Long‐Term Effects of High‐Intensity Aerobic Training on Metabolic Syndrome: An 8‐Year Follow‐Up Randomized Clinical Trial

Abstract

ABSTRACT

Background

Metabolic syndrome (MetS) is a set of five cardiometabolic risk factors that typically worsen with age. One exercise‐training programme is effective at improving those factors in middle‐aged individuals with MetS. To our knowledge, exercise‐training efficacy as MetS individuals age has not been explored. This study determined the effectiveness of a periodized exercise training programme for individuals with MetS after a follow‐up period of 8 years.

Methods

Forty‐seven individuals with MetS were block‐randomized into an EXERCISE (n = 22, 52 ± 8 years old, 23% women) or a CONTROL group (n = 25, 53 ± 8 years old, 32% women). Both groups received standard health care, including medical counselling and lifestyle advice at least every 6 months, while participants in EXERCISE also underwent a supervised exercise programme. The intervention lasted 8 years and consisted of 4 months per year (November to March) of high‐intensity interval training thrice weekly. At baseline, and after 4 and 8 years of treatment, we assessed body composition, MetS components (i.e., MetS Z score), medication use, cardiorespiratory fitness (CRF; assessed by VO_2MAX) and maximal leg cycling power output (W_MAX).

Results

Paradoxically, MetS Z score and body weight were reduced after 8 years (subjects aged from 52 to 60 years old) in both groups (time effect p < 0.001 and p = 0.008; time × group interaction p = 0.253 and p = 0.130). However, in those 8 years, the medicine use score increased threefold in CONTROL (137% increase; from 1.7 to 3.9; p < 0.001) while it did not change in EXERCISE (33%; from 2.0 to 2.7; p = 0.066). In 8 years, CRF and W_MAX increased in EXERCISE by 14% (3.4 ± 5.6 mL·kg⁻¹·min⁻¹) and 4% (7 ± 37 W) while decreasing in CONTROL by −7% (−1.6 ± 3.4 mL·kg⁻¹·min⁻¹) and −14% (−24 ± 27 W) being different between groups after 4 and 8 years (both time × group interaction p = 0.002). Pearson correlations showed that MetS Z score improvements were significantly associated with increases in medication use score in the CONTROL group (r = 0.491; p = 0.013) and with W_MAX enhancement in the EXERCISE group (r = 0.613; p = 0.002).

Conclusions

Our data suggest that annual exercise training has similar clinical efficacy to triple oral medication for the management of MetS in individuals aged 50 to 60 years. The health of individuals with cardiometabolic disorders can be maintained as they age by increasing medication or by participating in an annual intensive exercise programme.

Introduction

Metabolic syndrome (MetS) is a complex of interconnected cardiometabolic disorders that typically increase with age [1]. Not only does the prevalence of MetS increase with age [2] but having MetS at any given age results in elevation in DNA markers of premature epigenetic ageing [3]. Thus, it is likely that MetS accelerates the deterioration of the cardiometabolic system beyond the natural decline in function associated with ageing. A hypocaloric diet, exercise and oral medication therapy are the foundations for MetS clinical management [4]. It is unclear if those combined therapies are similarly effective as individuals age. MetS is a great model for a comprehensive study of the impact of ageing, exercise and medication because it has defined thresholds for clinical risk factors such as arterial pressure, blood glucose, triglycerides, HDL and central obesity [5].

Compounding the effects of ageing, the medication that ageing people habitually take, could interfere with training adaptations. It is well established that some of the prescriptions that middle-aged and old individuals regularly take to control atherosclerotic cardiovascular risk, blunt the positive adaptation of training in muscle mitochondria. For instance, statins [S41] and metformin [S42] lessen exercise-induced mitochondrial adaptation and whole-body increases in cardiorespiratory fitness (CRF, as assessed by VO_2MAX) after high-intensity aerobic training [6, 7]. Because mitochondrial capacity correlates with insulin sensitivity [8], the combination of ageing and certain oral medications may prevent exercise training from alleviating insulin resistance [9]. Some studies suggest that metformin blunts insulin-like growth factor 1 (IGF-1) [7] and muscle strength gains following training in middle-aged and older individuals [10], which would result in reduced protection against ageing. In contrast, oral medicines that lower blood pressure could allow more intense training potentiating training adaptations [11]. Thus, medication is a factor that should always be factored in when reporting the health-promoting effects of exercise training in the ageing population.

Regular exercise promotes healthspan in the ageing population [S43] and could even delay mortality [12]. Training programme characteristics influence the magnitude of skeletal muscle and cardiometabolic adaptations to exercise in a dose–response manner [13]. Strong evidence exists that aerobic exercise intensity mediates mitochondrial adaptations to exercise and improvements in maximal aerobic capacity (VO_2MAX [14]). Additionally, repeated exposure to an exercise dose is required to consolidate transient improvements in health parameters into durable health adaptations in MetS patients [15]. The maintenance of both, CRF and muscular strength while ageing are probably the most critical health-related outcome measures of healthspan and are strongly associated with reduced mortality due to cardiovascular diseases [16]. Previous studies have found a strong association between low levels of CRF and muscular strength and increased incidence of MetS in men and women [17, 18]. Conversely, higher levels of CRF [19] and muscular strength [20] protect against the development of MetS as individuals age.

