# Differential effects of exercise training protocols on blood pressures and lipid profiles in older adults patients with hypertension: A systematic review and meta-analysis

Keyvan Hejazi, Zahra Ataran Iraj, Ayoub Saeidi, Anthony C. Hackney, Fatiha Laziri, Katsuhiko Suzuki, Ismail Laher, Hassane Zouhal

► To cite this version:

Keyvan Hejazi, Zahra Ataran Iraj, Ayoub Saeidi, Anthony C. Hackney, Fatiha Laziri, et al. Differential effects of exercise training protocols on blood pressures and lipid profiles in older adults patients with hypertension: A systematic review and meta-analysis. Archives of Gerontology and Geriatrics, 2024, 131, pp.105737. 10.1016/j.archger.2024.105737. hal-04928185

HAL Id: hal-04928185

https://hal.science/hal-04928185v1

Submitted on 4 Feb 2025

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and 95 % confidence intervals. The systematic search identified 1998 articles, of which 92 studies met the inclusion criteria and were deemed eligible for inclusion. The results of the meta-analysis indicated that reduced systolic (SBP) and diastolic blood pressures (DBP) after aerobic training (p < 0.01), resistance training (p < 0.01), combined (aerobic + resistance) exercise training (p < 0.01) and isometric handgrip training (p < 0.01). Significant reductions were also observed in low-density lipoprotein (LDL) and triglyceride (TG) levels following combined (aerobic + resistance) exercise training (p < 0.05 and p < 0.001), and resistance training (p < 0.01), respectively. High-density lipoprotein (HDL) levels were increased following aerobic training (p < 0.01), and combined (aerobic + resistance) exercise training (p < 0.01), but not after resistance and Tai chi training. Isometric handgrip training leads to greater reductions in blood pressure in hypertensive patients compared to the effects of aerobic, resistance, combined aerobic and resistance exercise, and tai chi training. Additional studies are needed to determine the exercise prescription protocols to maximize the health of older adults patients with hypertension.

## Key Points

Significant reductions in systolic blood pressure (SBP) and diastolic blood pressure (DBP) were observed across different exercise types, with isometric handgrip training showing the most substantial effect on blood pressure reduction.

The analysis revealed that aerobic training, resistance training, and combined exercise training effectively lowered LDL and triglyceride levels, while HDL levels increased significantly following aerobic and combined training.

Gender and body mass index (BMI) influenced the effectiveness of exercise interventions, with variations in blood pressure and lipid profile improvements noted among different demographic groups.

The study concluded that while exercise training is beneficial for managing hypertension in the older adults, further research is needed to optimize exercise prescriptions and understand the impact of specific factors such as exercise frequency and intensity.

# 1. Introduction

The global older adults population is projected to reach 1.5 billion by 2050, according to the United Nations. Aging is commonly associated with physiological changes that often lead to age-related conditions, including sarcopenia, disabilities, and chronic diseases such as hypertension (Ramos et al., 2018). Hypertension, commonly known as high blood pressure, is an important global health issue and a leading cause of death and illness worldwide. The World Health Organization estimates that around 40 % of adults are affected by hypertension, contributing to approximately 9.4 million deaths each year. The prevalence of hypertension varies significantly by region; for example, in Korea, it affects 28 % of adults aged 20 and older. Furthermore, the number of individuals diagnosed with hypertension has doubled globally from 1990 to 2019, highlighting the urgent need for effective prevention and management strategies (Kim et al., 2023; Noh et al., 2024). Hypertension and hyperlipidaemia affect approximately 70 % of the older adults patients (Dalal et al., 2012; Go et al., 2013). Hypertension, characterized by persistently high blood pressure, is a major public health concern due to its strong association with several negative health outcomes including stroke and cardiac abnormalities (Go et al., 2013; Soltani et al., 2020). Hypertension and high cholesterol often coexist and are termed hypertensive dyslipidaemia (DH) (Dalal et al., 2012; Kannel, 2000). This association may be related to shared risk factors such as obesity and hormonal imbalances. Moreover, high cholesterol levels can lead to arterial damage, contributing to the development of atherosclerosis and potentially disrupting blood pressure regulation (Otsuka et al., 2016).

Lifestyle changes can be equally effective as single-drug pharmacotherapy in reducing blood pressure (Burke et al., 2007; Dickinson et al., 2006; Marin-Couture et al., 2024).

Regular exercise and healthy lifestyle habits provide numerous

benefits for the elderly, especially those diagnosed with systemic arterial hypertension, as these practices lowering blood pressure. Additionally, engaging in regular physical activity also improves body composition, muscle strength, and other vital aspects that enhance independence and quality of life in the elderly (Oliveira et al., 2020). Regular physical activity has been shown to prevent high blood pressure (Chobanian et al., 2003a; Pescatello et al., 2004) and reduce organ damage associated with hypertension (Ito et al., 2016). Chronic exercise aids in regulating blood pressure in both healthy individuals and those with hypertension (Chiang et al., 2010; Kumbhani et al., 2013). While moderate aerobic exercise is often recommended and can lower blood pressure by up to 8.9 mmHg (Almeida et al., 2021), other forms of exercise, such as walking, resistance training, and their combination, also mitigate hypertension (Almeida et al., 2021; Véronique A Cornelissen et al., 2011; Veronique A Cornelissen & Smart, 2013; Fu et al., 2022; Igarashi & Nogami, 2018; Igarashi et al., 2018; Kelley & Kelley, 2000; Malem et al., 2024; Takahashi et al., 2013; Whelton et al., 2002).

Meta-analysis integrates both quantitative and qualitative analysis, and serves to augment the sample size of the analysis that yields more objective results (Bechthold et al., 2019). Previous studies focussed on the effects of different exercise modalities on blood pressure improvement, but with a lack of consensus on the ideal research framework, exercise duration, frequency, volume, and other variables including the effects of different exercise types in the treatment of individuals with hypertension (Almeida et al., 2021; Henkin et al., 2023; Pescatello et al., 2021; Zhou et al., 2023).

Several meta-analyses have previously examined the efficacy of exercise in reducing blood pressure levels (Berge et al., 2015; da Silva et al., 2021; Conceição et al., 2016; Dai et al., 2021; Pescatello et al., 2021). However, these studies examined variations in terms of participant age range (Conceição et al., 2016; da Silva et al., 2021), physical activity levels (Berge et al., 2015; Pescatello et al., 2021), and intervention types (Dai et al., 2021) when compared to the current meta-analysis. Furthermore, these reviews incorporated a combination of randomized controlled trials (RCTs), conference proceedings, theses, and non-randomized trials (Dong et al., 2021). The lack of high-quality trials investigating the effects of different exercise regimens makes it challenging to determine the most effective approach to reduce blood pressure. The study amalgamates data from RCTs and controlled trials to evaluate the effect of different exercise modalities on the blood pressure and lipid profiles of older adults patients with hypertension.

# 2. Methods

## 2.1. Search strategy

This systematic review and meta-analysis was conducted according to the recommendations outlined in the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) statement (Page et al., 2021). The review protocol was registered in the PROSPERO database (registration number CRD42024569150).

Five databases (Web of Science, Cochrane, PubMed, Google Scholar,
and Scopus) were searched from the earliest record to September 09, 2024, with an updated search performed to March 03, 2024. The search strategy combined the terms: "Hypertension" OR "Hypertensive" OR "High blood pressure" OR "Mean arterial" OR "Blood pressure" OR "Arterial pressure" OR "Systolic pressure" OR "Diastolic pressure" OR "Pulse pressure" OR "Venous pressure" OR "Pressure monitor" OR "Prehypertension" OR "BP" OR "Heart rate" OR "HR" OR "High-density lipoprotein" OR "Low-density lipoprotein" OR "Triglyceride" OR "Total cholesterol" OR "Randomized controlled trial" OR "Clinical trial" OR "Randomized Clinical" OR "Random allocation" OR "Randomization" OR "RCT" OR "Elderly" OR "Old" OR "Aging" OR "Aged" OR "Strength training" OR "Physical activity" OR "Combined training" OR "Exercise training" OR "Walking" OR "Aerobic training" OR "Resistance training" OR "Circuit training" OR "Interval training" OR "Lifestyle activity" OR "Home training" OR "Water exercise" OR "Tai chi" OR "Whole-body vibration training" OR "Swim" OR "Isometric handgrip training" OR "Blood flow-restricted resistance training" OR "Thai mind-body exercise" OR "Walk" OR "Run" OR "Power training" OR "Exergame" OR "Bicycle exercise". All relevant studies and other available systematic reviews (including meta-analyses) and the reference lists of the identified articles were manually searched for additional eligible studies. The Boolean search terms (AND, OR, or NOT) were used to merge search terms exercise training participation with the outcomes blood pressure, hypertension, systolic pressure, and diastolic pressure.

