Validation of the BIOPAC indirect calorimeter for determining resting energy expenditure in healthy free-living older people

Wearable Piezoelectric Airflow Transducers for Human Respiratory and Metabolic Monitoring

Despite the importance of respiration and metabolism measurement in daily life, they are not widely available to ordinary people because of sophisticated and expensive equipment. Here, we first report a straightforward and economical approach to monitoring respiratory function and metabolic rate using a wearable piezoelectric airflow transducer (WPAT). A self-shielded bend sensor is designed by sticking two uniaxially drawn piezoelectric poly l-lactic acid films with different cutting angles, and then the bend sensor is mounted on one end of a plastic tube to engineer the WPAT. The airflow sensing principle of the WPAT is theoretically determined through finite element simulation, and the WPAT is calibrated with a pulse calibration method. We prove that the WPAT has similar accuracy (correlation coefficient >0.99) to a pneumotachometer in respiratory flow and lung volume assessment. We demonstrate metabolism measurement using the WPAT and the relationship between minute volume and metabolic rates via human wear trials. The mean difference of measured metabolic rates between the WPAT and a Biopac indirect calorimeter is 0.015 kcal/min, which shows comparable performance. Significantly, unlike the Biopac indirect calorimeter with an airflow sensor, an oxygen gas sensor, and a carbon dioxide gas sensor, we merely use the simple-structured WPAT to measure metabolism. Thus, we expect the WPAT technology to provide a precise, convenient, and cost-effective respiratory and metabolic monitoring solution for next-generation medical home care applications and wearable healthcare systems.

Prediction of resting energy expenditure in healthy older adults: A systematic review

BACKGROUND & AIMS

Estimates of energy requirements, based on measured or predicted resting energy expenditure (REE), are needed to avoid undernutrition or overnutrition (and their clinical consequences) in elderly subjects. The aims of this systematic review were to evaluate the prediction accuracy of REE in healthy elderly subjects and to ascertain which equation is more reliable at group level and/or individual level.

METHODS

Studies assessing prediction of REE in general elderly population were systematically searched using PubMed, EMBASE, Web of Science and CINAHL until March 2020. Prediction accuracy of REE was assessed at both group (bias) and individual (precision) level for each equation.

RESULTS

Fourteen studies met the inclusion criteria of this systematic review. Bias was reported in 8 papers and calculated in another 5 from absolute values. There was a prevalent tendency towards an overestimation of REE across the studies. The least bias was observed for the Mifflin (-0.3%) and Harris-Benedict (+2.6%) equations, with values above 5% for the FAO/WHO/UNU, Fredrix and Muller equations. Precision widely varied between studies for the same equation. The higher precision was observed using the Harris-Benedict equation (~70%), while the Henry and Mifflin equations provided estimates within 10% of measured values in 65% and 61% of elderly individuals, respectively.

CONCLUSIONS

None of the prediction equations considered provides accurate and precise REE estimates in healthy older adults. However, the best prediction is given by the Mifflin equation at group level and by the Harris-Benedict equation at individual level. Further studies with strong quality design are needed to evaluate the variability and accuracy of REE in the elderly general population.

The frailty syndrome: a comprehensive review

The frailty syndrome is defined as unintentional weight and muscle loss, exhaustion, and declines in grip strength, gait speed, and activity. Evidence with respect to the clinical definition, epidemiology, mechanisms, interactions, assessment, prevention, and treatment of frailty in the older adult is reviewed.

Body circumferences are predictors of weight adjusted resting energy expenditure in older people

OBJECTIVE

To evaluate predictors of resting energy expenditure (REE) in older people which are more comfortable for them than indirect calorimetry and which are suitable for field studies.

DESIGN

Cross-sectional study.

SETTING

Department of Human Biology, Kiel University.

PARTICIPANTS

100 (51 males, 49 females) healthy independently-living normal-weight (BMI, males 26.0±2.67 kg/m², females 25.0±3.29 kg/m²) Germans, aged 60-83 years.

MEASUREMENTS

REE, body composition, anthropometry, peak expiratory flow rate (PEF), and physical activity level were determined using indirect calorimetry, bioimpedance analysis, anthropometrics, peak-flow-meter, and standardized questionnaire, respectively. Stepwise linear multiple regression analysis was performed with REE or weight adjusted REE as dependent variables. Independent variables were body height, weight, body mass index (BMI), waist circumference, abdomen circumference, hip circumference, waist-to-hip ratio (WHR), lean body mass (LBM), PEF, and physical activity level.

RESULTS

The only significant predictor of REE was LBM in males and BMI in females. Trunk circumferences emerged as strong predictors of weight adjusted REE. Abdomen circumference and hip circumference explained in males and females 69% and 70% of variation in adjusted REE, respectively. Weaker predictors were LBM in males (R² increased from 0.69 to 0.80) as well as body height and BMI in females (R² increased from 0.70 to 0.91). Waist circumference, WHR, physical activity level, and PEF were no significant determinants of adjusted REE.

CONCLUSION

These findings demonstrate that trunk circumferences, but not WHR, are very strong predictors of weight adjusted REE in non-geriatric older people. This implies that the sex-specific use of abdomen or hip circumference in combination with LBM or body height and BMI seems to be well sufficient to predict weight adjusted REE in the aged. These measures might also be of clinical relevance, because they are more comfortable for older sick people than indirect calorimetry. Further studies are needed to test the applicability of the prediction equations to frail older populations.

Accuracy of a portable multisensor body monitor for predicting resting energy expenditure in older people: a comparison with indirect calorimetry

BACKGROUND

Accurate and comfortable methods are needed to determine resting energy expenditure (REE) in older people who are characterized by a lowered metabolic rate. The portable SenseWear® armband (SWA) body monitor, worn on the right upper arm, can easily be used by this age group in an ambulatory manner.

OBJECTIVE

The purpose of this study was to evaluate the reliability and accuracy of the SWA armband in determining REE in healthy, normal-weight older people.

METHODS

Participants were 49 older, community-dwelling volunteers aged 60-87 years. Reliability was tested in all subjects. Accuracy was analyzed in 32 subjects by comparing REE estimated by SWA against REE measured by indirect calorimetry as a criterion method. Data were simultaneously and continuously recorded for 20 min in the morning. In the same subjects, REE determined by SWA from night recording was evaluated for accuracy against indirect calorimetry. The agreement between methods was assessed by the Bland-Altman procedure.

RESULTS

(1) REE measured by SWA was reliable when comparing 2 consecutive measurements (typical error: 1.9%). (2) REE calculated from morning recording (1,543 ± 181 kcal/24 h) was higher than REE from night recording (1,564 ± 192 kcal/24 h; p = 0.018). (3) Compared with REE by indirect calorimetry (1,377 ± 228 kcal/24 h) for accuracy, the SWA overestimated mean REE in the older people by 12 and 14%, respectively, for morning and night recording (each p < 0.001).

CONCLUSIONS

The SWA provides a reliable estimate of REE in healthy older subjects and has the advantage of easy handling. The 20-min recording time, which was recommended by the manufacturer, can be applied. However, the SWA overestimates REE in this group, possibly due to age-related changes in skin conductance and thermoregulation, both being measured by sensors of the SWA armband. This requires improving the SWA by developing better fitting algorithms for predicting REE in older people.