Several studies endorse that a 4- to 6-month intense aerobic exercise training programme effectively reduces MetS components [S44, S45]. However, those studies do not integrate in their findings the concurrent effects of oral medication or the effects of ageing in these individuals. Other rigorously controlled randomized trials in obese participants (Diabetes Prevention Program [DPP] [21], Look AHEAD [22], U-TURN [23] and PROPEL [24]) show a reduction in cardiometabolic risk factors and medication use when combining physical activity and diet to achieve clinically relevant body weight loss (i.e., > 5%). However, these interventions require a drastic lifestyle change rarely sustained after the experiment is completed [25]. In contrast, lifestyle interventions based on incorporating supervised exercise programmes could correct several risk factors simultaneously and be sustainable in time.

We recently reported that yearly repetition of a 4-month aerobic training programme for five consecutive years improves MetS without requiring large body weight loss [26]. However, the time frame of our previous study was too short to assess the effects of ageing on exercise-related health outcomes. In the present study, we followed a sample of individuals with MetS as they aged for 8 years (52–60 years old). We block-randomized the sample into a control group under lifestyle medical counselling and a group that yearly completed 4 months of supervised high-intensity interval aerobic training. This RCT design allowed us to assess whether the decline in physical fitness (cardiovascular and muscular) was due to the effects of ageing per se or to a lack of supervised exercise training. Our main hypothesis was that short-term ageing (from 50–60 years old) would significantly worsen MetS factors, but exercise training could compensate for the ageing-related deterioration of the cardiometabolic systems.

Methods

Participants

Forty-seven middle-aged (53 ± 8 years) overweight and obese subjects (body mass index [BMI], 33.4 ± 4.2 kg·m⁻²) with MetS criteria completed the study. Participants were previously inactive (< 150 min·week⁻¹ of the moderate-intensity activity assessed by 7-d IPAQ [S46]. MetS was defined according to the updated International Diabetes Federation 2009 criteria using population Europid waist circumference cutpoints [27]. Exclusion criteria were untreated cardiovascular or renal disease or any condition associated with exercise intolerance. The protocol did not require any method changes during the follow-up period. All subjects provided written, witnessed and informed consent under a protocol approved by the local Virgen de la Salud Hospital's Ethics Committee and according to the Declaration of Helsinki. This is a substudy part of a larger clinical trial evaluating the effects of interactions of medicine and exercise in individuals with MetS (ClinicalTrials.gov Identifier: NCT03019796). The main study outcomes were MetS Z score and medication use score. We maintained the targeted outcomes during the experiment.

Experimental Design

Following a parallel group randomized controlled trial design, participants were recruited, clinically screened and tested in compliance with CONSORT (i.e., Consolidated Standards of Reporting Trials statement; Figure 1). After baseline assessment, 64 participants were stratified in blocks using a specific randomization software. An independent statistician determined a computer-generated random number sequence. The sequence was given to a research team member who was not involved in the study procedures. Randomization was stratified by age (< 50 and ≥ 50 years), number of MetS factors (there, four and five Mets components) and BMI (< 30 kg/m² and ≥ 30 kg/m²). Within each block, participants were randomly assigned to the exercise training (EXERCISE) or standard medical care (CONTROL) groups in a 1:1 ratio. Physiological, anthropometric and blood biochemistry measurements were taken on three occasions: before exercise intervention (baseline) and after 4 and 8 years of treatment. Additional interim analysis was performed after 5 years of follow-up, which provided information of the short-term effects of yearly exercise training on cardio-metabolic health [26, 28]. Body composition and physiological measurements were performed at the Exercise Physiology Laboratory facilities, and blood biochemical variables were assessed at Eurofins Megalab laboratory (Toledo, Spain). Pre-training data were always collected in early November to avoid seasonal effects. All participants received attention from the Spanish healthcare system, including medical counselling and lifestyle advice at least every 6 months. Physicians were not included in the research group and were naïve to the experimental group assignment. Conversely, personnel responsible for measurements and intervention administration were not blinded to the group assignment (open-label).

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Intervention

Both groups received standard health care while, in addition, participants in EXERCISE underwent a supervised exercise programme (3 sessions·per week) at the sports facilities of the University. Training consisted of high-intensity interval training (HIIT) on stationary bikes for 4 months yearly (mid-November to mid-March) for eight consecutive years. Each exercise session included a 10-min warm-up at 70% of peak heart rate (HR_MAX) followed by 4 × 4-min intervals at 90% of HR_MAX interspersed with a 3-min active recovery at 70% of HR_MAX and a 5-min cool-down period. Heart rate (HR) was continuously displayed on a large screen (Seego Realtrack Sytems, Almería, Spain) and participants self-adjusted the workload to reach their HR target. A research team member monitored each session to ensure adherence to the training scheme. At each evaluation window (baseline, Year 4 and Year 8), before starting the exercise intervention period, participants completed a 3-day food diary (CESNICD v1.0; Barcelona, Spain) and physical activity pattern (Polar Electro, Kempele, Finland) for 1 week (i.e., the daily number of steps, standing time and supine resting time; see Table S1).