Searches were limited to studies involving human participants and published in the English language. Titles and abstracts of retrieved articles were individually evaluated by two reviewers (K.H., Z.A.) to assess their eligibility for review and meta-analysis. When abstracts did not provide sufficient information to examine study eligibility, the full-text was retrieved for evaluation.

## 2.2. Eligibility criteria

Articles were eligible for inclusion if they met the following criteria: randomized controlled trials; peer-reviewed articles published in English; an exercise intervention of ≥ 4 weeks duration, adults (mean ≥ 60 years) with prehypertension or high-normal blood pressure (SBP between 130 and 139 mmHg and/or DBP between 85 and 89 mmHg) or hypertension (SBP = 140 mmHg and/or DBP = 90 mmHg) and/or use of antihypertensive drug[s]) (Daskalopoulou et al., 2015; Mancia et al., 2014). The mean values of baseline BP were adopted for the inclusion criteria following the same procedures of previous systematic reviews on the effects of exercise training on resting (Veronique A Cornelissen & Smart, 2013) and ambulatory (Veronique A Cornelissen et al., 2013; Sosner et al., 2017) blood pressures. Studies including individuals with additional risk factors (e.g., high cholesterol, overweight, obesity, pre-diabetes, etc.) or known cardiometabolic diseases (e.g., type 2 diabetes, coronary heart disease, heart failure, etc.) were eligible for inclusion.

These markers specifically included the following: blood pressure (e. g., systolic pressure, diastolic pressure), HDL, LDL, TG and TC. Studies also required participants to be physically inactive (< 150 min per week of moderate-intensity aerobic exercise or < 75 min per week of vigorous aerobic exercise) and no participation in an exercise program within the previous 6 months. Articles were deemed ineligible if only abstracts were available, did not involve humans (i.e., animal studies), participants aged < 60 years), or baseline blood pressure values were not reported. Studies in which the eligibility criteria are not clear regarding the inclusion of prehypertensive and/or hypertensive individuals were also excluded.

## 2.3. Data extraction

The information extracted comprised publication details such as participant characteristics, descriptions of interventions, mean and standard deviation (SD) of blood pressures (systolic pressure, diastolic pressure), and lipid profiles (HDL, LDL, TG, and TC) values at baseline,

post-intervention and/or changes between baseline and post-intervention. If standard errors were reported, these values were converted to SD (Higgins et al., 2003). Any data presented in graphs were extracted using web-based software (GetData Graph Digitizer) (Wojtyniak et al., 2020). If data were unavailable or could not be extracted from figures, the study corresponding author was emailed to provide the data.

## 2.4. Study quality

The methodological quality of the studies were examined independently based on a fifteen-point scale using Tool for the Assessment of Study Quality and Reporting in Exercise (TESTEX), which is a validated tool for evaluating the quality (5 points maximum) and reporting (10 points maximum) of exercise training studies (Smart et al., 2015).

## 2.5. Statistical analyses

All meta-analyses were performed with Review Manager 5.3 (The Nordic Cochrane Centre, Copenhagen, Denmark). Effect size (ES) values were expressed as weighted mean difference (WMD) and 95 % confidence interval (CI). The mean difference (MD) between the intervention and control conditions was calculated for all included randomized controlled trials (RCTs) to summarize the effect size of the outcomes. Random-effects models were employed to calculate the MD and corresponding 95 % CI, as the reporting techniques for outcomes were similar. To obtain the necessary outcomes data, the change in mean and standard deviation (SD) values were used. Specifically, the pre-intervention mean was subtracted from the post-intervention mean, and the change SD was computed using the subject numbers from the study group, along with group p-values or 95 % CI in cases where the change in mean and SD was not reported (Higgins et al., 2003).

When a study involved a control group and more than one exercise group, ESs were calculated for each exercise group, and the sample size of the control group was divided by the number of exercise groups. Between-study variability was examined for heterogeneity using I² statistics for quantifying inconsistency. Heterogeneity thresholds included I² = 25 % (low), I² = 50 % (moderate), and I² = 75 % (high) (Higgins et al., 2003). A conservative random-effects model of meta-analysis was applied to the pooled data. Significance was set as *p* < 0.01. Subgroup analyses were employed to recognize potential causes of heterogeneity among the studies. Exercise training modalities (i.e., aerobic, resistance combined (aerobic + resistance) tai chi training, and isometric handgrip training,); exercise duration (i.e., ≤ 8 weeks, between 8 and 12 weeks and >12 weeks); and body mass index (BMI) (normal: < 25 kg/m², overweight: 25.0–29.9 kg/m² versus obese: ≥ 30 kg/m²), weight, and gender (male, female and both (male and female)) were considered as the predefined sources of heterogeneity. Publication bias was examined visually via funnel plots and statistically using Egger's test (*p* < 0.05) (Egger et al., 1997).

# 3. Results

## 3.1. Study selection

The initial search identified 1998 records, of which 521 studies were included for full-text review after removing duplicates and following title/abstract screening of those 521 studies, 92 studies met the eligibility criteria. A flow diagram of the study search and selection, including reasons for exclusion, is shown in Fig. 1.

## 3.2. Study and participant characteristics

One thousand nine hundred and ninety-eight (1998) records were identified in the initial search. After removing duplicates and animal research (n = 52), the remaining studies were screened based on the title
<figure><img src="image_2.png" /><figcaption>Fig. 1. The Preferred Reporting Items for Systematic Reviews and Meta Analyses (PRISMA) flow chart of the systematic literature research.</figcaption></figure>

and the abstract, and 521 articles were then omitted, leaving 92 full-text articles that met our inclusion criteria and which were then entered in the meta-analysis (PRISMA flow diagram; Fig. 1).

Studies were carried out in Brazil (n = 19) (Agner et al., 2018; Arca et al., 2014; Bertani et al., 2018; Cezar et al., 2016; Coelho-Júnior & Uchida, 2021; da Cunha et al., 2018; Dantas et al., 2016; Gerage et al., 2013; Goncalves et al., 2014; Gurjão et al., 2013; Kanegusuku et al., 2011; Monteiro et al., 2010; Montrezol et al., 2014; Mota et al., 2013; Ramos et al., 2018; do Rego et al., 2011; Terra et al., 2008; Tomeleri et al., 2018; Wanderley et al., 2013), USA (n = 23) (Agurs-Collins et al., 1997; Balducci et al., 2010; Campo et al., 2015; Castaneda et al., 2002; Cononie et al., 1991; Craighead et al., 2021; Dengel et al., 1998; Douglas & Reiling, 1991; Hagberg et al., 1989; 1989; Haykowsky et al., 2012; Heffernan et al., 2013; Izquierdo-Porrera et al., 2000; Jaime et al., 2019; Lee et al., 2019; Nualnim et al., 2012; Roberson et al., 2018; Simons & Andel, 2006; Stewart et al., 2006; Turner et al., 2000; Vincent et al., 2003; Wolf et al., 2006; Wong et al., 2020), South Korea (n = 13) (Ahn & Kim, 2022; Choi et al., 2020; Jo et al., 2020; Lee, 2017; Park et al., 2017; 2015; 2017; 2020; 2011; Shin et al., 2015; Son et al., 2020; 2017; Woo-Cheol et al., 2016), Saudi Arabia (n = 1) (Alzahrani et al., 2023), Canada (n = 5) (Badrov et al., 2013; McGowan et al., 2008; Millar et al., 2013; Stiller-Moldovan et al., 2012; Taylor et al., 2003), Italy (n = 1)

