Hypertension is the most common, costly, and preventable cardiovascular disease risk factor. Numerous professional organizations and committees recommend exercise as initial lifestyle therapy to prevent, treat, and control hypertension. Yet, these recommendations differ in the components of the Frequency, Intensity, Time, and Type (FITT) principle of exercise prescription (Ex R_x); the evidence upon which they are based is only of fair methodological quality; and the individual studies upon which they are based generally do not include people with hypertension, which are some of the limitations in this literature. The purposes of this review are to (1) overview the professional exercise recommendations for hypertension in terms of the FITT principle of Ex R_x; (2) discuss new and emerging research related to Ex R_x for hypertension; and (3) present an updated FITT Ex R_x for adults with hypertension that integrates the existing recommendations with this new and emerging research.

Blood pressure (BP) is immediately lowered after a session of dynamic exercise, e.g. postexercise hypotension (PEH). The optimal exercise intensity needed to evoke PEH has not been established. We examined the effect of light (LITE) and moderate (MOD) exercise intensity on PEH. Subjects were 49 men (mean ± SEM, 43.8 ± 1.4 years) with high normal to stage 1 hypertension (145.0 ± 1.5/85.8 ± 1.1 mmHg). Men randomly completed three blinded experiments: a control session and two cycle exercise bouts, one at 40% (LITE) and the other at 60% (MOD) of maximal oxygen consumption. Experiments began with a baseline period and were conducted at the same time of day and separated by ≥ 2 days. Subjects wore an ambulatory BP monitor after the experiments. Repeated measure analysis of variance (ANOVA) tested if BP and heart rate differed over time and between experimental conditions. Multivariate regression tested factors related to the BP response. For 9 h after all experiments, average awake systolic blood pressure (SBP) increased and diastolic blood pressure (DBP) decreased compared with baseline (P < 0.001). Average awake SBP increased up to 6.9 mmHg less (P < 0.001) and DBP decreased 2.6 mmHg more (P < 0.05) after exercise versus control. For 5 h, PEH was greater after MOD; but over the course of 9 h, LITE was as effective as MOD in eliciting PEH. Baseline BP was the primary factor explaining the BP response (β = −0.434 to −0.718, r 2 = 0.096–0.295). LITE and MOD evoked PEH throughout the daytime hours. Lower intensity dynamic exercise such as walking, contributes to BP control in men with hypertension.

Background: Regular physical activity is critical for health and disease prevention. Yet, health care providers and patients face barriers to implement evidence-based lifestyle recommendations. The potential to augment care with the increased availability of artificial intelligence (AI) technologies is limitless; however, the suitability of AI-generated exercise recommendations has yet to be explored. Objective: The purpose of this study was to assess the comprehensiveness, accuracy, and readability of individualized exercise recommendations generated by a novel AI chatbot. Methods: A coding scheme was developed to score AI-generated exercise recommendations across ten categories informed by gold-standard exercise recommendations, including (1) health condition–specific benefits of exercise, (2) exercise preparticipation health screening, (3) frequency, (4) intensity, (5) time, (6) type, (7) volume, (8) progression, (9) special considerations, and (10) references to the primary literature. The AI chatbot was prompted to provide individualized exercise recommendations for 26 clinical populations using an open-source application programming interface. Two independent reviewers coded AI-generated content for each category and calculated comprehensiveness (%) and factual accuracy (%) on a scale of 0%-100%. Readability was assessed using the Flesch-Kincaid formula. Qualitative analysis identified and categorized themes from AI-generated output. Results: AI-generated exercise recommendations were 41.2% (107/260) comprehensive and 90.7% (146/161) accurate, with the majority (8/15, 53%) of inaccuracy related to the need for exercise preparticipation medical clearance. Average readability level of AI-generated exercise recommendations was at the college level (mean 13.7, SD 1.7), with an average Flesch reading ease score of 31.1 (SD 7.7). Several recurring themes and observations of AI-generated output included concern for liability and safety, preference for aerobic exercise, and potential bias and direct discrimination against certain age-based populations and individuals with disabilities. Conclusions: There were notable gaps in the comprehensiveness, accuracy, and readability of AI-generated exercise recommendations. Exercise and health care professionals should be aware of these limitations when using and endorsing AI-based technologies as a tool to support lifestyle change involving exercise.

