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  • 1. Armstrong, Neil
    et al.
    Tomkinson, Grant R.
    Ekelund, Ulf
    Örebro University, School of Health and Medical Sciences.
    Aerobic fitness and its relationship to sport, exercise training and habitual physical activity during youth2011In: British Journal of Sports Medicine, ISSN 0306-3674, E-ISSN 1473-0480, Vol. 45, no 11, p. 849-858Article in journal (Refereed)
    Abstract [en]

    Aim To analyse aerobic fitness and its relationship with sport participation, exercise training and habitual physical activity (HPA) during youth. Methods Studies were located through computer searches of Medline, SPORT Discus and personal databases. Systematic reviews of time trends in aerobic fitness/performance, and exercise training and peak oxygen uptake (peak VO(2)) are reported. Results Peak VO(2) increases with age and maturation. Boys' peak VO(2) is higher than girls'. Despite data showing a decrease in performance test estimates of aerobic fitness there is no compelling evidence to suggest that young people have low levels of peak VO(2) or that it is declining over time. The primary time constant of the VO(2) kinetics response to moderate and heavy intensity exercise slows with age and the VO(2) kinetics response to heavy intensity exercise is faster in boys. There is a negative correlation between lactate threshold as a percentage of peak VO(2) and age but differences related to maturation or sex remain to be proven. Young athletes have higher peak VO(2), a faster primary time constant and accumulate less blood lactate at the same relative exercise intensity than their untrained peers. Young people can increase their peak VO(2) through exercise training but a meaningful relationship between aerobic fitness and HPA has not been demonstrated. Conclusions During youth the responses of the components of aerobic fitness vary in relation to age, maturation and sex. Exercise training will enhance aerobic fitness but a relationship between young people's current HPA and aerobic fitness remains to be proven.

  • 2. Barker, Adam
    et al.
    Sharp, Stephen J.
    Timpson, Nicholas J.
    Bouatia-Naji, Nabila
    Warrington, Nicole M.
    Kanoni, Stavroula
    Beilin, Lawrence J.
    Brage, Soren
    Deloukas, Panos
    Evans, David M.
    Grontved, Anders
    Hassanali, Neelam
    Lawlor, Deborah A.
    Lecoeur, Cecile
    Loos, Ruth J. F.
    Lye, Stephen J.
    McCarthy, Mark I.
    Mori, Trevor A.
    Ndiaye, Ndeye Coumba
    Newnham, John P.
    Ntalla, Ioanna
    Pennell, Craig E.
    St Pourcain, Beate
    Prokopenko, Inga
    Ring, Susan M.
    Sattar, Naveed
    Visvikis-Siest, Sophie
    Dedoussis, George V.
    Pahner, Lyle J.
    Froguel, Philippe
    Smith, George Davey
    Ekelund, Ulf
    Örebro University, School of Health and Medical Sciences.
    Wareham, Nicholas J.
    Langenberg, Claudia
    Association of genetic loci with glucose levels in childhood and adolescence a meta-analysis of over 6,000 children2011In: Diabetes, ISSN 0012-1797, E-ISSN 1939-327X, Vol. 60, no 6, p. 1805-1812Article in journal (Refereed)
    Abstract [en]

    OBJECTIVE-To investigate whether associations of common genetic variants recently identified for fasting glucose or insulin levels in nondiabetic adults are detectable in healthy children and adolescents. RESEARCH DESIGN AND METHODS-A total of 16 single nucleotide polymorphisms (SNPs) associated with fasting glucose were genotyped in six studies of children and adolescents of European origin, including over 6,000 boys and girls aged 9-16 years. We performed meta-analyses to test associations of individual SNPs and a weighted risk score of the 16 loci with fasting glucose. RESULTS-Nine loci were associated with glucose levels in healthy children and adolescents, with four of these associations reported in previous studies and five reported here for the first time (GLIS3, PROX1, SLC2A2, ADCY5, and CRY2). Effect sizes were similar to those in adults, suggesting age-independent effects of these fasting glucose loci. Children and adolescents carrying glucose-raising alleles of G6PC2, MTNR1B, GCK, and GLIS3 also showed reduced p-cell function, as indicated by homeostasis model assessment of beta-cell function. Analysis using a weighted risk score showed an increase [beta (95% CI)] in fasting glucose level of 0.026 mrnol/L (0.021-0.031) for each unit increase in the score. CONCLUSIONS-Novel fasting glucose loci identified in genome-wide association studies of adults are associated with altered fasting glucose levels in healthy children and adolescents with effect sizes comparable to adults. In nondiabetic adults, fasting glucose changes little over time, and our results suggest that age-independent effects of fasting glucose loci contribute to long-term interindividual differences in glucose levels from childhood onwards. Diabetes 60:1805-1812, 2011

  • 3. Corder, Kirsten
    et al.
    Ekelund, Ulf
    Örebro University, School of Health and Medical Sciences.
    Physical activity2008In: Paediatric exercise science and medicine / [ed] Neil Armstrong, Willem van Mechelen, Oxford: Oxford University Press , 2008, 2, p. 129-144Chapter in book (Other academic)
  • 4.
    den Hoed, Marcel
    et al.
    Epidemiol Unit, Inst Metab Sci, Medical Research Council (MRC), Cambridge, England.
    Ekelund, Ulf
    Örebro University, School of Health and Medical Sciences. Epidemiol Unit, Inst Metab Sci, Medical Research Council (MRC), Cambridge, England.
    Brage, Soren
    Epidemiol Unit, Inst Metab Sci, Medical Research Council (MRC), Cambridge, England.
    Grontved, Anders
    Inst Sport Sci & Clin Biomech, Univ So Denmark, Odense, Denmark.
    Zhao, Jing Hua
    Epidemiol Unit, Inst Metab Sci, Medical Research Council (MRC), Cambridge, England.
    Sharp, Stephen J.
    Epidemiol Unit, Inst Metab Sci, Medical Research Council (MRC), Cambridge, England.
    Ong, Ken K.
    Epidemiol Unit, Inst Metab Sci, Medical Research Council (MRC), Cambridge, England.
    Wareham, Nicholas J.
    Epidemiol Unit, Inst Metab Sci, Medical Research Council (MRC), Cambridge, England.
    Loos, Ruth J. F.
    Epidemiol Unit, Inst Metab Sci, Medical Research Council (MRC), Cambridge, England.
    Genetic susceptibility to obesity and related traits in childhood and adolescence influence of loci identified by genome-wide association studies2010In: Diabetes, ISSN 0012-1797, E-ISSN 1939-327X, Vol. 59, no 11, p. 2980-2988Article in journal (Refereed)
    Abstract [en]

    Objective: Large-scale genome-wide association (GWA) studies have thus far identified 16 loci incontrovertibly associated with obesity-related traits in adults. We examined associations of variants in these loci with anthropometric traits in children and adolescents.

    Research design and methods: Seventeen variants representing 16 obesity susceptibility loci were genotyped in 1,252 children (mean +/- SD age 9.7 +/- 0.4 years) and 790 adolescents (15.5 +/- 0.5 years) from the European Youth Heart Study (EYHS). We tested for association of individual variants and a genetic predisposition score (GPS-17), calculated by summing the number of effect alleles, with anthropometric traits. For 13 variants, summary statistics for associations with BMI were meta-analyzed with previously reported data (N-total = 13,071 children and adolescents).

    Results: In EYHS, 15 variants showed associations or trends with anthropometric traits that were directionally consistent with earlier reports in adults. The meta-analysis showed directionally consistent associations with BMI for all 13 variants, of which 9 were significant (0.033-0.098 SD/allele; P < 0.05). The near-TMEM18 variant had the strongest effect (0.098 SD/allele P = 8.5 x 10(-11)). Effect sizes for BMI tended to be more pronounced in children and adolescents than reported earlier in adults for variants in or near SEC16B, TMEM18, and KCTD15, (0.028-0.035 SD/allele higher) and less pronounced for rs925946 in BDNF (0.028 SD/allele lower). Each additional effect allele in the GPS-17 was associated with an increase of 0.034 SD in BMI (P = 3.6 x 10(-5)), 0.039 SD, in sum of skinfolds (P = 1.7 x 10(-7)), and 0.022 SD in waist circumference (P = 1.7 X 10(-4)), which is comparable with reported results in adults (0.039 SD/allele for BMI and 0.033 SD/allele for waist circumference).

    Conclusions: Most obesity susceptibility loci identified by GWA studies in adults are already associated with anthropometric traits in children/adolescents. Whereas the association of some variants may differ with age, the cumulative effect size is similar. Diabetes 59:2980-2988, 2010

  • 5.
    Ekelund, Ulf
    et al.
    Örebro University, School of Health and Medical Sciences.
    Anderssen, Sigmund
    Andersen, Lars Bo
    Riddoch, Chris J.
    Sardinha, Luis B.
    Luan, Jian An
    Froberg, Karsten
    Brage, Sören
    Prevalence and correlates of the metabolic syndrome in a population-based sample of European Youth2009In: American Journal of Clinical Nutrition, ISSN 0002-9165, E-ISSN 1938-3207, Vol. 89, no 1, p. 90-96Article in journal (Refereed)
    Abstract [en]

    BACKGROUND: Until recently, there has been no unified definition of the metabolic syndrome (MetS) in the youth. Therefore, the prevalence of MetS and its association with potential correlates are largely unknown. OBJECTIVE: The objective was to quantify the prevalence, identify the correlates, and examine the independent associations between potential correlates with MetS. DESIGN: A population-based cohort study was conducted in 10- and 15-y-old youth from Estonia, Denmark, and Portugal (n = 3193). MetS was defined according to the International Diabetes Federation. Correlates included maternal socioeconomic status, body mass index (BMI), hypertension, and prevalent diabetes and maternally reported child's birth weight and duration of breastfeeding. Data on sexual maturity, objectively measured physical activity, cardiorespiratory fitness, self-reported sports participation, television viewing, and regular play were collected for the children. RESULTS: The prevalence of MetS was 0.2% and 1.4% in 10- and 15-y-olds, respectively. Cardiorespiratory fitness (standardized odds ratio: 0.33; 95% CI: 0.15, 0.75), physical activity (standardized odds ratio: 0.40; 95% CI: 0.18, 0.88), and maternal BMI (standardized odds ratio: 1.61; 95% CI: 1.11, 2.34) were all independently associated with MetS after adjustment for sex, age group, study location, birth weight, and sexual maturity. An increase in daily moderate-intensity physical activity by 10-20% was associated with a 33% lower risk of being categorized with MetS. CONCLUSIONS: High maternal BMI and low levels of cardiorespiratory fitness and physical activity independently contribute to the MetS and may be targets for future interventions. Relatively small increases in physical activity may significantly reduce the risk of MetS in healthy children.