(Beltran Valls et al., 2014), Australia (n = 2) (Cao et al., 2019; Sun & Buys, 2015), Israel (n = 1) (Carmeli et al., 2003), New Zealand (n = 1) (M. A. R. Da Silva et al., 2020), Spain (n = 1) (Serrano-Guzman et al., 2016), Egypt (n = 1) (Abd Elwahaab et al., 2019), Iran (n = 3) (Hooshmand-Moghadam et al., 2021; Izadi et al., 2018; Ramezani et al., 2021), China (n = 1) (Hou et al., 2023), Taiwan (1) (Hsieh et al., 2018), Indiana (n = 1) (Huang et al., 2006), Germany (2) (Nguyen & Kruse, 2012; Van Hoof et al., 1996), Greece (1) (Kadoglou et al., 2012), Japan (n = 6) (Kawasaki et al., 2011; Miura et al., 2015; Ohkubo et al., 2001; Okamoto et al., 2020; Shiotsu et al., 2018; Yasuda et al., 2014), Portugal (n = 1) (Leitão et al., 2021), Thailand (n = 3) (Ngowsiri et al., 2018; Ruangthai & Phoemsapthawee, 2019; Sarinukul et al., 2023), Austria (n = 1) (Niederseer et al., 2011), Switzerland (n = 1 of 92 studies) (Stutz et al., 2022), Hong Kong (n = 1) (Thomas et al., 2005), Ireland (n = 1) (Timmons et al., 2018), and UK (n = 1) (Ubolsakka-Jones et al., 2017).

The mean age of the participants in the 92 studies was 66.48 years; the 92 included articles had 4988 subjects, with 2842 in the intervention groups and 2146 in the control groups. Of the 92 studies 36 studies recruited female subjects exclusively (Agurs-Collins et al., 1997; Ahn & Kim, 2022; Arca et al., 2014; Campo et al., 2015; Cao et al., 2019; Cezar et al., 2016; da Cunha et al., 2018; Dantas et al., 2016; Gerage et al., 2013; Goncalves et al., 2014; Gurjão et al., 2013; Hagberg et al., 1989;
Haykowsky et al., 2012; Hou et al., 2023; Jaime et al., 2019; Jo et al., 2020; Leitão et al., 2021; Miura et al., 2015; Monteiro et al., 2010; Montrezol et al., 2014; Mota et al., 2013; Park et al., 2017; 2015; 2017; 2011; do Rego et al., 2011; Ramezani et al., 2021; Sarinukul et al., 2023; Serrano-Guzman et al., 2016; Shin et al., 2015; Son et al., 2020; 2017; Terra et al., 2008; Tomeleri et al., 2018; Wong et al., 2020; Woo-Cheol et al., 2016), **7 studies recruited only male subjects** (Abd Elwahaab et al., 2019; Dengel et al., 1998; Hooshmand-Moghadam et al., 2021; Izquierdo-Porrera et al., 2000; Park et al., 2020; Shiotsu et al., 2018; Van Hoof et al., 1996), **while 48 studies recruited both females and males** (Agner et al., 2018; Alzahrani et al., 2023; Badrov et al., 2013; Balducci et al., 2010; Beltran Valls et al., 2014; Bertani et al., 2018; Carmeli et al., 2003; Castaneda et al., 2002; Choi et al., 2020; Coelho-Júnior & Uchida, 2021; Cononie et al., 1991; Craighead et al., 2021; Da Silva et al., 2020; Douglas & Reiling, 1991; Hagberg et al., 1989; Heffernan et al., 2013; Hsieh et al., 2018; Izadi et al., 2018; Kadoglou et al., 2012; Kanegusuku et al., 2011; Kawasaki et al., 2011; Lee et al., 2019; Lee, 2017; McGowan et al., 2008; Millar et al., 2013; Ngowsiri et al., 2018; Nguyen & Kruse, 2012; Niederseer et al., 2011; Nualnim et al., 2012; Ohkubo et al., 2001; Okamoto et al., 2020; Ramos et al., 2018; Roberson et al., 2018; Ruangthai & Phoemsapthawee, 2019; Simons & Andel, 2006; Stewart et al., 2006; Stiller-Moldovan et al., 2012; Stutz et al., 2022; Sun & Buys, 2015; Taylor et al., 2003; Thomas et al., 2005; Timmons et al., 2018; Turner et al., 2000; Ubolsakka-Jones et al., 2017; Vincent et al., 2003; Wanderley et al., 2013; Wolf et al., 2006; Yasuda et al., 2014) and one study did not report the sex of the participants (Huang et al., 2006).

Based on BMI classification criteria, 19 investigations had subjects who were classified as being of normal weight (Beltran Valls et al., 2014; Gerage et al., 2013; Huang et al., 2006; Jaime et al., 2019; Kawasaki et al., 2011; Lee et al., 2019; Ngowsiri et al., 2018; Nguyen & Kruse, 2012; Ohkubo et al., 2001; Okamoto et al., 2020; Ruangthai & Phoemsapthawee, 2019; Sarinukul et al., 2023; Shin et al., 2015; Shiotsu et al., 2018; Son et al., 2017; Sun & Buys, 2015; Thomas et al., 2005; Wong et al., 2020; Yasuda et al., 2014), **43 studies involved overweight subjects (BMI of ≥25-29.9 kg/m²)** (Abd Elwahaab et al., 2019; Alzahrani et al., 2023; Arca et al., 2014; Badrov et al., 2013; Cao et al., 2019; Choi et al., 2020; Coelho-Júnior & Uchida, 2021; Craighead et al., 2021; da Cunha et al., 2018; Da Silva et al., 2020; Dantas et al., 2016; Goncalves et al., 2014; Gurjão et al., 2013; Heffernan et al., 2013; Hooshmand-Moghadam et al., 2021; Hou et al., 2023; Hsieh et al., 2018; Izadi et al., 2018; Izquierdo-Porrera et al., 2000; Jo et al., 2020; Kanegusuku et al., 2011; Millar et al., 2013; Monteiro et al., 2010; Montrezol et al., 2014; Mota et al., 2013; Niederseer et al., 2011; Park et al., 2017; 2015; 2017; 2020; do Rego et al., 2011; Ramezani et al., 2021; Serrano-Guzman et al., 2016; Son et al., 2020; Stewart et al., 2006; Stutz et al., 2022; Terra et al., 2008; Timmons et al., 2018; Tomeleri et al., 2018; Turner et al., 2000; Ubolsakka-Jones et al., 2017; Wanderley et al., 2013; Wolf et al., 2006), **12 studies involved obese subjects (BMI of ≥30 kg/m²)** (Agner et al., 2018; Agurs-Collins et al., 1997; Balducci et al., 2010; Castaneda et al., 2002; Cezar et al., 2016; Haykowsky et al., 2012; Kadoglou et al., 2012; Leitão et al., 2021; Nualnim et al., 2012; Ramos et al., 2018; Roberson et al., 2018; Stiller-Moldovan et al., 2012) and **18 studies did not report BMI** (Ahn & Kim, 2022; Bertani et al., 2018; Campo et al., 2015; Carmeli et al., 2003; Cononie et al., 1991; Dengel et al., 1998; Douglas & Reiling, 1991; Hagberg et al., 1989; 1989; Lee, 2017; McGowan et al., 2008; Miura et al., 2015; Park et al., 2011; Timmons & Andel, 2006; Taylor et al., 2003; Van Hoof et al., 1996; Vincent et al., 2003; Woo-Cheol et al., 2016).

