consistently reported across the included studies. As WHR is a ratio, it does not clarify whether changes are driven by reductions in waist circumference, increases in hip circumference, or both, which limits interpretation of the specific nature of body composition changes. Although the use of WHR has its limitations, it has been shown in previous research to be a reliable and valid indicator of central adiposity and obesity-related health risk.^6,30 Moreover, there is currently no consensus on the most appropriate anthropometric measure, with ongoing debate surrounding the use of WHR, waist circumference, waist-to-height ratio, body roundness index, and other indices.^100–102

Clinical considerations

Previous research has demonstrated that a reduction of 1% HbA1c, 5 mm/Hg SBP, and 1 mmol/L LDL is of clinical relevance, as it reduces the risk of cardiovascular diseases and mortality.^2–5 An increase of 0.01 in WHR has been associated with a 5% increase in the risk for cardiovascular diseases.⁶ Considering these thresholds, the statistically significant pooled effect estimates presented in our review suggest that clinically relevant reductions can be achieved in WHR with moderate and progressive intensity resistance training and in SBP with progressive resistance training. Our findings show positive effects of different resistance training intensities on CVRFs. However, achieving a clinically relevant reduction in the risk of cardiovascular diseases may require more than resistance training alone. In clinical practice, resistance training should be used in a broader, multicomponent intervention including changes towards a healthy lifestyle, such as healthy nutrition, no smoking, limited alcohol use, and good sleep, other training modalities, and, if needed, medication.¹ However, further research is needed in order to evaluate the effectiveness of different combinations of lifestyle interventions and medication.

Adults with CVRFs often have higher age, multiple chronic conditions, and an unhealthy lifestyle with low physical activity levels.¹ These factors can increase the risk for injuries and impact the ability to perform resistance training when not done with the right guidance and supervision.⁷ Multimorbidity and low levels of physical activity also can lead to deconditioning and insecurity to exercise, which may impede starting with resistance training, especially at a higher intensity. Therefore, starting with low intensity resistance training may be needed.⁷ Furthermore, due to comorbidities, such as obesity, people might feel physically uncomfortable while exercising or have had previous negative experiences with exercise.^7,101 Starting with an easy low intensity resistance training could contribute to a positive experience with exercise. A more cautious approach in resistance training with a gradually increase in intensity can decrease the risk of injuries and increase confidence in exercising. Given that all training intensities demonstrated clinically relevant effects and considering the complexity involved in training with adults with CVRFs, progressive resistance training could be considered as a suitable resistance training intervention in clinical practice. The initial intensity and progression should be personalized by the clinician based on medical history and individual abilities.

Future research

For further clarification of the effectiveness of different resistance training intensities on CVRFs, future research should focus on comparing different intensities directly. Given the limited number of trials investigating the effect of low, high, and progressive intensity resistance training on CVRFs, future research should prioritize investigating these intensities. Although progressive resistance training includes all other intensities, we consider it to be both conceptually and physiologically different from protocols that use a fixed intensity. In comparison to fixed intensities, progressive resistance training avoids performance plateaus and stimulates neuromuscular and structural adaptations.^100,103 These differences could influence the effect of resistance training on CVRFs, and therefore we recommend considering progressive intensity resistance training as a separate category.

To address the observed heterogeneity in our meta-analyses, future research should also focus on the association between person-characteristics and training effects. Identifying person-characteristics that act as moderating factors will allow for better personalized training suggestions.

Additionally, future research should aim to include and report a broader range of anthropometric measurements.^101,102,104 This will allow for a more accurate interpretation of anthropometric changes and their association with health outcomes. Using multiple measures can help clarify whether observed effects are due to changes in fat mass, muscle mass, or body shape.

Finally, as current evidence is of moderate to low quality, future studies should improve the transparency of the reported methods considering the randomization process and missing outcome data to reduce risk of bias. Additionally, future trials should consider applying statistical methodologies that account for baseline differences between study groups. This will contribute to reducing bias and allow for a more accurate estimation of the true effect. In turn, this will enhance the quality of evidence of future meta-analyses.

Conclusion

This review investigated the effect of low, moderate, high, and progressive intensity resistance training on CVRFs in adults who are at higher risk of cardiovascular diseases. Our findings showed no significant differences in effect between resistance training intensities for HbA1c, SBP, and LDL. One study showed that high intensity was more effective than low intensity in reducing WHR. These results are of low to moderate certainty of evidence. Further research is needed to explore the effect of different resistance training interventions with each other and individual characteristics, to enable personalized training recommendations in the future. The quality of the reported results must be increased. Based on the current evidence, clinicians should personalize the intensity of resistance training based on individual and medical factors.

Supplementary Material

oeaf093_Supplementary_Data

oeaf093_supplementary_data.zip^{(290.2KB, zip)}

Acknowledgements

We would like to thank the medical library of Erasmus MC, University Medical Center Rotterdam, specifically W.B. for his help in constructing the systematic search. We would also like to thank L.K. and S.B. for their help with data extraction and risk of bias assessments.

Contributor Information

Kirsten I de Oude, Department of General Practice, Intellectual Disability Medicine Research, Erasmus MC, University Medical Center Rotterdam, NA 1909, P.O. Box 2040, Rotterdam, 3000 CA, The Netherlands; Academic Collaborative Research Center Healthy Ageing and Intellectual Disabilities, NA 1909, P.O. Box 2040, Rotterdam, 3000 CA, The Netherlands.

