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Current Evidence for Estimating Energy Requirements. Clare Soulsby, Research Dietitian. Main components of energy expenditure:. basal metabolic rate (BMR) alteration in BMR due to disease process (stress factors) activity diet induced thermogenesis (DIT). Estimating BMR: controversies.

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Current evidence for estimating energy requirements

Current Evidence for Estimating Energy Requirements

Clare Soulsby, Research Dietitian

Main components of energy expenditure
Main components of energy expenditure:

  • basal metabolic rate (BMR)

  • alteration in BMR due to disease process (stress factors)

  • activity

  • diet induced thermogenesis (DIT)

Estimating bmr controversies
Estimating BMR: controversies

  • basal metabolic rate (BMR) vs. resting energy expenditure (REE)

  • prediction equations vs. measured energy expenditure (MEE)

Conditions essential for measuring bmr
Conditions essential for measuring BMR

  • post-absorptive (12 hour fast)

  • lying still at physical and mental rest

  • thermo-neutral environment (27 – 29oC)

  • no tea/coffee/nicotine in previous 12 hours

  • no heavy physical activity previous day

  • gases must be calibrated

  • establish steady-state (~ 30 minutes)

    * if any of the above conditions are not met = REE

Estimating bmr controversies1
Estimating BMR: controversies

  • basal metabolic rate (BMR) vs. resting energy expenditure (REE)

  • prediction equations vs. measured energy expenditure (MEE)

Estimating bmr prediction equations
Estimating BMR: prediction equations

  • may over or under-estimate (compared with MEE)

  • inadequately validated

  • poor predictive value for individuals

  • open to misinterpretation

    (Cortes & Nelson, 1989; Malone, 2002; Reeves & Capra, 2003)

Estimating bmr which equation
Estimating BMR:which equation?

  • Harris-Benedict

  • Schofield Equations

  • disease specific eg Ireton Jones

  • Kcal/kg

Estimating bmr harris benedict equations
Estimating BMR: Harris Benedict Equations

  • Developed in 1919

  • From data collected between 1909 and 1917 (Harris Benedict 1919)

  • Study population:

    • 136 men; mean age 27 ± 9 yrs, mean BMI 21.4 ± 2.8

    • 103 women; mean age 31 ± 14 yrs, mean BMI 21.5 ± 4.1

  • Tends to overestimate in healthy individuals (Daly 1985, Owen 1986, Owen 1987)

Estimating bmr schofield equations
Estimating BMR: Schofield Equations

  • developed in 1985 (Schofield 1985)

  • meta analysis of 100 studies of 3500men and 1200 women

  • studies conducted between 1914 and 1980 (including Harris Benedict data)

  • 2200 (46%) subjects were military Italian adults

  • 88 (1.2%) subjects were >60 years

  • SE 153-164kcal/d (women) 108 -119kcal/d (men) (Schofield 1985)

Estimating bmr disease specific equations
Estimating BMR: disease specific equations

  • developed for specific patient groups (Ireton Jones 1992, Ireton Jones 2002)

  • advantage over Schofield/ HB equations:

    • Schofield /HB estimate BMR of a healthy individual then necessary to adjust for disease using a stress factors

    • disease specific equations include patients in their database so aim to more accurately reflect BMR of hospitalised patients

Estimating bmr ireton jones energy equations
Estimating BMR: Ireton-Jones energy equations

  • ventilated and breathing ICU patients

  • 3 x 1 minute measurements 200 patients

  • unclear whether measurements took place during feed infusion/ after treatment etc

  • 52% burns, 31% trauma

  • validation studies, IJEE had a better agreement with MEE:

    • HBx1.2, HBx1.3, 21kcal/kg

Estimating bmr
Estimating BMR

  • Schofield equation derived using meta analysis:

    • greater power than small/ local studies

  • compiled from unstructured data set obtained for diverse reasons:

    • problems with sampling assumptions

  • accuracy approx ±15%

  • disease specific equations useful in some circumstances

Estimating bmr1
Estimating BMR

  • what about:

    • the elderly?

    • the obese?

Estimating bmr the elderly
Estimating BMR: the elderly

  • Original Schofield equations:

    • only 88 (1.2%) of subjects >60 years

    • particularly unsuitable for >75yr

    • included data on subjects from the tropics

  • Revised equations for the elderly:

    • published in the 1991 COMA (DH 1991)

    • include additional data from 2 studies; 101 Glaswegian men (60-70yr) 170 Italian men and 180 Italian women

    • excluded data collected in the tropics

Estimating bmr obesity
Estimating BMR: Obesity

  • equations (such as Schofield) are linear

  • weight increases linearly with estimated BMR

  • may overestimate in obese

Estimating bmr obesity2
Estimating BMR: Obesity

  • obese data primarily obtained from 2 groups:

    • Burmese hill dwellers

    • retired Italian military

  • there were significant differences in weight/ BMR association between groups, Italian group showed greatest difference

  • obese subjects in Schofield data may not be a statistically representative sample of the population is general

Estimating bmr obesity3
Estimating BMR: Obesity

  • recent (Horgan 2003) reassessed validity of the Schofield data to predict BMR in obese

  • conclusions:

    • BMR increases more slowly at heavier weights

    • to ignore this is to over predict energy requirements

    • any general equation for predicting BMR may be biased for some groups or populations.