MetS Components and Body Composition

Patients arrived at the laboratory in the morning after an overnight fast. For EXERCISE, post-training measurements were scheduled at least 48 h after the last exercise training session. Nude body weight (Hawk; Metler, Toledo, OH, USA), height (Stadiometer; Secca 217, Hamburg, Germany) and waist circumference (flexible tape) were measured. Fat mass (FM) and fat-free mass (FFM) were determined by bioelectrical impedance analysis (Tanita bc-418; Tanita Corp, Tokyo, Japan). After 10 min of supine rest, blood pressure was measured in triplicate using a calibrated ECG-gated electro-sphygmomanometer (Tango, Suntec Medical; NC). Following, a 7-mL blood sample was collected to determine serum glucose, insulin and lipid levels (triglycerides, total cholesterol, HDL and LDL-cholesterol). Insulin sensitivity was calculated using the homeostasis model assessment for insulin resistance (HOMA-IR). Sex-specific Z scores were calculated for each MetS criterion using the group SD, with the sum of the Z scores for each MetS component divided by six to compile the MetS risk score with units of SD. The equations used to calculate the MetS Z score were:

Men's MetS Z score = [(40 − HDL-cholesterol)/SD] + [(triglycerides − 150)/SD] + [(glucose − 100)/SD] + [(waist circumference − 94)/SD] + [(systolic blood pressure − 130)/SD] + [(diastolic blood pressure − 85)/SD].

Women's MetS Z score = [(50 − HDL-cholesterol)/SD] + [(triglycerides − 150)/SD] + [(glucose − 100)/SD] + [(waist circumference − 80)/SD] + [(systolic blood pressure − 130)/SD] + [(diastolic blood pressure − 85)/SD].

Cardiorespiratory Fitness and Maximal Power Output

Maximal oxygen uptake (VO_2MAX), maximal cycling power (W_MAX) and maximal HR (HR_MAX) were assessed during a graded exercise test (GXT) on an electronically braked cycle ergometer (Ergoselect 200; Ergoline, Germany) using indirect calorimetry (Quark b²; Cosmed, Italy). Heart electrical activity was continuously monitored using a standard 12-lead ECG (Quark T12; Cosmed). After 3 min of warm-up at 30 W for women and 50 W for men, the workload increased every minute (15 W for women and 20 W for men) until volitional exhaustion. This test was followed by a verification test at 110% of the maximal workload reached to ensure the achievement of VO_2MAX [29].

Medication Use

Participants were supervised by their primary care physician following the Spanish Society of Family and Community Medicine guidelines for MetS treatment [S47]. These guidelines include lifestyle advice, blood analysis every 6 months and pharmacological prescriptions adjusted to blood chemistry, blood pressure values and body weight evolution. Physicians were not included in the research group and were naïve to group allocation of the experiment. Participants brought all prescription medication to the laboratory at the three data collection visits to ensure recording accuracy. Only medicines to control MeS factors were registered. We used the defined daily dose (DDD; [S48]) by the international standard in drug utilization research (DUR) as recommended by the World Health Organization (WHO) since 1996. The DDD is the recommended daily dose for that specific drug in adults based on the main active chemical independent of manufacturer presentation. The use of DDD enabled us to monitor medication evolution in patients taking different brands of the same drug.

We developed a medicine use score that integrates the number and dose of medications taken by each participant, as follows [26]:$$$ {\displaystyle \begin{array}{c}\mathsf{Medicine}\ \mathsf{use}\ \mathsf{score}=\left[\mathsf{medicine}\ \mathsf{1}\ \left(\mathsf{subject}\ \mathsf{used}\ \mathsf{dose}/\mathsf{DDD}\ \mathsf{index}\right)\right]\hfill \\ {}\kern9.4em +\left[\mathsf{medicine}\ \mathsf{2}\ \left(\mathsf{subject}\ \mathsf{used}\ \mathsf{dose}/\mathsf{DDD}\ \mathsf{index}\right)\right]\hfill \\ {}\kern9.4em +\dots \dots \dots \hfill \\ {}\kern9.4em +\left[\mathsf{medicine}\ \mathsf{n}\ \left(\mathsf{subject}\ \mathsf{used}\ \mathsf{dose}/\mathsf{DDD}\ \mathsf{index}\right)\right].\hfill \end{array}} $$$

