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Biomedical subjects

Kong Y Chen

Publications and source records attributed to Kong Y Chen.

12 recordsLinked to original sources
PubMed2006

Autonomic contribution to blood pressure and metabolism in obesity.

Obesity is associated with alterations in the autonomic nervous system that may contribute to the increase in blood pressure and resting energy expenditure present in this condition. To test this hypothesis, we induced autonomic withdrawal with the ganglionic blocker trimethaphan in 10 lean (32+/-3 years) and 10 obese (35+/-3 years) subjects. Systolic blood pressure fell more in obese compared with lean subjects (-17+/-3 versus -11+/-1 mm Hg; P=0.019) because of a greater decrease in total peripheral resistance (-310+/-41 versus 33+/-78 dynes/sec/cm(-5); P=0.002). In contrast, resting energy expenditure decreased less in obese than in lean subjects, (-26+/-21 versus -86+/-15 kcal per day adjusted by fat-free mass; P=0.035). We confirmed that the autonomic contribution to blood pressure was greater in obesity after including additional subjects with a wider range of blood pressures. Systolic blood pressure decreased -28+/-4 mm Hg (95% CI: -38 to -18.0; n=8) in obese hypertensive subjects compared with lean (-9+/-1 mm Hg; 95% CI: -11 to -6; n=22) or obese normotensive subjects (-14+/-2 mm Hg; 95% CI: -18 to -10; n=20). After removal of autonomic influences, systolic blood pressure remained higher in obese hypertensive subjects (109+/-3 versus 98+/-2 mm Hg in lean and 103+/-2 mm Hg in obese normotensive subjects; P=0.004) suggesting a role for additional factors in obesity-associated hypertension. In conclusion, sympathetic activation induced by obesity is an important determinant to the blood pressure elevation associated with this condition but is not effective in increasing resting energy expenditure. These results suggest that the sympathetic nervous system could be targeted in the treatment of obesity-associated hypertension.

Adult↗
PubMed2006

Tracking workload in the emergency department.

OBJECTIVE: The primary objective of this study was to create a methodology for measuring transient levels of physician workload in a live emergency department (ED) environment. BACKGROUND: Characterizing, defining, and measuring aspects of this interrupt-driven work environment represent the preliminary steps in addressing impending issues concerning ED overcrowding, efficiency, and patient and provider safety. METHODS: A time-motion task analysis was conducted. Twenty emergency medicine (EM) physicians were observed for 180-min intervals in an ED of an academic medical center. Near continuous workload measures were developed and used to track changing workload levels in time. These measures were taken from subjective, objective, and physiological perspectives. The NASA-Task Load Index was administered to each physician after observational sessions to measure subjective workload. Physiological measurements were taken throughout the duration of the observation to measure stress response. Additional information concerning physicians' patient quantity and patient complexity was extracted from the ED information system. RESULTS: Graphical workload profiles were created by combining observational and subjective data with system state data. Methodologies behind the creation of workload profiles are discussed, the workload profiles are compared, and quantitative and qualitative analyses are conducted. CONCLUSION: Using human factors methods to measure workload in a setting such as the ED proves to be challenging but has relevant application in improving the efficiency and safety of EM. APPLICATION: Techniques implemented in this research are applicable in managing ED staff and real-time monitoring of physician workload.

Emergency Service, Hospital↗
PubMed2005

The technology of accelerometry-based activity monitors: current and future.

PURPOSE: This paper reviews accelerometry-based activity monitors, including single-site first-generation devices, emerging technologies, and analytical approaches to predict energy expenditure, with suggestions for further research and development. METHODS: The physics and measurement principles of the accelerometer are described, including the sensor properties, data collections, filtering, and integration analyses. The paper also compares these properties in several commonly used single-site accelerometers. The emerging accelerometry technologies introduced include the multisensor arrays and the combination of accelerometers with physiological sensors. The outputs of accelerometers are compared with criterion measures of energy expenditure (indirect calorimeters and double-labeled water) to develop mathematical models (linear, nonlinear, and variability approaches). RESULTS: The technologies of the sensor and data processing directly influence the results of the outcome measurement (activity counts and energy expenditure predictions). Multisite assessment and combining accelerometers with physiological measures may offer additional advantages. Nonlinear approaches to predict energy expenditure using accelerometer outputs from multiple sites and orientation can enhance accuracy. CONCLUSIONS: The development of portable accelerometers has made objective assessments of physical activity possible. Future technological improvements will include examining raw acceleration signals and developing advanced models for accurate energy expenditure predictions.

Acceleration↗
PubMed2004

Use of air displacement plethysmography in the determination of percentage of fat mass in african american children.