  • 6.
    Ekelund, Ulf
    et al.
    Örebro University, School of Health and Medical Sciences.
    Anderssen, Sigmund
    Froberg, Karsten
    Sardinha, Luis B.
    Andersen, Lars Bo
    Brage, Sören
    Independent associations of physical activity and cardiorespiratory fitness with metabolic risk factors in children: the European youth heart study2007In: Diabetologia, ISSN 0012-186X, E-ISSN 1432-0428, Vol. 50, no 9, p. 1832-1840Article in journal (Refereed)
    Abstract [en]

    AIMS/HYPOTHESIS: High levels of cardiorespiratory fitness (CRF) and physical activity (PA) are associated with a favourable metabolic risk profile. However, there has been no thorough exploration of the independent contributions of cardiorespiratory fitness and subcomponents of activity (total PA, time spent sedentary, and time spent in light, moderate and vigorous intensity PA) to metabolic risk factors in children and the relative importance of these factors. METHODS: We performed a population-based, cross-sectional study in 9- to 10- and 15- to 16-year-old boys and girls from three regions of Europe (n = 1709). We examined the independent associations of subcomponents of PA and CRF with metabolic risk factors (waist circumference, BP, fasting glucose, insulin, triacylglycerol and HDL-cholesterol levels). Clustered metabolic risk was expressed as a continuously distributed score calculated as the average of the standardised values of the six subcomponents. RESULTS: CRF (standardised beta = -0.09, 95% CI -0.12, -0.06), total PA (standardised beta = -0.08, 95% CI -0.10, -0.05) and all other subcomponents of PA were significantly associated with clustered metabolic risk. After excluding waist circumference from the summary score and further adjustment for waist circumference as a confounding factor, the magnitude of the association between CRF and clustered metabolic risk was attenuated (standardised beta = -0.05, 95% CI -0.08, -0.02), whereas the association with total PA was unchanged (standardised beta = -0.08 95% CI -0.10, -0.05). CONCLUSIONS/INTERPRETATION: PA and CRF are separately and independently associated with individual and clustered metabolic risk factors in children. The association between CRF and clustered risk is partly mediated or confounded by adiposity, whereas the association between activity and clustered risk is independent of adiposity. Our results suggest that fitness and activity affect metabolic risk through different pathways.

  • 7.
    Ekelund, Ulf
    et al.
    Örebro University, School of Health and Medical Sciences, Örebro University, Sweden. MRC Epidemiology Unit, Institute of Metabolic Science, Cambridge, United Kingdom; Department of Sport Medicine, Norwegian School of Sport Science, Oslo, Norway .
    Luan, Jian'an
    MRC Epidemiology Unit, Institute of Metabolic Science, Cambridge, United Kingdom .
    Sherar, Lauren B.
    College of Kinesiology, University of Saskatchewan, Saskatoon, Canada; School of Sport, Exercise and Health Sciences, Loughborough University, Loughborough, United Kingdom.
    Esliger, Dale W.
    College of Kinesiology, University of Saskatchewan, Saskatoon, Canada; School of Sport, Exercise and Health Sciences, Loughborough University, Loughborough, United Kingdom.
    Griew, Pippa
    School of Sport and Health Sciences, University of Exeter, Exeter, United Kingdom.
    Cooper, Ashley
    Exercise, Nutrition and Health Sciences, School for Policy Studies, University of Bristol, Bristol, United Kingdom.
    Moderate to vigorous physical activity and sedentary time and cardiometabolic risk factors in children and adolescents2012In: Journal of the American Medical Association (JAMA), ISSN 0098-7484, E-ISSN 1538-3598, Vol. 307, no 7, p. 704-712Article in journal (Refereed)
    Abstract [en]

    Context: Sparse data exist on the combined associations between physical activity and sedentary time with cardiometabolic risk factors in healthy children.

    Objective: To examine the independent and combined associations between objectively measured time in moderate- to vigorous-intensity physical activity (MVPA) and sedentary time with cardiometabolic risk factors.

    Design, Setting, and Participants: Pooled data from 14 studies between 1998 and 2009 comprising 20 871 children (aged 4-18 years) from the International Children's Accelerometry Database. Time spent in MVPA and sedentary time were measured using accelerometry after reanalyzing raw data. The independent associations between time in MVPA and sedentary time, with outcomes, were examined using meta-analysis. Participants were stratified by tertiles of MVPA and sedentary time.

    Main Outcome Measures: Waist circumference, systolic blood pressure, fasting triglycerides, high-density lipoprotein cholesterol, and insulin.

    Results: Times (mean [SD] min/d) accumulated by children in MVPA and being sedentary were 30 (21) and 354 (96), respectively. Time in MVPA was significantly associated with all cardiometabolic outcomes independent of sex, age, monitor wear time, time spent sedentary, and waist circumference (when not the outcome). Sedentary time was not associated with any outcome independent of time in MVPA. In the combined analyses, higher levels of MVPA were associated with better cardiometabolic risk factors across tertiles of sedentary time. The differences in outcomes between higher and lower MVPA were greater with lower sedentary time. Mean differences in waist circumference between the bottom and top tertiles of MVPA were 5.6 cm (95% CI, 4.8-6.4 cm) for high sedentary time and 3.6 cm (95% CI, 2.8-4.3 cm) for low sedentary time. Mean differences in systolic blood pressure for high and low sedentary time were 0.7 mm Hg (95% CI, -0.07 to 1.6) and 2.5 mmHg (95% CI, 1.7-3.3), and for high-density lipoprotein cholesterol, differences were -2.6 mg/dL(95% CI, -1.4 to -3.9) and -4.5 mg/dL(95% CI, -3.3 to -5.6), respectively. Geometric mean differences for insulin and triglycerides showed similar variation. Those in the top tertile of MVPA accumulated more than 35 minutes per day in this intensity level compared with fewer than 18 minutes per day for those in the bottom tertile. In prospective analyses (N=6413 at 2.1 years' follow-up), MVPA and sedentary time were not associated with waist circumference at follow-up, but a higher waist circumference at baseline was associated with higher amounts of sedentary time at follow-up.

    Conclusion: Higher MVPA time by children and adolescents was associated with better cardiometabolic risk factors regardless of the amount of sedentary time.

  • 8.
    Ekelund, Ulf
    et al.
    Örebro University, School of Health and Medical Sciences.
    Ong, Ken K.
    Linné, Yvonne
    Neovius, Martin
    Brage, Sören
    Dunger, David B.
    Wareham, Nicholas J.
    Rössner, Stephan
    Association of weight gain in infancy and early childhood with metabolic risk in young adults2007In: Journal of Clinical Endocrinology and Metabolism, ISSN 0021-972X, E-ISSN 1945-7197, Vol. 92, no 1, p. 98-103Article in journal (Refereed)
    Abstract [en]

    CONTEXT: Early postnatal life has been suggested as an important window during which risks for long-term health may be influenced. OBJECTIVE: The aim of this study was to examine the independent associations between weight gain during infancy (0-6 months) and early childhood (3-6 yr) with components of the metabolic syndrome in young adults. DESIGN: This was a prospective cohort study (The Stockholm Weight Development Study). SETTING: The study was conducted in a general community. PARTICIPANTS: Subjects included 128 (54 males) singletons, followed from birth to 17 yr. MAIN OUTCOME MEASURE: None of these young adults met the full criteria for the metabolic syndrome. We therefore calculated a continuous clustered metabolic risk score by averaging the standardized values of the following components: waist circumference, blood pressure, fasting triglycerides, high-density lipoprotein cholesterol, glucose, and insulin level. RESULTS: Clustered metabolic risk at age 17 yr was predicted by weight gain during infancy (standardized beta = 0.16; P < 0.0001) but not during early childhood (standardized beta = 0.10; P = 0.23), adjusted for birth weight, gestational age, current height, maternal fat mass, and socioeconomic status at age 17 yr. Further adjustment for current fat mass and weight gain during childhood did not alter the significant association between infancy weight gain with the metabolic risk score (standardized beta = 0.20; P = 0.007). CONCLUSIONS: Rapid weight gain during infancy (0-6 months) but not during early childhood (3-6 yr) predicted clustered metabolic risk at age 17 yr. Early interventions to moderate rapid weight gain even at very young ages may help to reduce adult cardiovascular disease risks.

  • 9.
    Ekelund, Ulf
    et al.
    Örebro University, School of Health and Medical Sciences, Örebro University, Sweden. Unit for Preventive Nutrition, Department of Medical Nutrition, Karolinska Institutet, Huddinge, Sweden.
    Poortvliet, Eric
    Unit for Preventive Nutrition, Department of Medical Nutrition, Karolinska Institutet, Huddinge, Sweden.
    Nilsson, Andreas
    Örebro University, School of Health and Medical Sciences, Örebro University, Sweden. Unit for Preventive Nutrition, Department of Medical Nutrition, Karolinska Institutet, Huddinge, Sweden.
    Yngve, Agneta
    Unit for Preventive Nutrition, Department of Medical Nutrition, Karolinska Institutet, Huddinge, Sweden.
    Holmberg, Anders
    Department of Statistics, Örebro University, 701 82 Örebro, Sweden.
    Sjöström, Michael
    Department of Physical Education and Health, Örebro University, Örebro, Sweden; Unit for Preventive Nutrition, Department of Medical Nutrition, Karolinska Institutet, Huddinge, Sweden.
    Physical activity in relation to aerobic fitness and body fat in 14- to 15-year-old boys and girls2001In: European Journal of Applied Physiology, ISSN 1439-6319, E-ISSN 1439-6327, Vol. 85, no 3-4, p. 195-201Article in journal (Refereed)
    Abstract [en]

    The purpose of this study was to examine the strength of the relationship between different variables of physical activity and aerobic fitness and body fat in adolescent boys and girls. Activity energy expenditure (AEE), time spent in a sedentary state, and time spent engaged in moderate and vigorous physical activity (MVPA, > or = 50% peak oxygen uptake, VO2peak) were assessed by the minute-by-minute heart rate monitoring method in 82 randomly selected 14- to 15-year olds (42 boys, 40 girls). Body fat was determined by measuring skinfold thicknesses. VO2peak was measured by indirect calorimetry. Somatic maturity level was determined by percentages of adult (i.e. 18 years) height attained at examination. AEE was related to aerobic fitness for both genders (boys, r = 0.30, P = 0.056; girls, r = 0.45, P = 0.003). For boys, there was a significant relationship between maturity level and VO2peak (r = 0.48, P < 0.001). For both genders, body fat was significantly and negatively related to VO2peak (r = -0.48 and r = -0.43, P < 0.01). Body fat and maturity explained 47% of the variation in VO2peak in boys, whereas AEE and body fat explained 22% of the variation in VO2peak in girls. No significant associations between physical activity variables and the data on body fat were observed. The total amount of physical activity (AEE) was related to VO2peak, at least in adolescent girls. Although VO2peak seems to be influenced by the maturity level in adolescent boys, the data support the promotion of a daily active lifestyle among young people.

  • 10.
    Ekelund, Ulf
    et al.
    Örebro University, Department of Health Sciences.
    Poortvliet, Eric
    Yngve, Agneta
    Hurtig-Wennlöf, Anita
    Örebro University, Department of Clinical Medicine.
    Nilsson, Andreas
    Örebro University, Department of Health Sciences.
    Sjöström, Michael
    Heart rate as an indicator of the intensity of physical activity in human adolescents2001In: European Journal of Applied Physiology, ISSN 1439-6319, E-ISSN 1439-6327, Vol. 85, no 3-4, p. 244-249Article in journal (Refereed)
    Abstract [en]

    The aims of this study were, in a group of adolescents, firstly to identify the absolute heart rates (HR) and the percentages of maximal heart rates (HRmax) corresponding to 40%, 60% and 80% of peak oxygen uptake (PVO2), secondly to identify absolute and relative (%PVO2) oxygen uptakes (VO2) corresponding to HR of 120, 140 and 160 beats.min-1, and thirdly to examine a possible effect of fatness and fitness on the relationship between HR and VO2. The subjects were 127 (60 boys, 67 girls) adolescents with a mean age of 14.8 (SD 0.3) years. The HR and VO2 were measured by means of an incremental exercise test to exhaustion. Linear regressions were performed for the HR-VO2 and VO2-HR relationships using absolute and relative (%HRmax, %PVO2) data for each individual. From these regressions, target HR and VO2 were computed. Average target HR corresponding to 40%, 60% and 80% of PVO2 were: 119 (SD 9), 145 (SD 9), 171 (SD 8), and 120 (SD 10), 146 (SD 8), 172 (SD 8) beats.min-1 for boys and girls, respectively. Average VO2 corresponding to HR of 120, 140 and 160 beats.min-1 were: 22 (SD 5), 30 (SD 5), 38 (SD 6) and 18 (SD 4), 24 (SD 4), 31 (SD 4) mlO2.kg-1.min-1 for boys and girls, respectively. An analysis of covariance showed a significant fitness effect (P < 0.001) for predicted VO2 at all HR studied. The results suggest that the use of absolute HR to define exercise intensity levels when assessing young people's physical activity using HR monitoring detracts from the validity of the interpretation of the data.

