Effects of high-intensity interval training on physical morphology, cardiopulmonary function, and metabolic indicators in older adults: A PRISMA-based systematic review and meta-analysis

Effects of high-intensity interval training on physical morphology, cardiopulmonary function, and metabolic indicators in older adults: A PRISMA-based systematic review and meta-analysis | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Article Effects of high-intensity interval training on physical morphology, cardiopulmonary function, and metabolic indicators in older adults: A PRISMA-based systematic review and meta-analysis Jie #Men, Chengrui Zhao, Chenmin Xiang, Guoyu Zhu, Zhengyang Yu, and 14 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-4253175/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract Background Despite the growing attention towards the efficacy of high-intensity interval training (HIIT) on elderly health, a consensus regarding the pleiotropic effects of HIIT in this population is yet to be reached. Previous studies have predominantly focused on specific outcomes or particular groups, lacking comprehensive analysis. Objective We aimed to conduct a systematic evaluation of the impact of HIIT on body composition, cardiopulmonary function, and metabolic parameters in older adults. Methods The databases searched included PubMed, Web of Science, Cochrane Library, Scopus, WanFang, and other relevant sources from the inception of the database until July 2023. We supplemented the randomized controlled trials (RCTs) and retrieved relevant meta-analyses, and found that 5 highly relevant non-RCTs were also included in the supplement to study the effects of high-intensity interval training (HIIT) on body composition, cardiopulmonary function and metabolic parameters in the elderly. Result A total of 92 studies, including 87 RCTs and 5 non-RCTs, involving a sample size of 4355 elderly individuals were included in the analysis. The meta-analysis results demonstrated that HIIT significantly improved body mass index (BMI) [MD: -0.38kg m-2,P = 0.01], body fat percentage (BF%) [MD༚-1.38%, P <0.00001], maximal oxygen uptake (VO2max) [MD:2.23ml min − 1 kg − 1 , P <0.00001], maximal heart rate (HRmax) [MD:2.84 beats min − 1 , P = 0.02], and high-density lipoprotein levels (HDL) [MD:0.04mmol L − 1 , P = 0.0007] among the elderly population. However, no significant improvements were observed for systolic blood pressure (SBP) [MD: -0.28mmHg, P = 0.75], resting heart rate (HRrest) [MD: -0.95time min − 1 , P = 0.24], triglycerides (TG) [MD: -0.04mmol L − 1 , P = 0.27], low-density lipoprotein (LDL) [MD: -0.05mmol L − 1 , P = 0.23]. Sensitivity analysis found that HIIT significantly improved waist circumference (WC) [MD: -2.13cm, P = 0.04], diastolic blood pressure (DBO) [MD: -0.96 mmHg, P = 0.03], respiratory exchange rate (RER) [MD: 0.01, P = 0.04], total cholesterol (TC) [MD: 0.15 mmol L − 1 , P = 0.009], fasting plasma glucose (FPG) [MD: -0.23 mmol L − 1 , P = 0.04]in the elderly, but the results lacked robustness. Conclusions The results of this study provide further support for HIIT to improve the physical health of the elderly, especially in terms of body shape and cardiopulmonary function, more importantly, provide a reference for HIIT in clinical practice and family health management of the elderly and the development of HIIT guidelines. Health sciences/Health care Health sciences/Medical research Figures Figure 1 Figure 2 1 Introduction The latest research predicts that the global elderly population aged 60 and above is projected to reach 2 billion by 2050[ 1 ]. With advancing age, there is a decline in physiological system functionality and an increased susceptibility to stress response [ 2 ]. At the same time, inadequate physical activity can accelerate the aging process and contribute to adverse outcomes, such as an increased susceptibility to falls, hospitalization, premature mortality, and all-cause mortality[ 3 ]. It is important to note that while the decline in systemic function among older individuals can be prevented and delayed, it may become irreversible once it manifests as an adverse event. Therefore, in addition to mitigating risk factors for adverse events, greater emphasis should be placed on preventing/delaying the deterioration of systemic functions to achieve healthy aging[ 4 ]. Copenhagen Consensus Statement 2019 highlights that physical activity is a crucial determinant for maintaining health and the normal functioning of physiological systems [ 3 ], and it represents one of the primary strategies to delay age-related decline in physical function among older adults [ 5 ]. Despite its significant role in reducing mortality risk [ 6 ], cardiovascular disease, and certain cancers [ 7 ], a majority of elderly individuals refrain from engaging in exercise or leisure physical activities [ 8 ], due to concerns regarding potential risks associated with exercise. A cross-sectional population study noted that the annual incidence of exercise-related cardiac arrest in the elderly is extremely rare [ 9 ], which means that the benefits of exercise far outweigh the possible risks. More and more studies have demonstrated that exercise can enhance age-related body composition[ 10 ]、ameliorate dyslipidemia, improve cardiopulmonary function[ 11 ], prevent the onset of type 2 diabetes, hypertension, cardiovascular disease, and cancer[ 12 ], as well as reduce overall mortality rates [ 13 ], The health benefits of exercise have garnered consensus among experts [ 14 , 15 ]. Currently, three forms of physical activity exhibit significant potential in promoting the health of older adults. The first category encompasses non-exercise physical activities (low-intensity), such as walking and household chores. Recent evidence unequivocally indicates that low-intensity physical activities also confer health advantages for older adults. The second form is moderate-intensity aerobic exercise, which is supported by substantial evidence establishing a dose-response relationship with health outcomes and recommended by global guidelines[ 15 ]. However, the intervention duration of aerobic exercise is prolonged and the rhythm is monotonous. The anticipated adherence rate is 27%[ 16 ], yet the actual adherence rate falls below 5%[ 17 ]. HIIT presents itself as a promising alternative for promoting health among older adults. Intermittent training incorporates short bursts of high-intensity anaerobic exercise followed by low-intensity aerobic recovery, yielding comparable exercise effects to moderate-intensity aerobic exercise. Moreover, HIIT offers advantages in terms of time efficiency and cost-effectiveness[ 18 ]. It holds great potential for widespread utilization in elderly health promotion endeavors. Importantly, unlike other pharmacological treatments that solely target a single outcome, exercise typically exerts positive effects on multiple physiological systems[ 19 ]. Recent studies have demonstrated that engaging in 3 to 4 minutes of HIIT per day can significantly reduce the risk of all-cause and cancer mortality by 38–40%, as well as decrease the risk of cardiovascular disease (CVD) mortality by 48–49%[ 20 ]. Furthermore, numerous meta-analyses have provided support for the role of HIIT in enhancing the health status of older individuals[ 18 , 21 – 29 ]. However, previous investigations on the health benefits of HIIT in older adults possess certain limitations. Firstly, most outcome measures were assessed within a single[ 18 , 22 , 25 , 26 , 29 ] or dual[ 21 , 23 , 27 ] physiological system. Secondly, only specific diseases [ 18 , 21 , 26 ], or particular risk factors[ 23 , 27 – 29 ]; were considered. Thirdly ,the majority of studies had small sample sizes and included non-elderly participants within their populations[ 18 ];Additionally, a meta-analysis encompassing ten studies incorporated six studies from a single research group[ 29 ]. All these factors inevitably restrict the comprehensive interpretation of the health effects of HIIT in older adults. Furthermore, a significant number of included studies were deemed to be of low quality[ 21 , 22 , 27 ]. While most research findings support the positive health effects of HIIT on elderly individuals, particularly about certain physiological systems, it is important to note that these systematic reviews or meta-analyses primarily focus on specific improvements within individual physiological systems or diseases. Considering that the human body functions as an integrated whole, our emphasis lies in examining the overall health impacts of HIIT and recognizing the essentiality of valid scientific evidence when formulating strategies to address global health issues among older populations. Given the above considerations, a systematic review was conducted to evaluate the effects of HIIT on 14 outcomes of body shape, cardiopulmonary function and metabolism in older adults. We also conducted subgroup analysis on the factors that may affect the conclusions, such as study type, intervention period, and disease type, in order to obtain more comprehensive data and provide evidence support for clinical or family health management and the development of HIIT guidelines/recommendations. 2 Methods 2.1 Search strategy The present review adhered to the guidelines of the Preferred Reporting Items for Systematic Reviews and Meta-analyses (PRISMA) [ 30 ]. It was prospectively registered in the International Registry of Prospective Systematic Reviews (PROSPERO) database under registration number "CRD42023460252" on September 5, 2023. The following databases were electronically searched: PubMed, Web of Science, Cochrane Library, Scopus, and WanFang database. A comprehensive search was conducted for RCTs investigating the HIIT on body composition, cardiopulmonary function, and metabolic indicators in older adults. The search period ranged from the inception of each database to July 1, 2023. Additionally, relevant literature and previously published systematic reviews were manually screened to identify any studies missed during the initial search process. 2.2 Inclusion criteria: Two researchers independently conducted a comprehensive literature review, eliminating duplicate and irrelevant studies, extracting relevant data, and cross-verifying the selected literature. In case of any discrepancies, they consulted with each other or sought input from a third party for discussion. A screening flow chart is presented in Fig. 1 . This meta-analysis included older adults aged ≥ 60 years without any restrictions on country, race, or gender except for athletes. The articles in both English and Chinese reported at least one outcome measure, with the intervention being HIIT. The outcome measures included: BMI, BF%, WC, VO 2max , SBP, DBP, HR rest , HR max , RER, TC, TG, HDL, LDL and FPG. 2.3 Data extraction The data extraction encompassed the following components: basic information of the included literature (first author's name, title, publication year), characteristics of study subjects (age, gender, number of subjects), training variables (intensity, form, frequency, intervention period), main results and key elements of risk of bias assessment. To calculate effect sizes for physical fitness measures in the intervention and control groups, baseline and follow-up mean as well as standard deviations were extracted. In case any required data were missing, we contacted the corresponding author to obtain them. If relevant data could not be provided by the author, they were excluded from the analysis. The characteristics of the included studies are presented in Table 1 . 2.4 Biased risk assessment RCTs were analyzed using the Cochrane Risk of Bias Tool 2.0. [ 31 ]. There are three levels: low-risk, high-risk and uncertain. "It involves the method of randomization, the concealment of randomization, the blinding of participants and interveners, the blinding of outcome raters, the completeness of outcome data, the possibility of selective reporting, and other sources of bias." For non-randomised controlled trials, the Risk of bias in non-randomised Intervention Studies (ROBINS-I) was used. The ROBINS-I considers bias from seven domains, classified by time of occurrence: pre-intervention (confusion, selection of study participants), intervention (classification of intervention) and post-intervention (deviation from intended intervention, missing outcome data, measurement of outcome and selection of reported outcome). The risk of biased judgment in each domain was interpreted as low risk, moderate risk, severe risk, borderline risk, or no information. [ 32 ] Two reviewers independently assessed the risk of bias, and any disagreements were resolved through a third party. In addition, the risk of publication bias was assessed using funnel plots when the meta-analysis included ≥ 10 studies. 2.5 Statistical Analysis Review Manager 5.3 (RevMan) software was used for statistical analysis. mean difference (MD) was used as the effect analysis statistic, and 95% confidence interval (CI) was provided for each effect size. I 2 was used to evaluate the degree of heterogeneity: above 25%,50% and 75% were low, medium and high heterogeneity respectively[ 33 ], and the level of meta-analysis was set as α = 0.05. When I 2 ≤ 25%, the fixed effect model was used for combined analysis. If I 2 >25%, the random effects model was used for combined analysis. To increase the stability of the results, sensitivity analysis was performed by eliminating one by one. Publication bias was assessed using funnel plots. Subgroup analysis was performed when I 2 ≥ 50%. The analysis factors included study type (RCT vs. non-RCT), intervention duration (≤ 1 2 weeks vs. > 12 weeks), and disease type (cardiovascular disease, diabetes, hypertension, cancer, and others). Further analysis was performed when more than 5 studies were included in the subgroup. 3 Result 3.1 Study Selection Figure 1 describes the PRISMA process in detail. A total of 2278 studies were retrieved from the database, and 7 studies were obtained from other sources. After the strict screening, 92[ 28 – 119 ] studies were finally included, of which 87 met the criteria of RCTs and 5 met the criteria of non-RCTs, with a total of 4355 elderly people, including 2174 in the HIIT group and 2181 in the control group. Exercise frequency, duration, cycle, and outcome measures were reported. Figure 2 shows the geographical and sample distribution of the included studies. 66.29% of the studies are in Europe, 14.14% in North America and South America,13.78% in Asia, 4.87% in Australia and 0.92% in Africa, involving 21 countries and regions. Of these, 658 were from Norway, 543 from Switzerland, 537 from Belgium, 280 from Denmark, 211 from Spain, 200 from the United Kingdom, 148 from Sweden, 144 from Germany, 140 from Italy, 26 from France, 244 from Canada, 222 from the United States, 150 from Brazil, 254 from China, 133 from Iran, 88 from Japan and 72 from South Korea People, 29 from Thailand, 24 from Indonesia, 212 from Australia and 40 from Egypt, a total of 4,355. TDOAIS = The degree of ageing is serious. TDOAIRH = The degree of ageing is relatively heavy. TDOAIM = The degree of ageing is moderate. TDOAIL = The degree of ageing is low; *When the disease mark appears in a certain area, it means that the subjects included in the area have the disease or are in a healthy state.; The proportion of the elderly population: TDOAIS > 17.91 17.91 > TDOAIRH > 13.15 13.15 > TDOAIM > 9.02 TDOAIL < 9.02 3.2 Quality assessment of included studies A total of 87 RCTs and 5 non-RCTs were included, and the overall risk of bias was low. Of these RCTs: 84/87 evaluated using randomized sequence generation; 84/87 assessments used allocation concealment; 77/87 subjects and staff were blinded; 77/87 were blinded to the outcome data evaluation; 84/87 had complete data; 86/87 no selectivity was reported; 39/87 had no other bias Among the included non-RCTs: 5/5Confounding;4/5Selection of participants;5/5Classification of intervention;5/5Missing data;0/5Measurement of the outcome;5/5Selection of reported result;5/5Overall risk of bias. (The results are shown in Annex 1) 3.3 Meta-analysis result 3.3.1 Body morphology indicators BMI A total of 32[ 34 , 36 , 38 , 46 , 49 – 53 , 58 , 67 – 69 , 72 , 75 , 78 – 80 , 86 , 87 , 95 , 99 , 103 , 104 , 106 , 107 , 111 , 115 , 117 , 119 , 122 , 125 ] studies were included, including 27 RCTs and 5 non-RCTs. Compared with the control group, HIIT significantly improved BMI in the elderly (MD: -0.38kg m − 2 , P = 0.01), but there was statistical heterogeneity (I 2 = 64%) (see Table 4 ). Sensitivity analysis showed that the results of this study were robust. Funnel plots were basically symmetric, and there was no evidence of publication bias. Differences between subgroups suggest that disease type may be a source of heterogeneity (P < 0.0001). (The results of subgroup analysis and funnel plot are shown in Annex 2) BF% A total of 20 [ 46 , 53 , 58 , 70 , 72 , 73 , 75 , 79 , 84 , 87 , 97 , 99 , 100 , 104 , 107 , 111 , 115 , 121 , 122 , 125 ] studies were included, including 16 RCTS and 4 non-RCTs. Compared with the control group, HIIT significantly improved BF% (MD: -1.38%, P < 0.00001) in the elderly, without significant heterogeneity (I 2 = 23%) (see Table 4 ). Sensitivity analysis showed that the results of this study were robust. Funnel plots were basically symmetric, and there was no evidence of publication bias. (See Annex 2 for funnel diagram) WC A total of 18[ 34 , 38 , 46 , 51 , 58 , 68 , 72 , 73 , 78 , 79 , 84 , 88 , 97 , 99 , 100 , 104 , 115 , 119 ] studies were included, including16 RCTs and 2 non-RCTs, Compared with the control group, HIIT had no significant effect on WC in the elderly (MD:-1.54cm, P = 0.16), but there was statistical heterogeneity (I 2 = 76%) (see Table 4 ). After excluding the study by TJØNNA AE et al.