Effects of aerobic exercise on home-based sleep among overweight and obese men with chronic insomnia symptoms : a randomized controlled trial

Objective: To determine the effect of a six-month aerobic exercise program on home-based sleep quality among overweight and obese men with chronic insomnia symptoms. Methods: Participants were 45 Finnish men (93% had body mass index >= 25) aged 30-65 years, with chronic months) insomnia symptoms as classified by the DSM-IV criteria. Participants were randomized into an exercise (n = 24) or control group (n = 21). The exercise group received six-month aerobic exercise intervention with one to five sessions per week of 30-60 minutes duration. The control group was instructed to maintain habitual lifestyle behaviors during the study period. Seven-night home sleep was measured with a piezoelectric bed sensor and sleep diary. Other assessments included the modified Basic Nordic Sleep Questionnaire, a health and behavior questionnaire, physical activity and diet diaries, anthropometry, fat mass, and physical fitness. Analysis of covariance controlling for baseline values, and repeated-measures analysis of variance were implemented for time-by-group comparisons and within group comparisons, respectively. Results: At six months, the exercise group showed reduced objective sleep onset latency (p = 0.010) and lowered frequency of difficulty initiating sleep (p = 0.021) than controls. Although a time-by-group difference was not significant, exercisers showed shorter objective wake after sleep onset (p = 0.004), reduced subjective nocturnal awakenings (p = 0.010), improved objective sleep efficiency (p <0.001), and improved morning-rated subjective sleep quality (p = 0.042) at six months than baseline. Conclusions: A six-month aerobic exercise can improve sleep, mainly by mitigating difficulty of initiating sleep among overweight and obese men with chronic insomnia symptoms. (C) 2016 Elsevier B.V. All rights reserved.Peer reviewe

PL-018 Effects and safety of exercise combined with medication and diet in treatment of diabetes and comorbidity