  • 11.
    Ekelund, Ulf
    et al.
    Örebro University, School of Health and Medical Sciences, Örebro University, Sweden. Unit for Preventive Nutrition, Department of Medical Nutrition, Karolinska Institutet, Stockholm, Sweden.
    Sjöström, Michael
    Unit for Preventive Nutrition, Department of Medical Nutrition, Karolinska Institutet, Stockholm, Sweden;.
    Yngve, Agneta
    Unit for Preventive Nutrition, Department of Medical Nutrition, Karolinska Institutet, Stockholm, Sweden;.
    Nilsson, Andreas
    Örebro University, School of Health and Medical Sciences, Örebro University, Sweden. Unit for Preventive Nutrition, Department of Medical Nutrition, Karolinska Institutet, Stockholm, Sweden;.
    Total daily energy expenditure and pattern of physical activity measured by minute-by-minute heart rate monitoring in 14-15 year old Swedish adolescents2000In: European Journal of Clinical Nutrition, ISSN 0954-3007, E-ISSN 1476-5640, Vol. 54, no 3, p. 195-202Article in journal (Refereed)
    Abstract [en]

    OBJECTIVE: To assess total daily energy expenditure (TDEE) and patterns of physical activity among Swedish male and female adolescents and to relate the amount and intensity of physical activity to existing recommendations (energy expenditure equal to or above 12.4 kJ/kg/day or accumulation of 30 min/day in moderate physical activity equal to 4.5 times sedentary energy expenditure or more).

    DESIGN: TDEE, physical activity level (PAL=TDEE/BMR), energy expenditure (EE) and time spent in different intensities of physical activity were assessed by using minute-by-minute heart rate monitoring in combination with laboratory measured sedentary energy expenditure (SEE) and peak oxygen uptake.

    SETTING: Department of Physical Education and Health, Orebro University, and Department of Clinical Physiology, Orebro Medical Centre Hospital, Sweden.

    SUBJECTS: Eighty-two 14-15 y old adolescents (42 boys, 40 girls) from the city of Orebro, randomly selected through a two-stage sampling procedure.

    RESULTS: TDEE was 12.8 MJ/day and 10.0 MJ/day for boys and girls respectively (P<0.001) and PAL was 1.74 and 1.67 (NS). Forty-four percent and 47%, respectively, of TDEE referred to EE in physical activity, of which 70% for both genders referred to light physical activity (corresponding to <4.5 times SEE). Eleven boys and 14 girls had an EE lower than 12.4 kJ/kg/day and/or did not accumulate 30 min/day in physical activity >/=4.5 SEE. Those (n=20) with the highest PAL values (>2.01 and 1.81, respectively) spent 149 min/day at a >/=4.5 SEE intensity level compared to 40 min/day for those (n=30) with the lowest PAL values (<1.55 and 1.45, respectively).

    CONCLUSIONS: Swedish adolescent boys and girls are similarly physically active. The major amount of time devoted to physical activity refers to light physical activity. At least thirty percent of adolescents seem not to achieve appropriate levels of physical activity considered to be beneficial for health.

  • 12.
    Ekelund, Ulf
    et al.
    Örebro University, School of Health and Medical Sciences, Örebro University, Sweden. Unit for Preventive Nutrition, Department of Medical Nutrition, Karolinska Institutet, Stockholm, Sweden.
    Sjöström, Michael
    Unit for Preventive Nutrition, Department of Medical Nutrition, Karolinska Institutet, Stockholm, Sweden.
    Yngve, Agneta
    Unit for Preventive Nutrition, Department of Medical Nutrition, Karolinska Institutet, Stockholm, Sweden.
    Poortvliet, Eric
    Unit for Preventive Nutrition, Department of Medical Nutrition, Karolinska Institutet, Stockholm, Sweden.
    Nilsson, Andreas
    Örebro University, School of Health and Medical Sciences, Örebro University, Sweden.
    Fröberg, Karsten
    Institute of Sport Science and Clinical Biomechanics, University of Southern Denmark, Odense, Denmark.
    Wedderkopp, Niels
    Institute of Sport Science and Clinical Biomechanics, University of Southern Denmark, Odense, Denmark.
    Westerterp, Klaas
    Department of Human Biology, Maastricht University, Maastricht, The Netherlands.
    Physical activity assessed by activity monitor and doubly labeled water in children2001In: Medicine & Science in Sports & Exercise, ISSN 0195-9131, E-ISSN 1530-0315, Vol. 33, no 2, p. 275-281Article in journal (Refereed)
    Abstract [en]

    PURPOSE: To validate the Computer Science and Application's (CSA) activity monitor for assessment of the total amount of physical activity during two school-weeks in 9-yr-old children and to develop equations to predict total energy expenditure (TEE) and activity energy expenditure (AEE) from activity counts and anthropometric variables.

    METHODS: A total of 26 children (15 boys and 11 girls, mean age 9.1 +/- 0.3 yr) were monitored for 14 consecutive days. TEE was simultaneously measured by the doubly labeled water method. Averaged activity counts (counts.min(-1)) were compared with data on: 1) TEE, 2) AEE = TEE minus basal metabolic rate (BMR; estimated from predictive equations), and 3) daily physical activity level (PAL = TEE/BMR).

    RESULTS: Physical activity determined by activity counts was significantly related to the data on energy expenditures: TEE (r = 0.39; P < 0.05), AEE (r = 0.54; P < 0.01), and PAL (r = 0.58; P < 0.01). Multiple stepwise regression analysis showed that TEE was significantly influenced by gender, body composition (body weight or fat free mass), and activity counts (R(2) = 0.54--0.60). AEE was significantly influenced by activity counts and gender (R(2) = 0.45). There were no significant differences between activity counts and PAL in discriminating among activity levels with "low" (PAL < 1.56), "moderate" (1.57 < or = PAL > or = 1.81), and "high" (PAL > 1.81) intensity.

    CONCLUSION: Activity counts from the CSA activity monitor seems to be a useful measure of the total amount of physical activity in 9-yr-old children. Activity counts contributed significantly to the explained variation in TEE and was the best predictor of AEE.

  • 13.
    Ekelund, Ulf
    et al.
    Örebro University, School of Health and Medical Sciences.
    Tomkinson, Grant R.
    Armstrong, Neil
    What proportion of youth are physically active?: Measurement issues, levels and recent time trends2011In: British Journal of Sports Medicine, ISSN 0306-3674, E-ISSN 1473-0480, Vol. 45, no 11, p. 859-865Article in journal (Refereed)
    Abstract [en]

    Aim The aim of this review is to summarise issues surrounding the measurement of physical activity (PA) by self-report and accelerometry in youth (2-18 years old). Current levels and temporal trends in PA and sport participation and the effect of assessment method on data interpretation will be summarised. Methods Relevant papers were extracted from a computerised literature search of MEDLINE and personal databases. Additional papers were extracted from reference lists of recently published reviews. Results The criterion validity (direct comparison with an objective method) of self-reported instruments is low to moderate, with correlation coefficients generally between 0.3 and 0.4. Self-report instruments overestimate the intensity and duration of PA and sport participation. The interpretation of PA data from accelerometry is a challenge, and specific issues include the definition of intensity thresholds and the influence of age on intensity thresholds. Recent data on self-reported PA in youth suggest that between 30% and 40% are sufficiently active. Prevalence values for sufficiently active youth measured by accelerometry range between 1% and 100%, depending on the intensity thresholds used. Sport participation is likely to contribute to higher levels of PA. The available evidence does not support the notion that PA levels and sport participation in youth have declined in recent decades. Conclusion The number of youth meeting current PA guidelines varies by assessment method and the intensity thresholds used when PA is measured by accelerometry. The available evidence does not firmly support the notion that PA in young people has declined during the last decades. It is unlikely that any self-report method is sufficiently accurate for examining cross-cultural differences and temporal trends in young people's PA and sport participation over time. Surveillance systems therefore need to strive for an international standardisation using objective measurements of PA to complement existing self-report instruments.

  • 14.
    Ekelund, Ulf
    et al.
    MRC Epidemiology Unit, Cambridge, United Kingdom; Department of Physical Education and Health, Örebro University, Örebro, Sweden; MRC Epidemiology Unit, Strangeways Research Laboratory, Worts Causeway, Cambridge, United Kingdom .
    Yngve, Agneta
    PREVNUT at Novum, Karolinska Institutet, Stockholm, Sweden .
    Brage, Sören
    Department of Physical Education and Health, Örebro University, Örebro, Sweden; Institute of Sport Science and Clinical Biomechanics, University of Southern Denmark, Odense, Denmark .
    Westerterp, Klaas
    Department of Human Biology, Maastricht University, Maastricht, Netherlands .
    Sjöström, Michael
    PREVNUT at Novum, Karolinska Institutet, Stockholm, Sweden .
    Body movement and physical activity energy expenditure in children and adolescents: how to adjust for differences in body size and age2004In: American Journal of Clinical Nutrition, ISSN 0002-9165, E-ISSN 1938-3207, Vol. 79, no 5, p. 851-856Article in journal (Refereed)
    Abstract [en]

    BACKGROUND: Physical activity data in children and adolescents who differ in body size and age are influenced by whether physical activity is expressed in terms of body movement or energy expenditure.

    OBJECTIVE: We examined whether physical activity expressed as body movement (ie, accelerometer counts) differs from physical activity energy expenditure (PAEE) as a function of body size and age.

    DESIGN: This was a cross-sectional study in children [n = 26; (+/-SD) age: 9.6 +/- 0.3 y] and adolescents (n = 25; age: 17.6 +/- 1.5 y) in which body movement and total energy expenditure (TEE) were simultaneously measured with the use of accelerometry and the doubly labeled water method, respectively. PAEE was expressed as 1) unadjusted PAEE [TEE minus resting energy expenditure (REE); in MJ/d], 2) PAEE adjusted for body weight (BW) (PAEE. kg(-1). d(-1)), 3) PAEE adjusted for fat-free mass (FFM) (PAEE. kg FFM(-1). d(-1)), and 4) the physical activity level (PAL = TEE/REE).

    RESULTS: Body movement was significantly higher (P = 0.03) in children than in adolescents. Similarly, when PAEE was normalized for differences in BW or FFM, it was significantly higher in children than in adolescents (P = 0.03). In contrast, unadjusted PAEE and PAL were significantly higher in adolescents (P < 0.01).

    CONCLUSIONS: PAEE should be normalized for BW or FFM for comparison of physical activity between children and adolescents who differ in body size and age. Adjusting PAEE for FFM removes the confounding effect of sex, and therefore FFM may be the most appropriate body-composition variable for normalization of PAEE. Unadjusted PAEE and PAL depend on body size.

