Individual Variability in Waist Circumference and Body Weight in Response to Exercise

Abstract

Purpose This study aimed to determine the magnitude of exercise-induced individual variability for waist circumference (WC) and body weight change after accounting for biological variability and measurement error. Determinants of response variability were also considered. Methods Participants (53 ± 7.5 yr) were 181 adults (61% women) with abdominal obesity randomized to the following: control; low-amount, low-intensity exercise (LALI); high-amount, low-intensity exercise (HALI); or high-amount, high-intensity exercise (HAHI) for 24 wk. Unstructured physical activity was measured by accelerometer. The variability in response to exercise for WC and body weight (SDR) was isolated by subtracting the SD values for the change scores in the exercise group from that of the control group. Results The variability of response due to exercise (SDR) for change in WC was 3.1, −0.3, and 3.1 cm for LALI, HALI, and HAHI groups, respectively. Corresponding values for body weight were 3.8, 2.0, and 3.5 kg for LALI, HALI, and HAHI, respectively. The high-amount exercise groups yielded the highest proportion of individuals with a clinically meaningful response. No variables predicted the response to exercise (P > 0.05). Conclusions Substantial variability in response to standardized exercise was observed for change in both WC and body weight after accounting for the variability not attributed to exercise. Potential determinants of the interindividual variability in response to exercise remain unclear.

Prevalence of responders for hepatic fat, adiposity and liver enzyme levels in response to a lifestyle intervention in children with overweight/obesity: EFIGRO randomized controlled trial

“…Occasionally, some studies have compared the prevalence of responders or non‐responders between different exercise intervention programs with the aim of knowing the most appropriate an effective design for the prevention/treatment of obesity or other obesity‐related comorbidities. Several studies in adults provided data of the interindividual variability in variables such as body composition or other health outcomes, while there is scarce evidence in the pediatric population . Our group has shown that the addition of supervised exercise to a family‐based lifestyle education program resulted in significantly greater reduction of percentage HF (≈20%) in children with overweight/obesity .…”

“…Interindividual variability exists after pharmacological, nutritional, or exercise interventions: whereas some participants improve in one or several outcomes after an intervention (responders), others do not change or even worsen their response (non‐responders) to the intervention . However, this information is rarely provided, and the vast majority of published studies only report the results as overall mean values .…”

“…Previous studies have identified genes, metabolic or behavioral responses, or diet and physical activity changes as potential determinants of interindividual variability. However, little is known about the role of changes in physical fitness after an intervention on interindividual variability.…”

Issues in the determination of ‘responders’ and ‘non‐responders’ in physiological research

“…Note in Table 1 and Figure 1 how the group differences in the observed mean response lead to group differences in the observed numbers of responders, adverse responders and trivial responders (according to a response threshold of 5 ml kg −1 min −1 and an adverse response threshold of −5 ml kg −1 min −1 ). Therefore, although researchers have made inferences relating to response heterogeneity or 'trainability' on the basis of such 'responder counts' (Bonafiglia, Ross, & Gurd, 2019;Hammond et al, 2019;Ross, de Lannoy, & Stotz, 2015;Williams et al, 2019), it is in fact the group differences in mean treatment response that explain the differences in responder counts between our groups (Figure 1), besides the fact that the responder counts cannot be correct in the first place. Therefore, such group comparisons of responder counts do not provide much information about response heterogeneity, as defined in the context of precision medicine (Section 2).…”

“…Recently, Hammond et al (2019) speculated that the SD of change comparison approach is 'questionable' when 'the control group is contaminated with other sources of variability, beyond that of which is random' . This statement denotes a lack of appreciation of the difference between systematic and random sources of variance.…”