PubMed Health⌕ Search

Biomedical subjects

Søren Brage

Publications and source records attributed to Søren Brage.

At least 19 recordsLinked to original sources
PubMed2007

Emotional distress as a predictor for low back disability: a prospective 12-year population-based study.

STUDY DESIGN: A population-based, prospective cohort. OBJECTIVE: To study associations between emotional distress and long-term low back disability in a general population. SUMMARY OF BACKGROUND DATA: In primary and hospital care studies, emotional, cognitive, and personality factors have been associated with low back disability, while the association between distress and novel back pain episodes has been uncertain. METHODS: A randomly drawn cohort of 1152 occupationally active persons aged 20-55 years was interviewed with a comprehensive psychosocial questionnaire in 1990, and was followed for 12 years in national registers over sickness, rehabilitation, and disability benefits. Data on emotional distress, earlier low back pain (LBP), education, life style, psychosocial, and work-related factors were collected at baseline. RESULTS: Long-term benefits due to low back disability were granted to 131 persons (11.4%) in the follow-up period. In multivariate analysis, earlier LBP, emotional distress, low grade of education, and high physical job stress were associated with low back disability. Persons with both emotional distress and earlier back pain were most at risk for disability (hazard ratio 2.91, 95% confidence interval 1.60-5.29). Persons with emotional distress but no earlier episodes of LBP had no increased risk for low back disability (hazard ratio 0.71, 95% confidence interval 0.34-1.45). CONCLUSIONS: Emotional distress is a predictor for low back disability in persons with earlier LBP, but not in persons without. To prevent low back disability, emotional distress should be considered and treated in persons with LBP.

Adult↗
PubMed2006

[Physical activity and clustering of CVD risk factors--secondary publication].

This study aimed to derive guidelines on physical activity. We did a cross-sectional study of 1732 9-year-old and 15-year-old children. Objectively measured physical activity was associated to clustered CVD risk with an OR for the least active of 3.29 compared with the most active quintile. The time spent in moderate activity in children where risk was elevated was less than 116 min per day in 9-year-old and less than 88 min per day in 15-year-old children. Physical activity levels should be higher than the current international guidelines of at least 1 h per day to prevent clustering of CVD risk factors.

English Abstract↗
PubMed2006

Association of weight gain in infancy and early childhood with metabolic risk in young adults.

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.

Adolescent↗
PubMed2006

Physical activity and clustered cardiovascular risk in children: a cross-sectional study (The European Youth Heart Study).

BACKGROUND: Atherosclerosis develops from early childhood; physical activity could positively affect this process. This study's aim was to assess the associations of objectively measured physical activity with clustering of cardiovascular disease risk factors in children and derive guidelines on the basis of this analysis. METHODS: We did a cross-sectional study of 1732 randomly selected 9-year-old and 15-year-old school children from Denmark, Estonia, and Portugal. Risk factors included in the composite risk factor score (mean of Z scores) were systolic blood pressure, triglyceride, total cholesterol/HDL ratio, insulin resistance, sum of four skinfolds, and aerobic fitness. Individuals with a risk score above 1 SD of the composite variable were defined as being at risk. Physical activity was assessed by accelerometry. FINDINGS: Odds ratios for having clustered risk for ascending quintiles of physical activity (counts per min; cpm) were 3.29 (95% CI 1.96-5.52), 3.13 (1.87-5.25), 2.51 (1.47-4.26), and 2.03 (1.18-3.50), respectively, compared with the most active quintile. The first to the third quintile of physical activity had a raised risk in all analyses. The mean time spent above 2000 cpm in the fourth quintile was 116 min per day in 9-year-old and 88 min per day in 15-year-old children. INTERPRETATION: Physical activity levels should be higher than the current international guidelines of at least 1 h per day of physical activity of at least moderate intensity to prevent clustering of cardiovascular disease risk factors.

Adolescent↗
PubMed2006

Prevalence of low back pain and sickness absence: a "borderline" study in Norway and Sweden.