Statistical Analysis

We used per-protocol analysis, and only patients who completed the treatment protocol were included in the statistical analysis. Sample size calculation was based on MetS Z score data changes in individuals with MetS who completed a 16-week exercise training programme for three consecutive years [15]. Assuming 80% power and an α-error probability of 0.05, it was calculated that 16 patients would be required to detect a significant effect of long-term exercise training on improvement in the MetS Z score. Because the present study had a longer follow-up period, we doubled the initially randomized sample size. Data are presented as mean ± SD. Kolmogorov–Smirnov test revealed that all variables showed a normal distribution except the number of prescribed medications and medication use score. Mixed-design ANOVA without multiple imputations was used to analyse differences across time (repeated measures) and between experimental groups (CONTROL vs. EXERCISE) in anthropometric, MetS factors, CRF and muscular power levels. Despite our previous observation that the metabolic and cardiovascular responses to 4 months of HIIT in MetS patients are similar in men and women [S49], an analysis of covariance (ANCOVA) was performed to eliminate the potential influence of sex on the primary outcomes. When the time-by-group interaction was significant, vertical multiple comparisons were performed using Bonferroni post-hoc testing. The 95% confidence intervals (CI) were also calculated. To improve the interpretation of the differences, the effect size of time and time × group interaction were calculated using eta squared (η²). The effect size obtained from η² was considered large if ≥ 0.14, moderate ≥ 0.06 and small if < 0.06. The difference within and between groups in medication use (per type of drug) at 4- and 8-year follow-up compared with baseline was tested using a Cochran's Q test and chi-square (χ²), respectively. For nonnormally distributed quantitative differences, the median changes of the medication use score from baseline to 4- and 8-year follow-up were tested using a Friedman (within-group) test and Mann–Whitney U test (between-group). Pearson correlation coefficients (r) were used to test the association among variables. Stepwise linear regression analysis was used to examine the strength of the associations between the MetS Z score and the other variables. Statistical analyses were performed using SPSS (IBM Corporation, Armonk, New York, USA), version 28, and the statistical significance level was set at α < 0.05.

Results

Subjects and Exercise Characteristics

A flow diagram of study participants is shown in Figure 1. All participants were white living in southern Europe and women participants comprised 27% of all subjects. Data were analysed without sex differentiation since all women were postmenopausal and were not taking hormonal replacement therapy, and their responses did not differ from men's responses in the main outcomes of the study (time × sex interaction; MetS Z score, p = 0.53; medication use score, p = 0.30; body weight [kg], p = 0.66; VO_2MAX [L·min⁻¹], p = 0.56; and W_MAX [W], p = 0.66). During the 8 years of follow-up, participants in EXERCISE attended at least 90% of the prescribed exercise sessions, and no exercise-related adverse effects were noted. Subjects declared no involvement in a regular exercise programme during the months without supervised exercise (8 months per year). There were no significant differences in calorie intake or physical activity levels between the groups at any time (all p > 0.05; see Table S1).

MetS Components and Other Health Parameters

The evolution of MetS components and related parameters during 8 years of follow-up are depicted in Table 1. A significant improvement with time was observed for HDL-cholesterol (p = 0.009), systolic blood pressure (p = 0.001) and diastolic blood pressure (p < 0.001), when both groups were pooled together. However, only a significant time × group interaction effect was found in waist circumference (p = 0.049) with a tendency to increase after 8 years in the CONTROL group (3%; 95% CI −0.02 to 6.11 cm; p = 0.053). MetS Z score was similarly reduced over time in both groups (p < 0.001) and changes from baseline between the EXERCISE and CONTROL groups were not statistically different (Figure 2A).

TABLE 1 Eight-year evolution of anthropometric, metabolic syndrome factors and other clinical variables by group. Data are presented as mean ± SD.