[ 34 ], I 2 decreased to 39%, which was not statistically significant (MD: -0.38cm, P = 0.60). After excluding the study by Eeik Madssen et al.[ 51 ], there was no significant change in I 2 , but HIIT significantly improved WC in the elderly (MD: -2.13cm, P = 0.04). Sensitivity analysis suggested that the results were not robust. Funnel plots were basically symmetric, and there was no evidence of publication bias. (See Annex 2 for funnel diagram) 3.3.2 Cardiopulmonary function indicators VO2 max A total of 60[ 28 , 30 , 31 , 33 – 36 , 38 – 44 , 46 , 47 , 50 – 61 , 63 – 67 , 69 – 71 , 73 – 75 , 78 , 81 – 83 , 87 , 88 , 92 , 94 , 95 , 98 , 101 , 102 , 106 , 111 , 113 , 116 , 117 , 119 ] studies were included, including 56 RCTs,4 non-RCTs, Compared with the control group, HIIT had a significant effect on VO2max in the elderly (MD:2.23ml min − 1 kg − 1 , P < 0.00001), but there was statistical heterogeneity (I 2 = 82%) (see Table 4 ). Sensitivity analysis results suggested that the results of this study were robust. Funnel plots were basically symmetric, and there was no evidence of publication bias. Subgroup analysis showed that HIIT had a significant improvement in both the healthy and the sick elderly (P 0.05). (The results of subgroup analysis and funnel plot are shown in Annex 2) SBP A total of 43[ 34 – 36 , 38 , 40 , 42 , 46 , 51 , 54 , 57 , 58 , 62 , 65 , 68 , 69 , 72 , 73 , 79 – 81 , 84 , 86 , 87 , 89 , 91 , 93 – 95 , 98 , 99 , 102 – 108 , 116 , 119 , 121 , 122 ] studies were included, including 38 RCTs and 5 non-RCTs. Compared with the control group, HIIT had no significant effect on SBP in the elderly (MD: -0.28mmHg, P = 0.75) (see Table 4 ). Sensitivity analyses suggested that the results were robust. Funnel plots were basically symmetric, and there was no evidence of publication bias. (See Annex 2 for funnel diagram) DBP A total of 43[ 34 – 36 , 38 , 40 , 46 , 51 , 54 , 57 , 58 , 62 , 65 , 69 , 72 , 73 , 79 , 80 , 84 – 87 , 89 , 91 , 93 – 95 , 98 , 99 , 101 – 108 , 116 , 119 , 121 , 122 ] studies were included, including 38 RCTs and 5 non-RCTs. Compared with the control group, HIIT had no significant effect on DBP in the elderly (MD: -0.83mmHg, P = 0.06) (see Table 4 ). After excluding the study by Fernandes B et al. [ 40 ], there was no significant change in I 2 , but it significantly improved DBP in the elderly (MD: -0.96 mmHg, P = 0.03). Sensitivity analysis suggested that the results were not robust. Funnel plots were basically symmetric, and there was no evidence of publication bias. (See Annex 2 for funnel diagram) HR rest A total of 29[ 35 , 39 , 40 , 43 , 46 , 51 , 64 , 65 , 72 , 73 , 80 – 82 , 84 – 86 , 88 , 91 , 93 – 95 , 98 , 104 , 105 , 112 , 114 , 119 , 121 , 122 ] studies were included, including 27 RCTs and 2 non-RCTs. Compared with the control group, HIIT had no significant effect on HRrest in the elderly (MD: -0.95 BPM − 1 , P = 0.24) (see Table 4 ). Sensitivity analyses suggested that the results were robust. Funnel plots were basically symmetric, and there was no evidence of publication bias. (See Annex 2 for funnel diagram) HR max A total of 40[ 34 – 36 , 39 , 42 , 43 , 46 , 47 , 49 , 51 , 52 , 55 , 62 , 64 , 65 , 69 , 73 , 80 – 83 , 85 , 90 , 91 , 93 , 95 , 96 , 98 , 102 , 104 – 106 , 109 , 112 – 114 , 116 , 118 – 120 ] studies were included, including 39 RCTs and 1 non-RCTs. Compared with the control group, HIIT significantly improved HRmax in the elderly (MD:2.84 BPM − 1 , P = 0.02), but there was statistical heterogeneity (I 2 = 79%) (see Table 4 ). Sensitivity analyses suggested that the results were robust. Funnel plots were basically symmetric, and there was no evidence of publication bias. Differences between subgroups suggest that disease type may be a source of heterogeneity (P < 0.0001). (The results of subgroup analysis and funnel plot are shown in Annex 2) RER A total of 26[ 42 , 43 , 46 , 52 , 55 , 62 , 63 , 77 , 81 – 83 , 90 , 106 , 112 – 114 , 116 , 119 ] studies were included, 26 RCTs and 0 non-RCTs. Compared with the control group, HIIT had no significant effect on RER in the elderly (MD: 0.01, P = 0.20) (see Table 4 ). After excluding studies by Villelabeitia-Jaureguizar K et al. [ 83 ] I 2 was reduced to 33% and RER was significantly improved (MD: 0.01, P = 0.04). Sensitivity analysis results suggested that the results of this study lacked robustness. Funnel plots were basically symmetric, and there was no evidence of publication bias. (See Annex 2 for funnel diagram) 3.3.3 Metabolic index TC A total of 22[ 36 , 37 , 46 , 51 , 55 , 57 , 65 , 67 , 68 , 72 , 86 , 94 , 95 , 97 , 99 , 103 , 107 , 108 , 115 , 116 , 119 , 122 ] studies were included, including 20 RCTs and 2 non-RCTs. Compared with the control group, HIIT had no significant effect on TC in the elderly (MD: 0.12 mmol L − 1 , P = 0.06), but there was statistical heterogeneity (I 2 = 31%) (see Table 4 ). After excluding the study of Gjellesvik TI et al. [ 116 ], the heterogeneity decreased to 18% and significantly improved TC (MD: 0.15 mmol L − 1 , P = 0.009). Sensitivity analysis showed that the results of this study were not robust. Funnel plots were basically symmetric, and there was no evidence of publication bias. (See Annex 2 for funnel diagram) TG A total of 29[ 34 , 36 – 38 , 43 , 46 , 51 , 55 , 57 , 58 , 65 , 68 , 72 , 86 , 94 , 95 , 97 , 99 , 103 , 107 , 108 , 111 – 116 , 119 , 122 ] studies were included, including 26 RCTs and 3 non-RCTs. Compared with the control group, HIIT had no significant effect on TG (MD: -0.04mmol L − 1 , P = 0.27) (see Table 4 ). Sensitivity analyses suggested that the results were robust. Funnel plots were basically symmetric, and there was no evidence of publication bias. (See Annex 2 for funnel diagram) HDL A total of 28[ 36 – 38 , 43 , 46 , 51 , 55 , 57 , 58 , 65 , 67 , 68 , 72 , 86 , 94 , 95 , 97 , 99 , 103 , 107 , 111 – 116 , 119 , 122 ] studies were included, including 25 RCTs and 3 non-RCTs. Compared with the control group, HIIT significantly improved HDL (MD: 0.04mmol L − 1 , P = 0.0007) in the elderly, with low statistical heterogeneity (I 2 = 25%) (see Table 4 ). Sensitivity analysis showed that the results of this study were robust. Funnel plots were basically symmetric, and there was no evidence of publication bias. There was no significant difference between subgroups (P > 0.05). (See Annex 2 for funnel diagram) LDL A total of 25[ 36 – 38 , 43 , 46 , 51 , 55 , 57 , 58 , 65 , 68 , 72 , 86 , 94 , 95 , 97 , 99 , 103 , 107 , 111 , 112 , 115 , 116 , 119 , 122 ] studies were included, including 22 RCTs and 3 non-RCTs. HIIT had no significant effect on LDL compared with the control group (MD: -0.05mmol L − 1 , P = 0.23) (see Table 4 ). Sensitivity analyses suggested that the results were robust. Funnel plots were basically symmetric, and there was no evidence of publication bias. (See Annex 2 for funnel diagram) FPG A total of 24[ 34 , 36 , 38 , 46 , 51 , 53 , 55 , 57 , 67 , 68 , 86 , 88 , 95 , 97 , 99 , 108 , 111 – 115 , 119 , 122 , 124 ] studies were included, including 23 RCTs and 1 non-RCTs. Compared with the control group, HIIT had no significant effect on FPG in the elderly (MD: -0.20 mmol L − 1 , P = 0.07). After excluding the study by Dolan LB et al. [ 88 ], there was no significant change in I 2 , but FPG was significantly improved (MD: -0.23 mmol L − 1 , P = 0.04) (see Table 4 ). The results of sensitivity analysis suggested that the results of this study lacked robustness. Funnel plots were basically symmetric, and there was no evidence of publication bias. (See Annex 2 for funnel diagram) Table 4 Meta-analysis results Outcomes The number of studies P I ² (%) Effect model 95%CI BMI 32 0.01* 64 RE -0.38 [-0.68, -0.09] BF% 20 <0.00001** 23 FE -1.38[-1.93,-0.83] WC 18 0.16 76 RE -1.54 [-3.67, 0.60] VO 2max 60 <0.00001** 82 RE 2.23 [1.55, 2.91] SBP 43 0.75 81 RE -0.28 [-1.98, 1.42] DBP 43 0.06 73 RE -0.83 [-1.69, 0.03] HR rest 29 0.24 83 RE -0.95[-2.54,0.63] HR max 40 0.02* 79 RE 2.84[0.48,5.20] RER 26 0.20 45 RE 0.01[-0.00,0.02] TC 22 0.06 31 RE 0.12 [-0.00, 0.24] TG 29 0.27 44 RE -0.04 [-0.12, 0.03] HDL 28 0.0007** 25 FE 0.04 [0.02, 0.07] LDL 25 0.23 37 RE -0.05 [-0.14, 0.03] FPG 24 0.07 58 RE -0.20 [-0.41, 0.02] RE: random effects models FE: fixed effects model; MD: mean difference CI: confidence interval * P <0.05 4. Discussion This meta-analysis examined the overall impact of HIIT on elderly health by analyzing 14 clinical indicators across three categories: body composition, cardiopulmonary function, and metabolism. To our knowledge, this study is the largest in the world to evaluate HIIT's effects on elderly health, encompassing 92 eligible RCTs and non-RCTs studies involving 4,355 participants from various populations including healthy individuals as well as those with hypertension, cardiovascular disease, diabetes, cancer and other conditions. Our findings support the universal efficacy of HIIT in improving BMI, BF%, VO2max, HRmax, and HDL levels among older adults; however it does not affect SBP, HRrest, TG, and LDL levels. The results for DBP, RER TC and FPG should be interpreted with caution due to their lack of robustness which may be attributed to differences in disease type. These results further endorse HIIT as a preventive or therapeutic tool for managing elderly health both clinically and at home while providing scientific evidence for developing guidelines/recommendations. 4.1Body shape index Due to the intricate relationship between body shape and health as well as disease[ 126 ], it serves as a primary indicator for assessing the health status of older individuals. Two extensive cohort studies have demonstrated that both high BMI and BF% along with low BMI elevate the risk of mortality [ 127 , 128 ]. Therefore, it is crucial for elderly individuals to effectively manage their BMI and reasonably reduce their BF%. This meta-analysis aims to elucidate the impact of HIIT on three clinical parameters related to body shape in older adults. The results of the meta-analysis demonstrated that HIIT effectively improved BMI and body BF% in older adults, which is consistent with the findings reported by Wang Donghai et al.[ 129 ]and[ 23 ], but contradicts the conclusions drawn from other studies[ 18 , 21 , 22 , 24 – 29 ]. Unlike previous studies that primarily included individuals with normal weight as baseline data, our study focused on overweight and obese participants except for the research conducted by Nemoto K et al. [ 80 ]. The meta-analysis results indicated insufficient evidence regarding the impact of HIIT on waist circumference (WC) in older adults, aligning with most previous systematic reviews[ 18 , 21 , 22 , 24 – 29 ]. To further assess the stability of these combined results, a sensitivity analysis was performed. After excluding the study conducted by TJS ØNNA AE et al. [ 34 ], I 2 decreased from 76–39%, suggesting that this discrepancy may be attributed to differences in baseline data between this particular study and others. It is worth noting that, excluding the study by Eeik Madssen et al. [ 51 ] there was no significant change in I 2 ; however, WC exhibited a reversal (P = 0.04). Further analysis revealed that the exercise supervision implementation rate in the study was only 1/3, and this low compliance resulted in an increase in WC after HIIT intervention. This finding may further elucidate the insufficient effect of HIIT on WC combined results. Therefore, caution should be exercised when interpreting whether HIIT can improve WC in the elderly due to the lack of robustness of these results. 4.2 Cardiopulmonary function index The pleiotropic effects of maintaining a high level of cardiopulmonary function on the Health of the elderly have been widely recognized[ 130 ], and it has been identified as a priority for promoting the health of the elderly by the World Health Organization (WHO)[ 15 ] A total of 6 cardiopulmonary function indicators were included in this meta-analysis to evaluate the effects of HIIT on cardiopulmonary function in the elderly. The existing evidence shows that HIIT can effectively improve VO2max and HRmax in the elderly. The analysis of 60 studies showed that the increase of VO2max by 2.23ml/kg/min is very significant, and VO2max is recognized as the gold standard of cardiopulmonary function. A 44-year follow-up study showed that VO2max was inversely associated with the risk of cancer, cardiovascular events, and all-cause mortality[ 131 ],, and each 1-mets increase reduced cardiovascular events by 15% and all-cause mortality by 13%[ 132 ]. Subgroup analysis found that the effect of HIIT on VO2max in the elderly was generalized, and was independent of the intervention period and the health of the subjects. In addition, HRmax is also one of the important indexes to evaluate the cardiopulmonary function of the elderly, and it is positively correlated with VO2max. The improvement of HRmax is consistent with VO2max, but the improvement of HRmax is less extensive than VO2max. The results of this study show that there is insufficient evidence for HIIT to improve blood pressure in the elderly, which is consistent with the results of previous studies [ 22 – 29 , 129 ], but in sharp contrast to the study by Litao Du et al.[ 21 ], the difference in conclusions may be related to the training method (isometric exercise has a better effect on blood pressure change than other exercise methods [ 133 ])and the sensitivity of the subjects to HIIT. As blood pressure is the most important modifiable risk factor for all-cause morbidity and mortality, SBP did not change significantly after excluding one by one, but DBP showed a significant difference (P = 0.03) after excluding the study by Fernandes B et al. [ 40 ], a finding consistent with Juliana Moraes The conclusion of Leal et al. [ 18 ] was consistent, which may be related to the lack of effective supervision and administration of antihypertensive drugs during the HIIT intervention in that study. After the study by Villelabeitia-Jaureguizar K et al. [ 83 ] was excluded by RER, the results were reversed (P = 0.04). Since this study compared the improvement difference between moderate-intensity exercise and HIIT, the effect of HIIT was reduced. The results for DBP and RER need to be interpreted with caution, given the lack of robustness of the sensitivity analyses. Unfortunately, there is insufficient evidence on the effect of HIIT on HRrest in the elderly, so it was omitted from this meta-analysis. 4.3 Metabolic index Metabolic abnormalities can cause a variety of chronic diseases, including obesity, cardiovascular disease, diabetes, cancer, etc., which brings huge public health problems and medical burdens[ 134 ]. Metabolic disorders are often more serious in the elderly. Priority should be given to reducing the related risks in the elderly at this stage while preventing them. A total of 5 metabolic indicators were included in this meta-analysis, and the existing evidence showed that HIIT effectively improved HDL, which was in sharp contrast with previous studies [ 18 , 21 , 26 ] probably because previous studies were based on comparing the differences between HIIT and moderate intensity exercise, while most of our work was based on the comparison between HIIT and blank control. However, HIIT had no significant effect on TG and LDL, which is consistent with previous studies [ 23 , 24 ]. TC excluded the study of Gjellesvik TI et al. [ 116 ], and FPG excluded Dolan The results of LB et al. [ 88 ] were reversed after the study, which may be due to the differences in the baseline levels of our included studies, two types of exercise in some studies, and the use of drugs to treat metabolic abnormalities or affect metabolic indicators. These factors may reduce the improvement effect of HIIT on metabolic indicators, which is explained by the lack of robustness of TG and FPG results You need to be careful. 