AIMS: Low back pain (LBP) is a major public health problem in both Norway and Sweden. The aim of the study was to estimate the prevalence of LBP and sickness absence due to LBP in two neighbouring regions in Norway and Sweden. The two areas have similar socioeconomic status, but differ in health benefit systems. METHODS: A representative sample of 1,988 adults in Norway and 2,006 in Sweden completed questionnaires concerning LBP during 1999 and 2000. For this study only individuals in part or full time jobs, (n = 1,158 in Norway and n = 1,129 in Sweden) were included. RESULTS: In Norway the lifetime prevalence was 60.7% and in Sweden 69.6%, the one-year prevalence was 40.5% and 47.2%, and the point prevalence 13.4% and 18.2% respectively. There was a significantly higher risk of reporting LBP in Sweden, even after controlling for gender, age, education, and physical workload. There was no difference in risk of self-certified short-term sickness absence (1-3 days), but it was a 40% lower risk of sickness absence with medical sickness certification in Sweden compared with Norway. CONCLUSION: The prevalence of LBP was higher in the Swedish area than in the Norwegian. The risk of self-certified sickness absence, however, showed no differences and the risk of medically certified sickness absence was lower in the Swedish area. This contradiction might partly be explained by the economical "disincentives" in the Swedish health compensation system.

Adult↗
PubMed2006

Upward weight percentile crossing in infancy and early childhood independently predicts fat mass in young adults: the Stockholm Weight Development Study (SWEDES).

BACKGROUND: Rapid early postnatal weight gain predicts increased subsequent obesity and related disease risks. However, the exact timing of adverse rapid postnatal weight gain is unclear. OBJECTIVE: The objective was to examine the associations between rapid weight gain in infancy and in early childhood in relation to body composition at age 17 y. DESIGN: This prospective cohort study was conducted in 248 (103 males) singletons and their mothers. Height and weight were measured at birth, 6 mo, and 3 and 6 y. The rates of weight gain during infancy (0-6 mo) and early childhood (3-6 y) were calculated as changes in sex- and age-adjusted weight SD scores during these time periods. At 17 y, body composition was measured by air-displacement plethysmography. RESULTS: Increasing weight gain during infancy and early childhood were both independently associated with larger body mass index, fat mass, relative fat mass, fat-free mass, and waist circumference at 17 y (P < 0.005 for all; adjusted for sex, birth weight, gestational age, current height, maternal socioeconomic status, and maternal fat mass). Rapid weight gain in infancy, but not in early childhood, also predicted taller height at 17 y (P < 0.001). CONCLUSIONS: Rapid weight gain in both infancy and early childhood is a risk factor for adult adiposity and obesity. Rapid weight gain in infancy also predicted taller adult height. We hypothesize that rapid weight gains in infancy and early childhood are different processes and may allow separate opportunities for early intervention against obesity risk later in life.

Adipose Tissue↗
PubMed2006

TV viewing and physical activity are independently associated with metabolic risk in children: the European Youth Heart Study.

BACKGROUND: TV viewing has been linked to metabolic-risk factors in youth. However, it is unclear whether this association is independent of physical activity (PA) and obesity. METHODS AND FINDINGS: We did a population-based, cross-sectional study in 9- to 10-y-old and 15- to 16-y-old boys and girls from three regions in Europe (n = 1,921). We examined the independent associations between TV viewing, PA measured by accelerometry, and metabolic-risk factors (body fatness, blood pressure, fasting triglycerides, inverted high-density lipoprotein (HDL) cholesterol, glucose, and insulin levels). Clustered metabolic risk was expressed as a continuously distributed score calculated as the average of the standardized values of the six subcomponents. There was a positive association between TV viewing and adiposity (p = 0.021). However, after adjustment for PA, gender, age group, study location, sexual maturity, smoking status, birth weight, and parental socio-economic status, the association of TV viewing with clustered metabolic risk was no longer significant (p = 0.053). PA was independently and inversely associated with systolic and diastolic blood pressure, fasting glucose, insulin (all p < 0.01), and triglycerides (p = 0.02). PA was also significantly and inversely associated with the clustered risk score (p < 0.0001), independently of obesity and other confounding factors. CONCLUSIONS: TV viewing and PA may be separate entities and differently associated with adiposity and metabolic risk. The association between TV viewing and clustered metabolic risk is mediated by adiposity, whereas PA is associated with individual and clustered metabolic-risk indicators independently of obesity. Thus, preventive action against metabolic risk in children may need to target TV viewing and PA separately.

Adolescent↗
PubMed2005

Effect of combined movement and heart rate monitor placement on physical activity estimates during treadmill locomotion and free-living.