The purpose of this study was to determine the ability of air displacement plethysmography (ADP) to estimate percentage of fat mass (%FM) in African American children. %FM was determined in 21 boys and 13 girls (11.0 +/- 1.4 y, 18.6 +/- 4.2 kg/m(2) [mean +/- SD]) by ADP (using six published densitometric equations) and dual-energy x-ray absorptiometry (DXA). Measures were done within 2 h of one another, in random order. Regardless of equation, %FM(ADP) was significantly correlated with %FM(DXA) (R(2) = 0.67-0.71, all p < 0.001). %FM(ADP) using the equation of Siri (%FM(ADP-Siri) 20.3 +/- 9.0) agreed most closely with %FM(DXA) (20.0 +/- 10.2, difference p = 0.729). Together, surface area artifact and bone mineral content per unit of bone-free fat-free mass accounted for 29% of the variance in the residual between methods. The correlation between %FM(ADP-Siri) and %FM(DXA) was not significant for those <35 kg (n = 10; R(2) = 0.084, p = 0.417). There was a trend toward %FM(ADP-Siri) underestimating %FM(DXA) in girls (-1.46 +/- 3.0%FM; p = 0.103) but not in boys (1.43 +/- 6.4%FM; p = 0.315). Predicted lung volume was 40.1% higher than measured lung volume (p < 0.001). %FM(ADP-Siri) determined using predicted lung volume was 23.5 +/- 8.9, higher than that using measured lung volume (p < 0.001) and higher than %FM(DXA) (p = 0.001). We conclude that in 9- to 14-y-old African American children and provided lung volume is measured, %FM using ADP with Siri's equation approximates that obtained by DXA. Body composition results determined by ADP in children <35 kg should be interpreted with caution.

Absorptiometry, Photon↗
PubMed2004

Efficiency of walking and stepping: relationship to body fatness.

OBJECTIVE: To determine energetic efficiency of walking and stepping in a heterogeneous normal adult population and its association with body fatness and to assess within- and between-individual variations. RESEARCH METHODS AND PROCEDURES: Using a combination of a whole-room indirect calorimeter and a large precision force platform, we simultaneously measured minute-by-minute energy expenditure (EE) and mechanical work during walking and stepping in healthy adult men (n = 60) and women (n = 85). Efficiency was calculated as a ratio (percentage) of mechanical work and EE of activity. Efficiency of walking and stepping performed at various intensities was compared for reproducibility within the same day (morning and afternoon) and correlated with a subject's characteristics. RESULTS: The efficiency of walking was negatively correlated with body fatness in both men and women at 0.9 to 1.2 m/s but positively correlated with body fatness in men and not correlated in women at the slowest speed tested (0.6 m/s). Efficiency of walking and stepping of various intensities was reproducible during the same day. Compared at similar EE levels, walking was more efficient than stepping (26% to 27% vs. 18% to 22%, p < 0.01). Women were significantly (p < 0.01) more efficient than men during stepping. Age, sex, body mass, fat-free mass, fitness (maximal oxygen uptake), height, and speed variations contributed to the between-subject differences in efficiency. DISCUSSION: Obese individuals were less efficient than lean individuals during normal-speed walking. Significant interindividual variations in efficiency of walking and stepping may be attributed to habituation and physical characteristics such as age, sex, and fitness level.

Adult↗
PubMed2004

Energy expenditure, body composition, and biochemical indicators in healthy community women.

A cross-sectional study was conducted on the associations between energy expenditure (EE), body composition (lean mass, fat mass, body mass index), and biochemical indicators (leptin, glucagon, insulin, cortisol, and triglycerides) among 17 sedentary African-American and Caucasian women living in the community (age, 40.7+/-6.0 years; body mass index, 32.8+/-9.0 kg/m2). Measurements included total, resting, and sleeping EE (via whole-room indirect calorimetery), body composition (via air-displacement plethysmography), body mass index, and biochemical indicators (leptin, glucagon, cortisol, insulin, and triglycerides). Analysis of associations between EE and body composition showed that EE increased with increasing body size, with lean mass explaining 79%, 71%, and 73% of the variability in total, resting, and sleeping EE, respectively. Analysis of associations between body composition and the biochemical indicators showed that leptin, glucagon, and insulin were positively correlated with increasing body size, whereas cortisol was negatively correlated with increasing body size. Analysis of associations between EE and biochemical indicators prior to controlling for body size showed that leptin was positively correlated with EE, and that the correlation between leptin and sleeping EE was significantly greater than the correlation between leptin and resting EE. After controlling for body size, the correlations between leptin and EE were no longer significant, and the partial correlation between leptin and sleeping EE was no longer significantly different from the partial correlation between leptin and resting EE. Glucagon was positively correlated with EE, but not after controlling for body composition. Future research should incorporate the use of sleeping EE in addition to resting EE, since clearly, for some biochemicals such as leptin and glucagon, this distinction is important. Methodological improvements may provide better insight into the effects of obesity modulating hormones.