Based on health condition classification criteria, **1 as metabolic syndrome** (Agner et al., 2018), **7 as type 2 diabetes** (Agurs-Collins et al., 1997; Alzahrani et al., 2023; Balducci et al., 2010; Castaneda et al., 2002; Hsieh et al., 2018; Kadoglou et al., 2012; Monteiro et al., 2010), **48 as hypertensive** (Abd Elwahaab et al., 2019; Arca et al., 2014; Badrov et al., 2013; Bertani et al., 2018; Cao et al., 2019; Cezar et al., 2016; Coelho-Júnior & Uchida, 2021; Cononie et al., 1991; da Cunha et al., 2018; Da Silva et al., 2020; Dantas et al., 2016; Douglas & Reiling, 1991;

Goncalves et al., 2014; Hagberg et al., 1989; Heffernan et al., 2013; Hooshmand-Moghadam et al., 2021; Hou et al., 2023; Izadi et al., 2018; Leitão et al., 2021; McGowan et al., 2008; Millar et al., 2013; Miura et al., 2015; Montrezol et al., 2014; Mota et al., 2013; Ngowsiri et al., 2018; Nualnim et al., 2012; do Rego et al., 2011; Park et al., 2011; Ramos et al., 2018; Roberson et al., 2018; Ruangthai & Phoemsapthawee, 2019; Sarinukul et al., 2023; Serrano-Guzman et al., 2016; Son et al., 2020; 2017; Stewart et al., 2006; Stiller-Moldovan et al., 2012; Sun & Buys, 2015; Taylor et al., 2003; Terra et al., 2008; Thomas et al., 2005; Tomeleri et al., 2018; Turner et al., 2000; Ubolsakka-Jones et al., 2017; Wanderley et al., 2013; Wolf et al., 2006; Wong et al., 2020; Woo-Cheol et al., 2016), **2 as menopause** (Jaime et al., 2019; Wong et al., 2020), **1 as cancer** (Campo et al., 2015), **2 as cardiovascular disease (CVD)** (Izquierdo-Porrera et al., 2000; Jo et al., 2020), **1 as heart failure** (Haykowsky et al., 2012), **1 as sarcopenic** (Park et al., 2017), **1 as rheumatoid arthritis** (Shin et al., 2015), **29 studies did not report the health condition of participants** (Ahn & Kim, 2022; Beltran Valls et al., 2014; Carmeli et al., 2003; Choi et al., 2020; Craighead et al., 2021; Dengel et al., 1998; Gerage et al., 2013; Gurjão et al., 2013; Hagberg, Graves et al., 1989; Huang et al., 2006; Kanegusuku et al., 2011; Kwasaki et al., 2011; Lee et al., 2019; Lee, 2017; Nguyen & Kruse, 2012; Niederseer et al., 2011; Ohkubo et al., 2001; Okamoto et al., 2020; Park et al., 2015; 2017; 2020; Ramezani et al., 2021; Shiotsu et al., 2018; Simons & Andel, 2006; Stutz et al., 2022; Timmons et al., 2018; Van Hoof et al., 1996; Vincent et al., 2003; Yasuda et al., 2014).

The mean duration of the disease of participants in the 9 studies was 9.30 years and 83 studies did not report the duration of the disease. Only three of the 92 studies included in the study reported on the dietary status of patients with hypertension. The mean SBP of participants in the 92 studies was 139.16 mmHg and the mean DBP was 81.43 mmHg (Table S1).

### 3.3. Interventions

The relevant characteristics for each of the included studies are provided in Supplementary Table S2. The intervention periods in the studies varied from 4 to 48 weeks, with the duration of each exercise session in the range of 15–210 min and the frequency of the sessions from 1 to 7 days per week.

Based on exercise condition classification criteria, aerobic exercise was used in **31 studies** (Abd Elwahaab et al., 2019; Agurs-Collins et al., 1997; Alzahrani et al., 2023; Arca et al., 2014; Cao et al., 2019; Carmeli et al., 2003; Dengel et al., 1998; Douglas & Reiling, 1991; Hagberg et al., 1989; Haykowsky et al., 2012; Hou et al., 2023; Huang et al., 2006; Izadi et al., 2018; Izquierdo-Porrera et al., 2000; Jo et al., 2020; Kawasaki et al., 2011; Monteiro et al., 2010; Ngowsiri et al., 2018; Niederseer et al., 2011; Nualnim et al., 2012; do Rego et al., 2011; Park et al., 2017; Ramezani et al., 2021; Ramos et al., 2018; Sarinukul et al., 2023; Serrano-Guzman et al., 2016; Stutz et al., 2022; Turner et al., 2000; Ubolsakka-Jones et al., 2017; Wong et al., 2020; Woo-Cheol et al., 2016), **combined (aerobic + resistance training) protocols in 9 studies** (Agner et al., 2018; Balducci et al., 2010; Leitão et al., 2021; Ohkubo et al., 2001; Park et al., 2017; 2015; 2020; 2011; Son et al., 2017; Stewart et al., 2006), **resistance training in 31 studies** (Ahn & Kim, 2022; Badrov et al., 2013; Beltran Valls et al., 2014; Castaneda et al., 2002; Cezar et al., 2016; Choi et al., 2020; Coelho-Júnior & Uchida, 2021; Craighead et al., 2021; da Cunha et al., 2018; Da Silva et al., 2020; Dantas et al., 2016; Gerage et al., 2013; Goncalves et al., 2014; Gurjão et al., 2013; Heffernan et al., 2013; Hooshmand-Moghadam et al., 2021; Hsieh et al., 2018; Jaime et al., 2019; Kadoglou et al., 2012; Kanegusuku et al., 2011; Lee et al., 2019; Miura et al., 2015; Montrezol et al., 2014; Mota et al., 2013; Son et al., 2020; Terra et al., 2008; Tomeleri et al., 2018; Van Hoof et al., 1996; Vincent et al., 2003; Yasuda et al., 2014), **Tai Chi training in 6 studies** (Campo et al., 2015; Lee, 2017; Nguyen & Kruse, 2012; Shin et al., 2015; Sun & Buys, 2015; Wolf et al., 2006), **5 studies employed isometric handgrip training** (McGowan et al., 2008; Millar et al., 2013;
Okamoto et al., 2020; Stiller-Moldovan et al., 2012; Taylor et al., 2003), 7 studies reported aerobic training and resistance training (Bertani et al., 2018; Cononie et al., 1991; Hagberg, Graves et al., 1989; Roberson et al., 2018; Shiotsu et al., 2018; Simons & Andel, 2006; Wanderley et al., 2013), 2 studies reported aerobic training, resistance training and combined (aerobic + resistance training) (Ruangthai & Phoemsapthawee, 2019; Timmons et al., 2018) and 1 study reported Tai Chi training and resistance training (Thomas et al., 2005). A summary of the primary outcome analyses (including subgroup analyses) are summarized in Table S3.

### 3.4. Effect of exercise on blood pressure

#### 3.4.1. Systolic blood pressure

Physical exercise caused an overall decrease in SBP (WMD: -5.84 mmHg [95 % CI, -7.21 to -4.47], $p = 0.001$; $I^2=84\%$, $p = 0.001$).

A subgroup analysis by type of exercise revealed that aerobic training decreased SBP levels (WMD: -6.84 mmHg [95 % CI, -9.12 to -4.57], $p = 0.001$; $I^2=83\%$, $p = 0.001$), as did resistance training (WMD: -5.09 mmHg [95 % CI, -7.01 to -3.17], $p = 0.001$; $I^2=61\%$, $p = 0.001$), Tai chi training (WMD: -7.62 mmHg [95 % CI, -11.01 to -4.23], $p = 0.001$; $I^2=56\%$, $p = 0.001$) and isometric handgrip training (WMD: -10.62 mmHg [95 % CI, -12.45 to -8.79], $p = 0.001$; $I^2=3\%$, $p = 0.39$). On the other hand, combined (aerobic + resistance) exercise training alone had effects on SBP levels (WMD: -1.98 mmHg [95 % CI, -5.00 to 1.04], $p = 0.20$; $I^2=65\%$, $p = 0.001$) (Supplementary Fig. S1).

A subgroup analysis by gender of study participants revealed a decrease in SBP for male participants (WMD: -6.30 mmHg [95 % CI, -9.66 to -2.94], $p = 0.001$; $I^2=66\%$, $p = 0.001$), female participants (WMD: -8.56 mmHg [95 % CI, -10.33 to -6.78], $p = 0.001$; $I^2=76\%$, $p = 0.001$) and both (male and female) (WMD: -3.92 mmHg [95 % CI, -5.94 to -1.89], $p = 0.001$; $I^2=80\%$, $p = 0.001$) (Table S3).