A placement effect on activity measures from movement sensors has been reported during treadmill and free-living activity. Positioning of electrodes may impact on movement artifact susceptibility as well as surface ECG waveform amplitudes and thus potentially on the precision by which heart rate (HR) is ascertained from such ECG traces. The purpose of this study was to examine the extent to which placement of the combined HR and movement sensor, Actiheart, influences measurement of HR and movement, and estimates of energy expenditure. A total of 24 participants (20-39 years, 45-109 kg, 1.54-2.05 m, 19-29 kg m(-2)) were recruited. Whilst wearing two monitors, one placed at the level of the third intercostal space (upper position) and one just below the apex of the sternum (lower position), study participants performed level walking, incline walking, and level running on treadmill, and completed at least one day of free-living monitoring. Placement differences in HR data quality, movement counts, and energy expenditure (estimated from combined HR and movement) were analyzed with regression techniques. Quality of HR data was generally higher when monitors were placed in the lower position. This effect was more pronounced in men during both treadmill activity (relative risk, RR [95% CI] of noisy HR data in upper vs. lower position, RR=1.3[0.3; 5.6] in women, RR=174[14; 2,156] in men) and during free-living (RR=1.2[0.4; 3.3] in women, RR=25[9.6; 67] in men). There were minor placement differences (< or =8%) in movement counts only in women during incline walking and running. During free-living, no placement effect on counts was observed. In all test scenarios, estimates of energy expenditure from the two positions were not significantly different. Positioning the Actiheart at the level below the sternum may yield cleaner HR data. Regardless of which position is used, this has little or no effect on movement counts and energy expenditure estimates, which is encouraging for studies where research participants may have to position the monitors themselves.

Adult↗
PubMed2005

Associations between physical activity and fat mass in adolescents: the Stockholm Weight Development Study.

BACKGROUND: Obesity is multifactorial. However, the accumulation of fat mass (FM) is proposed to be due to a positive energy balance, which may be caused by reduced physical activity (PA). OBJECTIVE: The objectives of the study were to describe the independent associations between PA and FM in adolescents and to describe the intergenerational association of FM between mothers and their offspring. DESIGN: We conducted a cross-sectional study in 445 (190 M, 255 F) 17-y-old adolescents and their mothers. PA was assessed with a self-reported questionnaire and validated by comparison with accelerometric data in a subsample of the cohort. Body composition was measured by using air-displacement plethysmography. RESULTS: Males were significantly more active than were females (P<0.01). PA was significantly and inversely associated with FM (beta=-3.63, P=0.005) and percentage FM (beta=-3.117, P=0.017) in males but not in females (beta=-0.576, P=0.54; beta=-0.532, P=0.59, respectively) after adjustment for birth weight and maternal FM and education level. However, FM and percentage FM in females were significantly associated with maternal FM (beta=0.159, P<0.0001; beta=0.145, P=0.002, respectively) and education level (beta=-1.048, P<0.005; beta=-1.085, P=0.006, respectively). No such associations were observed in males. CONCLUSIONS: PA was independently associated with FM in males but not in females. The data also showed an intergenerational association of FM between mothers and their daughters but not between mothers and their sons.

Adipose Tissue↗
PubMed2005

Physical activity energy expenditure predicts changes in body composition in middle-aged healthy whites: effect modification by age.

BACKGROUND: It is unclear whether physical activity energy expenditure (PAEE) predicts changes in body composition. OBJECTIVE: The objective was to describe the independent associations between PAEE and changes in body composition in a population-based cohort. DESIGN: This was a prospective population-based study conducted in 739 (311 men and 428 women) healthy middle-aged (median age: 53.8 y) whites. The median follow-up was 5.6 y. PAEE (MJ/d) was assessed by heart rate monitoring, individually calibrated by using the FLEX heart rate method. Fat mass (FM) and fat-free mass (FFM) were assessed by bioimpedance. RESULTS: Body weight (BW) at follow-up was significantly related to baseline PAEE (P < 0.05) after adjustment for sex, baseline age, FM, FFM, and follow-up time. A significant interaction between PAEE and age (P = 0.023) was observed. After the subjects were stratified (above and below the median for age), BW increased by a mean (+/-SD) of 1.7 +/- 5.9 kg (P < 0.0001) in the younger cohort. In this group, follow-up FM was significantly associated with baseline PAEE (P = 0.036) after adjustment for confounders. In the older cohort, BW did not change between baseline and follow-up. In this group, in contrast with the younger population, follow-up BW, FM, and FFM were all significantly and positively associated with baseline PAEE (P < 0.01 for all). CONCLUSIONS: Baseline PAEE predicts a change in FM in younger adults, who as a group gained weight in this study. In contrast, baseline PAEE in older adults--who were on average weight stable--is associated with a gain in BW, which was explained by an increase in FM and FFM.

