Bidirectional associations between adiposity and physical activity: a longitudinal study from pre-puberty to early adulthood

ObjectiveThis study aimed to investigate directional influences in the association between adiposity and physical activity (PA) from pre-puberty to early adulthood.MethodsIn the Calex-study, height, weight, body fat and leisure-time physical activity (LTPA) were measured at age11.2-years, 13.2-years and 18.3-years in 396 Finnish girls. Body fat was measured by dual-energy X-ray absorptiometry, calculating fat mass index (FMI) as total fat mass in kilograms divided by height in meters squared. LTPA level was evaluated using a physical activity questionnaire. In the European Youth Heart Study (EYHS), height, weight and habitual PA were measured at age 9.6-years, 15.7-years and 21.8-years in 399 Danish boys and girls. Habitual PA and sedentary behaviour were assessed with an accelerometer. Directional influences of adiposity and PA were examined using a bivariate cross-lagged path panel model.ResultsThe temporal stability of BMI from pre-puberty to early adulthood was higher than the temporal stability of PA or physical inactivity over the same time period both in girls and boys. In the Calex-study, BMI and FMI at age 11.2-years were both directly associated with LTPA at age 13.2-years (β = 0.167, p = 0.005 and β = 0.167, p = 0.005, respectively), whereas FMI at age 13.2-years showed an inverse association with LTPA at age 18.3-years (β = - 0.187, p = 0.048). However, earlier LTPA level was not associated with subsequent BMI or FMI. In the EYHS, no directional association was found for physical inactivity, light-, moderate-, and vigorous-PA with BMI during the follow-up in girls. In boys, BMI at age 15.7-years was directly associated with moderate PA (β = 0.301, p = 0.017) at age 21.8-years, while vigorous PA at age 15.7-years showed inverse associations with BMI at age 21.8-years (β = - 0.185, p = 0.023).ConclusionOur study indicates that previous fatness level is a much stronger predictor of future fatness than level of leisure-time or habitual physical activity during adolescence. The directional associations between adiposity and physical activity are not clear during adolescence, and may differ between boys and girls depending on pubertal status

PO-279 Bidirectional Associations Between Physical Activity and Adiposity From Childhood to Early Adulthood

Objective Inverse association between physical activity and adiposity in children and adolescents have been documented in numerous studies. However, few studies have examined the direction of causation between these two variables. We aimed to examine the prospective bidirectional associations between physical activity and adiposity from childhood to early adulthood. Methods A total of 396 girls (mean age, 11.2 years at baseline) participated in a longitudinal study with 1, 2, 4, and 7 year follow-ups. Body height and weight were measured, body composition was assessed by DXA and BMI and fat mass index (FMI) were calculated. Leisure-time physical activity (LTPA) and physical inactivity was obtained from questionnaire and physical activity score and inactivity time was calculated. A bivariate cross-lagged panel model was used to estimate the bidirectional associations between physical activity and measures of adiposity across follow-up waves. We further examined whether persistently high or persistently low physical activity or change of physical activity level from low to high and high to low during pubertal years had differential effects on adiposity. For this, the study participants were first divided into two groups according to the median values of their LTPA scores at baseline and at the 7 year follow-up visit. Then four activity groups were formed: consistently high (CH), consistently low (CL), change from high to low (HL), and change from low to high (LH). Analysis of variance (ANOVA) with least significant difference post hoc test was used to compare differences in adiposity between the LTPA groups. Results BMI at each measurement wave strongly predicted subsequent BMI (standardized path coefficients ranged from 0.87 to 0.95, p < 0.001 for all). Similar pattern was observed for LTPA and physical inactivity, though the path coefficients tended to be notably smaller. This auto-regressive part of the model indicates that the temporal stability of BMI from childhood to early adulthood is higher than the temporal stability of LTPA or physical inactivity over the same time period. The cross-lagged effects indicated that higher BMI at baseline and at 4-year follow-up predicted lower LTPA at 2-year and 7-year follow-ups, respectively (p<0.05 for both), but LTPA did not predict subsequent BMI at any time point. Similarly, higher FMI at baseline and at 2-year follow-up predicted lower LTPA at subsequent follow-up waves (p<0.05 for both). No associations were found between sedentary time and adiposity between any time points. The difference in participation in LTPA between consistently high and consistently low PA groups were on average 4 hours per week (p<0.001); however, no significant difference in FMI was found at baseline, 2-year or 7-year follow-up). Similarly, no significant difference in FMI was found between the groups whose LTPA level changed from high to low or from low to high.  Conclusions Our results suggest that reduced physical activity in children and adolescents is the result of increased fatness rather than its cause. Current physical activity recommendations may not be sufficient to combat pediatric obesity