	EXERCISE (n = 22)	CONTROL (n = 25)	p (η2)
Baseline	4 years	8 years	Baseline	4 years	8 years	Time	Time × group
BMI (kg·m−2)	33.4 ± 4.6	32.9 ± 4.4	31.9 ± 3.8	33.5 ± 3.9	33.7 ± 4.3	33.4 ± 4.2	0.047 (0.13)	0.136 (0.09)
Weight (kg)	95.6 ± 14.1	93.8 ± 12.7	90.3 ± 11.6	92.1 ± 15.3	92.6 ± 16.1	90.9 ± 3.2	0.008 (0.20)	0.130 (0.09)
Fat mass (kg)	32.6 ± 8.3	31.3 ± 8.0	29.5 ± 7.9	33.2 ± 7.3	33.2 ± 7.5	32.7 ± 7.6	0.103 (0.10)	0.317 (0.05)
Trunk fat (kg)	19.1 ± 4.8	18.2 ± 4.2	17.4 ± 4.3	19.8 ± 4.6	19.3 ± 4.5	20.0 ± 5.0	0.169 (0.08)	0.079 (0.11)
Fat-free mass (kg)	62.9 ± 9.9	62.5 ± 9.6	60.8 ± 10.0	58.9 ± 11.5	59.5 ± 11.7	58.2 ± 11.5	0.035 (0.14)	0.308 (0.05)
Fat-free mass right leg (kg)	10.3 ± 1.8	10.7 ± 1.8	10.5 ± 1.9	9.3 ± 2.3	9.3 ± 2.3	9.1 ± 2.1	0.074 (0.11)	0.112 (0.10)
Waist circumference (cm)	109.2 ± 9.3	109.6 ± 9.0	107.9 ± 8.7	108.9 ± 9.9	110.8 ± 11.8	112.1 ± 2.2	0.425 (0.04)	0.049 (0.13)
Glucose (mg·dL−1)	118.4 ± 32.9	120.5 ± 48.5	115.1 ± 32.1	112.0 ± 21.0	118.1 ± 36.1	115.5 ± 49.8	0.561 (0.03)	0.768 (0.01)
Triglycerides (mg·dL−1)	140.8 ± 64.6	131.9 ± 45.2	144.3 ± 66.0	131.2 ± 85.3	142.7 ± 90.0	108.5 ± 44.9	0.520 (0.03)	0.053 (0.13)
HDL-c (mg·dL−1)	42.5 ± 11.1	47.0 ± 11.0	47.3 ± 10.2	43.2 ± 16.4	47.2 ± 17.2	45.4 ± 12.5	0.009 (0.19)	0.725 (0.02)
Systolic blood pressure (mmHg)	133.1 ± 16.9	127.8 ± 14.9	125.0 ± 12.7	134.4 ± 15.1	129.3 ± 14.1	123.2 ± 13.6	0.001 (0.26)	0.648 (0.02)
Diastolic blood pressure (mmHg)	81.0 ± 10.2	75.5 ± 8.7	72.9 ± 7.9	85.2 ± 11.4	81.5 ± 7.8	77.4 ± 8.3	< 0.001 (0.39)	0.736 (0.01)
MetS Z score (SD)	0.36 ± 0.60	0.07 ± 0.65	-0.01 ± 0.65	0.44 ± 0.49	0.26 ± 0.51	−0.02 ± 0.54	< 0.001 (0.36)	0.253 (0.06)
Insulin (μIU·mL−1)	13.4 ± 4.9	13.3 ± 6.8	10.7 ± 4.4	12.1 ± 4.3	12.9 ± 6.5	11.4 ± 4.9	0.003 (0.23)	0.259 (0.06)
HOMA-IR	4.0 ± 2.0	4.1 ± 2.6	3.1 ± 1.7	3.4 ± 1.3	3.7 ± 2.0	3.2 ± 1.6	0.011 (0.19)	0.228 (0.07)
T-Cholesterol (mg·dL−1)	191.6 ± 36.0	180.1 ± 35.4	180.0 ± 36.3	198.2 ± 43.2	190.2 ± 35.3	178.4 ± 43.7	0.049 (0.13)	0.435 (0.04)
LDL-c (mg·dL−1)	120.9 ± 30.1	106.8 ± 31.8	103.8 ± 35.0	128.7 ± 31.6	114.4 ± 27.8	111.2 ± 37.0	0.002 (0.24)	0.999 (0.00)
VO2MAX (L·min−1)	2.32 ± 0.66	2.52 ± 0.64a	2.50 ± 0.66	2.09 ± 0.53	2.09 ± 0.58c	1.94 ± 0.65a,b,c	0.029 (0.15)	0.011 (0.18)
VO2MAX (mL·kg·min−1)	24.4 ± 6.9	27.1 ± 7.4a	27.8 ± 7.1a	22.7 ± 4.3	22.5 ± 4.5c	21.1 ± 5.5c	0.101 (0.10)	0.002 (0.24)
Heart rate max (beat min−1)	156 ± 15	163 ± 15a	155 ± 14b	153 ± 16	150 ± 18c	147 ± 15a	0.001 (0.27)	0.020 (0.16)
Maximal power output (W)	185 ± 57	202 ± 56a	191 ± 54	170 ± 50	163 ± 51c	146 ± 51a,b,c	< 0.001 (0.35)	0.002 (0.24)
Maximal power output (W·kg)	1.9 ± 0.6	2.2 ± 0.7a	2.1 ± 0.6	1.8 ± 0.4	1.8 ± 0.4c	1.6 ± 0.4a,b,c	0.017 (0.17)	0.001 (0.28)

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Medication Use

The changes in pharmacological treatment during the 8-year follow-up are depicted in Table 2. The percentage of subjects in the CONTROL group under blood pressure-lowering (p = 0.011), lipid-lowering (p = 0.022), glucose-lowering (p = 0.022) and total medication (p = 0.011) increased from baseline after 8 years. The total number of prescribed medications increased in the CONTROL group from 4 to 8 years (p = 0.001). At 8 years of follow-up, the number of lipid-lowering (p = 0.036) and total medication (p = 0.033) were higher in CONTROL than in the EXERCISE group. The medicine use score of antihypertensive, lipid-lowering and total medicine increased above baseline after 8 years in the CONTROL (1.08; 91% increase; p = 0.016, 0.72; 233% increase; p = 0.006, and 2.27; 137% increase; p < 0.001, respectively). Changes from baseline in medicine use scores were statistically larger in CONTROL than EXERCISE groups after 4 and 8 years for lipid-lowering (p = 0.026 and p = 0.023) and total medication (p = 0.016, Figure 2B).

