Ability to predict resting energy expenditure with six equations compared to indirect calorimetry in octogenarian men

Prediction of resting energy expenditure in Italian older adults with severe obesity

Background

In the last decade a large number of studies proposed and/or validated equations to estimate the Resting Energy Expenditure (REE) in adults and/or older adults, however, no equation currently available showed good accuracy for older adults with severe obesity. Thus, this study aimed to develop and validate new predictive equations for REE, based on data from the indirect calorimetry, in Italian older adults with severe obesity.

Methods

A retrospective study was as conducted with 764 Caucasian older adults with severe obesity (age range: 60-74 years and BMI ≥ 35 kg/m/²). Four models were used to test the accuracy of anthropometry and body composition variables in multivariable prediction of REE. All models were derived by stepwise multiple regression analysis using a calibration group of 382 subjects [295 females and 87 males] and the equations were cross-validated in the remaining 382 subjects [295 females and 87 males] as validation group. The new prediction equations and the other published equations were tested using the Bland-Altman method. Prediction accuracy was defined as the percentage of subjects whose REE was predicted within ± 10% of measured REE.

Results

All the equations analyzed predicted higher energy requirements for males than females, and most of them underestimated the energy requirement values of our sample. The highest accuracy values were observed in the new equations, with 62% in the anthropometric model and 63% in the body composition model.

Conclusion

Although the accuracy of our equations was slightly higher in comparison with the other taken into consideration, they cannot be considered completely satisfactory for predicting REE in Italians older adults with severe obesity. When predicting equations cannot guarantee precise or acceptable values of REE, the use of indirect calorimetry (if available) should be always recommended, especially in clinical practice.

Time-restricted eating to improve cardiometabolic health: The New York Time-Restricted EATing randomized clinical trial - Protocol overview

Re-aligning eating patterns with biological rhythm can reduce the burden of metabolic syndrome in older adults with overweight or obesity. Time-restricted eating (TRE) has been shown to result in weight loss and improved cardiometabolic health while being less challenging than counting calories. The New York Time-Restricted EATing study (NY-TREAT) is a two-arm, randomized clinical trial (RCT) that aims to examine the efficacy and sustainability of TRE (eating window ≤10 h/day) vs. a habitual prolonged eating window (HABIT, ≥14 h/day) in metabolically unhealthy midlife adults (50-75 years) with overweight or obesity and prediabetes or type 2 diabetes (T2D). Our primary hypothesis is that the TRE will result in greater weight loss compared to HABIT at 3 months. The efficacy of the TRE intervention on body weight, fat mass, energy expenditure, and glucose is tested at 3 months, and the sustainability of its effect is measured at 12 months, with ambulatory assessments of sleep and physical activity (ActiGraph), eating pattern (smartphone application), and interstitial glucose (continuous glucose monitoring). The RCT also includes state-of-the-art measurements of body fat (quantitative magnetic resonance), total energy expenditure (doubly-labelled water), insulin secretion, insulin resistance, and glucose tolerance. Adherence to self-monitoring and reduced eating window are monitored remotely in real-time. This RCT will provide further insight into the effects of TRE on cardiometabolic health in individuals with high metabolic risk. Sixty-two participants will be enrolled, and with estimated 30% attrition, 42 participants will return at 12 months. This protocol describes the design, interventions, methods, and expected outcomes. Clinical trial registration:NCT04465721 IRB: AAAS7791.

Caloric adequacy of parenteral nutrition and its influence on the clinical outcome of hospitalised patients

Background: The adaptation of Parenteral Nutrition (PN) to actual energy requirements of hospitalised patients is essential, since excessive and insufficient nutritional intake have been associated with poor clinical outcomes. Aim: To evaluate the adaptation of prescribed PN to the estimated nutritional requirements using three predictive equations and the influence of excessive/insufficient nutrient intake on patient clinical outcomes (nutritional parameters, metabolic and infectious complications). Methods: Prospective, observational study in hospitalised patients nutritionally assessed. Data was collected the first and fifth/sixth day of PN with clinical (infection, length of hospital stay), biochemical (visceral proteins, cholesterol, glucose, triglycerides, lymphocytes, CRP) and anthropometric parameters (skin folds, height, weight). Theoretical requirements were calculated using Harris-Benedict (HB), Mifflin-St Jeor (MF) and 25 Kcal/Kg/day formulas. The HB formula was used to compare estimated and provided requirements. Results: A total of 94 patients (mean: 72 ± 13.7 years old) were included with initial mean weight and height of 69.2 Kg and 162.8 cm, respectively (mean BMI: 26.1 Kg/m²). No statistically significant differences were found between the actual (1620 Kcal/day) and estimated caloric mean calculated with HB (1643 Kcal/day) and MF (1628 Kcal/day). When comparing with the caloric estimation, 31.9% of patients were underfed, while 14.9% were overfed. Intergroup analysis demonstrated significant variations in albumin, prealbumin, glucose, cholesterol, triglycerides and MUAC, with a significant increase of hyperglycaemia (+37.86; p < 0.05) and hypertriglyceridemia (+63.10; p < 0.05), being higher in overfed patients. Conclusion: In our study, inadequate nutrient intake was associated with a higher degree of hyperglycaemia and hypertriglyceridemia, without positive impact on anthropometric parameters.