Estimating bmr adjusted body weight adj
Estimating BMR: adjusted body weight (ADJ)

  • estimate of how much of the extra body weight is lean and thus metabolically active

  • 2 methods:

  • 25% adjusted weight

    = (actual body weight x 0.25) + ideal body weight

  • adjusted average weight

    = (actual body weight + ideal body weight) x 0.5

Estimating bmr adjusted body weight adj1
Estimating BMR: adjusted body weight (ADJ)

  • first reported in newsletter Q&A format

  • not validated

  • studies suggest adjusted average weight has better predictive value than 25% adjusted weight (Glynn 1998, Barak 2002)

  • no longer included in ASPEN guidelines (2002)

Estimating bmr obesity4
Estimating BMR: Obesity

  • predicting BMR is very difficult (without measuring lean body mass)

  • adequacy of specific equations? (Ireton-Jones et al., 1992; Glynn et al., 1998)

  • actual body weight + stress + activity = overestimate

  • access to indirect calorimetry is limited

Determining energy requirements in obesity
Determining energy requirements in obesity

  • non stressed patients:

    • calculate as normal and - 400-1000kcal for decrease in energy stores

  • mild to moderately stress:

    • calculate as normal

    • omission of stress and activity avoids the adverse effects of overfeeding

  • severe stress

    • might be necessary to add a stress factor to BMR

  • *monitoring essential eg blood glucose

Estimating energy requirements
Estimating energy requirements

  • The main components of energy expenditure are estimated:

    • BMR

    • Alteration in BMR due to disease process (stress factors)

    • Activity

    • DIT

Levels of evidence
Levels of evidence

1. a) Meta-analyses

b) Systematic reviews of randomised controlled trials (RCTs)

c) RCTs

2. a) Systematic reviews of case-control or cohort studies

b) Case-control or cohort studies

3. Non-analytic studies e.g. case studies

4. Expert opinion

(adapted from: Draft NICE Guidelines for Nutrition Support in Adults, 2005)

Stress factors
Stress factors

  • timing of measurements

  • over (hyperalimentation) vs. under-feeding

  • changes in therapeutic interventions

    e.g. improved wound care, anti-pyretics, sedation, control of ambient room temperature

     err towards lower end of the range and monitor

Stress factors1
Stress factors

  • unable to include a stress factor for every disease or condition

  • many measured in far from ideal circumstances

  • limited by data available

  • may choose to underfeed in certain circumstances

  • necessary to refer back to the literature

  • included a checklist of factors to look for when reviewing papers

Adverse effect of over feeding
Adverse effect of over-feeding

  • excess carbohydrate:

    • difficulties controlling blood glucose

    • increased CO2 production

    • respiratory problems in vulnerable patients (eg COPD/ ventilated)

  • swings in blood glucose increase mortality in critically ill

  • aim not to exceed the glucose oxidation rate (4-7 mg glucose/ kg/ min)

  • long term excess carbohydrate can lead to steatohepatosis or fatty liver (Elwyn DH, 1987).

Estimating energy requirements1
Estimating energy requirements

  • The main components of energy expenditure are estimated:

    • BMR

    • Alteration in BMR due to disease process

    • Activity

    • DIT

Total energy expenditure
Total energy expenditure









Activity factor
Activity factor

  • energy expended during active movement of skeletal muscle

  • approximately 20-40% of energy expenditure in free living individuals

  • depends on duration and intensity of the exercise

  • activity is less than 20% of the energy expenditure in hospitalised or institutionalised

  • NB assumes normal muscle function

Activity factor abnormal muscle function
Activity factor:abnormal muscle function combined with DIT

  • hospital patients likely to have higher activity levels:

    • abnormal neuro-muscular function e.g. brain injury, Parkinson’s, cerebral palsy, motor neurone disease, and Huntington’s chorea

    • prolonged active physiotherapy

    • effort involved in moving injured or painful limbs

Community patients
Community patients combined with DIT

  • free living individuals have higher energy expenditure due to physical activity

  • nursing home and house bound patients ? similar activity levels to hospital patients

  • for active patients in the community a PAL should be added

Estimating energy requirements2
Estimating energy requirements combined with DIT

  • The main components of energy expenditure are estimated:

    • BMR

    • Alteration in BMR due to disease process

    • Activity

    • DIT

Diet induced thermogenesis
Diet-induced thermogenesis combined with DIT

  • Continuous infusion of enteral feed and parenteral nutrition do not significantly increase REE

  • Bolus feeding increases REE by ~ 5%

  • Mixed meal increases REE ~ 10 %

  • PALs include DIT (COMA, 1991)

     guidelines include combined factor for activity and DIT

Estimating requirements sources of error
Estimating requirements: sources of error combined with DIT

  • prediction equation for BMR

  • stress factor:

    • degree of stress inaccurately assessed

    • poor evidence to support stress factor used

  • activity level inaccurately assessed or poorly understood

  • DIT varies by 10% depending on feeding method

Sources of error inaccurate weight
Sources of error: inaccurate weight combined with DIT

  • Inaccurately measured weight

    • estimated weight

    • inaccurate scales

    • patient had their feet on the floor (chair scales)

    • patient was fluid overloaded ( 20% of hospital patients)

    • amputees

Conclusions combined with DIT

  • Estimated requirements are only a starting point

    - set realistic goals of treatment for each patient

    - monitor and amend as patient’s condition changes

  • Review and criticise the literature regularly

    - be aware of gaps in the evidence

    - understand the limitations of guidelines

    - check applicability to your patients

  • Contribute to research and audit projects