4.4 Adverse events and compliance Among the included studies, 25 studies provided comprehensive descriptions of medical supervision, while 29 studies lacked detailed information in this regard, and 38 studies did not mention it at all. Additionally, withdrawal from the intervention was reported in 26 studies due to reasons such as familial obligations, personal preferences, and other factors involving a total of 215 participants, accounting for approximately 4.94% of the overall sample size. Adverse events were documented in 46 cases with an incidence rate of approximately 1.06%. Importantly, none of these adverse events were attributed to HIIT. 4.5 Limitations The large sample size and high heterogeneity observed in our study were expected due to differences in methodology and study subjects, as the range of studies included all older adults except those with contraindications to exercise. Therefore, subgroup analyses and sensitivity points were conducted to assess the role and stability of the pooled results. Sensitivity analysis revealed that WC, DBP, RER, TC, and FPG lacked robustness. Despite implementing a rigorous search strategy, language bias was inevitable as only Chinese and English literature was retrieved within our constraints. Furthermore, variations in exercise equipment, interval time, and intervention duration among the HIIT studies included prevented us from conducting subgroup analysis; thus specific exercise doses cannot be recommended at this stage. Lastly, our included studies did not assess medication use or baseline/daily physical activity which are critical factors for evaluating the hypothesis that HIIT improves health in older adults. Additionally, we lacked data on other influencing factors such as gender and exercise capacity. 5 Conclusion The current evidence indicates that HIIT has a broad range of effects on enhancing body composition and cardiopulmonary function in older adults. These findings provide substantial support for the role of HIIT in promoting physical health among the elderly, thereby warranting its inclusion within preventive healthcare systems targeting this population. However, the optimal exercise dosage for HIIT remains uncertain, necessitating future multi-center, large-scale, high-quality studies and long-term prospective investigations to validate these outcomes. Declarations Ethics approval and consent to participate Not applicable. Author contributions Men Jie and Chenmin Xiang contributed to the conception and design of the study. Guoyu Zhu and Chenmin Xiang contributed to the development of the search strategy. Chengrui Zhao and Chenmin Xiang conducted the systematic review. Zhengyang Yu, Pengbo Wang, Simin Wu, Xiyu Zhang, Yishan Li, Liuliu Wang and Xueyan Gongcompleted the acquisition of data and performed the data analysis. All authors assisted with the interpretation. Men Jie, Chenmin Xiang, Guoyu Zhu and Chengrui Zhao were the principal writers of the manuscript. All authors contributed to the drafting and revision of the final article. All authors approved the final submitted version of the manuscript. Consent for publication Not applicable. Availability of data and materials Data may be available on request to the corresponding author. Competing interests The authors declare that they have no conflicts of interest relevant to the content of this review. Funding This paper is supported by the Institute of Metabolic Cardiovascular Diseases Key Laboratory Cultivation Base of Shanxi Province (TSGJ001); Teaching Reform and Innovation Project of Higher Education in Shanxi Province (J2021967); Teaching Reform Project of Fenyang College of Shanxi Medical University (FJ202013); Talent Introduction Start-up Fund of Fenyang College of Shanxi Medical University (2022A01); Innovation and Entrepreneurship Training Program for College Students in Shanxi Province(No. 20231800) and Fenyang College Students' Innovation and Entrepreneurship Program of Shanxi Medical University (FDC202104). References Manas A, Del PB, Rodriguez-Gomez I, Losa-Reyna J, Judice PB, Sardinha LB, et al. Breaking Sedentary Time Predicts Future Frailty in Inactive Older Adults: A Cross-Lagged Panel Model. J Gerontol A Biol Sci Med Sci. 2021;76(5):893–900. Dent E, Martin FC, Bergman H, Woo J, Romero-Ortuno R, Walston JD. 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High intensity aerobic interval exercise is superior to moderate intensity exercise for increasing aerobic capacity in patients with coronary artery disease. European Journal of Cardiovascular Prevention & Rehabilitation. 2004;11(3):216–22. Bruseghini P, Calabria E, Tam E, Milanese C, Oliboni E, Pezzato A, et al. Effects of eight weeks of aerobic interval training and of isoinertial resistance training on risk factors of cardiometabolic diseases and exercise capacity in healthy elderly subjects. Oncotarget. 2015;6(19):16998–7015. Bruseghini P, Tam E, Calabria E, Milanese C, Capelli C, Galvani C. High Intensity Interval Training Does Not Have Compensatory Effects on Physical Activity Levels in Older Adults. INT J ENV RES PUB HE. 2020;17(3):1083. Herrod PJJ, Blackwell JEM, Boereboom CL, Atherton PJ, Williams JP, Lund JN, et al. The time course of physiological adaptations to high-intensity interval training in older adults. AGING MEDICINE. 2020;3(4):245–51. Eser P, Jaeger E, Marcin T, Herzig D, Trachsel LD, Wilhelm M. Acute and chronic effects of high-intensity interval and moderate-intensity continuous exercise on heart rate and its variability after recent myocardial infarction: A randomized controlled trial. Annals of Physical and Rehabilitation Medicine. 2022;65(1):101444. Steen Krawcyk R, Vinther A, Petersen NC, Faber J, Iversen HK, Christensen T, et al. Effect of Home-Based High-Intensity Interval Training in Patients With Lacunar Stroke: A Randomized Controlled Trial. FRONT NEUROL. 2019;10(1):664. Siri MH, Marit RB, Grethe A, Arnt ET, Ulrik W, Charlotte BI. High-Intensity Interval Exercise Effectively Improves Cardiac Function in Patients With Type 2 Diabetes Mellitus and Diastolic Dysfunction. J AM COLL CARDIOL. 2014;64(16):1758–62. Keteyian SJ, Hibner BA, Bronsteen K, Kerrigan D, Aldred HA, Reasons LM, et al. Greater improvement in cardiorespiratory fitness using higher-intensity interval training in the standard cardiac rehabilitation setting. J Cardiopulm Rehabil Prev. 2014;34(2):98–105. Angadi SS, Mookadam F, Lee CD, Tucker WJ, Haykowsky MJ, Gaesser GA. High-intensity interval training vs. moderate-intensity continuous exercise training in heart failure with preserved ejection fraction: a pilot study. J APPL PHYSIOL. 2015;119(6):753–8. Madsen SM, Thorup AC, Overgaard K, Jeppesen PB. High Intensity Interval Training Improves Glycaemic Control and Pancreatic β Cell Function of Type 2 Diabetes Patients. PLOS ONE. 2015;10(8):e133286. Cassidy S, Thoma C, Hallsworth K, Parikh J, Hollingsworth KG, Taylor R, et al. High intensity intermittent exercise improves cardiac structure and function and reduces liver fat in patients with type 2 diabetes: a randomised controlled trial. DIABETOLOGIA. 2016;59(1):56–66. Banerjee S, Manley K, Shaw B, Lewis L, Cucato G, Mills R, et al. Vigorous intensity aerobic interval exercise in bladder cancer patients prior to radical cystectomy: a feasibility randomised controlled trial. SUPPORT CARE CANCER. 2017;26(6):1515–23. Mueller S, Winzer EB, Duvinage A, Gevaert AB, Edelmann F, Haller B, et al. Effect of High-Intensity Interval Training, Moderate Continuous Training, or Guideline-Based Physical Activity Advice on Peak Oxygen Consumption in Patients With Heart Failure With Preserved Ejection Fraction. JAMA. 2021;325(6):542. Twerenbold S, Hauser C, Gander J, Carrard J, Gugleta K, Hinrichs T, et al. Short-term high‐intensity interval training improves micro‐ but not macrovascular function in hypertensive patients. SCAND J MED SCI SPOR. 2023;33(7):1231–41. Moholdt TT, Amundsen BH, Rustad LA, Wahba A, Løvø KT, Gullikstad LR, et al. Aerobic interval training versus continuous moderate exercise after coronary artery bypass surgery: A randomized study of cardiovascular effects and quality of life. AM HEART J. 2009;158(6):1031–7. Moholdt T, Aamot IL, Granoien I, Gjerde L, Myklebust G, Walderhaug L, et al. Long-term follow-up after cardiac rehabilitation: a randomized study of usual care exercise training versus aerobic interval training after myocardial infarction. INT J CARDIOL. 2011;152(3):388–90. Moholdt T. Does fundamentally altering the staffing of clinical rehabilitation services impact their function? Australasian psychiatry: bulletin of Royal Australian and New Zealand College of Psychiatrists. 2012;26(1):33–44. Terada T, Friesen A, Chahal BS, Bell GJ, McCargar LJ, Boulé NG. Feasibility and preliminary efficacy of high intensity interval training in type 2 diabetes. DIABETES RES CLIN PR. 2013;99(2):120–9. Tor Ivar Gjellesvik MFBP, PhD HNPB, MD SLPT. Effects of High-Intensity Interval Training after Stroke (The HIIT-Stroke study) - A Multicenter Randomized Controlled Trial. 2020;101(6):939–47. Lohman T, Bains G, Cole S, Gharibvand L, Berk L, Lohman E. High-Intensity interval training reduces transcriptomic age: A randomized controlled trial. AGING CELL. 2023;22(6):e13841. Wisløff U, Støylen A, Loennechen JP, Bruvold M, Rognmo Ø, Haram PM, et al. Superior Cardiovascular Effect of Aerobic Interval Training Versus Moderate Continuous Training in Heart Failure Patients. CIRCULATION. 2007;115(24):3086–94. Conraads VM, Pattyn N, De Maeyer C, Beckers PJ, Coeckelberghs E, Cornelissen VA, et al. Aerobic interval training and continuous training equally improve aerobic exercise capacity in patients with coronary artery disease: The SAINTEX-CAD study. INT J CARDIOL. 2015;179(2015):203–10. Wyckelsma VL, Levinger I, Murphy RM, Petersen AC, Perry BD, Hedges CP, et al. Intense interval training in healthy older adults increases skeletal muscle [3 H]ouabain-binding site content and elevates Na+,K+ -ATPase α2 isoform abundance in Type II fibers. Physiological Reports. 2017;5(7):e13219. Coswig VS, Barbalho M, Raiol R, Del Vecchio FB, Ramirez-Campillo R, Gentil P. Effects of high vs moderate-intensity intermittent training on functionality, resting heart rate and blood pressure of elderly women. J TRANSL MED. 2020;18(1):88. Mitranun W, Deerochanawong C, Tanaka H, Suksom D. Continuous vs interval training on glycemic control and macro- and microvascular reactivity in type 2 diabetic patients. SCAND J MED SCI SPOR. 2014;24(2):e69-76. Karenovics W, Licker M, Ellenberger C, Christodoulou M, Diaper J, Bhatia C, et al. Short-term preoperative exercise therapy does not improve long-term outcome after lung cancer surgery: a randomized controlled study†. EUR J CARDIO-THORAC. 2017;52(1):47–54. Li X. Effect of high-intensity interval training on blood glucose control, adipocytokine secretion and oxidative stress response in patients with T2DM. Journal of Hainan Medical University (English version). 2018;24(5):14–8. Li X, Han T, Zou X, Zhang H, Feng W, Wang H, et al. Long-term high-intensity interval training increases serum neurotrophic factors in elderly overweight and obese Chinese adults. EUR J APPL PHYSIOL. 2021;121(10):2773–85. Ärnlöv J, Ingelsson E, Sundström J, Lind L. Impact of Body Mass Index and the Metabolic Syndrome on the Risk of Cardiovascular Disease and Death in Middle-Aged Men. CIRCULATION. 2010;121(2):230–6. Bhaskaran K, Dos-Santos-Silva I, Leon DA, Douglas IJ, Smeeth L. Association of BMI with overall and cause-specific mortality: a population-based cohort study of 3·6 million adults in the UK. The Lancet Diabetes & Endocrinology. 2018;6(12):944–53. Padwal R, Leslie WD, Lix LM, Majumdar SR. Relationship Among Body Fat Percentage, Body Mass Index, and All-Cause Mortality: A Cohort Study. ANN INTERN MED. 2016;164(8):532–41. Wang Donghai, Yang Shibao, Jie Changfu. The impact of high-intensity interval training on fitness and metabolic disease risk factors in elderly individuals:A Meta Analysis. Journal of Harbin Institute of Physical Education. 2022;40(3):80–9. Dallas KB, Rogo-Gupta L, Elliott CS. What Impacts the All Cause Risk of Reoperation after Pelvic Organ Prolapse Repair? A Comparison of Mesh and Native Tissue Approaches in 110,329 Women. J Urol. 2018;200(2):389–96. Jensen MT, Holtermann A, Bay H, Gyntelberg F. Cardiorespiratory fitness and death from cancer: a 42-year follow-up from the Copenhagen Male Study. BRIT J SPORT MED. 2017;51(18):1364–9. Kodama S, Saito K, Tanaka S, Maki M, Yachi Y, Asumi M, et al. Cardiorespiratory Fitness as a Quantitative Predictor of All-Cause Mortality and Cardiovascular Events in Healthy Men and Women: A Meta-analysis. JAMA: the journal of the American Medical Association. 2009;301(19):2024–35. Carlson DJ, Dieberg G, Hess NC, Millar PJ, Smart NA. Isometric Exercise Training for Blood Pressure Management: A Systematic Review and Meta-analysis. MAYO CLIN PROC. 2014;89(3):327 – 34. Chew NWS, Ng CH, Tan DJH, Kong G, Lin C, Chin YH, et al. The global burden of metabolic disease: Data from 2000 to 2019. CELL METAB. 2023;35(3):414–28. Tables Table 1 is available in the Supplementary Files section. Additional Declarations No competing interests reported. Supplementary Files table.docx Annex1.docx Annex2.docx Cite Share Download PDF Status: Posted Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-4253175","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Article","associatedPublications":[],"authors":[{"id":297553500,"identity":"4da977b7-11f9-4eff-93dd-28c155f07da3","order_by":0,"name":"Jie 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With advancing age, there is a decline in physiological system functionality and an increased susceptibility to stress response [\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e]. At the same time, inadequate physical activity can accelerate the aging process and contribute to adverse outcomes, such as an increased susceptibility to falls, hospitalization, premature mortality, and all-cause mortality[\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e]. It is important to note that while the decline in systemic function among older individuals can be prevented and delayed, it may become irreversible once it manifests as an adverse event. Therefore, in addition to mitigating risk factors for adverse events, greater emphasis should be placed on preventing/delaying the deterioration of systemic functions to achieve healthy aging[\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e]. Copenhagen Consensus Statement 2019 highlights that physical activity is a crucial determinant for maintaining health and the normal functioning of physiological systems [\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e], and it represents one of the primary strategies to delay age-related decline in physical function among older adults [\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e]. Despite its significant role in reducing mortality risk [\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e], cardiovascular disease, and certain cancers [\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e], a majority of elderly individuals refrain from engaging in exercise or leisure physical activities [\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e], due to concerns regarding potential risks associated with exercise. A cross-sectional population study noted that the annual incidence of exercise-related cardiac arrest in the elderly is extremely rare [\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e], which means that the benefits of exercise far outweigh the possible risks.