PubMed Health⌕ Search

Biomedical subjects

Søren Brage

Publications and source records attributed to Søren Brage.

24 records · Page 2Linked to original sources
PubMed2003

Association between physical activity and blood pressure is modified by variants in the G-protein coupled receptor 10.

Hypertension is strongly related to cardiovascular disease and all-cause mortality. Exercise reduces blood pressure but the response varies between individuals. The mechanisms by which physical activity energy expenditure (PAEE) modifies blood pressure are not fully defined but include modulation of sympathetic tone. Novel polymorphisms in the G-protein coupled receptor (GPR10) have been linked with high blood pressure. GPR10 may mediate the relationship between PAEE and blood pressure via central nervous mechanisms. We examined whether two GPR10 polymorphisms (G-62A and C914T) modify the association between PAEE and blood pressure in the MRC Ely study (N=687). When stratified by the C914T genotype, there were between-group differences for body mass index (BMI) (P=0.05), diastolic blood pressure (DBP) (P=0.006), and systolic blood pressure (SBP) (P=0.005). No differences were found between G-62A genotypes. The previously reported inverse relationship between PAEE and blood pressure was not observed in minor allele carriers for either polymorphism (A62 carriers: DBP beta-1.11, P=0.52; SBP beta-1.66, P=0.52. T914 carriers: SBP beta=3.27; P=0.60) but was in common allele homozygotes (G62G: DBP beta-6.18 P=0.00001; SBP beta-8.54 P=0.0001. C914C: SBP beta-7.07; P=0.00001). This corresponded to a significant interaction between PAEE and GPR10 polymorphisms on DBP (G-62A: P=0.006) and SBP (G-62A: P=0.008. C914T: P=0.068). Significant interactions were observed between haplotype (derived from G-62A and C914T), PAEE, and blood pressure (DBP: P=0.08; SBP: P=0.023). The effect of physical activity on blood pressure is highly variable at population level. Knowledge of GPR10 genotype may define those who are least likely to benefit from physical activity. These findings may have relevance in the targeted treatment of hypertensive disease.

Blood Pressure↗
PubMed2003

Branched equation modeling of simultaneous accelerometry and heart rate monitoring improves estimate of directly measured physical activity energy expenditure.

The combination of heart rate (HR) monitoring and movement registration may improve measurement precision of physical activity energy expenditure (PAEE). Previous attempts have used either regression methods, which do not take full advantage of synchronized data, or have not used movement data quantitatively. The objective of the study was to assess the precision of branched model estimates of PAEE by utilizing either individual calibration (IC) of HR and accelerometry or corresponding mean group calibration (GC) equations. In 12 men (20.6-25.2 kg/m2), IC and GC equations for physical activity intensity (PAI) were derived during treadmill walking and running for both HR (Polar) and hipacceleration [Computer Science and Applications (CSA)]. HR and CSA were recorded minute by minute during 22 h of whole body calorimetry and converted into PAI in four different weightings (P1-4) of the HR vs. the CSA (1-P1-4) relationships: if CSA > x, we used the P1 weighting if HR > y, otherwise P2. Similarly, if CSA < or = x, we used P3 if HR > z, otherwise P4. PAEE was calculated for a 12.5-h nonsleeping period as the time integral of PAI. A priori, we assumed P1 = 1, P2 = P3 = 0.5, P4 = 0, x = 5 counts/min, y = walking/running transition HR, and z = flex HR. These parameters were also estimated post hoc. Means +/- SD estimation errors of a priori models were -4.4 +/- 29 and 3.5 +/- 20% for IC and GC, respectively. Corresponding post hoc model errors were -1.5 +/- 13 and 0.1 +/- 9.8%, respectively. All branched models had lower errors (P < or = 0.035) than single-measure estimates of CSA (less than or equal to -45%) and HR (> or =39%), as well as their nonbranched combination (> or =25.7%). In conclusion, combining HR and CSA by branched modeling improves estimates of PAEE. IC may be less crucial with this modeling technique.

Adult↗
PubMed2003

Reexamination of validity and reliability of the CSA monitor in walking and running.