  • 15.
    Ekelund, Ulf
    et al.
    Unit for Preventive Nutrition, Department of Medical Nutrition, Karolinska Institutet, Stockholm; Department of Physical Education and Health, Örebro University, Sweden.
    Yngve, Agneta
    Unit for Preventive Nutrition, Department of Medical Nutrition, Karolinska Institutet, Stockholm.
    Sjöström, Michael
    Unit for Preventive Nutrition, Department of Medical Nutrition, Karolinska Institutet, Stockholm; Department of Physical Education and Health, Örebro University, Sweden.
    Total daily energy expenditure and patterns of physical activity in adolescents assessed by two different methods1999In: Scandinavian Journal of Medicine and Science in Sports, ISSN 0905-7188, E-ISSN 1600-0838, Vol. 9, no 5, p. 257-264Article in journal (Refereed)
    Abstract [en]

    Minute-by-minute heart rate monitoring and an activity diary were used simultaneously during three days in 30 randomly selected adolescents (16 boys, 14 girls; mean age 15.0+/-1.0). Total daily energy expenditure (TDEE) and its components (energy expenditure during sleep, during rest and in physical activity) and times spent at different intensity levels (sedentary, light, moderate physical activity and vigorous physical activity) were compared. TDEE from heart rate monitoring averaged 10.9+/-2.7 MJ x d(-1) compared to 11.3+/-2.3 MJ x d(-1) from the activity diary (NS). The limits of agreement (mean+/-2 SD) were -3.54 MJ x d(-1) and 2.74 MJ x d(-1). There was no significant difference for any of the TDEE components between the methods (MANOVA). A significant method effect (P<0.001) was observed for time spent in sedentary and light physical activity (MANOVA). No significant difference was observed for time spent in moderate and vigorous physical activity. According to this, heart rate monitoring and activity diary are comparable for group assessment of TDEE and its components, and for estimating time spent in moderate and vigorous physical activity. The activity diary underestimated time spent in moderate and vigorous physical activity for inactive subjects and consequently overestimated highly active subjects.

  • 16.
    Ekelund, Ulf
    et al.
    Unit for Preventive Nutrition, Department of Medical Nutrition, Karolinska Institutet, Stockholm, Sweden; Department of Physical Education and Health, Örebro of University, Örebro, Sweden .
    Yngve, Agneta
    Unit for Preventive Nutrition, Department of Medical Nutrition, Karolinska Institutet, Stockholm, Sweden .
    Sjöström, Michael
    Unit for Preventive Nutrition, Department of Medical Nutrition, Karolinska Institutet, Stockholm, Sweden; Department of Physical Education and Health, Örebro of University, Örebro, Sweden.
    Westerterp, Klaas
    Department of Human Biology, Maastricht University, Maastricht, Netherlands .
    Field evaluation of the Computer Science and Application's Inc. Activity monitor during running and skating training in adolescent athletes2000In: International Journal of Sports Medicine, ISSN 0172-4622, E-ISSN 1439-3964, Vol. 21, no 8, p. 586-592Article in journal (Refereed)
    Abstract [en]

    This study investigated the validity of the CSA activity monitor for assessment of the total amount of physical activity in adolescent athletes. Activity data were compared to data on daily energy expenditure and its derivatives measured by the doubly labeled water method. Seven athletes (speed skaters) with a mean age of 18.2+/-1.1 y were monitored twice (off-season and pre-season) by the activity monitor for eight consecutive days. The primary training during the off-season period was running whereas the pre-season period mainly involved skate training (i.e. inline skating, slideboard training, and skating imitations). Activity counts were significantly correlated to all energy estimates during the off-season period (r=0.93-0.96; P<0.01) whereas not during the pre-season period (r=0.32-0.57). A two-way multivariate analysis of variance showed a significant period effect for activity counts (668+/-163 vs. 548+/-91; P=0.026) whereas not for total daily energy expenditure (15.7+/-2.1 MJ x d(-1) vs. 16.0+/-1.0 MJ x d(-1); P=0.71). The relationship between activity counts and total daily energy expenditure seems to be affected by different training conditions. Therefore these circumstances have to be carefully considered in the interpretation of activity monitor data.

  • 17.
    Ekelund, Ulf
    et al.
    Unit for Preventive Nutrition at Novum, Department of Medical Nutrition/Biosciences, Karolinska Institutet, Stockholm, Sweden; Department of Physical Education and Health, Örebro University, Sweden.
    Yngve, Agneta
    Unit for Preventive Nutrition at Novum, Department of Medical Nutrition/Biosciences, Karolinska Institutet, Stockholm, Sweden.
    Westerterp, Klaas
    Department of Human Biology, Maastricht University, Maastricht, The Netherlands.
    Sjöström, Michael
    Unit for Preventive Nutrition at Novum, Department of Medical Nutrition/Biosciences, Karolinska Institutet, Stockholm, Sweden.
    Energy expenditure assessed by heart rate and doubly labeled water in young athletes2002In: Medicine & Science in Sports & Exercise, ISSN 0195-9131, E-ISSN 1530-0315, Vol. 34, no 8, p. 1360-1366Article in journal (Refereed)
    Abstract [en]

    PURPOSE: To compare total energy expenditure (TEE) estimated by the FLEX heart rate (HR) method with that measured by the doubly labeled water (DLW) technique in young speed skaters. We hypothesized that the accuracy of FLEX HR-estimated TEE would be affected by a) the definition of the FLEX HR and b) the type of training regimen.

    METHODS: Eight young athletes (mean age 18.2 +/- 1.3 yr) underwent measurements during two 10-d training periods: an off-season period with voluntary training (predominantly running) and a preseason period mainly focused on skating technique training. TEE was measured simultaneously by the DLW and FLEX HR methods. FLEX HR1 was defined as the mean of the HRs during all resting calibration activities and the lowest HR during exercising calibration activities. FLEX HR2 was defined as the mean of the highest HR during resting activities and the lowest HR during exercising.

    RESULTS: ANOVA showed that FLEX HR1 was significantly lower than FLEX HR2 (mean of both periods; 77 +/- 5 vs 84 +/- 6 beats.min(-1); P = 0.004). TEE values obtained by DLW were 16.8 +/- 3.8 and 16.9 +/- 2.9 MJ.d(-1) in the two periods, respectively. TEE values calculated from FLEX HR1 were 17.8 +/- 3.6 and 17.4 +/- 2.6 MJ.d(-1), and those from FLEX HR2 17.1 +/- 3.1 and 17.0 +/- 2.7 MJ.d-1, respectively. No significant period (P = 0.83) or method (P = 0.44) effect on TEE was observed.

    CONCLUSION: FLEX HR-estimated TEE was not affected by the definition of the FLEX HR or by the type of training regimen as compared with TEE measured by the DLW method in young athletes.

  • 18.
    Ekelund, Ulf
    et al.
    Unit for Preventive Nutrition, Department of Medical Nutrition/Biosciences, Karolinska Institutet, Stockholm, Sweden; Department of Physical Education and Health, Örebro University, Örebro, Sweden; .
    Åman, Jan
    Örebro University, School of Health and Medical Sciences. Unit for Preventive Nutrition, Department of Medical Nutrition/Biosciences, Karolinska Institutet, Stockholm, Sweden; .
    Yngve, Agneta
    Unit for Preventive Nutrition, Department of Medical Nutrition/Biosciences, Karolinska Institutet, Stockholm, Sweden .
    Renman, Cecilia
    Department of Pediatrics, Örebro Medical Center, Örebro, Sweden .
    Westerterp, Klaas
    Department of Human Biology, Maastricht University, Maastricht, Netherlands.
    Sjöström, Michael
    Unit for Preventive Nutrition, Department of Medical Nutrition/Biosciences, Karolinska Institutet, Stockholm, Sweden .
    Physical activity but not energy expenditure is reduced in obese adolescents: a case-control study2002In: American Journal of Clinical Nutrition, ISSN 0002-9165, E-ISSN 1938-3207, Vol. 76, no 5, p. 935-941Article in journal (Refereed)
    Abstract [en]

    BACKGROUND: The influence of physical activity on body weight in children and adolescents is controversial.

    OBJECTIVE: The objective was to test the hypothesis that the intensity and duration of physical activity differ between obese and normal-weight adolescents, with no difference in estimated energy expenditure.

    DESIGN: We compared physical activity in 18 (8 males, 10 females) obese [body mass index (in kg/m(2)) > 30] adolescents (14-19 y) with that in a matched, normal-weight (BMI < 27) control group. Total energy expenditure (TEE) was measured with the doubly labeled water method, and physical activity was measured simultaneously by accelerometry. The physical activity level was determined as the ratio of TEE to the resting metabolic rate (RMR) and activity energy expenditure as 0.9 TEE minus RMR. Accelerometry data included total physical activity (counts x min(-1) x d(-1)), accumulated and continuous duration of activity, and continuous 10-min periods of physical activity of moderate intensity.

    RESULTS: There was no significant difference in adjusted (analysis of covariance) TEE, RMR, or AEE between groups. The physical activity level was significantly lower (P < 0.05) in the obese group. No sex x group interaction was observed. Differences in total physical activity (P < 0.001), accumulated time (P < 0.05), continuous time (P < 0.01), and continuous 10-min periods of physical activity of moderate intensity (P < 0.01) were observed between groups.

    CONCLUSIONS: Obese adolescents are less physically active than are normal-weight adolescents, but physical activity-related energy expenditure is not significantly different between groups. The data suggest that physical activity is not necessarily equivalent to the energy costs of activity.

  • 19. Hemmingsson, E.
    et al.
    Uddén, J.
    Neovius, M.
    Ekelund, Ulf
    Örebro University, School of Health and Medical Sciences.
    Rössner, S.
    Increased physical activity in abdominally obese women through support for changed commuting habits: a randomized clinical trial2009In: International Journal of Obesity, ISSN 0307-0565, E-ISSN 1476-5497, Vol. 33, no 6, p. 645-652Article in journal (Refereed)
    Abstract [en]

    Background: Abdominally obese women can reduce their health risk through regular physical activity. There is, however, little evidence on the effectiveness of interventions that promote physical activity long-term, such as cycling and walking to and from work. Methods: This intervention focused on physically active commuting (cycling and walking) in middle-aged (30-60 years), abdominally obese (waist circumference >= 88 cm) women (n = 120), recruited by newspaper advertisement. The intervention group was a moderate-intensity programme with physician meetings, physical activity prescriptions, group counselling and bicycles. The control group was a low-intensity group support programme with pedometers. We used a randomized, controlled, 2-armed design with 18 months duration and intention-to-treat analysis (data collection 2005-2006). Treatment success was defined as bicycling >= 2 km/d (primary) or walking 10 000 steps per day (secondary). Results: At baseline, mean (s. d.) age was 48.2 years (7.4), waist circumference 103.8cm (7.8), walking 8471 steps per day (2646), bicycling 0 km per day. Attrition at 18 months was 10% for the intervention group and 25% in the control group (P = 0.03). The intervention group was more likely to achieve treatment success for cycling than controls: 38.7 vs 8.9% (odds ratio (OR) 7.8 (95% confidence interval = 4.0 to 15.0, P < 0.001)), but with no difference for compliance with the walking recommendation: 45.7 vs 39.3% (OR 1.2 (95% CI 0.7 to 2.0, P = 0.50)). Commuting by car and public transport were reduced by 34% (P < 0.01) and 37% (P < 0.001), respectively, with no differences between groups. Both groups attained similar waist reductions (-2.1 and -2.6 cm, P = 0.72). Conclusions: Abdominally obese women can increase PA long-term through moderate-intensity behavioural support aimed at changing commuting habits. International Journal of Obesity (2009) 33, 645-652; doi: 10.1038/ijo.2009.77; published online 5 May 2009

  • 20. Hemmingsson, Erik
    et al.
    Ekelund, Ulf
    Örebro University, School of Health and Medical Sciences.
    Is the association between physical activity and body mass index obesity dependent?2007In: International Journal of Obesity, ISSN 0307-0565, E-ISSN 1476-5497, Vol. 31, no 4, p. 663-668Article in journal (Refereed)
    Abstract [en]