In addition, subgroup analysis based on BMI indicated a significant decrease in SBP for participants with a BMI<25 kg/m² (WMD: -7.84 mmHg [95 % CI, -10.13 to -5.55], $p = 0.001$; $I^2=66\%$, $p = 0.001$), BMI between 25 and 29.9 kg/m² (WMD: -4.44 mmHg [95 % CI, -6.68 to -2.20], $p = 0.001$; $I^2=84\%$, $p = 0.001$), and BMI≥30 kg/m² (WMD: -6.59 mmHg [95 % CI, -11.11 to -2.70], $p = 0.001$; $I^2=79\%$, $p = 0.001$) (Table S3).

A subgroup analysis based on intervention duration indicated decreases in SBP for ≤ 8 weeks (WMD: -8.70 mmHg [95 % CI, -11.82 to -5.59], $p = 0.001$; $I^2=64\%$, $p = 0.001$), between 8 and 12 weeks (WMD: -5.74 mmHg [95 % CI, -7.60 to -3.87], $p = 0.001$; $I^2=86\%$, $p = 0.001$), and for > 12 weeks interventions (WMD: -4.81 mmHg [95 % CI, -6.66 to -2.96], $p = 0.001$; $I^2=61\%$, $p = 0.001$) (Table S3).

#### 3.4.2. Diastolic blood pressure

Physical exercise caused an overall decrease in DBP (WMD: -2.71 mmHg [95 % CI, -3.70 to -1.73], $p = 0.001$; $I^2=86\%$, $p = 0.001$).

A subgroup analysis by type of exercise indicated that aerobic training decreased DBP (WMD: -2.57 mmHg [95 % CI, -4.27 to -0.86], $p = 0.001$; $I^2=90\%$, $p = 0.001$), while resistance training (WMD: -2.84 mmHg [95 % CI, -3.89 to -1.80], $p = 0.001$; $I^2=40\%$, $p = 0.001$), combined (aerobic + resistance) exercise training (WMD: -2.67 mmHg [95 % CI, -3.69 to -1.64], $p = 0.001$; $I^2=4\%$, $p = 0.41$) and isometric handgrip training (WMD: -3.94 mmHg [95 % CI, -5.67 to -2.21], $p = 0.001$; $I^2=0\%$, $p = 0.88$) also decreasing DBP. However, Tai chi training did not lower DBP (WMD: -1.49 mmHg [95 % CI, -3.75 to 0.76], $p = 0.19$; $I^2=63\%$, $p = 0.001$) (Supplementary Fig. S2).

A subgroup analysis by gender of participants indicated that there were significant effects of exercise on DBP levels for male participants (WMD: -2.93 mmHg [95 % CI, -5.83 to -0.03], $p = 0.05$; $I^2=74\%$, $p = 0.001$), while there were decreases in female participants (WMD: -3.22 mmHg [95 % CI, -4.56 to -1.89], $p = 0.001$; $I^2=85\%$, $p = 0.001$) and for both (male and female) as a group (WMD: -2.31 mmHg [95 % CI, -3.66 to -0.97], $p = 0.001$; $I^2=76\%$, $p = 0.001$) (Table S3).

A subgroup analysis based of BMI indicated there were decreases in DBP for BMI<25 kg/m² (WMD: -3.21 mmHg [95 % CI, -5.61 to -0.82], $p = 0.001$; $I^2=86\%$, $p = 0.001$), BMI between 25 and 29.9 kg/m² (WMD: -2.07 mmHg [95 % CI, -3.57 to -0.58], $p = 0.001$; $I^2=83\%$, $p = 0.001$), and BMI≥30 kg/m² (WMD: -4.19 mmHg [95 % CI, -6.36 to -2.02], $p = 0.001$; $I^2=63\%$, $p = 0.001$) (Table S3).

A subgroup analysis based on intervention duration indicated decreases in DBP for ≤ 8 weeks (WMD: -3.28 mmHg [95 % CI, -4.50 to -2.06], $p = 0.001$; $I^2=5\%$, $p = 0.39$), between 8 and 12 weeks (WMD: -2.67 mmHg [95 % CI, -4.11 to -1.22], $p = 0.001$; $I^2=90\%$, $p = 0.001$), and, for > 12 weeks of intervention (WMD: -2.26 mmHg [95 % CI, -3.01 to -1.51], $p = 0.001$; $I^2=10\%$, $p = 0.30$) (Table S3).

#### 3.4.3. Low-density lipoproteins

Physical exercise resulted in decreased LDL levels (WMD: -3.78 mg/dl mmHg [95 % CI, -5.15 to -2.41], $p = 0.001$; $I^2=88\%$, $p = 0.001$).

A subgroup analysis by type of exercise revealed that there were no effects for aerobic training (WMD: -5.49 mg/dl [95 % CI, -13.14 to 2.15], $p = 0.16$; $I^2=70\%$, $p = 0.001$), resistance training (WMD: -0.03 mg/dl [95 % CI, -6.26 to 6.20], $p = 0.99$; $I^2=64\%$, $p = 0.001$) or Tai chi training (WMD: -18.53 mg/dl [95 % CI, -55.76 to 18.69], $p = 0.33$; $I^2=99\%$, $p = 0.001$) on LDL levels. On the other hand, combined (aerobic + resistance) exercise training lowered LDL levels (WMD: -5.14 mg/dl [95 % CI, -10.16 to -0.11], $p = 0.05$; $I^2=54\%$, $p = 0.04$) (Supplementary Fig. S3).

A subgroup analysis by gender of participants revealed a significant effects on LDL levels for male (WMD: -11.52 mg/dl [95 % CI, -18.79 to -4.24], $p = 0.002$; $I^2=0\%$, $p = 0.41$), and both (male and female) participants (WMD: -2.25 mg/dl [95 % CI, -3.69 to -0.80], $p = 0.002$; $I^2=90\%$, $p = 0.001$) on LDL levels, while there were no significant effects on LDL levels for female (WMD: -3.04 mg/dl [95 % CI, -9.18 to 3.10], $p = 0.33$; $I^2=65\%$, $p = 0.001$) (Table S3).

In addition, a further subgroup analysis based on BMI indicated there were no effects on LDL levels for BMI between 25 and 29.9 kg/m² (WMD: -0.64 mg/dl [95 % CI, -5.97 to 4.68], $p = 0.81$; $I^2=67\%$, $p = 0.001$), while there were reductions in LDL levels for BMI<25 kg/m² (WMD: -1.73 mg/dl [95 % CI, -3.17 to -0.28], $p = 0.02$; $I^2=96\%$, $p = 0.001$), BMI≥30 kg/m² (WMD: -9.01 mg/dl [95 % CI, -13.12 to -4.90], $p = 0.001$; $I^2=0\%$, $p = 0.99$) (Table S3).

The subgroup analysis of intervention duration showed no decreases in LDL levels for interventions lasting ≤ 8 weeks (WMD: -12.64 mg/dl [95 % CI, -47.82 to 22.54], $p = 0.48$; $I^2=89\%$, $p = 0.001$). Similarly, there were no significant changes in LDL levels for interventions lasting between 8 and 12 weeks (WMD: -0.12 mg/dl [95 % CI, -5.85 to 5.61], $p = 0.97$; $I^2=72\%$, $p = 0.001$). However, interventions lasting more than 12 weeks did result in significant reductions in LDL levels (WMD: -2.76 mg/dl [95 % CI, -4.17 to -1.35], $p = 0.001$; $I^2=94\%$, $p = 0.001$) (Table S3).

#### 3.4.4. High-density lipoproteins

Physical exercise significantly increased HDL (WMD: 1.42 mg/dl [95 % CI, 0.66 to 2.19], $p = 0.001$; $I^2=85\%$, $p = 0.001$).