Objective The role of exercise in the prevention and treatment of chronic diseases is widely accepted and regular physical exercise may play an irreplaceable role beyond traditional medicine and drug treatments. However, &nbsp;current guidelines do not provide details on the characteristics of exercise programs which are aimed to be carried out concomitantly to drug treatments. Moroever, the safety of combined exercise and drug treatments has rarely been considered. The future of exercise is medicine research will likely need to focus on questions such as how to build customized exercise programs for different patients in the context of individual physiological responses to exercise? When combining drug and concomitant exercise treatment, what is the optimal exercise prescription in terms of timing, intensity and duration? Does exercise only have an additive effect or may exercise actually reverse or even cancel out some of the expected effects induced by the drug treatment?&nbsp; What is the role of diet in exercise interventions? Does a given exercise program affect the lipid and glucose metabolism to the same extent? In this report, we will present different randomized clinical trials conducted in our research group to tackle some of the abovementioned questions. This particularly includes patients with comorbidity conditions (prediabetes and non-alcohol fatty liver disease,NAFLD), as well as patients with type 2 diabetes (T2D). Methods Two different randomized trials are included, both of which were conducted in China (ChiCTR-IOR-16008469 and ISRCTN 42622771). The ChiCTR-IOR-16008469 study was a randomized crossover trial. The aim of this study was to assess whether the duration between metformin administration and high-intensity cycling (HIIT) affects the glucose metabolism. T2D patients performed a single session of &nbsp;HIIT (~25 minutes) at 30 (EX30), 60 (EX60), and 90 (EX90) minutes following breakfast and metformin administration in a randomized order. Subjects’ diurnal glucose metabolism was assessed between 8:00 a.m. and 4:00 p.m. (Metf) of each exercise day as well as on a control day. Furthermore, insulin was assessed both before and immediately after each exercise bout. The ISRCTN42622771 trial was a four arm randomized trial. Six-hundred and three patients from seven clinics were recruited, out of which 115 individuals aged 50-65-year fulfilled the inclusion criteria (impaired fasting glucose (IFG) or impaired glucose tolerance (IGT) and NAFLD) and were randomly assigned (1:1:1:1) to either of the four groups: aerobic exercise (AEx, n = 29), diet intervention (Diet, n = 28), aerobic exercise plus diet intervention (AED = 29), or no intervention (NI = 29). The study spanned over anaverage period of 8.6 months (7-11 months). Progressive supervised aerobic exercise training (60-75% intensity) was carried out 2-3 times/week in 30-60 min/sessions, and the diet intervention consisted of a lunch with 38% carbohydrate and diet fibre of 12g per day, while the remaining meals were freely chosen but with supervised nutrition intakes. The hepatic fat content (HFC) assessed by 1H MRS, glycated haemoglobin (HbA1c) and insulin sensitivity were assessed by conventional methods. Results In study 1, we found that in diabetes patient glucose levels significantly decreased in all exercise settings, irrespective of the timing.&nbsp; However, whenHIIT was performed at 30 minutes post-metformin administration, the peak glucose was lowered, thereby further stabilizing the postprandial glucose fluctuation. The risk for hypoglycemia at different times to exercise after metformin administration was highest in EX90 (22.2%) compared to EX30 (3.7%) and EX60 (7.4%). While the lactate level was 19% higher in EX60 and 8% higher in EX90 compared to EX30. Compared with Metformin, the decrease in insulin was larger in EX30 and EX60 (both p &lt; 0 001). These results indicate that timing of exercise is an important factor to consider when prescribing exercise as adjuvant to metformin therapy for T2DM patients. In study 2, we showed that in patients with morbidity (prediabetes with NAFLD), HFC was significantly reduced in the AEx (–24.4%), diet (–23.2%), and AED (–47.9%) groups, as opposed to the 20.9% increase in the NI group (p=0.006, p=0.002, and P&lt;0.0001, respectively).Importantly, HFC decreased to normal levels (&lt;5.6%) in ten (44%) out of 23 participants in the exercise plus diet group and nine (41%) out of 22 participants in the diet group, while the in the exercise group it decreased only in three (14%) out of 29&nbsp; participants. Further, all intervention groups showed improvements ininsulin sensitivity (AEx 33%, p=0.023, Diet 37%, p=0.012, and AED 34%, p=0.029) but only the AED group significantly decreased HbA1c (-4.4%, p=0.01) compared with the NI group (1.9% and -0.6%). However, after controlling for the change of body weight as well as for the duration of the intervention and baseline values, the significant differences in HbA1cand insulin sensitivity between the groups disappeared. Furthermore, based on HbA1c IFG or IGT, no significant remission and progression from prediabetes to diabetes were observed between the intervention and NI. Conclusions The results derived from these two trials imply that: 1) the combined effects of exercise and metformin therapy on T2D should take into account that both exercise and metformin are likely to affect the lactic metabolism because T2D is considered as a redox disease. For the acute effect of exercise combined with metformin therapy, exercising at 30 minutes post-metformin administration appeared to be optimal for reducing glucose fluctuation. To avoid the risk for hypoglycemia and lactases with the combined treatment, selecting optimal timing may be the first and easiest step towards personalized exercise medicine. Thus, when exercise is recommended to diabetic patients, the timing of exercise may be an important consideration so that the therapeutic effects of metformin are not compromised. However, further studies are warranted to elucidate the long-term effects of combining metformin and exercise on glycemic control and lactic metabolism as well as the underlying mechanisms. 2) Aerobic exercise training combined with a fibre-enriched diet can aid reduce HFC more effectively than either exercise or increased fibre intake alone in pre-diabetic patients with NAFLD. However, the effect on glycaemic control and insulin sensitivity is not substantial. Therefore, it remains to be addressed why the same intervention protocol did not show the similar effect on the HFC and glycaemic control/insulin sensitivity in the same subjects. When these questions being uncovered, the combined intervention could be considered as an integral part of lifestyle interventions for patients with a cordiality condition for an increased risk of developing T2D

OR-042 Effect of exercise and dietary intervention on serum and adipose tissue metabolomics in patients with insomnia: a 6-month randomized-controlled trial