\u003c/p\u003e \u003cp\u003eMore and more studies have demonstrated that exercise can enhance age-related body composition[\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e]、ameliorate dyslipidemia, improve cardiopulmonary function[\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e], prevent the onset of type 2 diabetes, hypertension, cardiovascular disease, and cancer[\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e], as well as reduce overall mortality rates [\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e], The health benefits of exercise have garnered consensus among experts [\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e, \u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e]. Currently, three forms of physical activity exhibit significant potential in promoting the health of older adults. The first category encompasses non-exercise physical activities (low-intensity), such as walking and household chores. Recent evidence unequivocally indicates that low-intensity physical activities also confer health advantages for older adults. The second form is moderate-intensity aerobic exercise, which is supported by substantial evidence establishing a dose-response relationship with health outcomes and recommended by global guidelines[\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e]. However, the intervention duration of aerobic exercise is prolonged and the rhythm is monotonous. The anticipated adherence rate is 27%[\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e], yet the actual adherence rate falls below 5%[\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e]. HIIT presents itself as a promising alternative for promoting health among older adults. Intermittent training incorporates short bursts of high-intensity anaerobic exercise followed by low-intensity aerobic recovery, yielding comparable exercise effects to moderate-intensity aerobic exercise. Moreover, HIIT offers advantages in terms of time efficiency and cost-effectiveness[\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e]. It holds great potential for widespread utilization in elderly health promotion endeavors. Importantly, unlike other pharmacological treatments that solely target a single outcome, exercise typically exerts positive effects on multiple physiological systems[\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e]. Recent studies have demonstrated that engaging in 3 to 4 minutes of HIIT per day can significantly reduce the risk of all-cause and cancer mortality by 38\u0026ndash;40%, as well as decrease the risk of cardiovascular disease (CVD) mortality by 48\u0026ndash;49%[\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e]. Furthermore, numerous meta-analyses have provided support for the role of HIIT in enhancing the health status of older individuals[\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e, \u003cspan additionalcitationids=\"CR22 CR23 CR24 CR25 CR26 CR27 CR28\" citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e]. However, previous investigations on the health benefits of HIIT in older adults possess certain limitations. Firstly, most outcome measures were assessed within a single[\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e, \u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e, \u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e, \u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e, \u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e] or dual[\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e, \u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e, \u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e] physiological system. Secondly, only specific diseases [\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e, \u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e, \u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e], or particular risk factors[\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e, \u003cspan additionalcitationids=\"CR28\" citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e]; were considered. Thirdly ,the majority of studies had small sample sizes and included non-elderly participants within their populations[\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e];Additionally, a meta-analysis encompassing ten studies incorporated six studies from a single research group[\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e]. All these factors inevitably restrict the comprehensive interpretation of the health effects of HIIT in older adults. Furthermore, a significant number of included studies were deemed to be of low quality[\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e, \u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e, \u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e]. While most research findings support the positive health effects of HIIT on elderly individuals, particularly about certain physiological systems, it is important to note that these systematic reviews or meta-analyses primarily focus on specific improvements within individual physiological systems or diseases. Considering that the human body functions as an integrated whole, our emphasis lies in examining the overall health impacts of HIIT and recognizing the essentiality of valid scientific evidence when formulating strategies to address global health issues among older populations.\u003c/p\u003e \u003cp\u003eGiven the above considerations, a systematic review was conducted to evaluate the effects of HIIT on 14 outcomes of body shape, cardiopulmonary function and metabolism in older adults. We also conducted subgroup analysis on the factors that may affect the conclusions, such as study type, intervention period, and disease type, in order to obtain more comprehensive data and provide evidence support for clinical or family health management and the development of HIIT guidelines/recommendations.\u003c/p\u003e"},{"header":"2 Methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e\n \u003ch2\u003e2.1 Search strategy\u003c/h2\u003e\n \u003cp\u003eThe present review adhered to the guidelines of the Preferred Reporting Items for Systematic Reviews and Meta-analyses (PRISMA) [\u003cspan class=\"CitationRef\"\u003e30\u003c/span\u003e]. It was prospectively registered in the International Registry of Prospective Systematic Reviews (PROSPERO) database under registration number \u0026quot;CRD42023460252\u0026quot; on September 5, 2023. The following databases were electronically searched: PubMed, Web of Science, Cochrane Library, Scopus, and WanFang database. A comprehensive search was conducted for RCTs investigating the HIIT on body composition, cardiopulmonary function, and metabolic indicators in older adults. The search period ranged from the inception of each database to July 1, 2023. Additionally, relevant literature and previously published systematic reviews were manually screened to identify any studies missed during the initial search process.\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec4\" class=\"Section2\"\u003e\n \u003ch2\u003e2.2 Inclusion criteria:\u003c/h2\u003e\n \u003cp\u003eTwo researchers independently conducted a comprehensive literature review, eliminating duplicate and irrelevant studies, extracting relevant data, and cross-verifying the selected literature. In case of any discrepancies, they consulted with each other or sought input from a third party for discussion. A screening flow chart is presented in Fig. \u003cspan class=\"InternalRef\"\u003e1\u003c/span\u003e. This meta-analysis included older adults aged\u0026thinsp;\u0026ge;\u0026thinsp;60 years without any restrictions on country, race, or gender except for athletes. The articles in both English and Chinese reported at least one outcome measure, with the intervention being HIIT. The outcome measures included: BMI, BF%, WC, VO\u003csub\u003e2max\u003c/sub\u003e, SBP, DBP, HR\u003csub\u003erest\u003c/sub\u003e, HR\u003csub\u003emax\u003c/sub\u003e, RER, TC, TG, HDL, LDL and FPG.\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec5\" class=\"Section2\"\u003e\n \u003ch2\u003e2.3 Data extraction\u003c/h2\u003e\n \u003cp\u003eThe data extraction encompassed the following components: basic information of the included literature (first author\u0026apos;s name, title, publication year), characteristics of study subjects (age, gender, number of subjects), training variables (intensity, form, frequency, intervention period), main results and key elements of risk of bias assessment. To calculate effect sizes for physical fitness measures in the intervention and control groups, baseline and follow-up mean as well as standard deviations were extracted. In case any required data were missing, we contacted the corresponding author to obtain them. If relevant data could not be provided by the author, they were excluded from the analysis. The characteristics of the included studies are presented in Table \u003cspan class=\"InternalRef\"\u003e1\u003c/span\u003e.\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec6\" class=\"Section2\"\u003e\n \u003ch2\u003e2.4 Biased risk assessment\u003c/h2\u003e\n \u003cp\u003eRCTs were analyzed using the Cochrane Risk of Bias Tool 2.0. [\u003cspan class=\"CitationRef\"\u003e31\u003c/span\u003e]. There are three levels: low-risk, high-risk and uncertain. \u0026quot;It involves the method of randomization, the concealment of randomization, the blinding of participants and interveners, the blinding of outcome raters, the completeness of outcome data, the possibility of selective reporting, and other sources of bias.\u0026quot; For non-randomised controlled trials, the Risk of bias in non-randomised Intervention Studies (ROBINS-I) was used. The ROBINS-I considers bias from seven domains, classified by time of occurrence: pre-intervention (confusion, selection of study participants), intervention (classification of intervention) and post-intervention (deviation from intended intervention, missing outcome data, measurement of outcome and selection of reported outcome). The risk of biased judgment in each domain was interpreted as low risk, moderate risk, severe risk, borderline risk, or no information. [\u003cspan class=\"CitationRef\"\u003e32\u003c/span\u003e] Two reviewers independently assessed the risk of bias, and any disagreements were resolved through a third party. In addition, the risk of publication bias was assessed using funnel plots when the meta-analysis included\u0026thinsp;\u0026ge;\u0026thinsp;10 studies.\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec7\" class=\"Section2\"\u003e\n \u003ch2\u003e2.5 Statistical Analysis\u003c/h2\u003e\n \u003cp\u003eReview Manager 5.3 (RevMan) software was used for statistical analysis. mean difference (MD) was used as the effect analysis statistic, and 95% confidence interval (CI) was provided for each effect size. \u003cem\u003eI\u003c/em\u003e\u003csup\u003e2\u003c/sup\u003e was used to evaluate the degree of heterogeneity: above 25%,50% and 75% were low, medium and high heterogeneity respectively[\u003cspan class=\"CitationRef\"\u003e33\u003c/span\u003e], and the level of meta-analysis was set as \u0026alpha;\u0026thinsp;=\u0026thinsp;0.05. When \u003cem\u003eI\u003c/em\u003e\u003csup\u003e2\u003c/sup\u003e\u0026thinsp;\u0026le;\u0026thinsp;25%, the fixed effect model was used for combined analysis. If \u003cem\u003eI\u003c/em\u003e\u003csup\u003e2\u003c/sup\u003e\u0026gt;25%, the random effects model was used for combined analysis. To increase the stability of the results, sensitivity analysis was performed by eliminating one by one. Publication bias was assessed using funnel plots. Subgroup analysis was performed when \u003cem\u003eI\u003c/em\u003e\u003csup\u003e2\u003c/sup\u003e\u0026thinsp;\u0026ge;\u0026thinsp;50%. The analysis factors included study type (RCT vs. non-RCT), intervention duration (\u0026le;\u0026thinsp;1\u003csup\u003e2\u003c/sup\u003e weeks vs. \u0026gt; 12 weeks), and disease type (cardiovascular disease, diabetes, hypertension, cancer, and others). Further analysis was performed when more than 5 studies were included in the subgroup.\u003c/p\u003e\n\u003c/div\u003e"},{"header":"3 Result","content":"\u003cdiv id=\"Sec9\" class=\"Section2\"\u003e \u003ch2\u003e3.1 Study Selection\u003c/h2\u003e \u003cp\u003eFigure\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e describes the PRISMA process in detail. A total of 2278 studies were retrieved from the database, and 7 studies were obtained from other sources. After the strict screening, 92[\u003cspan additionalcitationids=\"CR29 CR30 CR31 CR32 CR33 CR34 CR35 CR36 CR37 CR38 CR39 CR40 CR41 CR42 CR43 CR44 CR45 CR46 CR47 CR48 CR49 CR50 CR51 CR52 CR53 CR54 CR55 CR56 CR57 CR58 CR59 CR60 CR61 CR62 CR63 CR64 CR65 CR66 CR67 CR68 CR69 CR70 CR71 CR72 CR73 CR74 CR75 CR76 CR77 CR78 CR79 CR80 CR81 CR82 CR83 CR84 CR85 CR86 CR87 CR88 CR89 CR90 CR91 CR92 CR93 CR94 CR95 CR96 CR97 CR98 CR99 CR100 CR101 CR102 CR103 CR104 CR105 CR106 CR107 CR108 CR109 CR110 CR111 CR112 CR113 CR114 CR115 CR116 CR117 CR118\" citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR119\" class=\"CitationRef\"\u003e119\u003c/span\u003e] studies were finally included, of which 87 met the criteria of RCTs and 5 met the criteria of non-RCTs, with a total of 4355 elderly people, including 2174 in the HIIT group and 2181 in the control group. Exercise frequency, duration, cycle, and outcome measures were reported. Figure\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e2\u003c/span\u003e shows the geographical and sample distribution of the included studies. 66.29% of the studies are in Europe, 14.14% in North America and South America,13.78% in Asia, 4.87% in Australia and 0.92% in Africa, involving 21 countries and regions. Of these, 658 were from Norway, 543 from Switzerland, 537 from Belgium, 280 from Denmark, 211 from Spain, 200 from the United Kingdom, 148 from Sweden, 144 from Germany, 140 from Italy, 26 from France, 244 from Canada, 222 from the United States, 150 from Brazil, 254 from China, 133 from Iran, 88 from Japan and 72 from South Korea People, 29 from Thailand, 24 from Indonesia, 212 from Australia and 40 from Egypt, a total of 4,355.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eTDOAIS\u0026thinsp;=\u0026thinsp;The degree of ageing is serious. TDOAIRH\u0026thinsp;=\u0026thinsp;The degree of ageing is relatively heavy. TDOAIM\u0026thinsp;=\u0026thinsp;The degree of ageing is moderate. TDOAIL\u0026thinsp;=\u0026thinsp;The degree of ageing is low; *When the disease mark appears in a certain area, it means that the subjects included in the area have the disease or are in a healthy state.; The proportion of the elderly population: TDOAIS\u0026thinsp;\u0026gt;\u0026thinsp;17.91 17.91\u0026thinsp;\u0026gt;\u0026thinsp;TDOAIRH\u0026thinsp;\u0026gt;\u0026thinsp;13.15 13.15\u0026thinsp;\u0026gt;\u0026thinsp;TDOAIM\u0026thinsp;\u0026gt;\u0026thinsp;9.02 TDOAIL\u0026thinsp;\u0026lt;\u0026thinsp;9.02\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec10\" class=\"Section2\"\u003e \u003ch2\u003e3.2 Quality assessment of included studies\u003c/h2\u003e \u003cp\u003eA total of 87 RCTs and 5 non-RCTs were included, and the overall risk of bias was low. Of these RCTs: 84/87 evaluated using randomized sequence generation; 84/87 assessments used allocation concealment; 77/87 subjects and staff were blinded; 77/87 were blinded to the outcome data evaluation; 84/87 had complete data; 86/87 no selectivity was reported; 39/87 had no other bias Among the included non-RCTs: 5/5Confounding;4/5Selection of participants;5/5Classification of intervention;5/5Missing data;0/5Measurement of the outcome;5/5Selection of reported result;5/5Overall risk of bias. (The results are shown in Annex 1)\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec11\" class=\"Section2\"\u003e \u003ch2\u003e3.3 Meta-analysis result\u003c/h2\u003e \u003cdiv id=\"Sec12\" class=\"Section3\"\u003e \u003ch2\u003e3.3.1 Body morphology indicators\u003c/h2\u003e \u003cp\u003e \u003cb\u003eBMI\u003c/b\u003e A total of 32[\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e, \u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e, \u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e38\u003c/span\u003e, \u003cspan citationid=\"CR46\" class=\"CitationRef\"\u003e46\u003c/span\u003e, \u003cspan additionalcitationids=\"CR50 CR51 CR52\" citationid=\"CR49\" class=\"CitationRef\"\u003e49\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR53\" class=\"CitationRef\"\u003e53\u003c/span\u003e, \u003cspan citationid=\"CR58\" class=\"CitationRef\"\u003e58\u003c/span\u003e, \u003cspan additionalcitationids=\"CR68\" citationid=\"CR67\" class=\"CitationRef\"\u003e67\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR69\" class=\"CitationRef\"\u003e69\u003c/span\u003e, \u003cspan citationid=\"CR72\" class=\"CitationRef\"\u003e72\u003c/span\u003e, \u003cspan citationid=\"CR75\" class=\"CitationRef\"\u003e75\u003c/span\u003e, \u003cspan additionalcitationids=\"CR79\" citationid=\"CR78\" class=\"CitationRef\"\u003e78\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR80\" class=\"CitationRef\"\u003e80\u003c/span\u003e, \u003cspan citationid=\"CR86\" class=\"CitationRef\"\u003e86\u003c/span\u003e, \u003cspan citationid=\"CR87\" class=\"CitationRef\"\u003e87\u003c/span\u003e, \u003cspan citationid=\"CR95\" class=\"CitationRef\"\u003e95\u003c/span\u003e, \u003cspan citationid=\"CR99\" class=\"CitationRef\"\u003e99\u003c/span\u003e, \u003cspan citationid=\"CR103\" class=\"CitationRef\"\u003e103\u003c/span\u003e, \u003cspan citationid=\"CR104\" class=\"CitationRef\"\u003e104\u003c/span\u003e, \u003cspan citationid=\"CR106\" class=\"CitationRef\"\u003e106\u003c/span\u003e, \u003cspan citationid=\"CR107\" class=\"CitationRef\"\u003e107\u003c/span\u003e, \u003cspan citationid=\"CR111\" class=\"CitationRef\"\u003e111\u003c/span\u003e, \u003cspan citationid=\"CR115\" class=\"CitationRef\"\u003e115\u003c/span\u003e, \u003cspan citationid=\"CR117\" class=\"CitationRef\"\u003e117\u003c/span\u003e, \u003cspan citationid=\"CR119\" class=\"CitationRef\"\u003e119\u003c/span\u003e, \u003cspan citationid=\"CR122\" class=\"CitationRef\"\u003e122\u003c/span\u003e, \u003cspan citationid=\"CR125\" class=\"CitationRef\"\u003e125\u003c/span\u003e] studies were included, including 27 RCTs and 5 non-RCTs. Compared with the control group, HIIT significantly improved BMI in the elderly (MD: -0.38kg m\u003csup\u003e\u0026minus;\u0026thinsp;2\u003c/sup\u003e, P\u0026thinsp;=\u0026thinsp;0.01), but there was statistical heterogeneity (I\u003csup\u003e2\u003c/sup\u003e\u0026thinsp;=\u0026thinsp;64%) (see Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e4\u003c/span\u003e). Sensitivity analysis showed that the results of this study were robust. Funnel plots were basically symmetric, and there was no evidence of publication bias. Differences between subgroups suggest that disease type may be a source of heterogeneity (P\u0026thinsp;\u0026lt;\u0026thinsp;0.0001). (The results of subgroup analysis and funnel plot are shown in Annex 2)\u003c/p\u003e \u003cp\u003e \u003cb\u003eBF%\u003c/b\u003eA total of 20 [\u003cspan citationid=\"CR46\" class=\"CitationRef\"\u003e46\u003c/span\u003e, \u003cspan citationid=\"CR53\" class=\"CitationRef\"\u003e53\u003c/span\u003e, \u003cspan citationid=\"CR58\" class=\"CitationRef\"\u003e58\u003c/span\u003e, \u003cspan citationid=\"CR70\" class=\"CitationRef\"\u003e70\u003c/span\u003e, \u003cspan citationid=\"CR72\" class=\"CitationRef\"\u003e72\u003c/span\u003e, \u003cspan citationid=\"CR73\" class=\"CitationRef\"\u003e73\u003c/span\u003e, \u003cspan citationid=\"CR75\" class=\"CitationRef\"\u003e75\u003c/span\u003e, \u003cspan citationid=\"CR79\" class=\"CitationRef\"\u003e79\u003c/span\u003e, \u003cspan citationid=\"CR84\" class=\"CitationRef\"\u003e84\u003c/span\u003e, \u003cspan citationid=\"CR87\" class=\"CitationRef\"\u003e87\u003c/span\u003e, \u003cspan citationid=\"CR97\" class=\"CitationRef\"\u003e97\u003c/span\u003e, \u003cspan citationid=\"CR99\" class=\"CitationRef\"\u003e99\u003c/span\u003e, \u003cspan citationid=\"CR100\" class=\"CitationRef\"\u003e100\u003c/span\u003e, \u003cspan citationid=\"CR104\" class=\"CitationRef\"\u003e104\u003c/span\u003e, \u003cspan citationid=\"CR107\" class=\"CitationRef\"\u003e107\u003c/span\u003e, \u003cspan citationid=\"CR111\" class=\"CitationRef\"\u003e111\u003c/span\u003e, \u003cspan citationid=\"CR115\" class=\"CitationRef\"\u003e115\u003c/span\u003e, \u003cspan citationid=\"CR121\" class=\"CitationRef\"\u003e121\u003c/span\u003e, \u003cspan citationid=\"CR122\" class=\"CitationRef\"\u003e122\u003c/span\u003e, \u003cspan citationid=\"CR125\" class=\"CitationRef\"\u003e125\u003c/span\u003e] studies were included, including 16 RCTS and 4 non-RCTs. Compared with the control group, HIIT significantly improved BF% (MD: -1.38%, P\u0026thinsp;\u0026lt;\u0026thinsp;0.00001) in the elderly, without significant heterogeneity (I\u003csup\u003e2\u003c/sup\u003e\u0026thinsp;=\u0026thinsp;23%) (see Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e4\u003c/span\u003e). Sensitivity analysis showed that the results of this study were robust. Funnel plots were basically symmetric, and there was no evidence of publication bias. (See Annex 2 for funnel diagram)\u003c/p\u003e \u003cp\u003e \u003cb\u003eWC\u003c/b\u003e A total of 18[\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e, \u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e38\u003c/span\u003e, \u003cspan citationid=\"CR46\" class=\"CitationRef\"\u003e46\u003c/span\u003e, \u003cspan citationid=\"CR51\" class=\"CitationRef\"\u003e51\u003c/span\u003e, \u003cspan citationid=\"CR58\" class=\"CitationRef\"\u003e58\u003c/span\u003e, \u003cspan citationid=\"CR68\" class=\"CitationRef\"\u003e68\u003c/span\u003e, \u003cspan citationid=\"CR72\" class=\"CitationRef\"\u003e72\u003c/span\u003e, \u003cspan citationid=\"CR73\" class=\"CitationRef\"\u003e73\u003c/span\u003e, \u003cspan citationid=\"CR78\" class=\"CitationRef\"\u003e78\u003c/span\u003e, \u003cspan citationid=\"CR79\" class=\"CitationRef\"\u003e79\u003c/span\u003e, \u003cspan citationid=\"CR84\" class=\"CitationRef\"\u003e84\u003c/span\u003e, \u003cspan citationid=\"CR88\" class=\"CitationRef\"\u003e88\u003c/span\u003e, \u003cspan citationid=\"CR97\" class=\"CitationRef\"\u003e97\u003c/span\u003e, \u003cspan citationid=\"CR99\" class=\"CitationRef\"\u003e99\u003c/span\u003e, \u003cspan citationid=\"CR100\" class=\"CitationRef\"\u003e100\u003c/span\u003e, \u003cspan citationid=\"CR104\" class=\"CitationRef\"\u003e104\u003c/span\u003e, \u003cspan citationid=\"CR115\" class=\"CitationRef\"\u003e115\u003c/span\u003e, \u003cspan citationid=\"CR119\" class=\"CitationRef\"\u003e119\u003c/span\u003e] studies were included, including16 RCTs and 2 non-RCTs, Compared with the control group, HIIT had no significant effect on WC in the elderly (MD:-1.54cm, P\u0026thinsp;=\u0026thinsp;0.16), but there was statistical heterogeneity (I\u003csup\u003e2\u003c/sup\u003e\u0026thinsp;=\u0026thinsp;76%) (see Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e4\u003c/span\u003e). After excluding the study by TJ\u0026Oslash;NNA AE et al.[\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e], I\u003csup\u003e2\u003c/sup\u003e decreased to 39%, which was not statistically significant (MD: -0.38cm, P\u0026thinsp;=\u0026thinsp;0.60). After excluding the study by Eeik Madssen et al.[\u003cspan citationid=\"CR51\" class=\"CitationRef\"\u003e51\u003c/span\u003e], there was no significant change in I\u003csup\u003e2\u003c/sup\u003e, but HIIT significantly improved WC in the elderly (MD: -2.13cm, P\u0026thinsp;=\u0026thinsp;0.04). Sensitivity analysis suggested that the results were not robust. Funnel plots were basically symmetric, and there was no evidence of publication bias. (See Annex 2 for funnel diagram)\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec13\" class=\"Section3\"\u003e \u003ch2\u003e3.3.2 Cardiopulmonary function indicators\u003c/h2\u003e \u003cp\u003e \u003cb\u003eVO2\u003c/b\u003e \u003csub\u003e \u003cb\u003emax\u003c/b\u003e \u003c/sub\u003e A total of 60[\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e, \u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e, \u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e, \u003cspan additionalcitationids=\"CR34 CR35\" citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e, \u003cspan additionalcitationids=\"CR39 CR40 CR41 CR42 CR43\" citationid=\"CR38\" class=\"CitationRef\"\u003e38\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e44\u003c/span\u003e, \u003cspan citationid=\"CR46\" class=\"CitationRef\"\u003e46\u003c/span\u003e, \u003cspan citationid=\"CR47\" class=\"CitationRef\"\u003e47\u003c/span\u003e, \u003cspan additionalcitationids=\"CR51 CR52 CR53 CR54 CR55 CR56 CR57 CR58 CR59 CR60\" citationid=\"CR50\" class=\"CitationRef\"\u003e50\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR61\" class=\"CitationRef\"\u003e61\u003c/span\u003e, \u003cspan additionalcitationids=\"CR64 CR65 CR66\" citationid=\"CR63\" class=\"CitationRef\"\u003e63\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR67\" class=\"CitationRef\"\u003e67\u003c/span\u003e, \u003cspan additionalcitationids=\"CR70\" citationid=\"CR69\" class=\"CitationRef\"\u003e69\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR71\" class=\"CitationRef\"\u003e71\u003c/span\u003e, \u003cspan additionalcitationids=\"CR74\" citationid=\"CR73\" class=\"CitationRef\"\u003e73\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR75\" class=\"CitationRef\"\u003e75\u003c/span\u003e, \u003cspan citationid=\"CR78\" class=\"CitationRef\"\u003e78\u003c/span\u003e, \u003cspan additionalcitationids=\"CR82\" citationid=\"CR81\" class=\"CitationRef\"\u003e81\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR83\" class=\"CitationRef\"\u003e83\u003c/span\u003e, \u003cspan citationid=\"CR87\" class=\"CitationRef\"\u003e87\u003c/span\u003e, \u003cspan citationid=\"CR88\" class=\"CitationRef\"\u003e88\u003c/span\u003e, \u003cspan citationid=\"CR92\" class=\"CitationRef\"\u003e92\u003c/span\u003e, \u003cspan citationid=\"CR94\" class=\"CitationRef\"\u003e94\u003c/span\u003e, \u003cspan citationid=\"CR95\" class=\"CitationRef\"\u003e95\u003c/span\u003e, \u003cspan citationid=\"CR98\" class=\"CitationRef\"\u003e98\u003c/span\u003e, \u003cspan citationid=\"CR101\" class=\"CitationRef\"\u003e101\u003c/span\u003e, \u003cspan citationid=\"CR102\" class=\"CitationRef\"\u003e102\u003c/span\u003e, \u003cspan citationid=\"CR106\" class=\"CitationRef\"\u003e106\u003c/span\u003e, \u003cspan citationid=\"CR111\" class=\"CitationRef\"\u003e111\u003c/span\u003e, \u003cspan citationid=\"CR113\" class=\"CitationRef\"\u003e113\u003c/span\u003e, \u003cspan citationid=\"CR116\" class=\"CitationRef\"\u003e116\u003c/span\u003e, \u003cspan citationid=\"CR117\" class=\"CitationRef\"\u003e117\u003c/span\u003e, \u003cspan citationid=\"CR119\" class=\"CitationRef\"\u003e119\u003c/span\u003e] studies were included, including 56 RCTs,4 non-RCTs, Compared with the control group, HIIT had a significant effect on VO2max in the elderly (MD:2.23ml min\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003ekg\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e, P\u0026thinsp;\u0026lt;\u0026thinsp;0.00001), but there was statistical heterogeneity (I\u003csup\u003e2\u003c/sup\u003e\u0026thinsp;=\u0026thinsp;82%) (see Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e4\u003c/span\u003e). Sensitivity analysis results suggested that the results of this study were robust. Funnel plots were basically symmetric, and there was no evidence of publication bias. Subgroup analysis showed that HIIT had a significant improvement in both the healthy and the sick elderly (P\u0026thinsp;\u0026lt;\u0026thinsp;0.00001), but the improvement was greater in the sick elderly. There was no significant difference between subgroups (P\u0026thinsp;\u0026gt;\u0026thinsp;0.05). (The results of subgroup analysis and funnel plot are shown in Annex 2)\u003c/p\u003e \u003cp\u003e \u003cb\u003eSBP\u003c/b\u003e A total of 43[\u003cspan additionalcitationids=\"CR35\" citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e, \u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e38\u003c/span\u003e, \u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e40\u003c/span\u003e, \u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e42\u003c/span\u003e, \u003cspan citationid=\"CR46\" class=\"CitationRef\"\u003e46\u003c/span\u003e, \u003cspan citationid=\"CR51\" class=\"CitationRef\"\u003e51\u003c/span\u003e, \u003cspan citationid=\"CR54\" class=\"CitationRef\"\u003e54\u003c/span\u003e, \u003cspan citationid=\"CR57\" class=\"CitationRef\"\u003e57\u003c/span\u003e, \u003cspan citationid=\"CR58\" class=\"CitationRef\"\u003e58\u003c/span\u003e, \u003cspan citationid=\"CR62\" class=\"CitationRef\"\u003e62\u003c/span\u003e, \u003cspan citationid=\"CR65\" class=\"CitationRef\"\u003e65\u003c/span\u003e, \u003cspan citationid=\"CR68\" class=\"CitationRef\"\u003e68\u003c/span\u003e, \u003cspan citationid=\"CR69\" class=\"CitationRef\"\u003e69\u003c/span\u003e, \u003cspan citationid=\"CR72\" class=\"CitationRef\"\u003e72\u003c/span\u003e, \u003cspan citationid=\"CR73\" class=\"CitationRef\"\u003e73\u003c/span\u003e, \u003cspan additionalcitationids=\"CR80\" citationid=\"CR79\" class=\"CitationRef\"\u003e79\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR81\" class=\"CitationRef\"\u003e81\u003c/span\u003e, \u003cspan citationid=\"CR84\" class=\"CitationRef\"\u003e84\u003c/span\u003e, \u003cspan citationid=\"CR86\" class=\"CitationRef\"\u003e86\u003c/span\u003e, \u003cspan citationid=\"CR87\" class=\"CitationRef\"\u003e87\u003c/span\u003e, \u003cspan citationid=\"CR89\" class=\"CitationRef\"\u003e89\u003c/span\u003e, \u003cspan citationid=\"CR91\" class=\"CitationRef\"\u003e91\u003c/span\u003e, \u003cspan additionalcitationids=\"CR94\" citationid=\"CR93\" class=\"CitationRef\"\u003e93\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR95\" class=\"CitationRef\"\u003e95\u003c/span\u003e, \u003cspan citationid=\"CR98\" class=\"CitationRef\"\u003e98\u003c/span\u003e, \u003cspan citationid=\"CR99\" class=\"CitationRef\"\u003e99\u003c/span\u003e, \u003cspan additionalcitationids=\"CR103 CR104 CR105 CR106 CR107\" citationid=\"CR102\" class=\"CitationRef\"\u003e102\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR108\" class=\"CitationRef\"\u003e108\u003c/span\u003e, \u003cspan citationid=\"CR116\" class=\"CitationRef\"\u003e116\u003c/span\u003e, \u003cspan citationid=\"CR119\" class=\"CitationRef\"\u003e119\u003c/span\u003e, \u003cspan citationid=\"CR121\" class=\"CitationRef\"\u003e121\u003c/span\u003e, \u003cspan citationid=\"CR122\" class=\"CitationRef\"\u003e122\u003c/span\u003e] studies were included, including 38 RCTs and 5 non-RCTs. Compared with the control group, HIIT had no significant effect on SBP in the elderly (MD: -0.28mmHg, P\u0026thinsp;=\u0026thinsp;0.75) (see Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e4\u003c/span\u003e). Sensitivity analyses suggested that the results were robust. Funnel plots were basically symmetric, and there was no evidence of publication bias. (See Annex 2 for funnel diagram)\u003c/p\u003e \u003cp\u003e \u003cb\u003eDBP\u003c/b\u003e A total of 43[\u003cspan additionalcitationids=\"CR35\" citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e, \u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e38\u003c/span\u003e, \u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e40\u003c/span\u003e, \u003cspan citationid=\"CR46\" class=\"CitationRef\"\u003e46\u003c/span\u003e, \u003cspan citationid=\"CR51\" class=\"CitationRef\"\u003e51\u003c/span\u003e, \u003cspan citationid=\"CR54\" class=\"CitationRef\"\u003e54\u003c/span\u003e, \u003cspan citationid=\"CR57\" class=\"CitationRef\"\u003e57\u003c/span\u003e, \u003cspan citationid=\"CR58\" class=\"CitationRef\"\u003e58\u003c/span\u003e, \u003cspan citationid=\"CR62\" class=\"CitationRef\"\u003e62\u003c/span\u003e, \u003cspan citationid=\"CR65\" class=\"CitationRef\"\u003e65\u003c/span\u003e, \u003cspan citationid=\"CR69\" class=\"CitationRef\"\u003e69\u003c/span\u003e, \u003cspan citationid=\"CR72\" class=\"CitationRef\"\u003e72\u003c/span\u003e, \u003cspan citationid=\"CR73\" class=\"CitationRef\"\u003e73\u003c/span\u003e, \u003cspan citationid=\"CR79\" class=\"CitationRef\"\u003e79\u003c/span\u003e, \u003cspan citationid=\"CR80\" class=\"CitationRef\"\u003e80\u003c/span\u003e, \u003cspan additionalcitationids=\"CR85 CR86\" citationid=\"CR84\" class=\"CitationRef\"\u003e84\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR87\" class=\"CitationRef\"\u003e87\u003c/span\u003e, \u003cspan citationid=\"CR89\" class=\"CitationRef\"\u003e89\u003c/span\u003e, \u003cspan citationid=\"CR91\" class=\"CitationRef\"\u003e91\u003c/span\u003e, \u003cspan additionalcitationids=\"CR94\" citationid=\"CR93\" class=\"CitationRef\"\u003e93\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR95\" class=\"CitationRef\"\u003e95\u003c/span\u003e, \u003cspan citationid=\"CR98\" class=\"CitationRef\"\u003e98\u003c/span\u003e, \u003cspan citationid=\"CR99\" class=\"CitationRef\"\u003e99\u003c/span\u003e, \u003cspan additionalcitationids=\"CR102 CR103 CR104 CR105 CR106 CR107\" citationid=\"CR101\" class=\"CitationRef\"\u003e101\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR108\" class=\"CitationRef\"\u003e108\u003c/span\u003e, \u003cspan citationid=\"CR116\" class=\"CitationRef\"\u003e116\u003c/span\u003e, \u003cspan citationid=\"CR119\" class=\"CitationRef\"\u003e119\u003c/span\u003e, \u003cspan citationid=\"CR121\" class=\"CitationRef\"\u003e121\u003c/span\u003e, \u003cspan citationid=\"CR122\" class=\"CitationRef\"\u003e122\u003c/span\u003e] studies were included, including 38 RCTs and 5 non-RCTs. Compared with the control group, HIIT had no significant effect on DBP in the elderly (MD: -0.83mmHg, P\u0026thinsp;=\u0026thinsp;0.06) (see Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e4\u003c/span\u003e). After excluding the study by Fernandes B et al. [\u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e40\u003c/span\u003e], there was no significant change in I\u003csup\u003e2\u003c/sup\u003e, but it significantly improved DBP in the elderly (MD: -0.96 mmHg, P\u0026thinsp;=\u0026thinsp;0.03). Sensitivity analysis suggested that the results were not robust. Funnel plots were basically symmetric, and there was no evidence of publication bias. (See Annex 2 for funnel diagram)\u003c/p\u003e \u003cp\u003e \u003cb\u003eHR\u003c/b\u003e \u003csub\u003e \u003cb\u003erest\u003c/b\u003e \u003c/sub\u003e A total of 29[\u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e, \u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e39\u003c/span\u003e, \u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e40\u003c/span\u003e, \u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e43\u003c/span\u003e, \u003cspan citationid=\"CR46\" class=\"CitationRef\"\u003e46\u003c/span\u003e, \u003cspan citationid=\"CR51\" class=\"CitationRef\"\u003e51\u003c/span\u003e, \u003cspan citationid=\"CR64\" class=\"CitationRef\"\u003e64\u003c/span\u003e, \u003cspan citationid=\"CR65\" class=\"CitationRef\"\u003e65\u003c/span\u003e, \u003cspan citationid=\"CR72\" class=\"CitationRef\"\u003e72\u003c/span\u003e, \u003cspan citationid=\"CR73\" class=\"CitationRef\"\u003e73\u003c/span\u003e, \u003cspan additionalcitationids=\"CR81\" citationid=\"CR80\" class=\"CitationRef\"\u003e80\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR82\" class=\"CitationRef\"\u003e82\u003c/span\u003e, \u003cspan additionalcitationids=\"CR85\" citationid=\"CR84\" class=\"CitationRef\"\u003e84\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR86\" class=\"CitationRef\"\u003e86\u003c/span\u003e, \u003cspan citationid=\"CR88\" class=\"CitationRef\"\u003e88\u003c/span\u003e, \u003cspan citationid=\"CR91\" class=\"CitationRef\"\u003e91\u003c/span\u003e, \u003cspan