Adipose Tissue↗
PubMed2005

Comparison of PAEE from combined and separate heart rate and movement models in children.

PURPOSE: Accurate measurement of physical activity in children is a challenge. Combining physiological (e.g., heart rate (HR)) and body movement registration (e.g., accelerometry) may overcome limitations with either method used alone. This study aimed to compare the estimated physical activity energy expenditure (PAEE) from hip- and ankle-mounted MTI Actigraphs, a hip-mounted Actical, and a new combined HR and movement sensor, the Actiheart (Cambridge Neurotechnology, Papworth, UK). METHODS: Resting EE and submaximal EE (treadmill walking and running) were measured in 39 children (13.2 +/- 0.3 yr) by indirect calorimetry during a progressive treadmill exercise bout. Associations between monitor outputs (activity counts, HR, and activity counts + HR) and the criterion were examined by linear regression models. The agreement between measured and predicted PAEE was examined by modified Bland-Altman plots in a subsample of participants. RESULTS: The combined Actiheart model (activity counts + HR) had the strongest relationship with PAEE (R2 = 0.86), compared with those from the single-measure models (R2 = 0.69 and 0.82 for the activity model and HR model). The explained variances from the other activity monitors were lower (R2 = 0.50, 0.37, and 0.67) for the hip MTI, ankle MTI, and Actical, respectively. In cross-validation analyses, significant correlations were observed between estimation errors of the methods with the criterion (r = 0.49 to 0.90) in all models using only activity counts indicating a large systematic error. The HR and combined models indicated less systematic error (r = 0.41 and 0.33, respectively). CONCLUSIONS: Of the techniques considered, combined HR and movement sensing is the most valid for estimating PAEE in children during treadmill walking and running, compared with movement or HR alone. It also has the lowest level of systematic error.

Adolescent↗
PubMed2005

Integration of physiological and accelerometer data to improve physical activity assessment.

PURPOSE: Accurate measurement of physical activity (PA) is a prerequisite to determine dose-response relationships between activity and health. The combination of HR and accelerometers (ACC) holds promise for improving the accuracy of PA assessment, but it is unclear how currently proposed modeling techniques compare and to what extent different levels of individual calibration (IC) of HR influence monitoring accuracy. METHODS: A total of 10 men and women (25.8 +/- 3.4 yr, 1.70 +/- 0.1 m, 71.7 +/- 11.8 kg, 24.4 +/- 5.0 kg.m-2) were recruited for this study, in which IC of HR to PA energy expenditure (PAEE) during both arm crank and treadmill activity were available. Participants completed 6 h of free-living activity, during which PAEE (obtained with indirect calorimetry), HR, hip ACC, arm ACC, and leg ACC were collected. PAEE was then modeled from two different methods of combining HR and ACC (arm-leg HR+M and branched model), both with IC and group-level calibration (GC) of HR, and also from hip ACC estimates alone. Estimates of PAEE were compared with criterion values for PAEE. RESULTS: Combined estimates of PAEE from the arm-leg HR+M and the branched model were similar when IC was used (R2 = 0.81, SEE = 0.55 METs and R2 = 0.75, SEE = 0.61 METs, respectively). When using GC, all estimates of PAEE had larger error, but the performance of the branched model suffered less than the arm-leg HR+M model (R2 = 0.75, SEE = 0.67 METs and R2 = 0.67, SEE = 0.88 METs, respectively). Both combination modeling techniques were more precise than single-measure hip ACC estimates (R2 = 0.41, SEE = 0.96 METs). CONCLUSION: The combination of HR and ACC improves the accuracy of PAEE estimates and could be applied in large-scale epidemiological studies.