    BACKGROUND: Most studies indicate an inverse relationship between physical activity (PA) and body mass index (BMI). However, the impact of obesity on this relationship is unclear. OBJECTIVE: To scrutinize the BMI/PA relationship by analysing multiple categories of PA from a sample with a wide BMI range. DESIGN: PA was measured with accelerometry for 7 consecutive days during free-living conditions in 85 severely obese outpatients (mean BMI 42.7 kg/m(2) (s.d. 6.1); age 43.0 year (12.6)) and 193 control subjects (24.0 kg/m(2) (3.5); 41.6 year (13.0)). Six categories of PA were calculated from the accelerometer data (min/day of sedentary time, min/day of light PA, min/day of moderate PA, min/day of vigorous PA, activity counts/day and steps/day). Participants were stratified in obese and non-obese subgroups (BMI=30 kg/m(2) as cutoff). Associations between BMI and PA were examined in the total sample, and in subgroups. The impact of sex and age on the BMI/PA association was tested. RESULTS: In the total sample, the association between BMI and PA was significant in all PA categories except for time spent sedentary (P=0.68). However, in subgroup analyses, the association between BMI and PA in non-obese was only significant for activity counts/day (r=-0.16, P<0.05) and vigorous intensity PA (r=-0.15, P=0.05). After adjustment for age, vigorous PA remained significantly associated with BMI in the non-obese (r=-0.17, P<0.05). In obese individuals, significant associations between BMI and PA were found for all six PA categories (age adjusted), sedentary time (r=0.26, P=0.05), light PA (r=-0.30, P<0.01), moderate PA (r=-0.35, P<0.01), vigorous PA (r=-0.39, P<0.001), activity counts/day (r=-0.50, P<0.001) and steps/day (r=-0.54, P<0.001). CONCLUSION: The association between PA and BMI was weak in non-obese individuals. In contrast, BMI was highly significantly associated with PA in obese individuals. Longitudinal studies are needed to tease out the direction of association between PA and BMI across BMI categories, as the cross-sectional associations seem to be dependent on obesity status.

  • 21. Hemmingsson, Erik
    et al.
    Hellenius, Mai-Lis
    Ekelund, Ulf
    Örebro University, School of Health and Medical Sciences.
    Bergström, Jakob
    Rössner, Stephan
    Impact of social support intensity on walking in the severely obese:  a randomized clinical trial2008In: Obesity, ISSN 1930-7381, Vol. 16, no 6, p. 1308-1313Article in journal (Refereed)
    Abstract [en]

    OBJECTIVE: There are few established methods for promoting physical activity (PA) in the severely obese. Because social support is a potential method for promoting PA, we compared mean steps/day during 18 weeks in severely obese outpatients receiving either standard support (SS) or added support (AS). METHODS AND PROCEDURES: Eighty severely obese outpatients from an obesity clinic were invited; 66 provided written consent, 55 were randomized, and 42 were included in final analyses (9 men, 33 women; age 44.4 +/- 13.1 years; BMI 41.9 +/- 5.5 kg/m(2)). All participants received a pedometer and a walking promotion booklet. In addition to SS, the AS group received ten 2-h group counseling sessions aimed at increasing weekly accumulated steps, every second week during the study. Each participant was asked to complete a 7-day walking diary every second week (10 observations). RESULTS: Baseline steps/day was 6,912 for the AS group and 5,311 for the SS group (P = 0.023). Data at 18 weeks showed that the AS group recorded 10,136 steps/day and the SS group 6,118 steps/day (P = 0.024). There was no allocation x time interaction (P = 0.46). During the follow-up period as a whole, the AS group recorded 1,794 more steps/day than the SS group (P = 0.0074). DISCUSSION: The AS group recorded more steps/day than the SS group, reaching a mean level of approximately 10,000 steps/day. However, the nonsignificant interaction between allocation x time suggests that this difference was present already at baseline and did not increase during follow-up.

  • 22. Kelliny, Clara
    et al.
    Ekelund, Ulf
    Örebro University, School of Health and Medical Sciences.
    Andersen, Lars Bo
    Brage, Sören
    Loos, Ruth J. F.
    Wareham, Nicholas J.
    Langenberg, Claudia
    Common genetic determinants of glucose homeostasis in healthy children: the European youth heart study2009In: Diabetes, ISSN 0012-1797, E-ISSN 1939-327X, Vol. 58, no 12, p. 2939-2945Article in journal (Refereed)
    Abstract [en]

    OBJECTIVE-The goal of this study was to investigate whether the effects of common genetic variants associated with fasting glucose in adults are detectable in healthy children. RESEARCH DESIGN AND METHODS-Single nucleotide polymorphisms in MTNR1B (rs10830963), G6PC2 (rs560887), and GCK (rs4607517) were genotyped in 2,025 healthy European children aged 9-11 and 14-16 years. Associations with fasting glucose, insulin, homeostasis model assessment (HOMA)-insulin resistance (IR) and HOMA-B were investigated along with those observed for type 2 diabetes variants available in this study (CDKN2A/B, IGF2BP2, CDKAL1, SLC30A8, HHEX-IDE, and Chr 11p12). RESULTS-Strongest associations were observed for G6PC2 and MTNR1B, with mean fasting glucose levels (95% Cl) being 0.084 (0.06-0.11) mmol/l, P = 7.9 x 10(-11) and 0.069 (0.04-0.09) mmol/l, p = 1.9 x 10(-7) higher per risk allele copy, respectively. A similar but weaker trend was observed for GCK (0.028 [-0.006 to 0.06] mmol/l, P = 0.11). All three variants were associated with lower P-cell function (HOMA-B P = 9.38 x 10(-5), 0.004, and 0.04, respectively). SLC30A8 (rs13266634) was the only type 2 diabetes variant associated with higher fasting glucose (0.033 mmol/l [0.01-0.06], P = 0.01). Calculating a genetic predisposition score adding the number of risk alleles of G6PC2, MTNR1B, GCK, and SLC30A8 showed that glucose levels were successively higher in children carrying a greater number of risk alleles (P = 7.1 x 10(-17)), with mean levels of 5.34 versus 4.91 mmol/l comparing children with seven alleles (0.6% of all children) to those with none (0.5%). No associations were found for fasting insulin or HOMA-IR with any of the variants. CONCLUSIONS-The effects of common polymorphisms influencing fasting glucose are apparent in healthy children, whereas the presence of multiple risk alleles amounts to a difference of >1 SD of fasting glucose. Diabetes 58:2939-2945, 2009

  • 23. Kilpelaeinen, Tuomas O.
    et al.
    den Hoed, Marcel
    Ong, Ken K.
    Grontved, Anders
    Brage, Sören
    Jameson, Karen
    Cooper, Cyrus
    Khaw, Kay-Tee
    Ekelund, Ulf
    Örebro University, School of Health and Medical Sciences.
    Wareham, Nicholas J.
    Loos, Ruth J. F.
    Obesity-susceptibility loci have a limited influence on birth weight: a meta-analysis of up to 28,219 individuals2011In: American Journal of Clinical Nutrition, ISSN 0002-9165, E-ISSN 1938-3207, Vol. 93, no 4, p. 851-860Article in journal (Refereed)
    Abstract [en]

    Background: High birth weight is associated with adult body mass index (BMI). We hypothesized that birth weight and BMI may partly share a common genetic background. Objective: The objective was to examine the associations of 12 established BMI variants in or near the NEGR1, SEC16B, TMEM18, ETV5, GNPDA2, BDNF, MTCH2, BCDIN3D, SH2B1, FTO, MC4R, and KCTD15 genes and their additive score with birth weight. Design: A meta-analysis was conducted with the use of 1) the European Prospective Investigation into Cancer and Nutrition (EPIC)-Norfolk, Hertfordshire, Fenland, and European Youth Heart Study cohorts (n(max) = 14,060); 2) data extracted from the Early Growth Genetics Consortium meta-analysis of 6 genome-wide association studies for birth weight (n(max) = 10,623); and 3) all published data (n(max) = 14,837). Results: Only the MTCH2 and FTO loci showed a nominally significant association with birth weight. The BMI-increasing allele of the MTCH2 variant (rs10838738) was associated with a lower birth weight (beta +/- SE: 213 +/- 5 g/allele; P = 0.012; n = 23,680), and the BMI-increasing allele of the FTO variant (rs1121980) was associated with a higher birth weight (beta +/- SE: 11 +/- 4 g/allele; P = 0.013; n = 28,219). These results were not significant after correction for multiple testing. Conclusions: Obesity-susceptibility loci have a small or no effect on weight at birth. Some evidence of an association was found for the MTCH2 and FTO loci, ie, lower and higher birth weight, respectively. These findings may provide new insights into the underlying mechanisms by which these loci confer an increased risk of obesity. Am J Clin Nutr 2011;93:851-60.

  • 24. Mountjoy, Margo
    et al.
    Andersen, Lars Bo
    Armstrong, Neil
    Biddle, Stuart
    Boreham, Colin
    Bedenbeck, Hans-Peter Brandl
    Ekelund, Ulf
    Örebro University, School of Health and Medical Sciences.
    Engebretsen, Lars
    Hardman, Ken
    Hills, Andrew
    Kahlmeier, Sonja
    Kriemler, Susi
    Lambert, Estelle
    Ljungqvist, Arne
    Matsudo, Victor
    McKay, Heather
    Micheli, Lyle
    Pate, Russell
    Riddoch, Chris
    Schamasch, Patrick
    Sundberg, Carl Johan
    Tomkinson, Grant
    van Sluijs, Esther
    van Mechelen, Willem
    International Olympic Committee consensus statement on the health and fitness of young people through physical activity and sport2011In: British Journal of Sports Medicine, ISSN 0306-3674, E-ISSN 1473-0480, Vol. 45, no 11, p. 839-848Article in journal (Refereed)
  • 25. Neovius, Martin
    et al.
    Rössner, Sophia M.
    Vågstrand, Karin
    Linné von Hausswolff-Juhlin, Yvonne
    Hoffstedt, Johan
    Ekelund, Ulf
    Örebro University, School of Health and Medical Sciences.
    Adiposity measures as indicators of metabolic risk factors in adolescents2009In: Obesity Facts, ISSN 1662-4025, E-ISSN 1662-4033, Vol. 2, no 5, p. 294-301Article in journal (Refereed)
    Abstract [en]

    Aim: To examine the relation between adiposity assessment methods (percentage body fat (%BF), BMI, and waist circumference (WC)) and individual metabolic risk factors (f-insulin, HDL cholesterol, triglycerides) and a combined measure of metabolic risk. Methods: Cross-sectional study of 300 males (BMI 20.8 +/- 3.0 kg/m(2)) and females (BMI 21.3 +/- 2.9 kg/m(2)) 17 years of age. F-insulin and components of the metabolic syndrome defined by the International Diabetes Federation (IDF) were used as metabolic risk indicators, with samples stratified into BMI, %BF, and WC groups, respectively. Diagnostic accuracy was expressed as the area under the ROC curve (AUC). Results: In males, diagnostic accuracy for HDL and f-insulin was poor to fair for BMI (AUC 0.70, p = 0.001; 0.60, p = 0.22), WC (0.68, p = 0.003; 0.63, p = 0.11), and %BF (0.65, p = 0.009; 0.66, p = 0.04). The diagnostic accuracy for triglycerides was greater for all three measures (BMI 0.92, WC 0.95, %BF 0.87; all p < 0.001). For females, neither test performed better than chance for f-insulin and HDL, and only %BF performed better than chance for triglycerides (0.65, p = 0.08). All three measures exhibited higher accuracy for presence of >= 2 metabolic risk factors (AUCs 0.76-0.91, p < 0.001) in both sexes. Conclusion: %BF was not superior to BMI and WC for detecting metabolic risk in the general adolescent population.