&nbsp;Objective Objectives: Insomnia is common in modern society, with a prevalence between 10-20% among adults. Insomnia is associated with numerous adverse health outcomes and carries a heavy burden for health-care system. Accumulating evidences have shown that lifestyle interventions such as exercise and dietary modification could benefit sleep by mitigating symptoms of insomnia. However, the metabolic profile change in people with insomnia following exercise or diet intervention is not clear. Methods Methods: Seventy-two Finnish men (age: 51.5 + 10.2 years; body mass index, BMI:29.3 + 3.9 kg/m2) with chronic insomnia symptoms participated in this study. They were then randomly assigned into three groups: exercise (n = 24), diet group (n=24) or control group (n = 21). Nordic walking or other aerobic exercise was performed 30 to 60 minutes per session, one to five sessions per week, at the intensity level of 60%–75% of estimated maximum heart rate. Specific individualized diet programs are developed after baseline assessments of each participant’s current dietary intakes (based on three-day food diary) and body weight. Blood samples were collected in the morning between 7:00 and 9:00 a.m. after overnight fasting. In addition, subcutaneous adipose tissue biopsies were obtained from a subgroup of 20 subjects. Gas Chromatography Time-Of-Flight Mass Spectrometry (GC-TOF-MS) method was used to investigate the serum and adipose tissue metabolites. Sleep was assessed by using a non-contact sleep monitoring system. Multivariate analysis and univariate analysis were used for metabolomics data analysis. Results Results: Sleep onset latency (SOL), wakefulness after sleep onset (WASO), and sleep efficiency (SE) were all significantly changed (p &lt; 0.05) after 6-month exercise intervention, and total sleep time (TST), SOL and SE were significantly changed (p &lt; 0.05) after 6-month diet intervention. A total of 223 known metabolites in serum and total of 154 known metabolites in adipose tissue were detected. Eleven metabolites were affected by exercise and eight metabolites were affected (Variable importance in the projection, VIP &gt; 1 from (orthogonal) partial least-squares-discriminant analysis (OPLS-DA) and p &lt; 0.05 from t test) by diet in adipose tissue. Among the metabolites detected in serum, there were 17 metabolites affected by exercise, 21 metabolites by diet and 13 changed in the control group (VIP &gt; 1 and p &lt; 0.05). We found that in the exercise group, in serum, change of shikimic acid correlated with change of WASO (r = -0.479, p = 0.038) and SE (r = 0.462, p = 0.047), change of Cystathionine correlated with change of TST (r = -0.545, p = 0.016) and SE (r = -0.6, p = 0.007), while in adipose tissue, change of cholesterol (r = -0.822, p = 0.023) and Behenic acid (r = -0.833, p = 0.02) correlated with change of SE. In diet group, change of leucine correlated with change of WASO (r = -0.655, p = 0.001) and change of SE (r = 0.499, p = 0.013), change of Linoelaidic acid correlated with change of WASO (r = -0.519, p = 0.009) and change of SE (r = 0.506, p = 0.012), change of L-Allothreonine (r = -0.460, p = 0.024) and Erythrose (r = -0.441, p = 0.031) correlated with change of BMI, change of L-Rhamnose correlated with change of TST (r = -0.480, p = 0.018) in serum, while change of glycylproline correlated with change of SOL (r = -0.845, p = 0.034) in adipose. In addition, change of acetanilide correlated with change of TST (r = -0.772, p &lt; 0.01), change of palmitoleic acid correlated with change of BMI (r = -0.491, p = 0.038) in serum but not association in adipose tissue was observed in control group. Conclusions Conclusion: Several metabolites related to energy metabolism are altered after exercise and dietary intervention in people with insomnia. The change of these metabolites may explain partly the underline mechanisms of improvement of sleep quality through lifestyle interventions

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 &lt; 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&lt;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&lt;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&lt;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.&nbsp; 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-185 Lifestyle intervention modify DNA methylation of adipose tissue in overweight and obese men with insomnia symptoms

Objective To study whether diet and exercise intervention affect sleep and obesity-related genes’ DNA methylation in overweight and obese men with insomnia symptoms Methods The study participants were a subgroup of a large intervention and consisted of 10 overweight or obesity men aged 34-65 years with insomnia symptoms. They participated in a 6-month progressive aerobic exercise training and individualized dietary consoling program and were randomly selected from diet (n=4), exercise (n=3) and control (n=3) groups. Body composition included fat mass and lean mass in the whole body and abdominal android region were assessed by dual-energy X-ray densitometry. The fitness level (VO2max) was determined by 2-km walk test using a standard protocol. Blood samples from venous were taken at fasted state in the morning. Total cholesterol, high density lipid cholesterol, low density lipid cholesterol, triglycerides, glucose, insulin, non-esterified fatty acid, alanine aminotransferase, aspartate aminotransferase and γ-glutamyltransferase were assessed by conventional methods. Subcutaneous adipose tissue was taken from abdominal region before and after the intervention. DNA was extracted from subcutaneous adipose tissue using a QIAamp DNeasy Tissue Kit. Whole genome-wide DNA methylation was obtained using MethylRAD-Seq. MethylRAD library preparation started from DNA digestion by FspEI, then digested products were run on agarose gel to verify digestion and DNA ligase was added to the digestion solution. After ligation products amplication, PCR was conducted by MyCycler thermal cycler (Bio-Rad). The target fragment was excised from polyacrylamide gel and DNA was diffused from the gel in nuclease-free water. For relative quantification of MethylRAD data, DNA methylation levels were determined using the normalized read depth (reads per million, RPM) for each site. For each restriction site, its methylation level was estimated by dividing the log-transformed depth of each site by the log-transformed maximum depth (representing 100% methylation; i.e. M-index ¼ log(depth site)/ log(depth max)), where depth max was summarized from the top 2% of sites (approx. 500 for the standard library) with the highest sequencing coverage. Heat map images are generated with Matlab 7.0 software and pathways are analysed by WEB-based Gene SeT AnaLysis Toolket. A statistical significance for methylated CpGs and pathways were set to p=0.001 and p=0.05, respectively. Results No significant group differences by time were found in sleep-related variables, body composition, lifestyle factors nor with measured lipid and glucose biomarkers. However, whole genome-wide DNA methylation was decreased after dietary intervention, but was increased after exercise intervention, respectively. Correspondingly, 1253 and 708 differentially methylated loci were found in diet and exercise groups by contrast to the control group. Among them, the overlap genes between diet and exercise had multiple differentially methylated CpGs, including e.g. MYT1L (4 CpGs), CAMTA1 (3 CpGs), NRXN1 (3 CpGs), RPS6KA2 (3 CpGs), SEMA4D (3 CpGs). DNA methylation in PCDH8 was negatively correlated with wake after sleep onset after exercise intervention and MYRIP associated with sleep duration showed lower methylation after the dietary intervention. Further, 13 (DIO1, GCK, GYS1, LMNA, LY86, PNMT, PPARA, PPARD, SERPINE1, TH, TMEM18, TNFRSF1B and UBL5) and 2 (SDCCAG8 and TNF) obesity-related genes’ DNA methylation profile changed in response to diet and exercise, respectively. Percentage changes of CpGs within KLHDC8A, ANKS1A, FGFRL1 and KDM3B were correlated with energy yield fat and carbohydrate, HOMA-IR and VO2max, respectively. Conclusions We found that both exercise and dietary interventions have impacts on these genes related to sleep indicating by DNA methylation in PCDH8 and MYRIP, respectively. Further diet may be more effective than aerobic exercise intervention since greater number of modified obesity-related genes observed after dietary intervention. Our results indicate that reduce insomnia symptoms may need to more focus on control obesity