Adult↗
PubMed2003

Predicting energy expenditure of physical activity using hip- and wrist-worn accelerometers.

To investigate the association between physical activity and health, we need accurate and detailed free-living physical activity measurements. The determination of energy expenditure of activity (EEACT) may also be useful in the treatment and maintenance of nutritional diseases such as diabetes mellitus. Minute-to-minute energy expenditure during a 24-h period was measured in 60 sedentary normal female volunteers (35.4 +/- 9.0 years, body mass index 30.0 +/- 5.9 kg/m2), using a state-of-the-art whole-room indirect calorimeter. The activities ranged from sedentary deskwork to walking and stepping at different intensities. Body movements were simultaneously measured using a hip-worn triaxial accelerometer (Tritrac-R3D, Hemokentics, Inc., Madison, Wisconsin) and a wrist-worn uniaxial accelerometer (ActiWatch AW64, MiniMitter Co., Sunriver, Oregon) on the dominant arm. Movement data from the accelerometers were used to develop nonlinear prediction models (separately and combined) to estimate EEACT and compared for accuracy. In a subgroup (n=12), a second 24-h study period was repeated for cross-validation of the combined model. The combined model, using Tritrac-R3D and ActiWatch, accurately estimated total EEACT (97.7 +/- 3.2% of the measured values, p=0.781), as compared with using ActiWatch (86.0 +/- 4.7%, p<0.001) or Tritrac-R3D (90.0 +/- 4.6%, p<0.001) alone. This model was also accurate for all intensity categories during various physical activities. The subgroup cross-validation also showed accurate and reproducible predictions by the combination model. In this study, we demonstrated that movement measured using accelerometers at the hip and wrist could be used to accurately predict EEACT of various types and intensity of activities. This concept can be extended to develop valid models for the accurate measurement of free-living energy metabolism in clinical populations.

Algorithms↗
PubMed2002

Patterns and energy expenditure of free-living physical activity in adolescents with sickle cell anemia.

OBJECTIVE: Our purpose was to examine the relationship between physical activity (PA), PA-associated energy expenditure (PAEE), and total daily energy expenditure (TEE) in free-living adolescents with sickle-cell anemia (SCA). STUDY DESIGN: Adolescents with SCA (n = 28) were matched for sex and age with 22 healthy control participants. PA was measured for 6 to 8 consecutive days with a triaxial accelerometer and resting energy expenditure (REE) by whole-room indirect calorimetry. TEE was calculated by summing PAEE and REE. RESULTS: TEE was similar, REE was higher (difference, 209 kcal x day(-1); P =.0001), and PAEE was lower (difference, 657 kcal x day(-1); P <.001) in patients with SCA than in control participants. In SCA, there was a positive linear relationship between PAEE and hemoglobin concentration (r (2) = 0.583). Time spent in PA of moderate and high intensity was lower in patients with SCA than in control participants (18 +/- 22 vs 48 +/- 31 min/d; P <.0001). CONCLUSION: In adolescents with SCA under free-living conditions, there is a significant intra and interindividual variability in the amount of PA, PAEE, and PA patterns. Because of a lower PAEE and a higher REE, TEE is similar in adolescents with SCA and healthy adolescents. An association of PAEE with hemoglobin concentration may be a part of an energy saving compensatory mechanism in SCA.

Adolescent↗
PubMed2002

Equation to estimate resting energy expenditure in adolescents with sickle cell anemia.

BACKGROUND: Basal energy requirements are higher in adolescents with sickle cell anemia (SCA) than in healthy control subjects. However, no equation is available to accurately predict their energy needs. OBJECTIVE: Our objective was to develop a clinically useful equation to estimate resting energy expenditure (REE) in adolescents with SCA. DESIGN: REE and other components of total energy expenditure were measured in adolescents with SCA (n = 37) and in control subjects (n = 23) for 24 h in a whole-room indirect calorimeter. Multiple linear regression analysis was used to describe the relations of REE with independent variables such as sex, weight, height, fat-free mass, fat mass, age, and hemoglobin concentration in adolescents with SCA. The Bland-Altman comparison technique was used to compare values predicted by existing equations with measured REE values. RESULTS: Mean (+/-SD) measured REEs were 7746 +/- 974 and 6332 +/- 869 kJ/d in the male and female subjects with SCA, respectively, and these values were 16% higher than those in the healthy control subjects. Standard equations underestimated REE by 12% (P </= 0.001) in adolescents with SCA and overestimated REE by 4% in control subjects (P = 0.01-0.29). Several REE regression equations for SCA were developed. The most parsimonious equation for males was REE (kJ/d) = 5461 + 77.7.weight (kg) - 233.2.hemoglobin (g/dL), or REE (kcal/d) = 1305 + 18.6.weight (kg) - 55.7.hemoglobin (g/dL). For females, the most parsimonious equation was REE (kJ/d) = 4603 + 55.6.weight (kg) - 126.2.hemoglobin (g/dL), or REE (kcal/d) = 1100 + 13.3.weight (kg) - 30.2.hemoglobin (g/dL). CONCLUSION: The new equations have better agreement with the basal metabolic needs of adolescents with SCA than do standard predictive equations.