additionalcitationids=\"CR94\" citationid=\"CR93\" class=\"CitationRef\"\u003e93\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR95\" class=\"CitationRef\"\u003e95\u003c/span\u003e, \u003cspan citationid=\"CR98\" class=\"CitationRef\"\u003e98\u003c/span\u003e, \u003cspan citationid=\"CR104\" class=\"CitationRef\"\u003e104\u003c/span\u003e, \u003cspan citationid=\"CR105\" class=\"CitationRef\"\u003e105\u003c/span\u003e, \u003cspan citationid=\"CR112\" class=\"CitationRef\"\u003e112\u003c/span\u003e, \u003cspan citationid=\"CR114\" class=\"CitationRef\"\u003e114\u003c/span\u003e, \u003cspan citationid=\"CR119\" class=\"CitationRef\"\u003e119\u003c/span\u003e, \u003cspan citationid=\"CR121\" class=\"CitationRef\"\u003e121\u003c/span\u003e, \u003cspan citationid=\"CR122\" class=\"CitationRef\"\u003e122\u003c/span\u003e] studies were included, including 27 RCTs and 2 non-RCTs. Compared with the control group, HIIT had no significant effect on HRrest in the elderly (MD: -0.95 BPM \u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e, P\u0026thinsp;=\u0026thinsp;0.24) (see Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e4\u003c/span\u003e). Sensitivity analyses suggested that the results were robust. Funnel plots were basically symmetric, and there was no evidence of publication bias. (See Annex 2 for funnel diagram)\u003c/p\u003e \u003cp\u003e \u003cb\u003eHR\u003c/b\u003e \u003csub\u003e \u003cb\u003emax\u003c/b\u003e \u003c/sub\u003e A total of 40[\u003cspan additionalcitationids=\"CR35\" citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e, \u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e39\u003c/span\u003e, \u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e42\u003c/span\u003e, \u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e43\u003c/span\u003e, \u003cspan citationid=\"CR46\" class=\"CitationRef\"\u003e46\u003c/span\u003e, \u003cspan citationid=\"CR47\" class=\"CitationRef\"\u003e47\u003c/span\u003e, \u003cspan citationid=\"CR49\" class=\"CitationRef\"\u003e49\u003c/span\u003e, \u003cspan citationid=\"CR51\" class=\"CitationRef\"\u003e51\u003c/span\u003e, \u003cspan citationid=\"CR52\" class=\"CitationRef\"\u003e52\u003c/span\u003e, \u003cspan citationid=\"CR55\" class=\"CitationRef\"\u003e55\u003c/span\u003e, \u003cspan citationid=\"CR62\" class=\"CitationRef\"\u003e62\u003c/span\u003e, \u003cspan citationid=\"CR64\" class=\"CitationRef\"\u003e64\u003c/span\u003e, \u003cspan citationid=\"CR65\" class=\"CitationRef\"\u003e65\u003c/span\u003e, \u003cspan citationid=\"CR69\" class=\"CitationRef\"\u003e69\u003c/span\u003e, \u003cspan citationid=\"CR73\" class=\"CitationRef\"\u003e73\u003c/span\u003e, \u003cspan additionalcitationids=\"CR81 CR82\" citationid=\"CR80\" class=\"CitationRef\"\u003e80\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR83\" class=\"CitationRef\"\u003e83\u003c/span\u003e, \u003cspan citationid=\"CR85\" class=\"CitationRef\"\u003e85\u003c/span\u003e, \u003cspan citationid=\"CR90\" class=\"CitationRef\"\u003e90\u003c/span\u003e, \u003cspan citationid=\"CR91\" class=\"CitationRef\"\u003e91\u003c/span\u003e, \u003cspan citationid=\"CR93\" class=\"CitationRef\"\u003e93\u003c/span\u003e, \u003cspan citationid=\"CR95\" class=\"CitationRef\"\u003e95\u003c/span\u003e, \u003cspan citationid=\"CR96\" class=\"CitationRef\"\u003e96\u003c/span\u003e, \u003cspan citationid=\"CR98\" class=\"CitationRef\"\u003e98\u003c/span\u003e, \u003cspan citationid=\"CR102\" class=\"CitationRef\"\u003e102\u003c/span\u003e, \u003cspan additionalcitationids=\"CR105\" citationid=\"CR104\" class=\"CitationRef\"\u003e104\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR106\" class=\"CitationRef\"\u003e106\u003c/span\u003e, \u003cspan citationid=\"CR109\" class=\"CitationRef\"\u003e109\u003c/span\u003e, \u003cspan additionalcitationids=\"CR113\" citationid=\"CR112\" class=\"CitationRef\"\u003e112\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR114\" class=\"CitationRef\"\u003e114\u003c/span\u003e, \u003cspan citationid=\"CR116\" class=\"CitationRef\"\u003e116\u003c/span\u003e, \u003cspan additionalcitationids=\"CR119\" citationid=\"CR118\" class=\"CitationRef\"\u003e118\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR120\" class=\"CitationRef\"\u003e120\u003c/span\u003e] studies were included, including 39 RCTs and 1 non-RCTs. Compared with the control group, HIIT significantly improved HRmax in the elderly (MD:2.84 BPM \u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e, P\u0026thinsp;=\u0026thinsp;0.02), but there was statistical heterogeneity (I\u003csup\u003e2\u003c/sup\u003e\u0026thinsp;=\u0026thinsp;79%) (see Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e4\u003c/span\u003e). Sensitivity analyses suggested that the results were robust. Funnel plots were basically symmetric, and there was no evidence of publication bias. Differences between subgroups suggest that disease type may be a source of heterogeneity (P\u0026thinsp;\u0026lt;\u0026thinsp;0.0001). (The results of subgroup analysis and funnel plot are shown in Annex 2)\u003c/p\u003e \u003cp\u003e \u003cb\u003eRER\u003c/b\u003e A total of 26[\u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e42\u003c/span\u003e, \u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e43\u003c/span\u003e, \u003cspan citationid=\"CR46\" class=\"CitationRef\"\u003e46\u003c/span\u003e, \u003cspan citationid=\"CR52\" class=\"CitationRef\"\u003e52\u003c/span\u003e, \u003cspan citationid=\"CR55\" class=\"CitationRef\"\u003e55\u003c/span\u003e, \u003cspan citationid=\"CR62\" class=\"CitationRef\"\u003e62\u003c/span\u003e, \u003cspan citationid=\"CR63\" class=\"CitationRef\"\u003e63\u003c/span\u003e, \u003cspan citationid=\"CR77\" class=\"CitationRef\"\u003e77\u003c/span\u003e, \u003cspan additionalcitationids=\"CR82\" citationid=\"CR81\" class=\"CitationRef\"\u003e81\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR83\" class=\"CitationRef\"\u003e83\u003c/span\u003e, \u003cspan citationid=\"CR90\" class=\"CitationRef\"\u003e90\u003c/span\u003e, \u003cspan citationid=\"CR106\" class=\"CitationRef\"\u003e106\u003c/span\u003e, \u003cspan additionalcitationids=\"CR113\" citationid=\"CR112\" class=\"CitationRef\"\u003e112\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR114\" class=\"CitationRef\"\u003e114\u003c/span\u003e, \u003cspan citationid=\"CR116\" class=\"CitationRef\"\u003e116\u003c/span\u003e, \u003cspan citationid=\"CR119\" class=\"CitationRef\"\u003e119\u003c/span\u003e] studies were included, 26 RCTs and 0 non-RCTs. Compared with the control group, HIIT had no significant effect on RER in the elderly (MD: 0.01, P\u0026thinsp;=\u0026thinsp;0.20) (see Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e4\u003c/span\u003e). After excluding studies by Villelabeitia-Jaureguizar K et al. [\u003cspan citationid=\"CR83\" class=\"CitationRef\"\u003e83\u003c/span\u003e] I\u003csup\u003e2\u003c/sup\u003e was reduced to 33% and RER was significantly improved (MD: 0.01, P\u0026thinsp;=\u0026thinsp;0.04). Sensitivity analysis results suggested that the results of this study lacked robustness. Funnel plots were basically symmetric, and there was no evidence of publication bias. (See Annex 2 for funnel diagram)\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec14\" class=\"Section3\"\u003e \u003ch2\u003e3.3.3 Metabolic index\u003c/h2\u003e \u003cp\u003e \u003cb\u003eTC\u003c/b\u003e A total of 22[\u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e, \u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e, \u003cspan citationid=\"CR46\" class=\"CitationRef\"\u003e46\u003c/span\u003e, \u003cspan citationid=\"CR51\" class=\"CitationRef\"\u003e51\u003c/span\u003e, \u003cspan citationid=\"CR55\" class=\"CitationRef\"\u003e55\u003c/span\u003e, \u003cspan citationid=\"CR57\" class=\"CitationRef\"\u003e57\u003c/span\u003e, \u003cspan citationid=\"CR65\" class=\"CitationRef\"\u003e65\u003c/span\u003e, \u003cspan citationid=\"CR67\" class=\"CitationRef\"\u003e67\u003c/span\u003e, \u003cspan citationid=\"CR68\" class=\"CitationRef\"\u003e68\u003c/span\u003e, \u003cspan citationid=\"CR72\" class=\"CitationRef\"\u003e72\u003c/span\u003e, \u003cspan citationid=\"CR86\" class=\"CitationRef\"\u003e86\u003c/span\u003e, \u003cspan citationid=\"CR94\" class=\"CitationRef\"\u003e94\u003c/span\u003e, \u003cspan citationid=\"CR95\" class=\"CitationRef\"\u003e95\u003c/span\u003e, \u003cspan citationid=\"CR97\" class=\"CitationRef\"\u003e97\u003c/span\u003e, \u003cspan citationid=\"CR99\" class=\"CitationRef\"\u003e99\u003c/span\u003e, \u003cspan citationid=\"CR103\" class=\"CitationRef\"\u003e103\u003c/span\u003e, \u003cspan citationid=\"CR107\" class=\"CitationRef\"\u003e107\u003c/span\u003e, \u003cspan citationid=\"CR108\" class=\"CitationRef\"\u003e108\u003c/span\u003e, \u003cspan citationid=\"CR115\" class=\"CitationRef\"\u003e115\u003c/span\u003e, \u003cspan citationid=\"CR116\" class=\"CitationRef\"\u003e116\u003c/span\u003e, \u003cspan citationid=\"CR119\" class=\"CitationRef\"\u003e119\u003c/span\u003e, \u003cspan citationid=\"CR122\" class=\"CitationRef\"\u003e122\u003c/span\u003e] studies were included, including 20 RCTs and 2 non-RCTs. Compared with the control group, HIIT had no significant effect on TC in the elderly (MD: 0.12 mmol L\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e, P\u0026thinsp;=\u0026thinsp;0.06), but there was statistical heterogeneity (I\u003csup\u003e2\u003c/sup\u003e\u0026thinsp;=\u0026thinsp;31%) (see Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e4\u003c/span\u003e). After excluding the study of Gjellesvik TI et al. [\u003cspan citationid=\"CR116\" class=\"CitationRef\"\u003e116\u003c/span\u003e], the heterogeneity decreased to 18% and significantly improved TC (MD: 0.15 mmol L\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e, P\u0026thinsp;=\u0026thinsp;0.009). Sensitivity analysis showed that the results of this study were not robust. Funnel plots were basically symmetric, and there was no evidence of publication bias. (See Annex 2 for funnel diagram)\u003c/p\u003e \u003cp\u003e \u003cb\u003eTG\u003c/b\u003e A total of 29[\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e, \u003cspan additionalcitationids=\"CR37\" citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e38\u003c/span\u003e, \u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e43\u003c/span\u003e, \u003cspan citationid=\"CR46\" class=\"CitationRef\"\u003e46\u003c/span\u003e, \u003cspan citationid=\"CR51\" class=\"CitationRef\"\u003e51\u003c/span\u003e, \u003cspan citationid=\"CR55\" class=\"CitationRef\"\u003e55\u003c/span\u003e, \u003cspan citationid=\"CR57\" class=\"CitationRef\"\u003e57\u003c/span\u003e, \u003cspan citationid=\"CR58\" class=\"CitationRef\"\u003e58\u003c/span\u003e, \u003cspan citationid=\"CR65\" class=\"CitationRef\"\u003e65\u003c/span\u003e, \u003cspan citationid=\"CR68\" class=\"CitationRef\"\u003e68\u003c/span\u003e, \u003cspan citationid=\"CR72\" class=\"CitationRef\"\u003e72\u003c/span\u003e, \u003cspan citationid=\"CR86\" class=\"CitationRef\"\u003e86\u003c/span\u003e, \u003cspan citationid=\"CR94\" class=\"CitationRef\"\u003e94\u003c/span\u003e, \u003cspan citationid=\"CR95\" class=\"CitationRef\"\u003e95\u003c/span\u003e, \u003cspan citationid=\"CR97\" class=\"CitationRef\"\u003e97\u003c/span\u003e, \u003cspan citationid=\"CR99\" class=\"CitationRef\"\u003e99\u003c/span\u003e, \u003cspan citationid=\"CR103\" class=\"CitationRef\"\u003e103\u003c/span\u003e, \u003cspan citationid=\"CR107\" class=\"CitationRef\"\u003e107\u003c/span\u003e, \u003cspan citationid=\"CR108\" class=\"CitationRef\"\u003e108\u003c/span\u003e, \u003cspan additionalcitationids=\"CR112 CR113 CR114 CR115\" citationid=\"CR111\" class=\"CitationRef\"\u003e111\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR116\" class=\"CitationRef\"\u003e116\u003c/span\u003e, \u003cspan citationid=\"CR119\" class=\"CitationRef\"\u003e119\u003c/span\u003e, \u003cspan citationid=\"CR122\" class=\"CitationRef\"\u003e122\u003c/span\u003e] studies were included, including 26 RCTs and 3 non-RCTs. Compared with the control group, HIIT had no significant effect on TG (MD: -0.04mmol L\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e, P\u0026thinsp;=\u0026thinsp;0.27) (see Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e4\u003c/span\u003e). Sensitivity analyses suggested that the results were robust. Funnel plots were basically symmetric, and there was no evidence of publication bias. (See Annex 2 for funnel diagram)\u003c/p\u003e \u003cp\u003e \u003cb\u003eHDL\u003c/b\u003e A total of 28[\u003cspan additionalcitationids=\"CR37\" citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e38\u003c/span\u003e, \u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e43\u003c/span\u003e, \u003cspan citationid=\"CR46\" class=\"CitationRef\"\u003e46\u003c/span\u003e, \u003cspan citationid=\"CR51\" class=\"CitationRef\"\u003e51\u003c/span\u003e, \u003cspan citationid=\"CR55\" class=\"CitationRef\"\u003e55\u003c/span\u003e, \u003cspan citationid=\"CR57\" class=\"CitationRef\"\u003e57\u003c/span\u003e, \u003cspan citationid=\"CR58\" class=\"CitationRef\"\u003e58\u003c/span\u003e, \u003cspan citationid=\"CR65\" class=\"CitationRef\"\u003e65\u003c/span\u003e, \u003cspan citationid=\"CR67\" class=\"CitationRef\"\u003e67\u003c/span\u003e, \u003cspan citationid=\"CR68\" class=\"CitationRef\"\u003e68\u003c/span\u003e, \u003cspan citationid=\"CR72\" class=\"CitationRef\"\u003e72\u003c/span\u003e, \u003cspan citationid=\"CR86\" class=\"CitationRef\"\u003e86\u003c/span\u003e, \u003cspan citationid=\"CR94\" class=\"CitationRef\"\u003e94\u003c/span\u003e, \u003cspan citationid=\"CR95\" class=\"CitationRef\"\u003e95\u003c/span\u003e, \u003cspan citationid=\"CR97\" class=\"CitationRef\"\u003e97\u003c/span\u003e, \u003cspan citationid=\"CR99\" class=\"CitationRef\"\u003e99\u003c/span\u003e, \u003cspan citationid=\"CR103\" class=\"CitationRef\"\u003e103\u003c/span\u003e, \u003cspan citationid=\"CR107\" class=\"CitationRef\"\u003e107\u003c/span\u003e, \u003cspan additionalcitationids=\"CR112 CR113 CR114 CR115\" citationid=\"CR111\" class=\"CitationRef\"\u003e111\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR116\" class=\"CitationRef\"\u003e116\u003c/span\u003e, \u003cspan citationid=\"CR119\" class=\"CitationRef\"\u003e119\u003c/span\u003e, \u003cspan citationid=\"CR122\" class=\"CitationRef\"\u003e122\u003c/span\u003e] studies were included, including 25 RCTs and 3 non-RCTs. Compared with the control group, HIIT significantly improved HDL (MD: 0.04mmol L\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e, P\u0026thinsp;=\u0026thinsp;0.0007) in the elderly, with low statistical heterogeneity (I\u003csup\u003e2\u003c/sup\u003e\u0026thinsp;=\u0026thinsp;25%) (see Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e4\u003c/span\u003e). Sensitivity analysis showed that the results of this study were robust. Funnel plots were basically symmetric, and there was no evidence of publication bias. There was no significant difference between subgroups (P\u0026thinsp;\u0026gt;\u0026thinsp;0.05). (See Annex 2 for funnel diagram)\u003c/p\u003e \u003cp\u003e \u003cb\u003eLDL\u003c/b\u003e A total of 25[\u003cspan additionalcitationids=\"CR37\" citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e38\u003c/span\u003e, \u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e43\u003c/span\u003e, \u003cspan citationid=\"CR46\" class=\"CitationRef\"\u003e46\u003c/span\u003e, \u003cspan citationid=\"CR51\" class=\"CitationRef\"\u003e51\u003c/span\u003e, \u003cspan citationid=\"CR55\" class=\"CitationRef\"\u003e55\u003c/span\u003e, \u003cspan citationid=\"CR57\" class=\"CitationRef\"\u003e57\u003c/span\u003e, \u003cspan citationid=\"CR58\" class=\"CitationRef\"\u003e58\u003c/span\u003e, \u003cspan citationid=\"CR65\" class=\"CitationRef\"\u003e65\u003c/span\u003e, \u003cspan citationid=\"CR68\" class=\"CitationRef\"\u003e68\u003c/span\u003e, \u003cspan citationid=\"CR72\" class=\"CitationRef\"\u003e72\u003c/span\u003e, \u003cspan citationid=\"CR86\" class=\"CitationRef\"\u003e86\u003c/span\u003e, \u003cspan citationid=\"CR94\" class=\"CitationRef\"\u003e94\u003c/span\u003e, \u003cspan citationid=\"CR95\" class=\"CitationRef\"\u003e95\u003c/span\u003e, \u003cspan citationid=\"CR97\" class=\"CitationRef\"\u003e97\u003c/span\u003e, \u003cspan citationid=\"CR99\" class=\"CitationRef\"\u003e99\u003c/span\u003e, \u003cspan citationid=\"CR103\" class=\"CitationRef\"\u003e103\u003c/span\u003e, \u003cspan citationid=\"CR107\" class=\"CitationRef\"\u003e107\u003c/span\u003e, \u003cspan citationid=\"CR111\" class=\"CitationRef\"\u003e111\u003c/span\u003e, \u003cspan citationid=\"CR112\" class=\"CitationRef\"\u003e112\u003c/span\u003e, \u003cspan citationid=\"CR115\" class=\"CitationRef\"\u003e115\u003c/span\u003e, \u003cspan citationid=\"CR116\" class=\"CitationRef\"\u003e116\u003c/span\u003e, \u003cspan citationid=\"CR119\" class=\"CitationRef\"\u003e119\u003c/span\u003e, \u003cspan citationid=\"CR122\" class=\"CitationRef\"\u003e122\u003c/span\u003e] studies were included, including 22 RCTs and 3 