A subgroup analysis by type of exercise revealed significant effects for both aerobic training (WMD: 3.24 mg/dl [95 % CI, 0.32 to 6.15], $p = 0.001$; $I^2=64\%$, $p = 0.001$) and combined (aerobic + resistance) exercise training (WMD: 1.91 mg/dl [95 % CI, 0.48 to 3.34], $p = 0.001$; $I^2=31\%$, $p = 0.18$). On the other hand, there were no effects on HDL levels due to either resistance training (WMD: 0.33 mg/dl [95 % CI, -1.10 to 1.76], $p = 0.65$; $I^2=61\%$, $p = 0.001$) or Tai chi training (WMD: -0.09 mg/dl [95 % CI, -2.58 to 2.41], $p = 0.95$; $I^2=73\%$, $p = 0.001$) (Supplementary Fig. S4).

A subgroup analysis by gender of participants indicated no effects on HDL levels for combined male and female groups (WMD: -0.17 mg/dl [95 % CI, -0.67 to 0.33], $p = 0.51$; $I^2=53\%$, $p = 0.001$) while there were increases in HDL for male participants (WMD: 2.81 mg/dl [95 % CI, 0.16 to 5.45], $p = 0.04$; $I^2=0\%$, $p = 0.59$), and female (WMD: 3.80 mg/dl
[95 % CI, 0.75 to 6.86], $p = 0.001$; $I^2 = 89 \%$, $p = 0.001$ (Table S3).

A subgroup analysis based on BMI indicated no effects in HDL levels for BMI<25 kg/m² (WMD: -0.01 mg/dl [95 % CI, -0.16 to 0.14], $p = 0.93$; $I^2 = 8 \%$, $p = 0.37$) and BMI between 25 and 29.9 kg/m² (WMD: 1.43 mg/dl [95 % CI, -0.01 to 2.87], $p = 0.05$; $I^2 = 59 \%$, $p = 0.001$), while there were increases in HDL levels in the groups with BMI≥30 kg/m² (WMD: 2.67 mg/dl [95 % CI, 1.19 to 4.16], $p = 0.001$; $I^2 = 0 \%$, $p = 0.77$) (Table S3).

Furthermore, subgroup analysis based on intervention durations indicated no changes in HDL levels for ≤ 8 weeks (WMD: 3.17 mg/dl [95 % CI, -1.52 to 7.87], $p = 0.19$; $I^2 = 0 \%$, $p = 0.46$), between 8 and 12 weeks (WMD: 2.33 mg/dl [95 % CI, -0.04 to 4.70], $p = 0.05$; $I^2 = 89 \%$, $p = 0.001$), and for > 12 weeks interventions (WMD: 0.14 mg/dl [95 % CI, -0.25 to 0.53], $p = 0.47$; $I^2 = 47 \%$, $p = 0.03$) (Table S3).

### 3.4.5. Triglycerides

Physical exercise decreased TG levels (WMD: -4.57 mg/dl [95 % CI, -6.61 to -2.52], $p = 0.001$; $I^2 = 91 \%$, $p = 0.001$).

A subgroup analysis by type of exercise revealed reductions in TG levels due to aerobic training (WMD: -9.84 mg/dl [95 % CI, -12.01 to -7.67], $p = 0.001$; $I^2 = 0 \%$, $p = 0.73$) and resistance training (WMD: -7.56 mg/dl [95 % CI, -11.69 to -3.43], $p = 0.001$; $I^2 = 80 \%$, $p = 0.001$), but not for either combined (aerobic + resistance) exercise training (WMD: -1.82 mg/dl [95 % CI, -5.74 to 2.11], $p = 0.36$; $I^2 = 46 \%$, $p = 0.09$) or Tai chi training (WMD: -0.01 mg/dl [95 % CI, -0.35 to 0.33], $p = 0.94$; $I^2 = 0 \%$, $p = 0.50$) (Supplementary Fig. S5).

A subgroup analysis by gender of participants indicated no effects on TG levels for female participants (WMD: -1.78 mg/dl [95 % CI, -8.32 to 4.76], $p = 0.59$; $I^2 = 85 \%$, $p = 0.001$), although there were reductions in TG levels in the male (WMD: -8.83 mg/dl [95 % CI, -16.54 to -1.11], $p = 0.02$; $I^2 = 0 \%$, $p = 0.47$) or combined (male and female) group (WMD: -4.91 mg/dl [95 % CI, -7.39 to -2.43], $p = 0.001$; $I^2 = 92 \%$, $p = 0.001$) (Table S3).

A subgroup analysis based on BMI indicated no significant effects in TG levels for BMI<25 kg/m² (WMD: -1.96 mg/dl [95 % CI, -5.03 to 1.11], $p = 0.21$; $I^2 = 97 \%$, $p = 0.001$), BMI between 25 and 29.9 kg/m² (WMD: -5.45 mg/dl [95 % CI, -12.06 to 1.15], $p = 0.11$; $I^2 = 78 \%$, $p = 0.001$), although there were reductions in TG levels in the BMI≥30 kg/m² (WMD: -5.78 mg/dl [95 % CI, -7.14 to -4.43], $p = 0.001$; $I^2 = 0 \%$, $p = 0.90$) (Table S3).

In addition, a subgroup analysis based on intervention durations indicated no changes in TG levels for ≤ 8 weeks (WMD: -5.00 mg/dl [95 % CI, -34.33 to 24.33], $p = 0.74$), while there were decreases in TG levels for the 8 to 12 weeks (WMD: -8.06 mg/dl [95 % CI, -13.72 to -2.39], $p = 0.001$; $I^2 = 80 \%$, $p = 0.001$) and the > 12 weeks intervention groups (WMD: -2.53 mg/dl [95 % CI, -4.97 to -0.10], $p = 0.001$; $I^2 = 96 \%$, $p = 0.001$) (Table S3).

### 3.4.6. Total cholesterol

Physical exercise as a whole reduced TC level (WMD: -2.63 mg/dl [95 % CI, -4.58 to -0.68], $p = 0.001$; $I^2 = 94 \%$, $p = 0.001$).

A subgroup analysis by type of exercise revealed that there were no effects for TC levels produced by aerobic training (WMD: -9.33 mg/dl [95 % CI, -19.84 to 1.17], $p = 0.08$; $I^2 = 95 \%$, $p = 0.001$), resistance training (WMD: 1.40 mg/dl [95 % CI, -1.54 to 4.33], $p = 0.35$; $I^2 = 47 \%$, $p = 0.04$), combined (aerobic + resistance) exercise training (WMD: -2.54 mg/dl [95 % CI, -5.72 to 0.64], $p = 0.12$; $I^2 = 10 \%$, $p = 0.35$) or Tai chi training (WMD: -7.44 mg/dl [95 % CI, -17.44 to 2.56], $p = 0.14$; $I^2 = 86 \%$, $p = 0.001$) (Supplementary Fig. S6).

A subgroup analysis by gender of participants revealed no effects on TC levels for females (WMD: -6.72 mg/dl [95 % CI, -15.78 to 2.34], $p = 0.15$; $I^2 = 96 \%$, $p = 0.001$) or a combination of males and females as a group (WMD: 0.04 mg/dl [95 % CI, -0.80 to 0.87], $p = 0.93$; $I^2 = 53 \%$, $p = 0.001$) while there were decreases in TC levels for males (WMD: -8.42 mg/dl [95 % CI, -15.91 to -0.93], $p = 0.03$; $I^2 = 0 \%$, $p = 0.43$) (Table S3).

A subgroup analysis of the role of BMI revealed no effects on TC levels for BMI<25 kg/m² (WMD: -0.14 mg/dl [95 % CI, -0.77 to 0.49], $p = 0.67$; $I^2 = 58 \%$, $p = 0.001$), BMI between 25 and 29.9 kg/m² (WMD: 1.03 mg/dl [95 % CI, -2.43 to 4.48], $p = 0.56$; $I^2 = 58 \%$, $p = 0.001$) or BMI≥30 kg/m² (WMD: -26.49 mg/dl [95 % CI, -84.92 to 31.95], $p = 0.38$; $I^2 = 97 \%$, $p = 0.001$) (Table S3).

