Exercise blood pressure and heart rate responses to graded exercise testing in intermediate versus morning chronotypes with obesity

Intermediate versus morning chronotype has lower vascular insulin sensitivity in adults with obesity

AIM

Chronotype reflects a circadian rhythmicity that regulates endothelial function. While the morning chronotype (MORN) usually has low cardiovascular disease risk, no study has examined insulin action on endothelial function between chronotypes. We hypothesized intermediate chronotypes (INT) would have lower vascular insulin sensitivity than morning chronotype (MORN).

MATERIALS AND METHODS

Adults with obesity were classified per Morningness-Eveningness Questionnaire (MEQ) as either MORN (n = 27, 22 female, MEQ = 63.7 ± 4.7, 53.8 ± 6.7 years, 35.3 ± 4.9 kg/m2) or INT (n = 29, 23 female, MEQ = 48.8 ± 6.7, 56.6 ± 9.0 years, 35.7 ± 6.1 kg/m2). A 120 min euglycaemic-hyperinsulinaemic clamp (40 mU/m2/min, 90 mg/dl) was conducted to assess macrovascular insulin sensitivity via brachial artery flow-mediated dilation (%FMD; conduit artery), post-ischaemic flow velocity (resistance arteriole), as well as microvascular insulin sensitivity via contrast-enhanced ultrasound [e.g. microvascular blood volume (perfusion)]. Fasting plasma arginine and citrulline, as well as fasting and clamp-derived plasma endothelin-1 and nitrate/nitrite, were assessed as surrogates of vasoconstriction and nitric oxide-mediated vasodilation. Aerobic fitness (VO2max) and body composition (dual-energy X-ray absorptiometry) were also collected.

RESULTS

MORN had a higher VO2max compared with INT (p < .01), although there was no difference in fat mass. While fasting FMD was similar between groups, insulin lowered FMD corrected to shear stress and microvascular blood volume in INT compared with MORN after co-varying for VO2max (both p ≤ .02). INT also had a lower fasting nitrate (p = .03) and arginine (p = .07). Higher MEQ correlated with elevated FMD (r = 0.33, p = .03) and lower post-ischaemic flow velocity (r = -0.33, p = .03) as well as shear rate (r = -0.36, p = .02) at 120 min.

CONCLUSION

When measured during the morning, INT had a lower vascular insulin sensitivity than MORN. Additional work is needed to understand endothelial function differences among chronotypes to optimize cardiovascular disease risk reduction.

Impact of Insulin-Induced Relative Hypoglycemia on Vascular Insulin Sensitivity and Central Hemodynamics in Prediabetes

CONTEXT

Relative hypoglycemia (RH) is linked to sympathetic responses that can alter vascular function in individuals with type 2 diabetes. However, less is known about the role of RH on hemodynamics or metabolic insulin sensitivity in prediabetes.

OBJECTIVE

Determine if RH alters peripheral endothelial function or central hemodynamics to a greater extent in those with prediabetes (PD) versus normoglycemia (NG).

METHODS

Seventy adults with obesity were classified using ADA criteria as PD (n=34 (28F); HbA1c=6.02±0.1%) or NG (n=36 (30F); HbA1c=5.4±0.0%). Brachial artery endothelial function, skeletal muscle capillary perfusion, and aortic waveforms were assessed at 0 and 120min of a euglycemic clamp (40 mU/m2/min, 90 mg/dl). Plasma nitrate/nitrite and endothelin-1 (ET-1) were measured as surrogates of nitric oxide-mediated vasodilation and vasoconstriction, respectively. RH was defined as the drop in glucose (%) from fasting to clamp steady state.

RESULTS

There were no differences in age, weight, or VO2max between groups. PD had higher HbA1c (P<0.01) and a greater drop in glucose in response to insulin (14 vs. 8%; P=0.03). Further, heart rate (HR) increased in NG compared to PD (P<0.01), while forward wave (Pf) decreased in PD (P=0.04). Insulin also tended to reduce arterial stiffness (cfPWV) in NG versus PD (P=0.07), despite similar increases in pre-occlusion diameter (P=0.02), blood flow (P=0.02), and lower augmentation index (AIx75) (P≤0.05).

CONCLUSION

Compared with NG, insulin-induced RH corresponded with a blunted rise in HR and drop in Pf during insulin infusion in adults with PD, independent of changes in peripheral endothelial function.