non-RCTs. HIIT had no significant effect on LDL compared with the control group (MD: -0.05mmol L\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e, P\u0026thinsp;=\u0026thinsp;0.23) (see Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e4\u003c/span\u003e). Sensitivity analyses suggested that the results were robust. Funnel plots were basically symmetric, and there was no evidence of publication bias. (See Annex 2 for funnel diagram)\u003c/p\u003e \u003cp\u003e \u003cb\u003eFPG\u003c/b\u003e A total of 24[\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e, \u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e, \u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e38\u003c/span\u003e, \u003cspan citationid=\"CR46\" class=\"CitationRef\"\u003e46\u003c/span\u003e, \u003cspan citationid=\"CR51\" class=\"CitationRef\"\u003e51\u003c/span\u003e, \u003cspan citationid=\"CR53\" class=\"CitationRef\"\u003e53\u003c/span\u003e, \u003cspan citationid=\"CR55\" class=\"CitationRef\"\u003e55\u003c/span\u003e, \u003cspan citationid=\"CR57\" class=\"CitationRef\"\u003e57\u003c/span\u003e, \u003cspan citationid=\"CR67\" class=\"CitationRef\"\u003e67\u003c/span\u003e, \u003cspan citationid=\"CR68\" class=\"CitationRef\"\u003e68\u003c/span\u003e, \u003cspan citationid=\"CR86\" class=\"CitationRef\"\u003e86\u003c/span\u003e, \u003cspan citationid=\"CR88\" class=\"CitationRef\"\u003e88\u003c/span\u003e, \u003cspan citationid=\"CR95\" class=\"CitationRef\"\u003e95\u003c/span\u003e, \u003cspan citationid=\"CR97\" class=\"CitationRef\"\u003e97\u003c/span\u003e, \u003cspan citationid=\"CR99\" class=\"CitationRef\"\u003e99\u003c/span\u003e, \u003cspan citationid=\"CR108\" class=\"CitationRef\"\u003e108\u003c/span\u003e, \u003cspan additionalcitationids=\"CR112 CR113 CR114\" citationid=\"CR111\" class=\"CitationRef\"\u003e111\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR115\" class=\"CitationRef\"\u003e115\u003c/span\u003e, \u003cspan citationid=\"CR119\" class=\"CitationRef\"\u003e119\u003c/span\u003e, \u003cspan citationid=\"CR122\" class=\"CitationRef\"\u003e122\u003c/span\u003e, \u003cspan citationid=\"CR124\" class=\"CitationRef\"\u003e124\u003c/span\u003e] studies were included, including 23 RCTs and 1 non-RCTs. Compared with the control group, HIIT had no significant effect on FPG in the elderly (MD: -0.20 mmol L\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e, P\u0026thinsp;=\u0026thinsp;0.07). After excluding the study by Dolan LB et al. [\u003cspan citationid=\"CR88\" class=\"CitationRef\"\u003e88\u003c/span\u003e], there was no significant change in I\u003csup\u003e2\u003c/sup\u003e, but FPG was significantly improved (MD: -0.23 mmol L\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e, P\u0026thinsp;=\u0026thinsp;0.04) (see Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e4\u003c/span\u003e). The results of sensitivity analysis suggested that the results of this study lacked robustness. Funnel plots were basically symmetric, and there was no evidence of publication bias. (See Annex 2 for funnel diagram)\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 4\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eMeta-analysis results\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"6\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eOutcomes\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eThe number of studies\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cem\u003eP\u003c/em\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cem\u003eI\u003c/em\u003e\u0026sup2; (%)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eEffect model\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003e95%CI\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBMI\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e32\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.01*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e64\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eRE\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-0.38 [-0.68, -0.09]\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBF%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e20\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e\u0026lt;0.00001**\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e23\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eFE\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-1.38[-1.93,-0.83]\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eWC\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e18\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.16\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e76\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eRE\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-1.54 [-3.67, 0.60]\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eVO\u003csub\u003e2max\u003c/sub\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e60\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e\u0026lt;0.00001**\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e82\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eRE\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e2.23 [1.55, 2.91]\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSBP\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e43\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.75\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e81\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eRE\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-0.28 [-1.98, 1.42]\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDBP\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e43\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.06\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e73\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eRE\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-0.83 [-1.69, 0.03]\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHR\u003csub\u003erest\u003c/sub\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e29\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.24\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e83\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eRE\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-0.95[-2.54,0.63]\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHR\u003csub\u003emax\u003c/sub\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e40\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.02*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e79\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eRE\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e2.84[0.48,5.20]\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eRER\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e26\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.20\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e45\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eRE\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.01[-0.00,0.02]\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTC\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e22\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.06\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e31\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eRE\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.12 [-0.00, 0.24]\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTG\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e29\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.27\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e44\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eRE\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-0.04 [-0.12, 0.03]\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHDL\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e28\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.0007**\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e25\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eFE\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.04 [0.02, 0.07]\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLDL\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e25\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.23\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e37\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eRE\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-0.05 [-0.14, 0.03]\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFPG\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e24\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.07\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e58\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eRE\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-0.20 [-0.41, 0.02]\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"6\"\u003eRE: random effects models FE: fixed effects model; MD: mean difference CI: confidence interval *\u003cem\u003eP\u003c/em\u003e\u0026lt;0.05\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003c/div\u003e"},{"header":"4. Discussion","content":"\u003cp\u003eThis meta-analysis examined the overall impact of HIIT on elderly health by analyzing 14 clinical indicators across three categories: body composition, cardiopulmonary function, and metabolism. To our knowledge, this study is the largest in the world to evaluate HIIT's effects on elderly health, encompassing 92 eligible RCTs and non-RCTs studies involving 4,355 participants from various populations including healthy individuals as well as those with hypertension, cardiovascular disease, diabetes, cancer and other conditions. Our findings support the universal efficacy of HIIT in improving BMI, BF%, VO2max, HRmax, and HDL levels among older adults; however it does not affect SBP, HRrest, TG, and LDL levels. The results for DBP, RER TC and FPG should be interpreted with caution due to their lack of robustness which may be attributed to differences in disease type. These results further endorse HIIT as a preventive or therapeutic tool for managing elderly health both clinically and at home while providing scientific evidence for developing guidelines/recommendations.\u003c/p\u003e \u003cdiv id=\"Sec16\" class=\"Section2\"\u003e \u003ch2\u003e4.1Body shape index\u003c/h2\u003e \u003cp\u003eDue to the intricate relationship between body shape and health as well as disease[\u003cspan citationid=\"CR126\" class=\"CitationRef\"\u003e126\u003c/span\u003e], it serves as a primary indicator for assessing the health status of older individuals. Two extensive cohort studies have demonstrated that both high BMI and BF% along with low BMI elevate the risk of mortality [\u003cspan citationid=\"CR127\" class=\"CitationRef\"\u003e127\u003c/span\u003e, \u003cspan citationid=\"CR128\" class=\"CitationRef\"\u003e128\u003c/span\u003e]. Therefore, it is crucial for elderly individuals to effectively manage their BMI and reasonably reduce their BF%. This meta-analysis aims to elucidate the impact of HIIT on three clinical parameters related to body shape in older adults. The results of the meta-analysis demonstrated that HIIT effectively improved BMI and body BF% in older adults, which is consistent with the findings reported by Wang Donghai et al.[\u003cspan citationid=\"CR129\" class=\"CitationRef\"\u003e129\u003c/span\u003e]and[\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e], but contradicts the conclusions drawn from other studies[\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e, \u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e, \u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e, \u003cspan additionalcitationids=\"CR25 CR26 CR27 CR28\" citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e]. Unlike previous studies that primarily included individuals with normal weight as baseline data, our study focused on overweight and obese participants except for the research conducted by Nemoto K et al. [\u003cspan citationid=\"CR80\" class=\"CitationRef\"\u003e80\u003c/span\u003e]. The meta-analysis results indicated insufficient evidence regarding the impact of HIIT on waist circumference (WC) in older adults, aligning with most previous systematic reviews[\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e, \u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e, \u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e, \u003cspan additionalcitationids=\"CR25 CR26 CR27 CR28\" citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e]. To further assess the stability of these combined results, a sensitivity analysis was performed. After excluding the study conducted by TJS \u0026Oslash;NNA AE et al. [\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e], I\u003csup\u003e2\u003c/sup\u003e decreased from 76\u0026ndash;39%, suggesting that this discrepancy may be attributed to differences in baseline data between this particular study and others. It is worth noting that, excluding the study by Eeik Madssen et al. [\u003cspan citationid=\"CR51\" class=\"CitationRef\"\u003e51\u003c/span\u003e] there was no significant change in I\u003csup\u003e2\u003c/sup\u003e; however, WC exhibited a reversal (P\u0026thinsp;=\u0026thinsp;0.04). Further analysis revealed that the exercise supervision implementation rate in the study was only 1/3, and this low compliance resulted in an increase in WC after HIIT intervention. This finding may further elucidate the insufficient effect of HIIT on WC combined results. Therefore, caution should be exercised when interpreting whether HIIT can improve WC in the elderly due to the lack of robustness of these results.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec17\" class=\"Section2\"\u003e \u003ch2\u003e4.2 Cardiopulmonary function index\u003c/h2\u003e \u003cp\u003eThe pleiotropic effects of maintaining a high level of cardiopulmonary function on the Health of the elderly have been widely recognized[\u003cspan citationid=\"CR130\" class=\"CitationRef\"\u003e130\u003c/span\u003e], and it has been identified as a priority for promoting the health of the elderly by the World Health Organization (WHO)[\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e] A total of 6 cardiopulmonary function indicators were included in this meta-analysis to evaluate the effects of HIIT on cardiopulmonary function in the elderly. The existing evidence shows that HIIT can effectively improve VO2max and HRmax in the elderly. The analysis of 60 studies showed that the increase of VO2max by 2.23ml/kg/min is very significant, and VO2max is recognized as the gold standard of cardiopulmonary function. A 44-year follow-up study showed that VO2max was inversely associated with the risk of cancer, cardiovascular events, and all-cause mortality[\u003cspan citationid=\"CR131\" class=\"CitationRef\"\u003e131\u003c/span\u003e],, and each 1-mets increase reduced cardiovascular events by 15% and all-cause mortality by 13%[\u003cspan citationid=\"CR132\" class=\"CitationRef\"\u003e132\u003c/span\u003e]. Subgroup analysis found that the effect of HIIT on VO2max in the elderly was generalized, and was independent of the intervention period and the health of the subjects. In addition, HRmax is also one of the important indexes to evaluate the cardiopulmonary function of the elderly, and it is positively correlated with VO2max. The improvement of HRmax is consistent with VO2max, but the improvement of HRmax is less extensive than VO2max. The results of this study show that there is insufficient evidence for HIIT to improve blood pressure in the elderly, which is consistent with the results of previous studies [\u003cspan additionalcitationids=\"CR23 CR24 CR25 CR26 CR27 CR28\" citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e, \u003cspan citationid=\"CR129\" class=\"CitationRef\"\u003e129\u003c/span\u003e], but in sharp contrast to the study by Litao Du et al.[\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e], the difference in conclusions may be related to the training method (isometric exercise has a better effect on blood pressure change than other exercise methods [\u003cspan citationid=\"CR133\" class=\"CitationRef\"\u003e133\u003c/span\u003e])and the sensitivity of the subjects to HIIT. As blood pressure is the most important modifiable risk factor for all-cause morbidity and mortality, SBP did not change significantly after excluding one by one, but DBP showed a significant difference (P\u0026thinsp;=\u0026thinsp;0.03) after excluding the study by Fernandes B et al. [\u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e40\u003c/span\u003e], a finding consistent with Juliana Moraes The conclusion of Leal et al. [\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e] was consistent, which may be related to the lack of effective supervision and administration of antihypertensive drugs during the HIIT intervention in that study. After the study by Villelabeitia-Jaureguizar K et al. [\u003cspan citationid=\"CR83\" class=\"CitationRef\"\u003e83\u003c/span\u003e] was excluded by RER, the results were reversed (P\u0026thinsp;=\u0026thinsp;0.04). Since this study compared the improvement difference between moderate-intensity exercise and HIIT, the effect of HIIT was reduced. The results for DBP and RER need to be interpreted with caution, given the lack of robustness of the sensitivity analyses. Unfortunately, there is insufficient evidence on the effect of HIIT on HRrest in the elderly, so it was omitted from this meta-analysis.