Prevalence of Non-responders for Glucose Control Markers after 10 Weeks of High-Intensity Interval Training in Adult Women with Higher and Lower Insulin Resistance

Abstract

Background: Exercise training improves performance and biochemical parameters on average, but wide interindividual variability exists, with individuals classified as responders (R) or non-responders (NRs), especially between populations with higher or lower levels of insulin resistance. This study assessed the effects of high-intensity interval training (HIIT) and the prevalence of NRs in adult women with higher and lower levels of insulin resistance.Methods: Forty adult women were assigned to a HIIT program, and after training were analyzed in two groups; a group with higher insulin resistance (H-IR, 40 ± 6 years; BMI: 29.5 ± 3.7 kg/m2; n = 20) and a group with lower insulin resistance (L-IR, 35 ± 9 years; 27.8 ± 2.8 kg/m2; n = 20). Anthropometric, cardiovascular, metabolic, and performance variables were measured at baseline and after 10 weeks of training.Results: There were significant training-induced changes [delta percent (Δ%)] in fasting glucose, fasting insulin, and homeostasis model assessment of insulin resistance (HOMA-IR) scores in the H-IR group (−8.8, −26.5, −32.1%, p < 0.0001), whereas no significant changes were observed in the L-IR. Both groups showed significant pre-post changes in other anthropometric variables [waist circumference (−5.2, p < 0.010, and −3.8%, p = 0.046) and tricipital (−13.3, p < 0.010, and −13.6%, p < 0.0001), supra-iliac (−19.4, p < 0.0001, and −13.6%, p < 0.0001), and abdominal (−18.2, p < 0.0001, and −15.6%, p < 0.010) skinfold measurements]. Systolic blood pressure decreased significantly only in the L-IR group (−3.2%, p < 0.010). Both groups showed significant increases in 1RMLE (+12.9, p < 0.010, and +14.7%, p = 0.045). There were significant differences in the prevalence of NRs between the H-IR and L-IR groups for fasting glucose (25 vs. 95%, p < 0.0001) and fasting insulin (p = 0.025) but not for HOMA-IR (25 vs. 45%, p = 0.185).Conclusion: Independent of the “magnitude” of the cardiometabolic disease (i.e., higher vs. lower insulin resistance), no differences were observed in the NRs prevalence with regard to improved HOMA-IR or to anthropometric, cardiovascular, and muscle performance co-variables after 10 weeks of HIIT in sedentary adult women. This research demonstrates the protective effect of HIIT against cardiometabolic disease progression in a sedentary population.

Ejercicio físico en pacientes con diabetes e hipertensión: prevalencia de respondedores y no respondedores para mejorar factores de riesgo cardiometabólicos

“…Aunque factores genéticos 13 , y ambientales [14][15][16] han sido escuetamente explorados, aún no se identifican los potenciales factores ambientales que dan cuenta de este fenómeno. Descartando la influencia genética que varía individualmente, no está del todo claro qué parámetros de salud, por ejemplo, composición corporal, presión arterial o marcadores metabólicos como los triglicéridos, presentan mayor o menor prevalencia de sujetos no respondedores en la población adherente a ejercicio.…”

Moving beyond threshold-based dichotomous classification to improve the accuracy in classifying non-responders

“…The current study demonstrated how recently proposed statistical approaches (Hopkins 2000b;Swinton et al 2018) can be used to improve the confidence when classifying non-responders. The major novel findings are: 1) despite its growing popularity in the individual response literature (Scharhag-Rosenberger et al 2012;Astorino and Schubert 2014;Ross et al 2015;Gurd et al 2016;Alvarez et al 2017;de Lannoy et al 2017;Montero and Lundby 2017;Astorino TA et al 2018), threshold-based dichotomous classification approaches misclassify individuals who have a high probability of a positive response as non-responders, and 2) using response CIs with zeroand/or SWC-based thresholds provides more information than dichotomous classification approaches regarding an individual's response. Application of these statistical approaches has the potential to improve evidenceinformed exercise prescription decision-making.…”

“…Much of the recent literature has dichotomously classified individuals as either "responders" or "non-responders" using a pre-determined threshold (Scharhag-Rosenberger et al 2012;Astorino and Schubert 2014;Ross et al 2015;Montero and Lundby 2017) including two times the typical error (2x TE) (Bouchard et al 2012;Bonafiglia et al 2016;Gurd et al 2016;Raleigh et al 2016;Alvarez et al 2017;de Lannoy et al 2017;Astorino TA et al 2018). Although 2x TE is a relatively robust threshold for the classification of "responders" (i.e., the true change for observed responses >29 TE above zero is >90% likely to be positive) (Hopkins 2000a), dichotomous classification of "non-responders" has significant limitations.…”

“…Although 2x TE is a relatively robust threshold for the classification of "responders" (i.e., the true change for observed responses >29 TE above zero is >90% likely to be positive) (Hopkins 2000a), dichotomous classification of "non-responders" has significant limitations. First, dichotomous classification fails to consider the continuous range of probabilities of a positive response and almost certainly misclassifies individuals as "non-responders;" and second, 2x TE has typically been applied relative to zero Gurd et al 2016;Raleigh et al 2016;Alvarez et al 2017;de Lannoy et al 2017;Astorino TA et al 2018), which fails to consider "non-response" within the context of meaningful benefit (Swinton et al 2018).…”

Interindividual responses to different exercise stimuli among insulin‐resistant women

“…For instance, some individuals show improvements with exercise training (eg, decrease in fasting glucose) and are considered responders , whereas others may not have such a response (eg, no change or even increases in fasting glucose) and are considered non‐responders . Individual variability has been reported mainly regarding fitness‐related variables, and in response to moderate‐intensity endurance (ET), resistance (RT), or high‐intensity interval training (HIT), and also in different age groups such as children, adults, or older populations, The existence of non‐responders for glucose homeostasis‐related variables has been confirmed more recently . In the present study, we confirmed a wide interindividual variability that is independent of the training‐induced changes after HIT, RT, or CT with regard to 20 outcomes and risk parameters, including 9 body composition, 3 cardiovascular, 3 metabolic, and 5 performance parameters.…”