Effect of Six-Month Diet Intervention on Sleep among Overweight and Obese Men with Chronic Insomnia Symptoms : A Randomized Controlled Trial

Growing evidence suggests that diet alteration affects sleep, but this has not yet been studied in adults with insomnia symptoms. We aimed to determine the effect of a six-month diet intervention on sleep among overweight and obese (Body mass index, BMI >= 25 kg/m(2)) men with chronic insomnia symptoms. Forty-nine men aged 30-65 years with chronic insomnia symptoms were randomized into diet (n = 28) or control (n = 21) groups. The diet group underwent a six-month individualized diet intervention with three face-to-face counseling sessions and online supervision 1-3 times per week; 300-500 kcal/day less energy intake and optimized nutrient composition were recommended. Controls were instructed to maintain their habitual lifestyle. Sleep parameters were determined by piezoelectric bed sensors, a sleep diary, and a Basic Nordic sleep questionnaire. Compared to the controls, the diet group had shorter objective sleep onset latency after intervention. Within the diet group, prolonged objective total sleep time, improved objective sleep efficiency, lower depression score, less subjective nocturnal awakenings, and nocturia were found after intervention. In conclusion, modest energy restriction and optimized nutrient composition shorten sleep onset latency in overweight and obese men with insomnia symptoms.Peer reviewe

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

Interactive effects of aging and aerobic capacity on energy metabolism-related metabolites of serum, skeletal muscle, and white adipose tissue

Aerobic capacity is a strong predictor of longevity. With aging, aerobic capacity decreases concomitantly with changes in whole body metabolism leading to increased disease risk. To address the role of aerobic capacity, aging, and their interaction on metabolism, we utilized rat models selectively bred for low and high intrinsic aerobic capacity (LCRs/HCRs) and compared the metabolomics of serum, muscle, and white adipose tissue (WAT) at two time points: Young rats were sacrificed at 9 months of age, and old rats were sacrificed at 21 months of age. Targeted and semi-quantitative metabolomics analysis was performed on the ultra-pressure liquid chromatography tandem mass spectrometry (UPLC-MS) platform. The effects of aerobic capacity, aging, and their interaction were studied via regression analysis. Our results showed that high aerobic capacity is associated with an accumulation of isovalerylcarnitine in muscle and serum at rest, which is likely due to more efficient leucine catabolism in muscle. With aging, several amino acids were downregulated in muscle, indicating more efficient amino acid metabolism, whereas in WAT less efficient amino acid metabolism and decreased mitochondrial beta-oxidation were observed. Our results further revealed that high aerobic capacity and aging interactively affect lipid metabolism in muscle and WAT, possibly combating unfavorable aging-related changes in whole body metabolism. Our results highlight the significant role of WAT metabolism for healthy aging.Peer reviewe

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