Roy G Elbers, Department of General Practice, Intellectual Disability Medicine Research, Erasmus MC, University Medical Center Rotterdam, NA 1909, P.O. Box 2040, Rotterdam, 3000 CA, The Netherlands; Academic Collaborative Research Center Healthy Ageing and Intellectual Disabilities, NA 1909, P.O. Box 2040, Rotterdam, 3000 CA, The Netherlands.

Heike Gerger, Department of General Practice, Erasmus MC, University Medical Center Rotterdam, Rotterdam, NA 1909, P.O. Box 2040, Rotterdam, 3000 CA, The Netherlands; Faculty of Psychology, Department of Clinical Psychology, Open University of the Netherlands, P.O. Box 2960, Heerlen, 6401 DL, The Netherlands.

Dederieke A M Maes-Festen, Department of General Practice, Intellectual Disability Medicine Research, Erasmus MC, University Medical Center Rotterdam, NA 1909, P.O. Box 2040, Rotterdam, 3000 CA, The Netherlands; Academic Collaborative Research Center Healthy Ageing and Intellectual Disabilities, NA 1909, P.O. Box 2040, Rotterdam, 3000 CA, The Netherlands.

Alyt Oppewal, Department of General Practice, Intellectual Disability Medicine Research, Erasmus MC, University Medical Center Rotterdam, NA 1909, P.O. Box 2040, Rotterdam, 3000 CA, The Netherlands; Academic Collaborative Research Center Healthy Ageing and Intellectual Disabilities, NA 1909, P.O. Box 2040, Rotterdam, 3000 CA, The Netherlands.

Lead author biography

graphic file with name oeaf093il1.jpg

Kirsten de Oude, MSc is a PhD student at the Academic Collaborative Research Center Healthy Ageing and Intellectual Disabilities at Erasmus Medical Centre in the Netherlands. With a background as a physical therapist, she has over 13 years of experience working with people with intellectual disabilities. She holds a master’s degree in geriatric physical therapy and specializes in cardiovascular disease and training. Her research focuses on improving health outcomes and promoting healthy ageing in individuals with intellectual disabilities, combining clinical expertise with a strong research foundation to advance evidence-based interventions in this underserved population.

Data availability

The data used in this meta-analysis were extracted from publicly available studies. Summary data underlying the main analyses are included in the article and its Supplementary materials. Due to copyright and licensing restrictions, full-text sources and raw extraction files cannot be shared publicly but are available through the original study publishers or upon request when permitted.

Supplementary material

Supplementary material is available at European Heart Journal Open online.

Author contributions

K.I.d.O., R.G.E., H.G., and A.O. contributed to the conception and design of the study. R.G.E. contributed to the development of the search strategy. K.I.d.O., R.G.E., H.G., and A.O. completed the data extraction and risk of bias assessments. K.I.d.O. performed the data analysis. K.I.d.O. is the principal writer of the manuscript. All authors contributed to the drafting and revision of the final article and approved the final submitted version of the manuscript.

Kirsten I. de Oude (Conceptualization [equal], Data curation [lead], Formal analysis [lead], Methodology, [equal], Project administration [lead], Visualization, [lead], Writing—original draft [lead]), Roy G. Elbers (Conceptualization [equal], Data curation [supporting], Methodology [equal], Supervision [equal], Writing—review & editing [equal]), Heike Gerger (Data curation [supporting], Formal analysis [supporting], Writing—review & editing [supporting]), Dederieke A.M. Maes-Festen (Supervision [supporting], Writing—review & editing [supporting]), and Alyt Oppewal (Conceptualization [equal], Data curation [supporting], Methodology [supporting], Supervision [lead], Writing—review & editing [lead])

Funding

This study received financial support from the Academic Collaborative Research Center Healthy Ageing and Intellectual Disabilities, the Netherlands. The healthcare organizations, associated with the research centre, are not involved in the analysis and interpretation of results.

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Associated Data

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Supplementary Materials

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Data Availability Statement

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PERMALINK

The effect of different resistance exercise training intensities on cardiovascular risk factors: a systematic review and meta-analysis

Kirsten I de Oude

Roy G Elbers

Heike Gerger

Dederieke A M Maes-Festen

Alyt Oppewal

Roles

Abstract

Graphical Abstract

Graphical Abstract.

Introduction

Methods

Study selection and eligibility criteria

Participants

Intervention

Outcomes

Search strategy and selection process

Data extraction

Risk of bias

Certainty of evidence

Data analysis

Results

Study selection

Figure 1.

Characteristics of included studies

Risk of bias assessment

Glycated haemoglobin

Figure 2.

Sensitivity analyses

Systolic blood pressure

Figure 3.

Sensitivity analyses

Low-density lipoprotein

Figure 4.

Sensitivity analyses

Waist-to-hip ratio

Figure 5.

Sensitivity analyses

Certainty of evidence

Table 1.

Discussion

Strengths and limitations

Clinical considerations

Future research

Conclusion

Supplementary Material

Acknowledgements

Contributor Information

Lead author biography

Data availability

Supplementary material

Author contributions

Funding

References

Associated Data

Supplementary Materials

Data Availability Statement

ACTIONS

PERMALINK

RESOURCES

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