PURPOSE: To evaluate the reliability and validity of the CSA (model 7164) accelerometer (MTI) in a wide walking-running speed range in laboratory and field. METHOD: Twelve male subjects performed three treadmill walking/running sessions and one field trial with the same continuous protocol involving progressively increasing velocities at 5 min per interval from 3 to 6 km x h(-1) (walking) and 8 to 20 km x h(-1) (running). In the field trial, this protocol was terminated after 35 min (14 km.h(-1)), but the trial then extended with 5-km running at a freely chosen velocity. In both scenarios, two CSAs were mounted on each hip and the step frequency measured at each velocity. Oxygen uptake VO(2) x kg(-1) was measured on the last two treadmill sessions. Correlation analyses were performed for mean CSA output relationship with speed, VO(2) per kilogram, and step frequency. RESULTS: In all trials, CSA output rose linearly (R2 = 0.92, P < 0.001) with increasing speed until 9 km.h-1 but remained at approximately 10000 counts.min-1 during running, thus underestimating VO(2) per kilogram at speeds > 9 km x h(-1). Estimation errors increased with speed from 11% (P < 0.01) at 10 km x h(-1) to 48% (P < 0.001) at 16 km x h(-1), when assuming a linear relationship. Freely chosen velocities in the field trial ranged from 10.9 to 16.3 km.h-1. No difference in the CSA-speed relationship was observed between the two scenarios. Differences in CSA output between subjects could partially be attributed to differences in step frequency (R = -0.34 (P = 0.02) for walking and R = -0.63 (P < 0.001) for running). CONCLUSION: CSA output increases linearly with speed in the walking range but not in running, presumably due to relatively constant vertical acceleration in running. Between-subject reliability was related to step frequency because CSA data are filtered most at higher movement frequencies. Epidemiological CSA data should thus be interpreted with these limitations in mind.

Acceleration↗
PubMed2003

PGC-1alpha genotype modifies the association of volitional energy expenditure with [OV0312]O2max.

UNLABELLED: Sedentary lifestyles are increasingly common and result in low cardiorespiratory fitness ([OV0312]O2max), a well-established predictor of early mortality and coronary heart disease (CHD). Adaptation in [OV0312]O2max after exercise training varies considerably between people. Because there are hereditary components to fitness, it is likely that genetic factors explain some of this variability. PPARGC1 (PGC-1alpha) coactivates genes involved in energy transduction and mitochondrial biogenesis. Transgenic mouse data demonstrate that overexpression of PGC-1alpha mRNA increases endurance capacity by transformation of nonoxidative to oxidative skeletal muscle tissue. Other murine studies demonstrate that exercise increases PGC-1alpha mRNA expression. PURPOSE: To explore whether a candidate polymorphism in the PGC-1alpha gene modifies the association between physical activity energy expenditure (PAEE) and predicted [OV0312]O2max ([OV0312]O2max.pred). METHOD: We examined whether the Gly482Ser polymorphism of PGC-1alpha modified the relationship between objectively measured PAEE and [OV0312]O2max.pred in a population-based sample of 599 healthy middle-aged people. PAEE was assessed using individual calibration with 4 d of heart rate monitoring. [OV0312]O2max.pred was measured during a submaximal exercise stress test on a bicycle ergometer. RESULTS: Homozygosity at the Ser482 allele was found in 12.7% of the cohort, whereas 38.9% and 48.4% carried the Gly482Gly and Gly482Ser genotypes, respectively. The association between PAEE and [OV0312]O2max.pred (mL x kg(-1) x min(-1)) was strongest in people homozygous for the Ser482 allele (beta = 12.03; P < 0.00001) compared with carriers of the Gly allele (beta = 5.61; P < 0.00001). In a recessive model for the Ser482 allele, the interaction between PAEE and genotype on [OV0312]O2max.pred (L x min(-1)) was highly significant (P = 0.009). CONCLUSION: Our results indicate that Ser482 homozygotes may be most capable of improving cardiorespiratory fitness when physically active, and that Gly482Ser may explain some of the between-person variance previously reported in cardiorespiratory adaptation after exercise training.

Adult↗
PubMed2002

[Utilization of national insurance in connection with functional somatic disorders].

BACKGROUND: Functional somatic disorders are often seen in medical practice. This study describes their financial consequences for the national insurance scheme. MATERIAL AND METHODS: National Insurance Administration data for the year 2000 were collected on sickness leave and disability pensions for fibromyalgia, whiplash injuries, chronic fatigue syndrome, dissociative and somatoform disorders, functional gastrointestinal disorders, chronic pelvic pain, and non-cardiac chest pain. RESULTS: Functional somatic disorders caused 2.9% of all sick leave among employees. Most of these were caused by fatigue/exhaustion or fibromyalgia. 6.3% of all new disability pensioners had a functional disorder, two thirds of them fibromyalgia. Functional disorders were more frequent in women, and in the 25-59 age group. INTERPRETATION: Functional disorders, fibromyalgia especially, are a great concern for the national insurance system. More focus on individual functioning rather than the disorder might contribute to better follow-up for these patients.

Adult↗