  • 26.
    Nilsson, Andreas
    et al.
    Örebro University, School of Health and Medical Sciences.
    Andersen, Lars Bo
    Ommundsen, Yngvar
    Froberg, Karsten
    Sardinha, Luis B.
    Piehl-Aulin, Karin
    Örebro University, School of Health and Medical Sciences.
    Ekelund, Ulf
    Örebro University, School of Health and Medical Sciences.
    Correlates of objectively assessed physical activity and sedentary time in children: a cross-sectional study (The European Youth Heart Study)2009In: BMC Public Health, ISSN 1471-2458, E-ISSN 1471-2458, Vol. 9, article id 322Article in journal (Refereed)
    Abstract [en]

    Background

    Identifying leisure time activities performed before and after school that influence time in physical activity (PA) and/or time spent sedentary can provide useful information when designing interventions aimed to promote an active lifestyle in young people. The purpose of this study was to examine associations between mode of transportation to school, outdoor play after school, participation in exercise in clubs, and TV viewing with objectively assessed PA and sedentary behaviour in children.

    Methods

    A total of 1327 nine- and 15-year-old children from three European countries (Norway, Estonia, Portugal) participated as part of the European Youth Heart Study. PA was measured during two weekdays and two weekend days using the MTI accelerometer, and average percent of time in moderate-to-vigorous PA (MVPA) and time spent sedentary were derived. Potential correlates were assessed by self-report. Independent associations between self-reported correlates with percent time in MVPA and percent time sedentary were analysed by general linear models, adjusted by age, gender, country, measurement period, monitored days and parental socio-economic status.

    Results

    In 9-year-olds, playing outdoors after school was associated with higher percent time in MVPA (P < 0.01), while participation in sport clubs was associated with higher percent time in MVPA (P < 0.01) in 15-year-olds. No associations with percent time sedentary were observed in either age group.

    Conclusion

    Frequency of outdoor play after school is a significant correlate for daily time in MVPA in 9-year-olds, while this correlate is attenuated in favour of participation in sport and exercise in clubs in 15-year-olds. Targeting walking to school or reduced TV viewing time in order to increase time in daily MVPA in children is unlikely to be sufficient. Correlates related to time spent sedentary need further examination.

  • 27.
    Nilsson, Andreas
    et al.
    Örebro University, School of Health and Medical Sciences.
    Anderssen, Sigmund A.
    Andersen, Lars Bo
    Froberg, Karsten
    Riddoch, Chris
    Sardinha, Luis B.
    Ekelund, Ulf
    Örebro University, School of Health and Medical Sciences.
    Between- and within-day variability in physical activity and inactivity in 9- and 15-year-old European children2009In: Scandinavian Journal of Medicine and Science in Sports, ISSN 0905-7188, E-ISSN 1600-0838, Vol. 19, no 1, p. 10-18Article in journal (Refereed)
    Abstract [en]

    To examine differences in levels of physical activity (PA), time spent at moderate-to-vigorous intensity PA (MVPA) and time spent sedentary between and within days in children from four European countries, 1954 9 - and 15-year-olds were included. PA was measured during 2 weekdays and 2 weekend days using the manufacturing technology-incorporated (MTI) accelerometer. Average count per minute, time spent sedentary, time spent at MVPA and the proportion of children accumulating > or =60 min of MVPA were calculated. Data were compared between weekdays and weekend days and between school time and leisure-time. Although not entirely consistent across countries, overall PA, time spent sedentary and the proportion of children accumulating > or =60 min of MVPA were higher during weekdays compared with weekend days. Differences in overall PA between school time and leisure-time were highly inconsistent between countries. Few children (4-31%) accumulated > or =60 min of MVPA either during school time or during leisure-time. Differences in activity patterns between weekdays and weekend days are explained by less accumulated time in MVPA during weekend days. Weekend days and leisure-time during weekdays seem appropriate targets when promoting PA in order to increase the proportion of children achieving current recommendations on health-enhancing PA.

  • 28.
    Nilsson, Andreas
    et al.
    Örebro University, School of Health and Medical Sciences.
    Brage, Sören
    Riddoch, Chris
    Anderssen, Sigmund A.
    Sardinha, Luis B.
    Wedderkopp, Niels
    Andersen, Lars Bo
    Ekelund, Ulf
    Örebro University, School of Health and Medical Sciences.
    Comparison of equations for predicting energy expenditure from accelerometer counts in children2008In: Scandinavian Journal of Medicine and Science in Sports, ISSN 0905-7188, E-ISSN 1600-0838, Vol. 18, no 5, p. 643-650Article in journal (Refereed)
    Abstract [en]

    Several prediction equations developed to convert body movement measured by accelerometry into energy expenditure have been published. The aim of this study was to examine the degree of agreement between three different prediction equations, when applied to data on physical activity in a large sample of children. We examined 1321 children (663 boys, 658 girls; mean age 9.6+/-0.4 years) from four different countries. Physical activity was measured by the MTI accelerometer. One equation, derived from doubly labeled water (DLW) measurements, was compared with one treadmill-based (TM) and one room calorimeter-based (CAL) equation (mixture of activities). Predicted physical activity energy expenditure (PAEE) was the main outcome variable. In comparison with DLW-predicted PAEE, both laboratory-derived equations significantly (P<0.001) overestimated PAEE by 17% and 83%, respectively, when based on a 24-h prediction, while the TM equation significantly (P<0.001) underestimated PAEE by 46%, when based on awake time only. In contrast, the CAL equation agreed better with the DLW equation under the awake time assumption. Predicted PAEE differ substantially between equations, depending on time-frame assumptions, and interpretations of average levels of PAEE in children from available equations should be made with caution. Further development of equations applicable to free-living scenarios is needed.

  • 29.
    Nilsson, Andreas
    et al.
    Örebro University, School of Health and Medical Sciences.
    Ekelund, Ulf
    Örebro University, School of Health and Medical Sciences.
    Yngve, Agneta
    Sjöström, Michael
    Assessing physical activity among children with accelerometers using different time sampling intervals and placements2002In: Pediatric Exercise Science, ISSN 0899-8493, Vol. 14, no 1, p. 87-96Article in journal (Refereed)
    Abstract [en]

    The aim was to investigate (a) the effect of five different time sampling intervals (epoch settings) on different intensity levels when assessing physical activity with an accelerometer (CSA, WAM 7164), and (b) whether the placement of the monitor (on the hip and back) would affect the outcome. Sixteen children (aged 7 yrs) were monitored for four consecutive days. A significant main epoch effect was found for time spent at very high (p < 01) and high (p < 01) intensity activities. No significant difference between the two placements regarding total amount of physical activity (cnts times mm super (-1)) or different intensity levels was observed. In conclusion, different time sampling intervals, but not placement, should be carefully considered when assessing physical activity.

  • 30. Nyberg, Gisela
    et al.
    Ekelund, Ulf
    Örebro University, School of Health and Medical Sciences.
    Marcus, Claude
    Physical activity in children measured by accelerometry: stability over time2009In: Scandinavian Journal of Medicine and Science in Sports, ISSN 0905-7188, E-ISSN 1600-0838, Vol. 19, p. 30-35Article in journal (Refereed)
    Abstract [en]

    The aim of this study was to examine the stability of objectively measured physical activity in Swedish children and to study variables that predicted physical activity and body mass index standard deviation score (BMI SDS) at follow-up. A total of 97 children provided valid repeated measurements of physical activity between 2002 and 2005. The children were on average 7.5 years at baseline (SD+/-0.92) and 9 years at follow-up (SD+/-0.92). The mean follow-up time was approximately 1.5 years (mean 558 days, SD+/-224). An accelerometer (Actiwatch, Cambridge Neurotechnology Ltd., Cambridge, UK) was used to measure physical activity during 7 consecutive days. Yearly weight and height were examined and BMI SDS was calculated. Baseline physical activity was significantly correlated with physical activity at follow-up (r=0.59) with a stronger correlation for boys (r=0.72) than for girls (r=0.51). High physical activity levels were more stable (r=0.74) than low physical activity levels (r=0.55). Physical activity at follow-up was explained by physical activity at baseline and season (R(2)=0.46) whereas BMI SDS at follow-up was explained by BMI SDS at baseline and age (R(2)=0.90). The results of this study suggest that physical activity levels are fairly stable in 6-10-year-old children.

  • 31. Nyberg, Gisela
    et al.
    Ekelund, Ulf
    Örebro University, School of Health and Medical Sciences.
    Yucel-Lindberg, Tulay
    Modeer, Thomas
    Marcus, Claude
    Differences in metabolic risk factors between normal weight and overweight children2011In: International Journal of Pediatric Obesity, ISSN 1747-7166, E-ISSN 1747-7174, Vol. 6, no 3-4, p. 244-252Article in journal (Refereed)
    Abstract [en]

    Background. The effect of overweight on metabolic risk factors and the role of physical activity (PA) in pre-pubertal children is unclear. Objective. To study differences in metabolic risk factors between groups of normal weight and overweight children and how these risk factors are associated with objectively measured PA and cardio-respiratory fitness (CRF). Design. A cross-sectional study was conducted with 68 children aged 8-11 years. Children were categorized into normal weight (n = 39) and overweight/obese (n = 24/5). PA and CRF were measured objectively. An oral glucose tolerance test (OGTT) was performed and triglycerides (TG) and HDL-cholesterol (HDL-C) were measured. A metabolic risk score (MRS) was calculated from the standardized values of insulin, glucose, TG, inverted HDL-C and blood pressure. Results. There was a significant (P < 0.05) difference between normal weight and overweight children in clustered metabolic risk, insulin (AUC), fasting insulin and systolic blood pressure. PA and CRF did not differ significantly between groups. In linear regression analysis combining the two groups, PA was negatively associated with insulin (AUC) (beta = -0.25, 95% CI = -0.50, -0.002) and CRF was negatively associated with fasting insulin (beta = -0.41, 95% CI = -0.67, -0.15). Conclusions. Metabolic risk factors are elevated in overweight pre-pubertal children compared with normal weight controls. This is not explained by lower PA or CRF in the overweight group although PA and CRF were associated with lower insulin levels in pooled analyses. This highlights the importance of preventing overweight in children from an early age in order to prevent the metabolic syndrome and its associated diseases.

  • 32. Ong, Ken K.
    et al.
    Elks, Cathy E.
    Li, Shengxu
    Zhao, Jing Hua
    Luan, Jian'an
    Andersen, Lars B.
    Bingham, Sheila A.
    Brage, Sören
    Smith, George Davey
    Ekelund, Ulf
    Örebro University, School of Health and Medical Sciences.
    Gillson, Christopher J.
    Glaser, Beate
    Golding, Jean
    Hardy, Rebecca
    Khaw, Kay-Tee
    Kuh, Diana
    Luben, Robert
    Marcus, Michele
    McGeehin, Michael A.
    Ness, Andrew R.
    Northstone, Kate
    Ring, Susan M.
    Rubin, Carol
    Sims, Matthew A.
    Song, Kijoung
    Strachan, David P.
    Vollenweider, Peter
    Waeber, Gerard
    Waterworth, Dawn M.
    Wong, Andrew
    Deloukas, Panagiotis
    Barroso, Ines
    Mooser, Vincent
    Loos, Ruth J.
    Wareham, Nicholas J.
    Genetic variation in LIN28B is associated with the timing of puberty2009In: Nature Genetics, ISSN 1061-4036, E-ISSN 1546-1718, Vol. 41, no 6, p. 729-733Article in journal (Refereed)
    Abstract [en]

    The timing of puberty is highly variable(1). We carried out a genome-wide association study for age at menarche in 4,714 women and report an association in LIN28B on chromosome 6 (rs314276, minor allele frequency (MAF) = 0.33, P = 1.5 x 10(-8)). In independent replication studies in 16,373 women, each major allele was associated with 0.12 years earlier menarche (95% CI = 0.08-0.16; P = 2.8 x 10(-10); combined P = 3.6 x 10(-16)). This allele was also associated with earlier breast development in girls (P = 0.001; N = 4,271); earlier voice breaking (P = 0.006, N = 1,026) and more advanced pubic hair development in boys (P = 0.01; N = 4,588); a faster tempo of height growth in girls (P = 0.00008; N = 4,271) and boys (P = 0.03; N = 4,588); and shorter adult height in women (P = 3.6 x 10(-7); N = 17,274) and men (P = 0.006; N = 9,840) in keeping with earlier growth cessation. These studies identify variation in LIN28B, a potent and specific regulator of microRNA processing(2), as the first genetic determinant regulating the timing of human pubertal growth and development.