Using artificial intelligence for exercise prescription in personalised health promotion: A critical evaluation of OpenAI's GPT-4 model

The rise of artificial intelligence (AI) applications in healthcare provides new possibilities for personalized health management. AI-based fitness applications are becoming more common, facilitating the opportunity for individualised exercise prescription. However, the use of AI carries the risk of inadequate expert supervision, and the efficacy and validity of such applications have not been thoroughly investigated, particularly in the context of diverse health conditions. The aim of the study was to critically assess the efficacy of exercise prescriptions generated by OpenAI's Generative Pre-Trained Transformer 4 (GPT-4) model for five example patient profiles with diverse health conditions and fitness goals. Our focus was to assess the model's ability to generate exercise prescriptions based on a singular, initial interaction, akin to a typical user experience. The evaluation was conducted by leading experts in the field of exercise prescription. Five distinct scenarios were formulated, each representing a hypothetical individual with a specific health condition and fitness objective. Upon receiving details of each individual, the GPT-4 model was tasked with generating a 30-day exercise program. These AI-derived exercise programs were subsequently subjected to a thorough evaluation by experts in exercise prescription. The evaluation encompassed adherence to established principles of frequency, intensity, time, and exercise type; integration of perceived exertion levels; consideration for medication intake and the respective medical condition; and the extent of program individualization tailored to each hypothetical profile. The AI model could create general safety-conscious exercise programs for various scenarios. However, the AI-generated exercise prescriptions lacked precision in addressing individual health conditions and goals, often prioritizing excessive safety over the effectiveness of training. The AI-based approach aimed to ensure patient improvement through gradual increases in training load and intensity, but the model's potential to fine-tune its recommendations through ongoing interaction was not fully satisfying. AI technologies, in their current state, can serve as supplemental tools in exercise prescription, particularly in enhancing accessibility for individuals unable to access, often costly, professional advice. However, AI technologies are not yet recommended as a substitute for personalized, progressive, and health condition-specific prescriptions provided by healthcare and fitness professionals. Further research is needed to explore more interactive use of AI models and integration of real-time physiological feedback.

Early chronotype favors appetite and reduced later day caloric intake among adults with obesity

Late chronotype (LC) is related to obesity and altered food intake throughout the day. But whether appetite perception and gut hormones differ among chronotypes is unclear. Thus, we examined if early chronotype (EC) have different appetite responses in relation to food intake than LC. Adults with obesity were categorized using the Morningness-Eveningness Questionnaire (MEQ) as either EC (n = 21, 18F, MEQ = 63.9 ± 1.0, 53.7 ± 1.2 yr, 36.2 ± 1.1 kg/m2) and LC (n = 28, 24F, MEQ = 47.2 ± 1.5, 55.7 ± 1.4 yr, 37.1 ± 1.0 kg/m2). Visual analog scales were used during a 120 min 75 g oral glucose tolerance test (OGTT) at 30 min intervals to assess appetite perception, as well as glucose, insulin, GLP-1 (glucagon-like polypeptide-1), GIP (glucose-dependent insulinotrophic peptide), PYY (protein tyrosine tyrosine), and acylated ghrelin. Dietary intake (food logs), resting metabolic rate (RMR; indirect calorimetry), aerobic fitness (maximal oxygen consumption (VO2max)), and body composition dual-energy X-ray absorptiometry (DXA) were also assessed. Age, body composition, RMR, and fasting appetite were similar between groups. However, EC had higher satisfaction and fullness as well as reduced desires for sweet, salty, savory, and fatty foods during the OGTT (P <0.05). Only GIP tAUC0-120 min was elevated in EC versus LC (p = 0.01). Daily dietary intake was similar between groups, but EC ate fewer carbohydrates (p = 0.05) and more protein (p = 0.01) at lunch. Further, EC had lower caloric (p = 0.03), protein (p = 0.03) and fat (p = 0.04) intake during afternoon snacking compared to LC. Dietary fat was lower, and carbohydrates was higher, in EC than LC (p = 0.05) at dinner. Low glucose and high insulin as well as GLP-1 tAUC60-120 min related to desires for sweet foods (p < 0.05). Taken together, EC had more favorable appetite and lower caloric intake later in the day compared with LC.