To examine associations among the angiotensin I-converting enzyme (ACE) insertion (I)/deletion (D) polymorphism and the response to a 12-wk (2 d.wk) unilateral, upper-arm resistance training (RT) program in the trained (T, nondominant) and untrained (UT, dominant) arms. Subjects were 631 (mean+/-SEM, 24.2+/-0.2 yr) white (80%) men (42%) and women (58%). The ACE ID genotype was in Hardy-Weinberg equilibrium with frequencies of 23.1, 46.1, and 30.8% for ACE II, ID, and DD, respectively (chi=1.688, P=0.430). Maximum voluntary contraction (MVC) and one-repetition maximum (1RM) assessed peak elbow flexor muscle strength. Magnetic resonance imaging measured biceps muscle cross-sectional area (CSA). Multiple variable and repeated-measures ANCOVA tested whether muscle strength and size differed at baseline and pre- to post-RT among T and UT and ACE ID genotype. Baseline muscle strength and size were greater in UT than T (Por= 0.05). In T, MVC increases were greater for ACE II/ID (22%) than DD (17%) (Por= 0.05). In UT, MVC increased among ACE II/ID (7%) (Por= 0.05). In UT, 1RM (11%) and CSA (2%) increases were greater for ACE DD/ID than ACE II (1RM, 7%; CSA, -0.1%) (P<0.05). ACE ID genotype explained approximately 1% of the MVC response to RT in T and approximately 2% of MVC, 2% of 1RM, and 4% of CSA response in UT (P<0.05). ACE ID genotype is associated with the contralateral effects of unilateral RT, perhaps more so than with the muscle strength and size adaptations that result from RT.

Objective: To evaluate the effects of resistance training on cardiometabolic health-related outcomes in patients with type 2 diabetes mellitus (T2DM) and overweight/obesity. Design: Systematic review and meta-analysis of randomised controlled trials (RCTs). Data sources: PubMed, Web of Science, Scopus, Science Direct, Cochrane Library and Google Scholar databases were searched from inception up to May 2024. The search strategy included the following keywords: diabetes, resistance exercise and strength training. Eligibility criteria for selecting studies: RCTs published in English comparing resistance training alone with non-exercising standard treatment. Participants were adults diagnosed with T2DM and concurrent overweight/obesity (body mass index (BMI) ≥25 kg/m²). Results: A total of 18 RCTs qualified involving 1180 patients (48.6/51.4 female/male ratio; 63.3±7.0 years; 29.3±4.3 kg/m²). Waist circumference (standardised mean differences (SMD) −0.85 cm, 95% CI −1.66 to −0.04), waist-to-hip ratio (SMD −0.72, 95% CI −1.30 to −0.15), high-density lipoprotein cholesterol (SMD +0.40 mg/dL, 95% CI 0.07 to −0.72), triglycerides (SMD −0.54 mg/dL, 95% CI −1.06 to −0.02), fasting blood glucose (SMD −0.65 mmol/L, 95% CI −1.19 to −0.12), fasting insulin (SMD −0.74 uIU/mL, 95% CI −1.12 to −0.36) and glycated haemoglobin (SMD −0.32%, 95% CI −0.63 to −0.01) improved compared with standard treatment. The risk of bias was low to unclear, and the quality of evidence was very low to moderate. Conclusions: Resistance training as a standalone exercise intervention in the management and treatment of T2DM with concurrent overweight/obesity is associated with many cardiometabolic benefits when compared with standard treatment without exercise. PROSPERO registration number: CRD42022355612.