  • 33. Poortvliet, Eric
    et al.
    Yngve, Agneta
    Ekelund, Ulf
    Örebro University, School of Health and Medical Sciences.
    Hurtig-Wennlöf, Anita
    Örebro University, Department of Clinical Medicine.
    Nilsson, Andreas
    Hagströmer, Maria
    Sjöström, Michael
    The European Youth Heart Survey (EYHS): an international study that addresses the multi-dimensional issues of CVD risk factors2003In: Forum of nutrition, ISSN 1660-0347, Vol. 56, p. 254-256Article in journal (Refereed)
  • 34. Ridgway, C. L.
    et al.
    Brage, S.
    Anderssen, S.
    Sardinha, L. B.
    Andersen, L. B.
    Ekelund, Ulf
    Örebro University, School of Health and Medical Sciences.
    Fat-free mass mediates the association between birth weight and aerobic fitness in youth2011In: International Journal of Pediatric Obesity, ISSN 1747-7166, E-ISSN 1747-7174, Vol. 6, no 2-2, p. E590-E596Article in journal (Refereed)
    Abstract [en]

    Objective. To investigate whether birth weight acts as a biological determinant of later aerobic fitness, and whether fat-free mass may mediate this association. Methods. The European Youth Heart Study (EYHS) is a population-based cohort of two age groups (9 and 15 years) from Denmark, Portugal, Estonia and Norway. Children with parentally reported birth weight >1.5 kg were included (n = 2 749). Data were collected on weight, height, and skinfold measures to estimate fat mass and fat-free mass. Aerobic fitness (peak power, watts) was assessed using a maximal, progressive cycle ergometer test. Physical activity was collected in a subset (n = 1 505) using a hip-worn accelerometer and defined as total activity counts/wear time, all children with >600 minutes/day for >= 3 days of wear were included. Results. Lower birth weight was associated with lower aerobic fitness, after adjusting for sex, age group, country, sexual maturity and socio-economic status (beta = 5.4; 95% CI: 3.5, 7.3 W per 1 kg increase in birth weight, p < 0.001). When fat-free mass was introduced as a covariate in the model, the association between birth weight and aerobic fitness was almost completely attenuated (p = 0.7). Birth weight was also significantly associated with fat-free mass (beta = 1.4; 95% CI: 1.1, 1.8, p < 0.001) and fat-free mass was significantly associated with aerobic fitness (beta = 3.6; 95% CI: 3.4, 3.7, p < 0.001). Further adjustment for physical activity did not alter the findings. Conclusion. Birth weight may have long-term influences on fat-free mass and differences in fat-free mass mediate the observed association between birth weight and aerobic fitness.

  • 35. Ridgway, Charlotte L.
    et al.
    Brage, Soren
    Anderssen, Sigmund A.
    Sardinha, Luis B.
    Andersen, Lars Bo
    Ekelund, Ulf
    Örebro University, School of Health and Medical Sciences.
    Do physical activity and aerobic fitness moderate the association between birth weight and metabolic risk in youth?: The European youth heart study2011In: Diabetes Care, ISSN 0149-5992, E-ISSN 1935-5548, Vol. 34, no 1, p. 187-192Article in journal (Refereed)
    Abstract [en]

    OBJECTIVE- Lower birth weight has been associated with a greater risk of metabolic diseases. The aim of this study was examine whether physical activity and aerobic fitness may modify associations between birth weigh and metabolic risk. RESEARCH DESIGN AND METHODS- The European Youth Heart Study is a population-based study of 9 and 15 year olds (n = 1,254). Birth weight was maternally reported. Skin fold measures were used to calculate body fat and fat mass index (FMI = fat mass [kilograms]/height(2)). Insulin was measured using fasting blood samples. Physical activity was measured using a hip-worn accelerometer (MTI Actigraph) for >600 min/day for >= 3 days and is expressed as "average activity" (counts per minute) and time spent in above moderate intensity activity (>2000 cpm). Aerobic fitness was assessed using a maximal cycle ergometry test (watts per kilogram fat-free mass). RESULTS- Higher birth weight was associated with higher FMI (beta = 0.49 [95% CI 0.21-0.80]; P = 0.001) and greater waist circumference (0.90 [0.32-1.47]; P < 0.001), adjusted for sex, age-group, sexual maturity, height, and socioeconomic status. Lower birth weight was associated with higher fasting insulin only after further adjustment for adolescent waist circumference and height (-0.059 [-0.107 to 0.011]; P = 0.016). There was no evidence for any modification of the associations after adjustment for physical activity or aerobic fitness. CONCLUSIONS- The present study did not find any evidence that physical activity or aerobic fitness can moderate the associations among higher birth weight and increased fat mass and greater waist circumference or between lower birth weight and insulin resistance in healthy children and adolescents.

  • 36. Sardinha, Luis B.
    et al.
    Andersen, Lars Bo
    Anderssen, Sigmund A.
    Quitero, Ana L.
    Ornelas, Rui
    Froberg, Karsten
    Riddoch, Chris J.
    Ekelund, Ulf
    Örebro University, School of Health and Medical Sciences.
    Objectively measured time spent sedentary is associated with insulin resistance independent of overall and central body fat in 9- to 10-year-old portuguese children2008In: Diabetes Care, ISSN 0149-5992, E-ISSN 1935-5548, Vol. 31, no 3, p. 569-575Article in journal (Refereed)
    Abstract [en]

    OBJECTIVE: We examined the independent relationships between objectively measured physical activity and insulin resistance in Portuguese children. RESEARCH DESIGN AND METHODS: This is a school-based, cross-sectional study in 147 randomly selected girls (aged 9.8 +/- 0.3 years; 27.8 +/- 9.3% body fat) and 161 boys (aged 9.8 +/- 0.3 years; 22.0 +/- 9.2% body fat). Physical activity was assessed by the Actigraph accelerometer for 4 days and summarized as time spent sedentary (accelerometer counts <500/min), in light-intensity (accelerometer counts 500-2,000/min), and in moderate- and vigorous-intensity activity (accelerometer counts >2,001/min). We measured total and central fat mass by dual-energy X-ray absorptiometry. Insulin resistance was expressed as the homeostasis model assessment score. RESULTS: Time (min/day) spent sedentary was significantly and positively associated with insulin resistance (beta-coefficient = 0.001 [95% CI 0.0002-0.002]; P = 0.013). Time spent in moderate- and vigorous-intensity physical activity (-0.002 [-0.003 to -0.001]; P = 0.0009) and overall physical activity (-0.001 [-0.008 to 0.003]; P < 0.0001) were significantly and inversely associated with insulin resistance. All associations remained statistically significant, although they were attenuated after further adjustments for sex, birth weight, sexual maturity, and total or central fat mass (P < 0.03). CONCLUSIONS: Physical activity is associated with insulin resistance independent of total and central fat mass in children. Our results emphasize the importance of decreasing sedentary behavior and increasing time spent in moderate- and vigorous-intensity activity in children, which may have beneficial effects on metabolic risk factors regardless of the degree of adiposity.

  • 37. Sardinha, Luis B.
    et al.
    Baptista, Fatima
    Ekelund, Ulf
    Örebro University, School of Health and Medical Sciences.
    Objectively measured physical activity and bone strength in 9-year-old boys and girls2008In: Pediatrics, ISSN 0031-4005, E-ISSN 1098-4275, Vol. 122, no 3, p. e728-e736Article in journal (Refereed)
    Abstract [en]

    OBJECTIVE: The purpose of this work was to analyze the relationship between intensity and duration of physical activity and composite indices of femoral neck strength and bone-mineral content of the femoral neck, lumbar spine, and total body. METHODS: Physical activity was assessed by accelerometry in 143 girls and 150 boys (mean age: 9.7 years). Measurement of bone-mineral content, femoral neck bone-mineral density, femoral neck width, hip axis length, and total body fat-free mass was performed with dual-energy radiograph absorptiometry. Compressive [(bone-mineral density x femoral neck width/weight)] and bending strength [(bone-mineral density x femoral neck width(2))/(hip axis length x weight)] express the forces that the femoral neck has to withstand in weight bearing, whereas impact strength [(bone-mineral density x femoral neck width x hip axis length)/(height x weight)] expresses the energy that the femoral neck has to absorb in an impact from standing height. RESULTS: Analysis of covariance (fat-free mass and age adjusted) showed differences between boys and girls of approximately 9% for compressive, 10% for bending, and 9% for impact strength. Stepwise regression analysis using time spent at sedentary, light, moderate, and vigorous physical activity as predictors revealed that vigorous physical activity explained 5% to 9% of femoral neck strength variable variance in both genders, except for bending strength in boys, and approximately 1% to 3% of total body and femoral neck bone-mineral content variance. Vigorous physical activity was then used to categorize boys and girls into quartiles. Pairwise comparison indicated that boys in the third and fourth quartiles (accumulation of >26 minutes/day) demonstrated higher compressive (11%-12%), bending (10%), and impact (14%) strength than boys in the first quartile. In girls, comparison revealed a difference between the fourth (accumulation of >25 minutes/day) and first quartiles for bending strength (11%). We did not observe any relationship between physical activity and lumbar spine strength. CONCLUSIONS: Femoral neck strength is higher in boys than girls. Vigorous intensity emerged as the main physical activity predictor of femoral neck strength but did not explain gender differences. Daily vigorous physical activity for at least approximately 25 minutes seems to improve femoral neck bone health in children.

  • 38. Sherar, Lauren B.
    et al.
    Griew, Pippa
    Esliger, Dale W.
    Cooper, Ashley R.
    Ekelund, Ulf
    Örebro University, School of Health and Medical Sciences.
    Judge, Ken
    Riddoch, Chris
    International children's accelerometry database (ICAD): design and methods2011In: BMC Public Health, ISSN 1471-2458, E-ISSN 1471-2458, Vol. 11, p. 485-Article in journal (Refereed)
    Abstract [en]

    Background: Over the past decade, accelerometers have increased in popularity as an objective measure of physical activity in free-living individuals. Evidence suggests that objective measures, rather than subjective tools such as questionnaires, are more likely to detect associations between physical activity and health in children. To date, a number of studies of children and adolescents across diverse cultures around the globe have collected accelerometer measures of physical activity accompanied by a broad range of predictor variables and associated health outcomes. The International Children's Accelerometry Database (ICAD) project pooled and reduced raw accelerometer data using standardized methods to create comparable outcome variables across studies. Such data pooling has the potential to improve our knowledge regarding the strength of relationships between physical activity and health. This manuscript describes the contributing studies, outlines the standardized methods used to process the accelerometer data and provides the initial questions which will be addressed using this novel data repository. Methods: Between September 2008 and May 2010 46,131 raw Actigraph data files and accompanying anthropometric, demographic and health data collected on children (aged 3-18 years) were obtained from 20 studies worldwide and data was reduced using standardized analytical methods. Results: When using >= 8, >= 10 and >= 12 hrs of wear per day as a criterion, 96%, 93.5% and 86.2% of the males, respectively, and 96.3%, 93.7% and 86% of the females, respectively, had at least one valid day of data. Conclusions: Pooling raw accelerometer data and accompanying phenotypic data from a number of studies has the potential to: a) increase statistical power due to a large sample size, b) create a more heterogeneous and potentially more representative sample, c) standardize and optimize the analytical methods used in the generation of outcome variables, and d) provide a means to study the causes of inter-study variability in physical activity. Methodological challenges include inflated variability in accelerometry measurements and the wide variation in tools and methods used to collect non-accelerometer data.