PO-168 Reliability and validity of a new accelerometer-based device for detecting physical activities and energy expenditure

Objective Objective assessments of sedentary behavior, physical activity (PA) and the associated energy expenditure (EE) using accelerometer-based wearable devices are ever expanding, given their importance in the global context of health maintenance. However, among these numerous devices, the different underlying algorithms and available output parameters make it difficult to determine their accuracy. Furthermore, the function and accuracy of those devices may significantly differ between the different wearing locations (i.e., wrist-worn, waist-worn or thigh-based), where the center of the body (hip or thigh) is the optimal recommendation. Thus, a thigh-based device that has the possibility to differentiate between sedentary behavior, PAs, and EE is required to optimize research in PA. This study aimed to determine the reliability and validity of a new accelerometer-based analyzer (Fibion) with two-fold: First, to assess the reliability of the Fibion as compared to a designed repeated protocol and ActiGraph GT9X (one of the most widely used devices with favorable validity and reliability) in a laboratory re-test protocol; Second, to determine the validity of the Fibion in differentiating PAs and estimating EE throughout a simulated 12-hour free-living day. Methods Fibion (Fibion Inc, Jyväskylä, Finland) is a new 3-axial lightweight (20g, L•W•T = 30•32•10mm) accelerometer-based device, which was designed to follow the orientation and movement of the thigh. Thus, it can be worn either on the thigh (FT) or in the front pocket of the trousers (FP). According to information provided by the manufacturer, it is able to detect no-wear time and differentiates between different types (sitting, long sitting, standing, walking, and cycling) and intensities (LPA, MVPA, and VPA) of PA and the associated EE through the use of proprietary algorithms. The study consisted of two parts: a reliability (n=18) and validity (n=19) test, respectively. All 37 participants were young and healthy volunteers, who were normal weight (i.e., BMI < 25 kg/m2) and recreationally physically active. Exclusion criteria included acute and chronic diseases, which would prevent participants from prolonged sitting and/or standing or would interfere with the basic metabolic rate. All participants were informed about the study procedures and provided written informed consent prior to commencing with testing. The study was carried out in accordance with the Declaration of Helsinki and the local Ethical Committee (ML16027). Reliability was assessed by a designed 15-min protocol by repeating sitting, standing, and walking (a total of 90 min = 15 min *3 types * 2 repeats) using both Fibion (FT) and ActiGraph. Validity was assessed by a prolonged 12-h protocol which was designed as simulated free-living conditions with two criteria. Criterion 1: Direct observation of the 12-h continuous sequence of tasks with measurement logs, to determine the duration of different types (sitting, standing, walking, and cycling) and intensities (light [LPA], moderate-to-vigorous [MVPA], and vigorous [VPA])) of PA. Indirect calorimetry served as the criterion 2 for EE estimation. Pulmonary gas exchange of the participants was continuously measured throughout the 12-h guided sequence of tasks by a portable breath-by-breath gas analyzer (Cosmed K4b2, Rome, Italy). During the entire 12-h protocol, two Fibion devices (worn both on the thigh (FT) and in the pocket (FP), respectively) and K4b2 were used simultaneously.  Results Reliability. Fibion located on the thigh (FT) (ICCs: 0.687-0.806) provided similar reliability for EE estimation as the Actigraph (ICCs: 0.661-0.806). However, the measurement error for FT indicated an underestimation of activity times by 5.1 ± 1.2%, 3.8 ± 0.3% and 14.9 ± 2.6% during sitting, walking, and standing, respectively. Furthermore, low correlations were observed between subsequent measurements with both devices (ICCs 0.189-0.459), especially in low intensities (sitting). Validity. During the prolonged 12-h simulated real-life conditions, FT but not FP showed a moderate agreement with the direct observation in assessing the duration of sitting, long sitting, LPA, MVPA, and VPA (p>0.05, ICCs: 0.071-0.537), but the low correlations between Fibion and the criteria (ICCs FT: 0.016-0.638; FP: -0.046 to 0.650) indicate that the measurement error is random. Similarly, FT but not FP showed a moderate agreement with the K4b2 for EE estimation of standing, LPA, MVPA, and VPA (p>0.05, ICCs: 0.673-0.894).  Conclusions In summary, the location of the accelerometer is essential for accurately assessing PA and EE. FT appeared to detect sitting and walking with a small measurement error, similar to that of the Actigraph. Considering the random error observed in our study, further studies with larger populations are needed to confirm the practical usability of Fibion (FT) for estimating different types and intensities of PA