Determinants of Resting Energy Expenditure in Very Old Nursing Home Residents

OBJECTIVES

This study aimed to measure resting energy expenditure (REE) in institutionalized old persons and to determine factors possibly related to change in REE as a basis for estimating energy requirements.

DESIGN AND SETTINGS

A monocentric cross-sectional study was conducted. Statistical approaches were conducted to determine independent factors associated with REE. Various published predictive equations of REE were compared to our population.

PARTICIPANTS

72 residents of a nursing home, mostly women (80.5%) aged 87.4±6.6 years were included.

MEASUREMENTS

REE (indirect calorimetry), body composition (bio-impedance analysis), biological and anthropometric data were collected.

RESULTS

Mean REE was 1006±181 kcal/d and was higher in men than in (1227±195 vs. 953±131 kcal/d, p<0.05). According to criteria adapted from the Global Leadership Initiative on Malnutrition consensus, 65.3 % of the institutionalized population were malnourished. In multivariate analysis adjusted on gender and age, REE was positively associated with calorie intake, fat-free mass (FFM), functional abilities (French Autonomie Gérontologie Groupe Iso Ressources scale), and elevated CRP level (> 25 mg/l). Significant differences (p<0.05) appeared between measured REE and predicted REE by using various published equations.

CONCLUSION

REE of very old nursing home residents is influenced by FFM, calorie intake, functional abilities, and CRP levels and is poorly predicted by classical equations based on age, gender, height, and weight. This suggests a metabolic adaptation to caloric restriction and inflammation and prompts to consider the level of physical activity and muscle loss when assessing caloric requirements in this population.

Nutritional status in older people - An explorative analysis

BACKGROUND & AIMS

The nutritional status is seldom defined in general, but is considered to be important throughout life span, especially in times of diseases and disabilities. We previously proposed a theoretical model of the nutritional status from a functional perspective [1], however without proposing a definition of the nutritional status. The model comprises four domains that might affect the nutritional and functional status in a bidirectional way. These four domains are: Food and nutrition; Health and somatic disorders; Physical function and capacity; and Cognitive, affective, and sensory function. This study contributes to the existing literature and knowledge by empirically analysing patterns and relationships of possible nutritional status indicators within and between the four domains.

METHODS

This study is based on a sample of 69 men and women; older than 65 years, receiving home health care. They were followed up for three years. A broad set of nutritional status indicators in the participants were assessed in their home yearly. Given the small sample size and large number of variables, we used both correlation and factor analysis to explore patterns of nutritional status indicators within the four domains and relationships between the four domains suggested by the theoretical model of nutritional status which we proposed earlier.

RESULTS

At baseline, between 4 and 18 components were extracted from the four domains, separately, using factor analysis. The first three components of each domain (called main components) were correlated (p < 0.05) with at least one of the main components of each of the other three domains (r = -0.34-0.79 at baseline, 0.38-0.74 at year 1, 0.40-0.77 at year 2 and 0.47-0.71 at year 3). At baseline, these main components explained, respectively, 31%, 52%, 57% and 63% of the sample variation in the four domains. This remained stable throughout all three years of follow up. In all four domains, there were statistically significant differences in prevalence of malnutrition, frailty, sarcopenia, and dehydration (all different inadequate nutritional status) between individuals' individual component scores.

CONCLUSIONS

This study provides empirical evidence for the relationship between nutritional status indicators within and between the four domains suggested by our theoretical model of nutritional status. Components in all four domains were associated with inadequate nutritional status, highlighting that a wide perspective of the nutritional status assessment is necessary to be applied in clinical practice.

Dehydration and loss of appetite: Key nutrition features in older people receiving home health care

OBJECTIVES

The aim was to describe a population of older people in home health care based on what is probably a novel theoretical model, previously published, and to analyze longitudinal changes in different dimensions of nutritional status.

METHODS

This explorative and longitudinal study examines nutritional status based on four domains in the novel theoretical model: health and somatic disorders; cognitive, affective, and sensory function; physical function and capacity; and food and nutrition. Inclusion criteria were age ≥65 y and need of home health care for more than three months. A total of 69 men and women were enrolled in the study. Participants' nutritional status was studied at baseline and regularly during the following three years.