  • 39.
    Sjöström, Michael
    et al.
    Unit for Preventive Nutrition, Department of Medical Nutrition, Karolinska Institutet, Stockholm, Sweden.
    Yngve, Agneta
    Unit for Preventive Nutrition, Department of Medical Nutrition, Karolinska Institutet, Stockholm, Sweden.
    Ekelund, Ulf
    Örebro University, Department of Health Sciences.
    Environmental planning and public health nutrition: interventions in Nordic communities2001In: Physical activity: a part of healthy eating? : report from a Nordic Seminar, Lahti, Finland, February 2000 / [ed] Mikael Fogelholm, København, 2001, Vol. 554, p. 117-124Conference paper (Refereed)
  • 40. Sjöström, Michael
    et al.
    Yngve, Agneta
    Poortvliet, Eric
    Ekelund, Ulf
    Örebro University, School of Health and Medical Sciences.
    Hurtig-Wennlöf, Anita
    Örebro University, Department of Clinical Medicine.
    Nilsson, Andreas
    Hagströmer, Maria
    Adolescent nutrition: a multidimensional challenge2003In: Modern aspects of nutrition: present knowledge and future perspectives / [ed] I. Elmadfa, E. Anklam, J. König, 2003, Vol. 56, p. 253-254Conference paper (Refereed)
  • 41.
    Sjöström, Michael
    et al.
    Unit for Preventive Nutrition, Department of Medical Nutrition, Karolinska Institutet, Stockholm, Sweden.
    Yngve, Agneta
    Unit for Preventive Nutrition, Department of Biosciences at NOVUM, Karolinska Institutet, Huddinge, Sweden.
    Warm, Daniel
    Ekelund, Ulf
    Örebro University, Department of Health Sciences.
    Isaksson, Per
    Poortvliet, Eric
    European Master's in Public Health Nutrition: Folkhälsovetenskap, Nutrition och Fysisk Aktivitet i kombination med Europadimension2000In: Socialmedicinsk Tidskrift, ISSN 0037-833X, Vol. 77, no 2, p. 170-178Article in journal (Refereed)
  • 42.
    Särnblad, Stefan
    et al.
    Örebro University, School of Medicine, Örebro University, Sweden. Department of Women’s and Children’s Health, Uppsala University, Uppsala, Sweden .
    Ekelund, Ulf
    Örebro University, School of Health and Medical Sciences, Örebro University, Sweden. Medical Research Council Epidemiology Unit, Cambridge, U.K. .
    Åman, Jan
    Örebro University, Department of Clinical Medicine. Department of Pediatrics, University Hospital, Örebro, Sweden; Department of Women’s and Children’s Health, Uppsala University, Uppsala, Sweden .
    Dietary fat intake predicts 1-year change in body fat in adolescent girls with type 1 diabetes2006In: Diabetes Care, ISSN 0149-5992, E-ISSN 1935-5548, Vol. 29, no 6, p. 1227-1230Article in journal (Refereed)
    Abstract [en]

    OBJECTIVE: The purpose of this study was to determine whether objectively measured physical activity and dietary macronutrient intake differentially predict body fat in adolescent girls with type 1 diabetes and control girls.

    RESEARCH DESIGN AND METHODS: This study comprised 23 girls (12-19 years) with type 1 diabetes and 19 age-matched healthy control girls. At baseline, physical activity and energy intake were assessed for 7 consecutive days by accelerometry and a structured food diary, respectively. Body composition was measured by dual-energy X-ray absorptiometry at baseline and after 1 year.

    RESULTS: Fat intake was positively related to a 1-year change in percentage body fat (P = 0.006), after adjustment for total energy intake. No significant interaction was observed (case-control group x main exposure), indicating that the association between fat intake and gain in body fat was similar in both groups. Physical activity did not predict gain in body fat; however, total physical activity was positively associated with a gain in lean body mass (P < 0.01). Girls treated with six daily dosages of insulin increased their percentage of body fat significantly more than those treated with four daily injections (P < 0.05).

    CONCLUSIONS: In this prospective case-control study, we found that fat intake predicted gain in percentage of body fat in both adolescent girls with type 1 diabetes and healthy control girls. The number of daily insulin injections seems to influence the accumulation of body fat in girls with type 1 diabetes.

  • 43. Tammelin, Tuija
    et al.
    Ekelund, Ulf
    Örebro University, School of Health and Medical Sciences.
    Remes, Juha
    Näyhä, Simo
    Physical activity and sedentary behaviors among Finnish youth2007In: Medicine & Science in Sports & Exercise, ISSN 0195-9131, E-ISSN 1530-0315, Vol. 39, no 7, p. 1067-1074Article in journal (Refereed)
    Abstract [en]

    PURPOSE: There is general concern about the low level of physical activity and the high amount of time devoted to sedentary behavior among adolescents. This study aimed to determine the proportion of young Finns meeting the current guidelines for youth physical activity (>or= 60 min of moderate- to vigorous-intensity physical activity per day) and TV viewing (< 2 h.d(-1)) and to examine associations between physical activity and different sedentary behaviors. METHODS: The study population consisted of 6928 boys and girls, members of the northern Finland birth cohort 1986 who, in 2001-2002, at age 15-16 yr, responded to a mailed questionnaire inquiring about their time spent in moderate to vigorous (MVPA), light (LPA), and commuting (CPA) physical activity, and different sedentary behaviors. RESULTS: Fifty-nine percent of the boys and 50% of the girls reported 60 min or more of total physical activity per day. Only 23% of boys and 10% of girls reported 60 min of MVPA per day. Forty-eight percent of boys and 44% of girls reported more than 2 h of daily TV viewing. High amounts of TV viewing and computer use were associated with lower levels of physical activity in both genders. CONCLUSION: Many adolescents exceeded the recommended level of TV viewing and did not meet current recommendations for health-related physical activity. The inverse associations of physical activity with TV viewing and computer use suggest that measures aimed to reduce sedentary behaviors may, at least partly, increase physical activity among youth.

  • 44.
    Warren, Janet M.
    et al.
    MRC Human Nutr Res, Elsie Widdowson Lab, Cambridge, England; Trowbridge Danone Baby Nutr, Wilts, England.
    Ekelund, Ulf
    Örebro University, School of Health and Medical Sciences. Inst Metab Sci, MRC, Epidemiol Unit, Addenbrookes Hosp, Cambridge, England.
    Besson, Herve
    School of Health and Medical Sciences, Örebro University, Örebro, Sweden; Julius Ctr UMCU, Utrecht, Netherlands.
    Mezzani, Alessandro
    Veruno Sci Inst, Div Cardiol, S Maugeri Fdn, Veruno NO, Italy.
    Geladas, Nickos
    Dept Sport Med & Biol Exercise, Univ Athens, Athens, Greece.
    Vanhees, Luc
    Dept Rehabil Sci Biomed Sci, Katholieke Univ Leuven, Leuven, Belgium.
    Assessment of physical activity - a review of methodologies with reference to epidemiological research: a report of the exercise physiology section of the European Association of Cardiovascular Prevention and Rehabilitation2010In: European Journal of Cardiovascular Prevention & Rehabilitation, ISSN 1741-8267, E-ISSN 1741-8275, Vol. 17, no 2, p. 127-139Article, review/survey (Refereed)
    Abstract [en]

    Physical activity has a fundamental role in the prevention and treatment of chronic disease. The precise measurement of physical activity is key to many surveillance and epidemiological studies investigating trends and associations with disease. Public health initiatives aimed at increasing physical activity rely on the measurement of physical activity to monitor their effectiveness. Physical activity is multidimensional, and a complex behaviour to measure; its various domains are often misunderstood. Inappropriate or crude measures of physical activity have serious implications, and are likely to lead to misleading results and underestimate effect size. In this review, key definitions and theoretical aspects, which underpin the measurement of physical activity, are briefly discussed. Methodologies particularly suited for use in epidemiological research are reviewed, with particular reference to their validity, primary outcome measure and considerations when using each in the field. It is acknowledged that the choice of method may be a compromise between accuracy level and feasibility, but the ultimate choice of tool must suit the stated aim of the research. A framework is presented to guide researchers on the selection of the most suitable tool for use in a specific study.

  • 45.
    Yngve, Agneta
    et al.
    Unit for Preventive Nutrition, Department of Medical Nutrition, Karolinska Institutet, Stockholm, Sweden.
    Ekelund, Ulf
    Örebro University, Department of Health Sciences.
    Sjöström, Michael
    Social Marketing in Public Health Nutriton: also for Nordic countries?2001In: Physical activity: a part of healthy eating? : report from a Nordic Seminar, Lahti, Finland, February 2000 / [ed] Mikael Fogelholm, København, 2001, Vol. 554, p. 79-87Conference paper (Refereed)
  • 46.
    Yngve, Agneta
    et al.
    Unit for Preventive Nutrition, Department of Medical Nutrition, Karolinska Institutet, Stockholm, Sweden.
    Nilsson, Andreas
    Unit for Preventive Nutrition, Department of Medical Nutrition, Karolinska Institutet, Stockholm, Sweden.
    Sjoström, Michael
    Unit for Preventive Nutrition, Department of Medical Nutrition, Karolinska Institutet, Stockholm, Sweden.
    Ekelund, Ulf
    Örebro University, School of Health and Medical Sciences, Örebro University, Sweden. Unit for Preventive Nutrition, Department of Medical Nutrition, Karolinska Institutet, Stockholm, Sweden.
    Effect of monitor placement and of activity setting on the MTI accelerometer output2003In: Medicine & Science in Sports & Exercise, ISSN 0195-9131, E-ISSN 1530-0315, Vol. 35, no 2, p. 320-326Article in journal (Refereed)
    Abstract [en]

    PURPOSE: To examine the effect of monitor placement (hip vs back) and of activity setting (treadmill vs track) on the output from the Manufacturing Technology Inc. (MTI), activity monitor (model WAM 7164).

    METHODS: In a laboratory study, 28 subjects (14 men, 14 women) walked at a normal pace, walked at a fast pace, and jogged at a comfortable pace on an indoor track. These activities were repeated on a treadmill using the individual speeds from the track locomotion. Oxygen uptake was measured simultaneously using a portable metabolic system. One activity monitor was worn on the hip and one on the lower back. In a field study, 34 subjects (18 men, 16 women) each wore two monitors (hip and low back placement) for seven consecutive days. In the laboratory study, ANOVA showed significant effects of placement ( P = 0.009) and setting ( P < 0.001), indicating that activity counts differ between different body sites and different settings (track vs treadmill). Gross energy expenditure predictive equations were developed and thereafter evaluated in the field study. Time spent at moderate and vigorous intensity of physical activity was 38% and 85% ( P < 0.001) higher when calculated from the treadmill-based equations as compared to the track-based equations. Free-living physical activity estimates were not affected by the placement.

    CONCLUSION: The relationship between activity counts and energy expenditure during laboratory locomotion is placement and setting-specific. When habitual physical activity is assessed in free-living subjects, the treadmill derived relationship between energy expenditure and activity counts may overestimate time spent at moderate intensity of physical activity, whereas the placement of the monitor does not influence on the interpretation of the data.

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