PL - 036 Interactive effects of exercise and metformin on lactic metabolism in type 2 diabetes

Objective Lactic acidosis is typically caused by an imbalance in lactic metabolism. This may be attributed to several reasons and is usually a result of complex interactions. There may be an increased risk for lactic acidosis in type 2 diabetes mellitus (T2D) patients when metformin treatment and physical exercise are combined since both metformin and exercise acutely affect lactic metabolism. As timing of exercise following metformin ingestion may determine the magnitude of long-term metabolic adaptations, this study aimed to test the acute effects of exercise performed at different times following metformin ingestion on lactic metabolism in T2D patients with a randomized crossover time series study design. Methods Participants were recruited from two clinical health-care centers in China using a two-step screening procedure. First, approximately 2 523 patients with T2D were screened from the local diabetes database and clinical outpatient registration with inclusion criteria being men and women (30–65 years old) diagnosed with T2D no more than 5 years ago and treated with metformin (maximal daily dose of 2000 mg). Out of 100 potential participants who met the inclusion criteria, 56 were interested and invited to a laboratory visit. Finally, 34 patients participated in the study and of those, 26 patients (14 women and 12 men, mean age = 53.8 ± 8.6 years) completed all testing procedures. All patients visited the laboratory on 4 occasions, each separated by at least 48 hours. Initially a control visit was performed and consisted of metformin administration only (Metf) and a maximal incremental cycle ergometer test in the afternoon. Thereafter, all participants performed a high-intensity interval training session (HIIT, 3 minutes at 40% followed by 1 minute of 85% of maximum power output) 30 minutes (EX30), 60 minutes (EX60), and 90 minutes (EX90) post breakfast and metformin administration, respectively, in a randomized order. Serum lactate and glucose concentrations were assessed enzymatically, while insulin was assessed by an electrochemiluminescence immunoassay and superoxide dismutase (SOD) activity was determined by spectrophotometry. Measurements were performed before breakfast as well as both before and immediately after each exercise bout. In addition, capillary blood glucose concentrations were measured immediately after sampling using Omron AS1 glucose test strips (HGM-114) and lactate concentrations were assessed by ARKRAY Lactate Pro 2 test strips throughout each measurement day. Dietary intake was standardized on the evening prior to each laboratory day as well as between 8:00 a.m. and 4:00 p.m. during each testing day. This trial is registered with ChiCTR-IOR-16008469 on 13th of May 2016. Results During all three-exercise sessions, the capillary lactate concentrations were significantly increased to a similar extent. However, sixty minutes following metformin administration, serum lactate levels began to accumulate to the highest level, where 30% of patients showed lactate concentrations above resting values (≥2 mmol·L-1). The increased lactate concentrations were statistically associated with increased glucose when exercise was performed 60 minutes post metformin administration (r=0.384, p=0.048). Furthermore, in EX60 and EX90 lactate concentrations were 19% and 8% higher, respectively, compared to EX30. In addition, we found that after exercise but not before exercise, the lactate level was positively correlated with SOD (EX30 r=0.478 and p=0.012, EX60 r=0.562 and p=0.002, EX90 r=0.562 and p=0.003, respectively). Conclusions We found that the changes of lactate concentrations were related to the timing of exercise post meal and after metformin ingestion. Thus, timing of exercise appears to be an important factor to be considered when prescribing exercise for T2D patients treated with metformin. In the present study, the optimal timing of HIIT exercise was 30 minutes after metformin administration, which was indicated by a minimized fluctuation of both glucose and lactate levels in T2D patients. Our results also suggest that lactic metabolism and oxidative stress could be among the main underlying molecular mechanisms that elucidate the combinational therapy of exercise and metformin treatment on T2D. Since both acute exercise and metformin may induce opposite effects on ATP production and reactive oxygen species formation, it is important to conduct further studies in an attempt to define the “safe time” for exercise after metformin administration