A subgroup analysis of intervention durations indicated no reductions in TC levels for ≤ 8 weeks (WMD: -7.33 mg/dl [95 % CI, -38.88 to 24.22], $p = 0.65$; $I^2 = 79 \%$, $p = 0.001$), between 8 and 12 weeks (WMD: 0.54 mg/dl [95 % CI, -5.17 to 6.26], $p = 0.85$; $I^2 = 91 \%$, $p = 0.001$), and > 12 weeks interventions (WMD: -0.98 mg/dl [95 % CI, -2.60 to 0.63], $p = 0.23$; $I^2 = 92 \%$, $p = 0.001$) (Table S3).

### 3.5. Study quality

A fifteen-point tool was used to evaluate the quality of our study and report in practice (TESTEX) (Smart et al., 2015). The overall methodological quality of included studies was estimated to be moderate to good, with a median TESTEX score of 10 (range 7–14) from a maximum score of 15.

Two investigations scored 14, five scored 13, ten scored 12, nineteen scored 11, twenty scored 10, nineteen scored 9, seventeen scored 8, and one scored 7 (Supplementary Table S4). The number of studies assessed to be of good quality (i.e., assigned a score of 1 based on the TESTEX criteria) was as follows: randomization specified 27/92 studies; allocation concealment 35/92 studies; blinding of assessor 31/92 studies; intention to treat analyses 11/92 studies; physical activity monitoring of the control groups 43/92 studies.

The other criteria were each met in at least 50 % of investigations such as eligibility criteria specified 92/92 studies, group similar at baseline 92/92 studies, outcome measures assessed in 85 % of patients 92/92 studies, between-group statistical comparisons were reported 92/92 studies, point measures and measures of variability for all reported outcome measures 92/92 studies, relative exercise intensity remained constant 84/92 studies and exercise volume and energy expenditure 91/92 studies.

## 4. Discussion

This systematic review and meta-analysis was designed to investigate the effects of different types of exercise training on the blood pressure of older adults patients with hypertension. The pooled results from 92 RCTs (with 4988 subjects, 1842 subjects in the intervention group, and 2146 in the control group) indicated that exercise training reduced SBP and DBP, LDL, TG, and TC levels in patients with hypertension, with increases in HDL levels following exercise. However, there were differential effects of the various types of exercise on reducing blood pressure (i.e., SBP and DBP), LDL, TG, and increasing HDL levels. Thus, aerobic training, resistance training, Tai chi training, and isometric handgrip training all reduced SBP, while only the latter four exercise training protocols (i.e., aerobic training, resistance training, combined exercise training (aerobic + resistance), and isometric handgrip training) reduced DBP levels.

Levels of LDLs and TG were improved following combined exercise training (aerobic + resistance) and resistance training respectively, but not after aerobic training and Tai chi training, while levels of HDLs were improved following aerobic training and combined (aerobic + resistance) exercise training, but not after resistance training and Tai chi training. No exercise training modality that were found to reduce TC levels in older adults patients with hypertension.

Additionally, gender status impacted the effectiveness of exercise with greater reductions in SBP in male, female, and both (male and female) participants, for DBP levels in female and both (male and female) participants, had greater reduction in DBP levels. In this regard, the variable of HDL is significant only in the group of females and not significant in both (male and female) groups.
Additionally, BMI status impacted the effectiveness of exercise with greater reductions in SBP and DBP in normal, overweight, and obese participants, but obese participants had a greater reduction in LDL, whereas HDL levels had a greater increase in overweight and obese participants. TC levels were significantly reduced only in participants with normal BMI. Overall, the quality of the literature included in the meta-analyses was moderate to good. Moderate to high heterogeneity and publication bias were found within most of the analyses. As such, some caution is warranted when interpreting the results of the meta-analyses. The exercise intervention duration appeared to influence its effectiveness with ≤ 8 weeks, between 8 and 12 weeks, and > 12 weeks of interventions favoring reductions in SBP and DBP levels. However, there was a significant decrease in levels of LDL only in the < 12 weeks intervention and the level of TG in the between 8 and 12 weeks and > 12 weeks interventions.

Exercise training significantly reduced blood pressure (i.e., SBP and DBP) in patients with hypertension. Aerobic training, resistance training, Tai chi training and isometric handgrip training were all effective for reducing SBP, while the latter four exercise training (i.e., aerobic training, resistance training, combined (aerobic + resistance) exercise training, and isometric handgrip training) modalities also led to reductions in DBP levels. Therefore, the effectiveness of isometric handgrip training was higher than other exercise programs in this research. The findings from the present review are consistent with the results of a meta-analysis conducted by Loaiza-Betancur et al. (2020), Jabbarzadeh Ganjeh et al. (2024). Loaiza-Betancur et al. (2020) discovered that isometric training is an effective method for reducing SBP and DBP. Jabbarzadeh Ganjeh et al. (2024) conducted a study on the effects of aerobic exercise on blood pressure and hemodynamic factors in adults with hypertension. They examined 34 articles from randomized controlled trials (RCTs) involving 1787 participants who engaged in 30 min of aerobic exercise per week. The findings indicated that performing 30 min of aerobic exercise per week significantly decreased both SBP and DBP. However, other systematic reviews and meta-analyses have not reported significant changes in DBP through exercise training among hypertensive patients (Palmeira et al., 2021). Palmeira et al. (2021) conducted a systematic review and meta-analysis to investigate the impact of isometric handgrip training on blood pressure among hypertensive patients. The results demonstrated that isometric handgrip training did not have a significant effect on DBP. Furthermore, the interventions did not affect heart rate variability and ambulatory blood pressure. Moreover, this review demonstrates that the degree of blood pressure reduction varies significantly across studies, regardless of exercise duration (less than 8 weeks, 8–12 weeks, and more than 12 weeks). Based on the results of this study, it can be concluded that isometric handgrip exercises are more effective for patients with hypertension than other types of exercises. These exercises can help to prevent and reduce the effects of hypertension-related conditions, such as cardiovascular diseases and atherosclerosis, ultimately reducing hypertension-induced complications while also lowering healthcare costs for patients. Furthermore, these findings provide valuable insights for coaches, physicians, and other specialists in the field, including those involved in designing targeted training and nutritional programs. Notably, exercise training lasting approximately 8 weeks may yield a more effective antihypertensive effect. However, it is important to consider the potential bias in the RCT studies, which may have influenced these findings. Furthermore, the pooled SBP and DBP after aerobic exercise exhibit a greater degree of heterogeneity compared to other forms of exercise training. Hypertension is a chronic age-related condition, (Sabbahi et al., 2016) and in a study by Duncan et al. (1985) the average age of participants was notably younger compared to other studies, which could be a contributing factor to the observed differences in results. Additionally, Nyberg et al. (2012) have reported that aerobic exercise training can regulate blood pressure through the nitric oxide and prostanoid systems, which are involved in blood vessel dilation. Furthermore, psychosocial stress plays a significant role in the

development of essential hypertension, whereas intensive aerobic exercise can help alleviate mental stress, thereby reducing sympathetic nervous system activity, which is associated with the onset of essential hypertension (Harshfield et al., 2009; Mayorov, 2011). In comparison to previous meta-analyses by Montero et al. (2014), Wen and Wang (2017), this study employed strict inclusion and exclusion criteria, as well as a comprehensive search strategy, to assess a wider range of outcome indicators (blood pressure, heart rate, and lipid profile). Moreover, this study specifically examined the impact of different exercise durations on blood pressure and lipid profile in hypertensive patients through subgroup analysis. Therefore, our findings provide valuable references for blood pressure management and different exercise training approaches.