RESULTS

At baseline, 44% (n = 27) reported one or more severe symptoms and 83% had polypharmacy (≥5 prescribed medications). The prevalence of malnutrition, sarcopenia, frailty, and dehydration at baseline were, respectively, 83% (n = 35), 44% (n = 24), 34% (n = 18), and 45% (n = 25). Participants that died during the 3-y follow-up (n = 14) differed from survivors in the following aspects: more reduced appetite, lower quality of life, worse cognitive function, lower physical activity, and less intake of dietary fiber and water. Dehydration at baseline was associated with lower function in several domains and with general decline over time.

CONCLUSIONS

Most participants had poor nutritional status. Dehydration and reduced appetite were important indicators of worsening nutritional and overall status and mortality.

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.

Resting Energy Expenditure in the Elderly: Systematic Review and Comparison of Equations in an Experimental Population

Elderly patients are at risk of malnutrition and need an appropriate assessment of energy requirements. Predictive equations are widely used to estimate resting energy expenditure (REE). In the study, we conducted a systematic review of REE predictive equations in the elderly population and compared them in an experimental population. Studies involving subjects older than 65 years of age that evaluated the performance of a predictive equation vs. a gold standard were included. The retrieved equations were then tested on a sample of 88 elderly subjects enrolled in an Italian nursing home to evaluate the agreement among the estimated REEs. The agreement was assessed using the intraclass correlation coefficient (ICC). A web application, equationer, was developed to calculate all the estimated REEs according to the available variables. The review identified 68 studies (210 different equations). The agreement among the equations in our sample was higher for equations with fewer parameters, especially those that included body weight, ICC = 0.75 (95% CI = 0.69-0.81). There is great heterogeneity among REE estimates. Such differences should be considered and evaluated when estimates are applied to particularly fragile populations since the results have the potential to impact the patient's overall clinical outcome.

Validity of Tools to Measure Physical Activity in Older Adults Following Total Knee Arthroplasty

Few validated tools exist for measuring physical activity following total knee arthroplasty (TKA) despite the importance of returning to sufficient levels of physical activity post-TKA to achieve health benefits. This study examined the validity of two clinical measures-the Fitbit, a commercially available personal activity monitor, and the Community Healthy Activities Model Program for Seniors (CHAMPS), a self-report questionnaire-compared with a reference standard accelerometer, the SenseWearTM Armband (SWA). At 6-month post-TKA, 47 participants wore the Fitbit and SWA for 4 days and then completed the CHAMPS. Moderate-to-good correlation was observed between the Fitbit and SWA for steps (intraclass correlation coefficient [ICC] = .79), energy expenditure (ICC = .78), and energy expenditure <3 METS (ICC = .79). Poor-to-moderate correlation was observed between the CHAMPS and SWA (ICC = .43) with the questionnaire reporting lower daily energy expenditures than the SWA. Results showed that Fitbit may be a reasonable measurement tool to measure steps and energy expenditures in older adults following TKA.

Clinical determinants of resting metabolic rate in geriatric outpatients

PURPOSE

Accurate estimation of the energy requirements including resting metabolic rate (RMR) is important for optimal nutritional care, yet its clinical determinants are unknown. This study examined the associations between clinical determinants of the Comprehensive Geriatric Assessment (CGA) domains with RMR among geriatric outpatients.

MATERIALS & METHODS

Data were retrieved from cohorts of community-dwelling older adults (n = 84, 54 female) referring to geriatrics outpatient mobility clinics in both Amsterdam, The Netherlands and Melbourne, Australia. Determinants within domains of the CGA included diseases (number, type and severity of diseases, polypharmacy), nutrition (body weight, body mass index, absolute and relative skeletal muscle mass, fat-free mass and fat mass, risk of malnutrition), physical function (handgrip strength, Short Physical Performance Battery, Timed Up & Go), cognition (Mini-Mental State Examination), psychological wellbeing (Geriatric Depression Scale) and blood pressure. RMR was objectively measured using indirect calorimetry with a canopy hood. Association between the clinical determinants with standardized RMR (country and sex-specific z-score) were analysed with linear regression adjusted for age, sex and body weight.

RESULTS

Determinants within the nutritional domain were associated with RMR; body weight showed the strongest association with RMR. Significant associations between determinants within the nutritional domain with RMR disappeared after further adjustment for body weight. None of the other domains were associated with RMR.

CONCLUSIONS

Body weight is the strongest clinical determinant of RMR and should be taken into account when estimating RMR in geriatric care.