Reliability and validity of a new accelerometer-based device for detecting physical activities and energy expenditure

Background Objective assessments of sedentary behavior and physical activity (PA) by using accelerometer-based wearable devices are ever expanding, given their importance in the global context of health maintenance. This study aimed to determine the reliability and validity of a new accelerometer-based analyzer (Fibion) for detecting different PAs and estimating energy expenditure (EE) during a simulated free-living day. Methods The study consisted of two parts: a reliability (n = 18) and a validity (n = 19) test. Reliability was assessed by a 45 min protocol of repeated sitting, standing, and walking (i.e., 3 × 15 min, repeated twice), using both Fibion and ActiGraph. Validity was assessed by a 12 h continuous sequence tasks of different types (sitting, standing, walking, and cycling) and intensities (light [LPA], moderate [MPA], and vigorous [VPA]) of PA. Two Fibion devices were worn on the thigh (FT) and in the pocket (FP), respectively and were compared with criteria measures, such as direct observation (criterion 1) and oxygen consumption by a portable gas analyzer, K4b2 (criterion 2). Results FT (intra-class correlation coefficients (ICCs): 0.687–0.806) provided similar reliability as the Actigraph (ICCs: 0.661–0.806) for EE estimation. However, the measurement error (ME) of FT compared to the actual time records indicated an underestimation of duration by 5.1 ± 1.2%, 3.8 ± 0.3% and 14.9 ± 2.6% during sitting, walking, and standing, respectively. During the validity test, FT but not FP showed a moderate agreement but lager variance with the criteria (1 and 2) in assessing duration of sitting, long sitting, LPA, MPA, and VPA (p > 0.05, ICCs: 0.071–0.537), as well as for EE estimation of standing, LPA, MPA, and VPA (p > 0.05, ICCs: 0.673–0.894). Conclusions FT provided similar reliability to that of the Actigraph. However, low correlations between subsequent measurements of both devices indicated large random MEs, which were somewhat diminished during the simulated 12 h real-life test. Furthermore, FT may accurately determine the types, intensities of PA and EE during prolonged periods with substantial changes in postures, indicating that the location of the accelerometer is essential. Further study with a large cohort is needed to confirm the usability of Fibion, especially for detecting the low-intensity PAs.peerReviewe

Exercise precision medicine for type 2 diabetes: Targeted benefit or risk?