Adolescent↗
PubMedDate not supplied

Increased resting energy expenditure in patients with end-stage renal disease.

BACKGROUND: Protein-calorie malnutrition is a significant problem for patients with end-stage renal disease. Increased resting energy expenditure may be an important contributing factor. We postulate that resting energy expen diture in the different stages of renal disease and treatments may be different. METHODS: Resting energy expenditure was measured using a whole-room indirect calorimeter (metabolic chamber) along with nutritional parameters and body composition after 12-hour fasting in 15 patients with advanced chronic renal failure patients, 15 patients on chronic hemodialysis, and 10 patients on peritoneal dialysis. Patients on hemodialysis were assessed on a non-dialysis day. A 2-day dietary recall was used to assess energy intake. RESULTS: Resting energy expenditure, adjusted for fat-free mass, was similar in patients on hemodialysis and peritoneal dialysis but significantly higher than in patients with chronic renal failure (p < .05). Resting energy expenditure in all patients were generally higher (10% to 20%) than predicted values using standard equations derived in normal and obese populations, whereas daily energy intake was less (26% to 34%) than energy expenditure for all groups, adjusted for light daily activity. CONCLUSIONS: End-stage renal disease patients displayed increases in resting energy expenditure over the predicted values derived using normal populations. Resting energy expenditure was significantly higher in patients receiving dialysis, regardless of the modality, than patients with chronic renal failure. Daily energy intake was substantially less than required in all patient groups studied, suggesting that patients with renal failure could develop protein-calorie malnutrition because of increased resting energy expenditure, which is exacerbated by dialysis.

Blood Proteins↗
PubMedDate not supplied

Bioelectrical impedance vs air displacement plethysmography and dual-energy X-ray absorptiometry to determine body composition in patients with end-stage renal disease.

BACKGROUND: Patients with end-stage renal disease (ESRD) have significant shifts in fluid homeostasis that may impair measurements of body composition using methods based upon determinations of body water. Estimates of body water are fundamental for bioelectrical impedance analysis (BIA), which measures electrical resistance to estimate total body water and body composition. METHODS: BIA was compared with 2 other techniques: (1) air displacement plethysmography (ADP), which relies on measurements of body density to estimate body fat and fat-free masses; and (2) dual-energy x-ray absorptiometry (DXA), which depends on the relative attenuation of an x-ray beam to produce images of body fat and bone mineral. In study 1, BIA and ADP were performed on 38 ESRD patients (21 men and 17 women; age 51.3 +/- 2.2 years; weight 79.8 +/- 2.9 kg; body mass index [BMI] 27.4 +/- 0.9 kg/m2). In study 2, BIA and DXA were performed on 47 patients (22 men and 25 women; age 52.7 +/- 2.3 years; weight 73.6 +/- 2.9 kg; BMI 25.9 +/- 1.0 kg/m2). RESULTS: The ranges of percent body fat using BIA in studies 1 and 2 were from 7% to 57% and from 6% to 52%, respectively. Percent body fat measurements were significantly (p < .0001) correlated for BIA vs ADP (r = .74) and for BIA vs DXA (r = .84). Mean body fat as determined by BIA and ADP in study 1 was 31.8 +/- 2.0% and 36.3 +/- 1.8%* and by BIA and DXA in study 2 was 29.6 +/- 1.5% and 31.8 +/- 1.8%*, respectively (*p < .05 vs BIA). All 3 methods had similar variability associated with their measurements (coefficients of variation approximately 5%). The average body fat measured by BIA was less than ADP or DXA, regardless of gender or race. Furthermore, the variation was not greater at lower or higher body fat values. CONCLUSIONS: Body fat measurements using ADP and DXA were correlated with those using BIA across a relatively wide range of body fat levels in adults with ESRD. However, BIA appeared to underestimate body fat and overestimate fat-free mass, possibly because of increased measurements of body water. Because ADP is convenient and does not use body water content in determination of body density and body composition, it has very good potential as a relatively new technique to estimate percent body fat in adults with ESRD.

Absorptiometry, Photon↗