TABLE 2 Eight-year evolution of medication use by group. Data are presented as number of subjects taking that drug (%) and the median of medication use (IQR; interquartile range).

	EXERCISE (n = 22)	CONTROL (n = 25)
Baseline	4 years	8 years	Baseline	4 years	8 years
Total medications
Subjects under pharmacological treatment, n (%)a,b	16 (73)	17 (77)	17 (77)	12 (48)	15 (60)	18 (72)e
Number of prescribed medications, median (IQR)c,d	1.7 (1.3)	2.0 (1.3)	2.4 (3.0)	1.5 (2.5)	2.1 (2.0)	3.2 (3.0)e,f,g
Medicine use score, median (IQR)c,d	2.0 (1.9)	2.4 (1.7)	2.7 (3.4)	1.7 (2.4)	2.6 (2.6)	3.9 (3.4)e,f,g
Lipid-lowering
Subjects under pharmacological treatment, n (%)a,b	10 (45)	9 (41)	9 (41)	12 (48)	15 (60)	17 (68)e
Number of prescribed medications, median (IQR)c,d	0.5 (1.0)	0.4 (1.0)	0.4 (1.0)	0.5 (1.0)	0.6 (1.0)	0.9 (1.0)g
Medicine use score, median (IQR)c,d	0.4 (0.8)	0.4 (0.7)	0.5 (0.8)	0.3 (0.7)	0.6 (1.0)f	1.0 (1.9)e,g
Glucose-lowering
Subjects under pharmacological treatment, n (%)a,b	4 (18)	6 (27)	7 (32)	3 (12)	6 (24)	8 (32)e
Number of prescribed medications, median (IQR)c,d	0.2 (0.0)	0.4 (1.0)	0.5 (1.0)	0.3 (0.0)	0.5 (0.5)	0.7 (1.5)
Medicine use score, median (IQR)c,d	0.1 (0.0)	0.3 (0.4)	0.3 (0.4)	0.2 (0.0)	0.3 (0.2)	0.6 (0.6)
Blood pressure-lowering
Subjects under pharmacological treatment, n (%)a,b	16 (73)	17 (77)	17 (77)	12 (48)	15 (60)	18 (72)e
Number of prescribed medications, median (IQR)c,d	1.0 (1.3)	1.2 (1.3)	1.4 (1.3)	0.8 (1.0)	1.0 (2.0)	1.6 (3.0)e
Medicine use score, median (IQR)c,d	1.5 (2.0)	1.6 (2.0)	1.9 (2.6)	1.2 (2.0)	1.7 (2.3)	2.3 (3.8)e

Body Weight and Composition

The evolution in body weight and body composition in each group are depicted in Table 1. There was a significant time effect in BMI (p = 0.047), weight (p = 0.008) and fat-free mass (p = 0.035); however, there were no significant time-by-group interaction effects (p = 0.136, p = 0.130 and p = 0.308, respectively).

Cardiorespiratory Fitness and Maximal Power

CRF (i.e., VO_2MAX), maximal power output (W_MAX) and HR max (HR_MAX) evolution during 8 years of follow-up are shown in Table 1. A significant time × group interaction effect emerged for VO_2MAX (p = 0.011), W_MAX (p = 0.002) and HR_MAX (p = 0.020). The EXERCISE group improved their VO_2MAX after 4 years (9%; 95% CI 0.05 to 0.36 L·min⁻¹; p = 0.006) and after 8 years (8%; 95% CI −0.01 to 0.39 L·min⁻¹; p = 0.069). Contrarily, the CONTROL group had a significant reduction in VO_2MAX after 8 years (−7%; 95% CI −0.34 to −0.02 L·min⁻¹; p = 0.042) and from 4 to 8 years (−8%; 95% CI −0.30 to −0.01 L·min⁻¹; p = 0.038). W_MAX increased in EXERCISE after 4 years (9%; 95% CI 5 to 30 W, p = 0.002) while decreasing in the CONTROL group after 8 years (−14%; 95% CI −39 to −9 W; p = 0.001) and from 4 to 8 years (−11%; 95% CI −28 to −7 W; p < 0.001). Changes from baseline in VO_2MAX and W_MAX between the EXERCISE and CONTROL groups were statistically different at 4 years (p = 0.020) and 8 years (p = 0.009; Figure 3A,B). The CONTROL group reduced their HR_MAX after 8 years (4%; 95% CI −10 to −1 beats min⁻¹; p = 0.021) while the EXERCISE group maintained HR_MAX resulting in a significant time by group interaction (p = 0.011).