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec18\" class=\"Section2\"\u003e \u003ch2\u003e4.3 Metabolic index\u003c/h2\u003e \u003cp\u003eMetabolic abnormalities can cause a variety of chronic diseases, including obesity, cardiovascular disease, diabetes, cancer, etc., which brings huge public health problems and medical burdens[\u003cspan citationid=\"CR134\" class=\"CitationRef\"\u003e134\u003c/span\u003e]. Metabolic disorders are often more serious in the elderly. Priority should be given to reducing the related risks in the elderly at this stage while preventing them. A total of 5 metabolic indicators were included in this meta-analysis, and the existing evidence showed that HIIT effectively improved HDL, which was in sharp contrast with previous studies [\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e, \u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e, \u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e] probably because previous studies were based on comparing the differences between HIIT and moderate intensity exercise, while most of our work was based on the comparison between HIIT and blank control. However, HIIT had no significant effect on TG and LDL, which is consistent with previous studies [\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e, \u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e]. TC excluded the study of Gjellesvik TI et al. [\u003cspan citationid=\"CR116\" class=\"CitationRef\"\u003e116\u003c/span\u003e], and FPG excluded Dolan The results of LB et al. [\u003cspan citationid=\"CR88\" class=\"CitationRef\"\u003e88\u003c/span\u003e] were reversed after the study, which may be due to the differences in the baseline levels of our included studies, two types of exercise in some studies, and the use of drugs to treat metabolic abnormalities or affect metabolic indicators. These factors may reduce the improvement effect of HIIT on metabolic indicators, which is explained by the lack of robustness of TG and FPG results You need to be careful.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec19\" class=\"Section2\"\u003e \u003ch2\u003e4.4 Adverse events and compliance\u003c/h2\u003e \u003cp\u003eAmong the included studies, 25 studies provided comprehensive descriptions of medical supervision, while 29 studies lacked detailed information in this regard, and 38 studies did not mention it at all. Additionally, withdrawal from the intervention was reported in 26 studies due to reasons such as familial obligations, personal preferences, and other factors involving a total of 215 participants, accounting for approximately 4.94% of the overall sample size. Adverse events were documented in 46 cases with an incidence rate of approximately 1.06%. Importantly, none of these adverse events were attributed to HIIT.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec20\" class=\"Section2\"\u003e \u003ch2\u003e4.5 Limitations\u003c/h2\u003e \u003cp\u003eThe large sample size and high heterogeneity observed in our study were expected due to differences in methodology and study subjects, as the range of studies included all older adults except those with contraindications to exercise. Therefore, subgroup analyses and sensitivity points were conducted to assess the role and stability of the pooled results. Sensitivity analysis revealed that WC, DBP, RER, TC, and FPG lacked robustness. Despite implementing a rigorous search strategy, language bias was inevitable as only Chinese and English literature was retrieved within our constraints. Furthermore, variations in exercise equipment, interval time, and intervention duration among the HIIT studies included prevented us from conducting subgroup analysis; thus specific exercise doses cannot be recommended at this stage. Lastly, our included studies did not assess medication use or baseline/daily physical activity which are critical factors for evaluating the hypothesis that HIIT improves health in older adults. Additionally, we lacked data on other influencing factors such as gender and exercise capacity.\u003c/p\u003e \u003c/div\u003e"},{"header":"5 Conclusion","content":"\u003cp\u003eThe current evidence indicates that HIIT has a broad range of effects on enhancing body composition and cardiopulmonary function in older adults. These findings provide substantial support for the role of HIIT in promoting physical health among the elderly, thereby warranting its inclusion within preventive healthcare systems targeting this population. However, the optimal exercise dosage for HIIT remains uncertain, necessitating future multi-center, large-scale, high-quality studies and long-term prospective investigations to validate these outcomes.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eEthics approval and consent to participate\u003c/strong\u003e Not applicable.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthor contributions\u003c/strong\u003e Men Jie and Chenmin Xiang contributed to the conception and design of the study. Guoyu Zhu and Chenmin Xiang contributed to the development of the search strategy. Chengrui Zhao and Chenmin Xiang conducted the systematic review.\u0026nbsp;Zhengyang Yu, Pengbo Wang, Simin Wu, Xiyu Zhang, Yishan Li, Liuliu Wang and Xueyan Gongcompleted the acquisition of data and performed the data analysis. All authors assisted with the interpretation. Men Jie, Chenmin Xiang, Guoyu Zhu and Chengrui Zhao were the principal writers of the manuscript.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eAll authors contributed to the drafting and revision of the final article.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eAll authors approved the final submitted version of the manuscript.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u0026nbsp;Consent for publication\u003c/strong\u003e Not applicable.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u0026nbsp;Availability of data and materials\u003c/strong\u003e Data may be available on request to the corresponding author.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u0026nbsp;Competing interests\u003c/strong\u003e The authors declare that they have no conflicts of interest relevant to the content of this review.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding\u003c/strong\u003e This paper is supported by the Institute of Metabolic Cardiovascular Diseases Key Laboratory Cultivation Base of Shanxi Province (TSGJ001); Teaching Reform and Innovation Project of Higher Education in Shanxi Province (J2021967); Teaching Reform Project of Fenyang College of Shanxi Medical University (FJ202013); Talent Introduction Start-up Fund of Fenyang College of Shanxi Medical University (2022A01); Innovation and Entrepreneurship Training Program for College Students in Shanxi Province(No. 20231800) and Fenyang College Students\u0026apos; Innovation and Entrepreneurship Program of Shanxi Medical University (FDC202104).\u0026nbsp;\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eManas A, Del PB, Rodriguez-Gomez I, Losa-Reyna J, Judice PB, Sardinha LB, et al. 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CIRCULATION. 2007;115(24):3086\u0026ndash;94.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eConraads VM, Pattyn N, De Maeyer C, Beckers PJ, Coeckelberghs E, Cornelissen VA, et al. Aerobic interval training and continuous training equally improve aerobic exercise capacity in patients with coronary artery disease: The SAINTEX-CAD study. INT J CARDIOL. 2015;179(2015):203\u0026ndash;10.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eWyckelsma VL, Levinger I, Murphy RM, Petersen AC, Perry BD, Hedges CP, et al. Intense interval training in healthy older adults increases skeletal muscle [3 H]ouabain-binding site content and elevates Na+,K+ -ATPase α2 isoform abundance in Type II fibers. Physiological Reports. 2017;5(7):e13219.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eCoswig VS, Barbalho M, Raiol R, Del Vecchio FB, Ramirez-Campillo R, Gentil P. Effects of high vs moderate-intensity intermittent training on functionality, resting heart rate and blood pressure of elderly women. J TRANSL MED. 2020;18(1):88.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eMitranun W, Deerochanawong C, Tanaka H, Suksom D. Continuous vs interval training on glycemic control and macro- and microvascular reactivity in type 2 diabetic patients. SCAND J MED SCI SPOR. 2014;24(2):e69-76.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eKarenovics W, Licker M, Ellenberger C, Christodoulou M, Diaper J, Bhatia C, et al. Short-term preoperative exercise therapy does not improve long-term outcome after lung cancer surgery: a randomized controlled study\u0026dagger;. EUR J CARDIO-THORAC. 2017;52(1):47\u0026ndash;54.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eLi X. Effect of high-intensity interval training on blood glucose control, adipocytokine secretion and oxidative stress response in patients with T2DM. Journal of Hainan Medical University (English version). 2018;24(5):14\u0026ndash;8.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eLi X, Han T, Zou X, Zhang H, Feng W, Wang H, et al. Long-term high-intensity interval training increases serum neurotrophic factors in elderly overweight and obese Chinese adults. EUR J APPL PHYSIOL. 2021;121(10):2773\u0026ndash;85.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003e\u0026Auml;rnl\u0026ouml;v J, Ingelsson E, Sundstr\u0026ouml;m J, Lind L. Impact of Body Mass Index and the Metabolic Syndrome on the Risk of Cardiovascular Disease and Death in Middle-Aged Men. CIRCULATION. 2010;121(2):230\u0026ndash;6.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eBhaskaran K, Dos-Santos-Silva I, Leon DA, Douglas IJ, Smeeth L. Association of BMI with overall and cause-specific mortality: a population-based cohort study of 3\u0026middot;6 million adults in the UK. The Lancet Diabetes \u0026amp; Endocrinology. 2018;6(12):944\u0026ndash;53.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003ePadwal R, Leslie WD, Lix LM, Majumdar SR. Relationship Among Body Fat Percentage, Body Mass Index, and All-Cause Mortality: A Cohort Study. ANN INTERN MED. 2016;164(8):532\u0026ndash;41.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eWang Donghai, Yang Shibao, Jie Changfu. The impact of high-intensity interval training on fitness and metabolic disease risk factors in elderly individuals:A Meta Analysis. Journal of Harbin Institute of Physical Education. 2022;40(3):80\u0026ndash;9.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eDallas KB, Rogo-Gupta L, Elliott CS. What Impacts the All Cause Risk of Reoperation after Pelvic Organ Prolapse Repair? A Comparison of Mesh and Native Tissue Approaches in 110,329 Women. J Urol. 2018;200(2):389\u0026ndash;96.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eJensen MT, Holtermann A, Bay H, Gyntelberg F. Cardiorespiratory fitness and death from cancer: a 42-year follow-up from the Copenhagen Male Study. BRIT J SPORT MED. 2017;51(18):1364\u0026ndash;9.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eKodama S, Saito K, Tanaka S, Maki M, Yachi Y, Asumi M, et al. Cardiorespiratory Fitness as a Quantitative Predictor of All-Cause Mortality and Cardiovascular Events in Healthy Men and Women: A Meta-analysis. JAMA: the journal of the American Medical Association. 2009;301(19):2024\u0026ndash;35.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eCarlson DJ, Dieberg G, Hess NC, Millar PJ, Smart NA. Isometric Exercise Training for Blood Pressure Management: A Systematic Review and Meta-analysis. MAYO CLIN PROC. 2014;89(3):327\u0026thinsp;\u0026ndash;\u0026thinsp;34.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eChew NWS, Ng CH, Tan DJH, Kong G, Lin C, Chin YH, et al. The global burden of metabolic disease: Data from 2000 to 2019. CELL METAB. 2023;35(3):414\u0026ndash;28.\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"},{"header":"Tables","content":"\u003cp\u003eTable 1 is available in the Supplementary Files section.\u003c/p\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"","lastPublishedDoi":"10.21203/rs.3.rs-4253175/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-4253175/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003ch2\u003eBackground\u003c/h2\u003e \u003cp\u003eDespite the growing attention towards the efficacy of high-intensity interval training (HIIT) on elderly health, a consensus regarding the pleiotropic effects of HIIT in this population is yet to be reached. Previous studies have predominantly focused on specific outcomes or particular groups, lacking comprehensive analysis.\u003c/p\u003e\u003ch2\u003eObjective\u003c/h2\u003e \u003cp\u003eWe aimed to conduct a systematic evaluation of the impact of HIIT on body composition, cardiopulmonary function, and metabolic parameters in older adults.\u003c/p\u003e\u003ch2\u003eMethods\u003c/h2\u003e \u003cp\u003eThe databases searched included PubMed, Web of Science, Cochrane Library, Scopus, WanFang, and other relevant sources from the inception of the database until July 2023. We supplemented the randomized controlled trials (RCTs) and retrieved relevant meta-analyses, and found that 5 highly relevant non-RCTs were also included in the supplement to study the effects of high-intensity interval training (HIIT) on body composition, cardiopulmonary function and metabolic parameters in the elderly.\u003c/p\u003e\u003ch2\u003eResult\u003c/h2\u003e \u003cp\u003eA total of 92 studies, including 87 RCTs and 5 non-RCTs, involving a sample size of 4355 elderly individuals were included in the analysis. The meta-analysis results demonstrated that HIIT significantly improved body mass index (BMI) [MD: -0.38kg m-2,P\u0026thinsp;=\u0026thinsp;0.01], body fat percentage (BF%) [MD༚-1.38%, \u003cem\u003eP\u003c/em\u003e\u0026lt;0.00001], maximal oxygen uptake (VO2max) [MD:2.23ml min\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003ekg\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e, \u003cem\u003eP\u003c/em\u003e\u0026lt;0.00001], maximal heart rate (HRmax) [MD:2.84 beats min\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.02], and high-density lipoprotein levels (HDL) [MD:0.04mmol L\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.0007] among the elderly population. However, no significant improvements were observed for systolic blood pressure (SBP) [MD: -0.28mmHg, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.75], resting heart rate (HRrest) [MD: -0.95time min\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.24], triglycerides (TG) [MD: -0.04mmol L\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.27], low-density lipoprotein (LDL) [MD: -0.05mmol L\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.23]. Sensitivity analysis found that HIIT significantly improved waist circumference (WC) [MD: -2.13cm, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.04], diastolic blood pressure (DBO) [MD: -0.96 mmHg, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.03], respiratory exchange rate (RER) [MD: 0.01, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.04], total cholesterol (TC) [MD: 0.15 mmol L\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.009], fasting plasma glucose (FPG) [MD: -0.23 mmol L\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.04]in the elderly, but the results lacked robustness.\u003c/p\u003e\u003ch2\u003eConclusions\u003c/h2\u003e \u003cp\u003e The results of this study provide further support for HIIT to improve the physical health of the elderly, especially in terms of body shape and cardiopulmonary function, more importantly, provide a reference for HIIT in clinical practice and family health management of the elderly and the development of HIIT guidelines.\u003c/p\u003e","manuscriptTitle":"Effects of high-intensity interval training on physical morphology, cardiopulmonary function, and metabolic indicators in older adults: A PRISMA-based systematic review and meta-analysis","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2024-05-02 20:40:36","doi":"10.21203/rs.3.rs-4253175/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"95eacd6a-5832-4506-9e02-8693cfa94ba8","owner":[],"postedDate":"May 2nd, 2024","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[{"id":31387825,"name":"Health sciences/Health care"},{"id":31387826,"name":"Health sciences/Medical research"}],"tags":[],"updatedAt":"2024-10-23T05:55:21+00:00","versionOfRecord":[],"versionCreatedAt":"2024-05-02 20:40:36","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-4253175","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-4253175","identity":"rs-4253175","version":["v1"]},"buildId":"qtupq5eGEP_6zYnWcrvyt","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}