Acceleration↗
PubMed2005

Variation in the eNOS gene modifies the association between total energy expenditure and glucose intolerance.

Endothelium-derived nitric oxide (NO) facilitates skeletal muscle glucose uptake. Energy expenditure induces the endothelial NO synthase (eNOS) gene, providing a mechanism for insulin-independent glucose disposal. The object was to test 1) the association of genetic variation in eNOS, as assessed by haplotype-tagging single nucleotide polymorphisms (htSNPs) with type 2 diabetes, and 2) the interaction between eNOS haplotypes and total energy expenditure on glucose intolerance. Using multivariate models, we tested associations between eNOS htSNPs and diabetes (n = 461 and 474 case and control subjects, respectively) and glucose intolerance (two cohorts of n = 706 and 738 U.K. and Spanish Caucasians, respectively), and we tested eNOS x total energy expenditure interactions on glucose intolerance. An overall association between eNOS haplotype and diabetes was observed (P = 0.004). Relative to the most common haplotype (111), two haplotypes (121 and 212) tended to increase diabetes risk (OR 1.22, 95% CI 0.96-1.55), and one (122) was associated with decreased risk (0.58, 0.39-0.86). In the cohort studies, no association was observed between haplotypes and 2-h glucose (P > 0.10). However, we observed a significant total energy expenditure-haplotype interaction (P = 0.007). Genetic variation at the eNOS locus is associated with diabetes, which may be attributable to an enhanced effect of total energy expenditure on glucose disposal in individuals with specific eNOS haplotypes. Gene-environment interactions such as this may help explain why replication of genetic association frequently fails.

Aged↗
PubMed2005

Physical activity energy expenditure predicts progression toward the metabolic syndrome independently of aerobic fitness in middle-aged healthy Caucasians: the Medical Research Council Ely Study.

OBJECTIVE: To examine over a period of 5.6 years the prospective associations between physical activity energy expenditure (PAEE), aerobic fitness (Vo(2max)), obesity, and the progression toward the metabolic syndrome in a population-based cohort of middle-aged men and women (n = 605) who were free of the metabolic syndrome at baseline. RESEARCH DESIGN AND METHODS: PAEE was measured objectively by individually calibrated heart rate against energy expenditure. Vo(2max) was predicted from a submaximal exercise stress test. Fat mass and fat-free mass were assessed by bio-impedance. A metabolic syndrome score was computed by summing the standardized values for obesity, hypertension, hyperglycemia, insulin resistance, hypertriglyceridemia, and the inverse level of HDL cholesterol and expressed as a continuously distributed outcome. Generalized linear models were used to examine the independent prospective associations between PAEE and Vo(2max) and the metabolic syndrome score after adjusting for sex, baseline age, smoking, socioeconomic status, follow-up time, and baseline phenotypes. RESULTS: PAEE predicted progression toward the metabolic syndrome, independent of baseline metabolic syndrome, body fat, Vo(2max), and other confounding factors (standardized beta = -0.00085, P = 0.046). This association was stronger when excluding the adiposity component from the metabolic syndrome (standardized beta = -0.0011, P = 0.035). Vo(2max) was not an independent predictor of the metabolic syndrome after adjusting for physical activity (standardized beta = 0.00011, P = 0.93). CONCLUSIONS: PAEE predicts progression toward the metabolic syndrome independent of aerobic fitness, obesity, and other confounding factors. This finding underscores the importance of physical activity for metabolic disease prevention even when an improvement in aerobic fitness is absent.

Adult↗
PubMed2004

[Norwegian Functional Scale--a new instrument in sickness certification and disability assessments].

BACKGROUND: Functional assessments are requested in the follow-up of sick-listed persons and for disability benefit decisions. We describe the development of the Norwegian Functional Scale that may assist health providers in getting an insight into patients' self-evaluated functioning. MATERIAL AND METHODS: An expert panel developed a 40-item functional scale to be completed by sick-listed persons. The scale was based on the WHO Classification of Functioning, Disability, and Health (ICF). In April 2001 the scale, SF-36, and COOP/WONCA charts were tested on 798 persons who had been sick-listed for six weeks. Factor analysis was used to group single items into functional dimensions. Correlation analysis was applied for validity testing against the established instruments. RESULTS: 48% filled in the questionnaire. The factor analysis confirmed four physical dimensions of functioning (walking/standing, holding/handling, lifting/carrying and sitting), and three mental (coping, communicating and senses). The scale correlated significantly with corresponding dimensions in SF-36, COOP/WONCA and a question on ability to go back to work. INTERPRETATION: The Norwegian Functional Scale showed considerably reduced functioning in sick-listed persons. The scale appears to be valid.