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Correlations and Multiple Regression Analysis

Stepwise linear regression model predicting the evolution of MetS Z score after 8 years included W_MAX and medication use, accounting for 31% of the variance in MetS Z score (r = 0.581; p < 0.001). Pearson correlations showed that changes in MetS Z score were significantly associated with changes in medication use score in the CONTROL group (r = 0.491; p = 0.013; Figure 4A) and with W_MAX evolution in the EXERCISE group (r = 0.613; p = 0.002; Figure 4B).

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Discussion

This study was designed to evaluate if repeated yearly exercise training maintains its health-promoting effects on the clinical management of MetS as individuals age from 50 to 60 years, a key decade where the incidence of cardiometabolic diseases rises exponentially [2]. The CONTROL group, which received lifestyle advice, demonstrated comparable improvements in their MetS Z score and body weight to those in the EXERCISE group. This result could lead to the conclusion that ageing is beneficial for the management of MetS and that yearly exercise is worthless. However, a careful record of the subject's medication revealed that the CONTROL group lowered their MetS Z score at the expense of tripling the dose of medication to control their hypertension, hyperglycaemia and dyslipidaemia. We have published prior observations of this apparent paradox [28] but wanted to extend our observations for 8 years to observe if either exercise or medicine prescription reduced their effects with ageing. The main finding is that both healthcare strategies (exercise and polymedication) are effective when used in individuals with MetS in the 50 to 60 years age group.

We developed a medication use score that allowed us to accurately examine the changes in the use of medications for the clinical control of MetS (i.e., lipid–glucose–blood pressure-lowering drugs). The finding that the CONTROL group had similar improvements in blood pressure and blood lipids as the EXERCISE group (all-time effect p < 0.05; Table 1) could be explained by the significant increase in the medication use score of antihypertensive and lipid-lowering medications (91% and 233%, respectively; Table 2), mainly represented by an increment in the use of statins, beta-blockers and diuretics in the CONTROL group (see Table S2). Thus, in the CONTROL group, we found a significant association between the improvements in MetS Z score and the increases in medication use score (r = 0.491, p = 0.013, Figure 4A). Increasing medicine intake raises the possibility of adverse side effects and drug interactions when different medicines are prescribed (polypharmacy; [30]). In addition, increasing the dose of medicine results in drug tolerance and decreases its biological effects [S50]. With long-term use of orally delivered medicines, there are risks of gastrointestinal discomfort and drug metabolism and excretion could overload liver and kidney function [S51, S52]. Lastly, polypharmacy is tied in with increased economic health costs [4]. In contrast, there was no evidence that the same exercise training dose (4 months of HIIT) repeated over the years, had less of an effect on MetS Z score reduction when individuals aged from 52 to 60 years. This is remarkable because training commitment was only 4 months per year and this dose of intense aerobic exercise, without concomitant dieting, had equivalent health effects to tripling oral medication use.

MetS is a comorbidity that is strongly associated with the development of premature frailty and polypharmacy [S53–S54]. It is therefore imperative to consider unintentional weight loss, patients' levels of physical activity and diet composition in ageing populations, as these factors are likely to be significant contributors to the onset of risk factors and frailty [31]. As risk factors accrue, the efficacy of individual medications for each component is often inadequate to achieve effective control, necessitating the administration of multiple drugs (see Table S2). As the number of medicines needed to control risk factors and complications increases, so does the potential for adverse effects—side effects, drug–drug interactions, nonadherence and medication prescription errors. Our results suggest that despite 8 years of ageing (from 50 to 60 years old), there was no change in dietary pattern (total calories and nutrient composition) or physical activity levels between groups (see Table S1). This monitoring supports our primary finding that participating in an annual intensive exercise programme while maintaining diet and physical activity reduces the deterioration of the cardiometabolic systems, delaying polypharmacy and likely preventing premature frailty.

Some studies show that intensive lifestyle interventions combining diet and exercise can result in clinically meaningful weight loss (body weight loss > 6.5% [21–23]). In these studies, individuals reduce obesity-related conditions such as diabetes, hypertension and dyslipidaemia to the point that clinicians de-prescribe some medication. In the U-TURN study, 74% of participants in the lifestyle group reduced their glucose-lowering medication after 12 months, primarily due to a 7% loss in body weight [23] in a dose–response relationship with exercise volume [S54]. However, follow-up monitoring of these individuals reveals that only 37% of the individuals in the lifestyle intervention arm of the DPP study maintained weight loss after 3 years [32], and 27% of individuals in the intensive lifestyle intervention arm of the Look AHEAD maintained weight loss after 8 years [33]. In general, it is estimated that only 20% of overweight individuals maintain weight loss after 1 year of participation in a weight loss programme [34]. Eventually, the almost unavoidable weight rebound requires the reintroduction of medication to manage cardiometabolic disease risk [35]. These findings suggest that intervention programmes involving significant weight changes do not sustain the initial efforts of patients over time [S55]. In contrast, our training programme without dietary manipulation elicited a progressive weight reduction (2% and 5% after 4 and 8 years). Due to the progressive loss of body weight, we avoided weight rebound while maintaining medicine use from significantly increasing during the 8 years that data collection lasted.