Concurrent exercise and metformin administration may reduce the acute and chronic effects of exercise on glucose metabolism in the patients with type 2 diabetes (T2D). However, several studies suggest that combing metformin and exercise treatment may have neither additive effect nor even cause adverse effects in T2D patients. This case report aimed to highlight the challenges associated with prescribing exercise to type 2 diabetes patients undergoing metformin treatment. A 67-years old woman was followed-up for five months, including assessment of the acute and chronic glucose and lactate metabolism induced by concomitant exercise and metformin. The findings were four-fold: 1) During a high-intensity interval training bout, blood glucose systematically decreased, while blood lactate concentrations fluctuated randomly; 2) Basal blood lactate levels were well above 2 mmol/L on days with medication only; 3) Combined exercise and metformin administration induced additive effects on the normalization of glucose and 4) high levels of physical activity had a positive impact on the continuous glucose fluctuations, while decreased levels of physical activity induced a large fluctuation of glucose due to home confinement of an infectious disease caused by the SARS-CoV-2 virus. Our findings showed that when combined with exercise and metformin treatment for T2D patients, exercise may contribute to improving glycemic control while metformin may elevate lactate levels in the long term. The observed results underline the need to prescribe exercise and monitor lactate levels for reducing possible risks associated with metformin treatment and reinforce the importance of tailoring exercise therapy

Effect of Chronic Exercise Training on Blood Lactate Metabolism Among Patients With Type 2 Diabetes Mellitus : A Systematic Review and Meta-Analysis

Purpose: To assess the effect of chronic exercise training on blood lactate metabolism at rest (i.e., basal lactate concentrations) and during exercise (i.e., blood lactate concentration at a fixed load, load at a fixed blood lactate concentration, and load at the individual blood lactate threshold) among patients with type 2 diabetes mellitus (T2DM). Methods: PubMed (MedLine), Embase, Web of Science, and Scopus were searched. Randomized controlled trials, non-randomized controlled trials, and case-control studies using chronic exercise training (i.e., 4 weeks) and that assessed blood lactate concentrations at rest and during exercise in T2DM patients were included. Results: Thirteen studies were eligible for the systematic review, while 12 studies with 312 participants were included into the meta-analysis. In the pre-to-post intervention meta-analysis, chronic exercise training had no significant effect on changes in basal blood lactate concentrations (standardized mean difference (SMD) = -0.20; 95% CI, -0.55 to 0.16; p = 0.28), and the results were similar when comparing the effect of intervention and control groups. Furthermore, blood lactate concentration at a fixed load significantly decreased (SMD = -0.73; 95% CI, -1.17 to -0.29; p = 0.001), while load at a fixed blood lactate concentration increased (SMD = 0.40; 95% CI, 0.07 to 0.72; p = 0.02) after chronic exercise training. No change was observed in load at the individual blood lactate threshold (SMD = 0.28; 95% CI, -0.14 to 0.71; p = 0.20). Conclusion: Chronic exercise training does not statistically affect basal blood lactate concentrations; however, it may decrease the blood lactate concentrations during exercise, indicating improvements of physical performance capacity which is beneficial for T2DM patients' health in general. Why chronic exercise training did not affect basal blood lactate concentrations needs further investigation.peerReviewe

The Impact of Nordic Walking on Bone Properties in Postmenopausal Women with Pre-Diabetes and Non-Alcohol Fatty Liver Disease

This study investigated the impact of Nordic walking on bone properties in postmenopausal women with pre-diabetes and non-alcohol fatty liver disease (NAFLD). A total of 63 eligible women randomly participated in the Nordic walking training (AEx, n = 33), or maintained their daily lifestyle (Con, n = 30) during intervention. Bone mineral content (BMC) and density (BMD) of whole body (WB), total femur (TF), femoral neck (FN), and lumbar spine (L2-4) were assessed by dual-energy X-ray absorptiometry. Serum osteocalcin, pentosidine, receptor activator of nuclear factor kappa-B ligand (RANKL) levels were analyzed by ELISA assay. After an 8.6-month intervention, the AEx group maintained their BMCTF, BMDTF, BMCL2−4, and BMDL2−4, and increased their BMCFN (p = 0.016), while the Con group decreased their BMCTF (p = 0.008), BMDTF (p = 0.001), and BMDL2−4 (p = 0.002). However, no significant group × time interaction was observed, except for BMDL2−4 (p = 0.013). Decreased pentosidine was correlated with increased BMCWB(r = −0.352, p = 0.019). The intervention has no significant effect on osteocalcin and RANKL. Changing of bone mass was associated with changing of pentosidine, but not with osteocalcin and RANKL. Our results suggest that Nordic walking is effective in preventing bone loss among postmenopausal women with pre-diabetes and NAFLD.peerReviewe