Regular physical activity is a valuable approach for preventing and managing hypertension, and individuals who lead active lifestyles are at a lower risk of developing hypertension compared to those who are sedentary (Chobanian et al., 2003b; Fagard, 2006; Pescatello et al., 2004; 2004). Additionally, numerous studies demonstrate that even a single bout of exercise can reduce blood pressure during the recovery phase (Casonatto. et al, 2016; Mariano et al, 2022; Pescatello et al., 2004). Meta-analyses further indicates that aerobic exercise lowers blood pressure in both the general population and individuals with hypertension (Fagard, 2006; Pescatello et al., 2004). However, it is important to consider factors such as the characteristics of the population studied, the types of exercise performed, and the methods used for measuring blood pressure when assessing the impact of exercise. The effects of exercise on blood pressure may vary between normotensive and hypertensive individuals due to the alterations in cardiovascular hemodynamics induced by hypertension. Additionally, the effects of aerobic and resistance exercise on blood pressure are likely distinct, given their differing mechanical properties as aerobic exercise involves the performance of cyclic movements, engaging large muscle groups at low to moderate intensities over extended periods, while resistance training—also referred to as strength or weight training—entails exercises targeting specific muscle groups, where the muscles contract against an external force opposing the movement (Perloff et al, 1983). Resistance training, or strength exercise, can directly influence blood pressure regulation by promoting central and peripheral vasodilation, primarily through an increased bioavailability of endothelial-derived nitric oxide. This type of exercise also reduces inflammatory markers and improves autonomic regulation. Furthermore, it can also lead to reactive hyperemia, lower sympathetic drive, and modulate of cholinergic receptor sensitivity. Additionally, resistance training helps to regulate the pituitary-adrenal axis and hormonal factors such as adrenaline and the renin-angiotensin system. Enhanced myo-capillary perfusion, improved oxygen extraction, and increased sensitivity of ergoreceptors and metabolic receptors can further contribute to reduced blood pressure (Chandrasekaran et al., 2017). However, the molecular mechanisms associated of resistance training induced reductions in blood pressure are not completely understood.

Exercise training significantly decreased LDL, TG, and TC levels, but the levels of HDL increased significantly following the exercise training. As for LDL and TG levels, this was improved following combined (aerobic + resistance) exercise training and resistance training respectively, but not after aerobic training and Tai chi training. For HDL levels, this was improved following aerobic training and combined exercise training (aerobic + resistance), but not after resistance training and Tai chi training. There was no specific exercise training modality that effectively reduced TC in patients with hypertension. The results obtained from the present meta-analysis are consistent with the findings of Yun et al. (2023), Fei et al. (2022). Yun et al. (2023) in the meta-analysis research investigated the effects of different exercise modalities on lipid profile in the older adults population. This study identified 20 RCTs with a total of 988 subjects. Their analysis showed that aerobic training significantly reduced TC, TG, and LDL-C while increasing HDL-C in the older adults population. Resistance training significantly reduced the elevation of TC and LDL-C indices in the older adults population, while
combined exercise training had a significant effect on decreasing TC and LDL-C indices. Fei et al. (2022) in the network meta-analysis research evaluated the comparing the effects of aerobic training, resistance training, and aerobic combined with resistance training on blood lipids for patients with hypertension. The results showed that aerobic combined with resistance training had the most significant effect on TC, TG, LDL, and HDL. Buzdagli et al. (2022) conducted a study to investigate the impact of various types of exercise on blood lipid profiles. Their findings revealed that anaerobic exercise yielded the most significant results in terms of biomarker development. Additionally, both aerobic and resistance exercises were found to be effective in improving blood lipid profiles. Surprisingly, neither form of exercise demonstrated a significant effect on HDL levels. Previous research has shown that regular exercise has a positive influence on lipid metabolism in skeletal muscle. One possible mechanism for this improvement is the increased activity of lecithin-cholesterol acyltransferase, an enzyme responsible for transferring esters from human plasma to HDL cholesterol (Calabresi & Franceschini, 2010). Moreover, exercise training has been shown to enhance the activity of lipoprotein lipase, which plays a vital role in lipid uptake by muscles (Riedl et al., 2010). Kraus et al. (2002) conducted a study exploring the effects of exercise volume and intensity on lipid levels. They concluded that high exercise volume had a greater positive impact on lipid profiles and the prevention of cardiovascular disease compared to low exercise volume. The study specifically highlighted that training volume, rather than training intensity, was the primary determinant of improvements in lipid levels. A review of exercise interventions lasting 8 to 12 weeks and more than 12 weeks has demonstrated improvements in lipid profiles, such as LDL and TG, in patients with hypertension. Longer duration exercise interventions may offer the advantage of potentially greater weight loss, which would positively affect the aforementioned markers. It has been observed that exercise influences serum TG levels. A subset analysis of 200 men enrolled in the HERITAGE Family Study revealed that 22 weeks of exercise resulted in a 15% reduction in plasma TG levels, particularly in men with low HDL, elevated TGs, and abdominal obesity (Couillard et al., 2001).

The present study has several limitations that should be taken into account when interpreting the results. Firstly, we only included studies published in English, despite implementing a comprehensive search strategy. This implies that relevant studies published in other languages were overlooked. Another limitation is the inconsistency in timing and conditions for measuring blood pressure across different studies, including differences in the time of day and whether measurements were taken at the patient's home or in outpatient clinics. Moreover, we encountered challenges in locating certain studies for comprehensive analysis, even after contacting the authors. Additionally, the quality of the included trials varied, which may have impacted the estimation of treatment effects. Due to the moderate to high heterogeneity and risk of publication bias identified in most of the analyses in this meta-analysis, we are unable to confidently provide practical and specific recommendations regarding the use of exercise as an alternative intervention for individuals with hypertension.

However, physical exercise does show promise as an adjunctive treatment for hypertension in clinical practice involving the older adults. Furthermore, although we included various exercise protocols (such as aerobic, resistance, combined, Tai Chi, and isometric handgrip exercises) in this meta-analysis, we did not extensively investigate the specific effects of exercise frequency, intensity, participant health status, time since diagnosis of high blood pressure, duration of medications for high blood pressure and lipid lowering, and whether the participants followed any specific diet. It is important to control these variables in patients with hypertension. It is also recognized that relative to exercise modality (i.e., type) a preponderance of studies involving the older adults tend to excessively use isometric handgrip exercises due to safety concerns, which may have created a bias in the data. Despite these limitations, our systematic review and meta-analysis provide an up-to-date literature search from multiple databases and supplement

previously published systematic reviews. The strength of this study lies in the comprehensive analysis of all the included studies, comparing the effects of different types of exercise on blood pressure and lipid profile in older patients with hypertension. The studies included in this meta-analysis were conducted in a wide range of countries, potentially increasing the generalizability of the results. Moreover, this study is innovative as it considered both blood pressure and lipid profile indicators in patients with hypertension.

## 5. Conclusion

This meta-analysis confirms that diverse forms of exercise can substantially enhance blood pressure and lipid profile in individuals diagnosed with hypertension. Isometric handgrip training, among the exercise options examined, demonstrates a notably effective ability to reduce blood pressure in hypertensive patients when compared to aerobic, resistance, combination, and tai chi training. The duration of the exercise program, as well as the patients' gender and body mass index, could potentially impact the effectiveness of exercise in improving blood pressure. However, additional research is required to explore these factors in depth and establish the most optimum exercise regimen for optimizing health outcomes in patients with hypertension.

## Declarations

None.

## Availability of data and material

The data that support the findings of this study are available from the corresponding author upon reasonable request.

## CRediT authorship contribution statement

**Keyvan Hejazi:** Writing – review & editing, Writing – original draft, Validation, Software, Methodology, Formal analysis, Data curation, Conceptualization. **Zahra Ataran Iraj:** Writing – review & editing, Validation, Software, Methodology, Data curation. **Ayoub Saeidi:** Writing – review & editing, Writing – original draft, Validation, Software, Methodology, Data curation, Conceptualization. **Anthony C. Hackney:** Writing – review & editing, Validation, Formal analysis. **Fatiha Laziri:** Writing – review & editing, Validation, Formal analysis. **Katsuhuko Suzuki:** Writing – review & editing, Validation, Formal analysis. **Ismail Laher:** Writing – review & editing, Validation, Formal analysis, Data curation. **Zouhal Hassane:** Writing – review & editing, Writing – original draft, Validation, Supervision, Software, Formal analysis, Data curation, Conceptualization.

## Declaration of competing interest

The authors declare that they have no competing interests.

## Acknowledgments

We want to thank all authors of the studies included in the current meta-analysis for providing their change score data upon request.

## Supplementary materials

Supplementary material associated with this article can be found, in the online version, at doi:10.1016/j.archger.2024.105737.

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