Adult↗
PubMed2004

Does the association of habitual physical activity with the metabolic syndrome differ by level of cardiorespiratory fitness?

OBJECTIVE: Cardiovascular fitness (VO(2max)) and physical activity are both related to risk of metabolic disease. It is unclear, however, whether the metabolic effects of sedentary living are the same in fit and unfit individuals. The purpose of this study was, therefore, to describe the association between physical activity and the metabolic syndrome and to test whether fitness level modifies this relationship. RESEARCH DESIGN AND METHODS: Physical activity was measured objectively using individually calibrated heart rate against energy expenditure. VO(2max) was predicted from a submaximal exercise stress test. Fat mass and fat-free mass (FFM) were calculated using impedance biometry. A metabolic syndrome score was computed by summing the standardized values for obesity, hypertension, hyperglycemia, insulin resistance, hypertriglyceridemia, and the inverse level of HDL cholesterol and was expressed as a continuously distributed outcome. To correct for exposure measurement error, a random subsample (22% of cohort) re-attended for three repeat measurements in the year following the first assessment. RESULTS: The relationship of VO(2max) (ml O2.kg(FFM)(-1).min(-1)) and the metabolic syndrome score was of borderline significance after adjusting for age, sex, physical activity, and measurement error (beta = -0.58, P = 0.06). The magnitude of the association between physical activity (kJ.d(-1).kg(FFM)(-1)) and the metabolic syndrome was more than three times greater than for VO(2max) (standardized beta = -1.83, P = 0.0042). VO(2max), however, modified the relationship between physical activity energy expenditure and metabolic syndrome (P = 0.036). CONCLUSIONS: This study demonstrates a strong inverse association between physical activity and metabolic syndrome, an association that is much steeper in unfit individuals. Thus, prevention of metabolic disease may be most effective in the subset of unfit inactive people.

Adipose Tissue↗
PubMed2004

Features of the metabolic syndrome are associated with objectively measured physical activity and fitness in Danish children: the European Youth Heart Study (EYHS).

OBJECTIVE: Features of the metabolic syndrome are becoming increasingly evident in children. Decreased physical activity is likely to be an important etiological factor, as shown previously for subjective measures of physical activity in selected groups. The purpose of this study was to examine the relationship between the metabolic syndrome and objectively measured physical activity and whether fitness modified this relationship. RESEARCH DESIGN AND METHODS: A total of 589 Danish children (310 girls, 279 boys, mean [+/-SD] age 9.6 +/- 0.44 years, mean weight 33.6 +/- 6.4 kg, mean height 1.39 +/- 0.06 m) were randomly selected. Physical activity was measured with the uni-axial Computer Science & Applications accelerometer (MTI actigraph) worn at the hip for at least 3 days (>/=10 h/day) and fitness with a maximal bike test. As outcomes, we measured sitting systolic and diastolic blood pressure, degree of adiposity (sum of four skinfolds), and, finally, insulin, glucose, triglicerides, and HDL cholesterol in fasting blood samples. The outcome variables were statistically normalized and expressed as the number of SDs from the mean. (i.e., Z scores). A metabolic syndrome risk score was computed as the mean of these Z scores. Multiple linear regression was used to test the association between physical activity and metabolic risk, adjusted primarily for age, sex, sexual maturation, ethnicity, parental smoking, socioeconomic factors, and the Computer Science & Applications unit, as well as for fitness. Robust SEs were computed by clustering on school. RESULTS: All children were in the nondiabetic range of fasting glucose. Metabolic risk was inversely related to physical activity (P = 0.008). The relationship was weakened after adjustment for fitness, but there was a significantly positive interaction between physical activity and fitness. CONCLUSIONS: Physical activity is inversely associated with metabolic risk, independently of potential confounders. The interaction between physical activity and fitness suggests that the potential beneficial effect of activity may be greatest in children with lower cardiorespiratory fitness.

Blood Pressure↗