Assessment of sleep disturbances with the athlete sleep screening Questionnaire in Chinese athletes

This study investigated the factors that are associated with sleep disturbances among Chinese athletes. Sleep quality and associated factors were assessed by the Athlete Sleep Screening Questionnaire (ASSQ, n ​= ​394, aged 18–32 years, 47.6% female). Sleep difficulty score (SDS) and level of sleep problem (none, mild, moderate, or severe) were used to classify participants' sleep quality. Categorical variables were analyzed by Chi-square or fisher's exact tests. An ordinal logistic regression analysis was used to explore factors with poor sleep (SDS ≥8). Approximately 14.2% of participants had moderate to severe sleep problem (SDS ≥8). Fifty-nine percent of the athletes reported sleep disturbance during travel, while 43.3% experienced daytime dysfunction when travelling for competition. No significant difference was found in the SDS category between gender, sports level and events. Athletes with evening chronotype were more likely to report worse sleep than athletes with morning and intermediate chronotype (OR, 2.25; 95%CI, 1.44–3.52; p ​< ​0.001). For each additional year of age, there was an increase of odds ratio for poor sleep quality (OR, 1.15; 95%CI, 1.04–1.26; p ​= ​0.004), while each additional year of training reduced the odds ratio (OR, 0.95; 95%CI, 0.91–0.99; p ​= ​0.044). To improve sleep health in athletes, chronotype, travel-related issues, age and years of training should be taken into consideration.peerReviewe

Changes in health behaviors and conditions during COVID-19 pandemic strict campus lockdown among Chinese university students

Objective: To explore how a stringent campus lockdown affects the physical activity (PA), sleep and mental health of Chinese university students living in student dormitories during the COVID-19 pandemic. Methods: Data on PA, sleep and mental health were collected between 24 March and 4 April 2022 from 2084 university students (mean age = 22.4 years, 61.1% male students) via an online questionnaire distributed by the students’ advisers of each dormitory. The Chinese short version of the International Physical Activity Questionnaire (IPAQ-C), Athens Insomnia Scale (CAIS) and General Health Questionnaire 12-item (GHQ-12) were applied. The Mann–Whitney test and Kruskal-Wallis tests were used to evaluate the PA profile differences between genders, before and during the lockdown period and between students’ living environments. Chi-squared (χ2) or Fisher’s exact test was used to assess changes in health behaviors by gender and students’ living environment compared to before the lockdown. A mediation model was used to examine whether sleep disorder mediated the relationship between PA and mental health in different students’ living environments. Results: Participants reported a significant decrease in weekly total PA levels (63.9%). Mean daily sedentary time increased by 21.4% and daily lying time increased by 10.7% compared to before lockdown. Among the participants, 21.2% had experienced insomnia, and 39.0% reported having high mental distress. Female students reported 10% higher rates of sleep disorders than male students (p < 0.001), and also experienced a higher incidence of mental disorders (p < 0.001). Students living with three roommates had a larger decrease in frequencies and durations of participation in light PA than other students (p < 0.001). PA was negatively associated with sleep and mental health, and sleep disorder was a mediating factor between PA and mental health in the students living with two and three roommates. Conclusion: This study showed that strict lockdowns within university dormitories during the COVID-19 pandemic had a negative effect on the health of university students by changing their health behaviors, physical activity and sleep. Our findings indicate a need for strategies to promote an active lifestyle for students in space-limited dormitories in order to maintain health during a prolonged lockdown.peerReviewe