A cross-sectional study shows that high muscular strength and cardiorespiratory fitness levels are independently and inversely associated with MetS prevalence [36]. Muscle strength level represents a robust predictor of mortality as individuals age [12], and muscle power is related to independence in daily living activities in older individuals [S56] reasons why some have regarded muscle power as the best clinical hallmark of ageing. Literature evidences a natural reduction of leg muscle power of 1.1%–1.4% per year in middle-aged individuals (40–60 years; [37]). Coinciding with those studies, the CONTROL group decreased 4% and 14% leg cycling muscle power in 4 and 8 years, respectively. However, the ageing-induced decline in leg muscle power disappeared when these middle-aged MetS patients were involved in a 4-month yearly cycling exercise training intervention. Moreover, we have found that MetS improvements (i.e., Z score) were associated with muscle power gains following training (r = 0.613, p = 0.002, Figure 4B), which aligns with results from previous studies using cross-sectional data [36]. Therefore, MetS patients benefit from exercise training in their cardiometabolic systems along with protection from age-induced muscle power decline.

Physical fitness is considered a strong risk factor for chronic disease that is not routinely assessed in clinical practice, and CRF is one of the best predictors of longevity [38]. CRF inevitably declines with age, but the rate of decline accelerates after age 45 years, influenced by factors such as sex, physical activity and body composition [S57]. Metabolic disease and likely MetS reduce CRF improvements with aerobic training [S58]. Therefore, our finding that CRF increased by 14% (3.4 mL·kg⁻¹·min⁻¹; 1MET; Table 1) after 8 years of follow-up with a 4-month high-intensity aerobic exercise intervention supports the yearly trainability of individuals with MetS, reverses of the expected declines in CRF with age (see Figure S1, Electronic Supporting Information). The EXERCISE group in 8 years of training, increased by 1 MET their CRF which is associated with an 11% reduction in all-cause mortality [39]. In addition, many of them entered the 9.0 METs category, which is associated with a 50% reduction in mortality risk [40], these findings are potentially important and public health providers should emphasize improvements in population CRF. Our study is not long enough to analyse all-cause mortality but according to previous data, EXERCISE treatment may be delaying the incidence of major adverse cardiovascular events.

The present study has limitations and strengths worth mentioning. In this RCT, we studied a relatively small sample (n = 47) of individuals with MetS which could bring doubt about the clinical relevance of the findings. Although there are ageing studies measuring health variables in athletes (mostly runners) as they became master athletes, few have a control group, and almost none focused on a sample of individuals with cardiometabolic disease. However, in this population, exercise may have the largest impact on reducing the progression of their cardiometabolic disease as they age. We present a myriad of hard clinical health variables (i.e., blood pressure, body composition, carbohydrate and lipid blood profile, muscle power and cardiovascular fitness). Still, we did not take muscle biopsies to study cell signalling or do more detailed genetic blood analysis to investigate by which mechanisms exercise slows ageing. In turn, the major strength of the study is that we conducted an 8-year-long randomized controlled trial, which allows us to assess the sustainability of the health benefits of exercise based on the highest level of evidence. Although lifestyle interventions have been demonstrated to be effective at improving health in the context of experiments, it is crucial to ensure their sustained effects over the years if they are to have a meaningful impact on public health.

In this study, we followed during 8 years a group of individuals with MetS while in a randomized fashion, we allocated them either into a supervised yearly intense exercise-training programme or remained with their normal activity pattern. Paradoxically, both groups similarly improved their MetS Z score (a compound of all cardiometabolic risk factors). A closer analysis of the data revealed that the nonexercising CONTROL group reduced their MetS Z score at the expense of tripling their oral medication (Table 2 and Figure 2B). This evidence a worsening of their disease that had to be compensated by increasing pharmacological therapy. On the other hand, the EXERCISE group did not need to increase medication in 8 years to improve their MetS. The factor that better predicted MetS evolution was leg cycling power in the EXERCISE group while it was medicine use score in the CONTROL group (Figure 4A,B). In summary, our data suggest that individuals with cardiometabolic disease, who do not exercise regularly as they age, render the control of their disease to pharmacological treatment alone. Lastly, our data suggest that exercise training has similar clinical power to tripling oral medication to control MetS as individuals age 50 to 60 years.

Acknowledgements

The study received support from the Spanish Ministry of Economy, Industry and Competivity (DEP-2017-83244-R) and Spanish Ministry of Science and Innovation (PID2020-116159RB-IOO MCIN/AEI/10.13039/501100011033). The granting agencies have no role in the design, execution or reporting of the results of this study. The authors acknowledge the invaluable contribution of the subjects of the study.

Conflicts of Interest

The authors declare no conflicts of interest.

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