Nutrition Care Process: Assessment
Nutrition Assessment
 The purpose of nutrition assessment is to collect
and interpret relevant patient/client information to
identify nutrition-related problems and their
causes
 Is the first step in the Nutrition Care Process
 Different from monitoring and evaluation where
similar or same data may be used to determine
changes in client behavior or nutrition status and
the efficacy of nutrition intervention
ADA IDNT Reference Manual, 2008, p. 8
Nutrition Assessment Involves
Critical Thinking
 Determine appropriate data to collect and
selecting valid and reliable tools
 Distinguish relevant from irrelevant data
 Select appropriate norms and standards for
comparing the data
 Organizing and categorizing the data in a
meaningful way that relates to nutrition
problems
Nutrition Assessment Is Ongoing
 Is the first step in the
Nutrition Care Process
but not an isolated
event
 A dynamic process
that evolves
throughout the NCP as
the pt’s status changes
or new information
becomes available
Nutrition Assessment
 In ADA’s draft Standards of Professional
Practice (SOPP), nutrition assessment is a
function of the registered dietitian
 A dietetic technician, registered, contributes
by collecting data, providing some
interventions, and evaluating and
monitoring patient/client response
 Assessment parameters and possible
nutrition diagnoses are listed in the IDNT
manual and pocket guide
Nutrition Assessment Data
 Data collected depends on the practice setting
 For individuals, data can come directly from
pt/client through interview, observations, and
measurement; from health care providers or
referring agencies, medical record or laboratory
tests
 For populations, data from surveys, administrative
data sets, and epidemiological and research studies
are used
ADA IDNT Reference Manual, 2008, p. 8
Categories of Nutrition Assessment Data
 Food/nutrition history
 Biochemical data,
medical tests and
procedures
 Anthropometric
measurements
 Physical examination
findings
 Client history
IDNT Reference Manual, ADA, 2008, p. 9
Food/Nutrition Histories: Food Intake
 Composition and adequacy of food and
nutrient intake, meal and snack patterns,
environmental cues to eating, food and
nutrient tolerance, and current diets and/or
food modifications
ADA IDNT Reference Manual,
2008, p. 11)
Food/Nutrition Histories: Nutrition and
Health Awareness
 Knowledge and beliefs about nutrition
recommendations, self-monitoring/
management practices, and past nutrition
counseling and education
ADA IDNT Reference Manual,
2008, p. 11)
Food/Nutrition Histories: Physical
Activity and Exercise
 Functional status, activity patterns, amount
of sedentary time (TV, phone, computer)
and exercise intensity, frequency, and
duration
ADA IDNT Reference Manual, 2008, p. 11
Food/Nutrition Histories: Food
Availability
 Food planning, purchasing, preparation
abilities and limitations, food safety
practices, food/nutrition program utilization,
and food insecurity
ADA IDNT Reference Manual, 2008, p. 11
Biochemical Data, Medical Tests and
Procedures
 Include laboratory data (e.g. electrolytes,
glucose, lipid panel
 Gastric emptying time
 Colonoscopy, CT scan or EKG results
Anthropometric Measurements
 Include height, weight, body mass index,
growth chart percentile, growth rate, and
rate of weight change
Physical Examination Findings
 Include oral health, general physical
appearance, muscle and subcutaneous fat
wasting, and affect
Client History
 Social history: socioeconomic status, social and
medical support, cultural and religious beliefs,
housing situation, and social isolation/connection
 Personal history: factors including age,
occupation, role in family, and education level
 Medical/health history includes chief nutrition
complaint, present/past illness, surgical history,
chronic disease or complication risk, family
medical history, mental/emotional health and
cognitive abilities
 Medication/supplement history: prescription and
over-the-counter drugs, herbal and dietary
supplements, and illegal drugs
IDNT Reference Manual, ADA, 2008, p. 11
Food/Nutrition History Information
Food/Nutrition History Information —
cont’d
Methods of Obtaining Intake Data
 Direct observation and nutrient analysis: can be
used only in controlled settings; doesn’t represent
usual intake; calorie counts fall into this category
 Food record or diary: prospective tool; asks client
to record or weigh food intake for a specific time
period
 Food frequency questionnaire: retrospective; asks
client to complete a survey about food intake over
a specific time period
 24-hour recall: retrospective tool; asks client about
food intake during the previous 24 hours
24-Hour Recall
Strengths
Weaknesses
Less likely to modify
dietary behavior
Memory dependent
Quick and inexpensive
Overestimates low intake
Low client burden
Underestimates high
intake
Literacy independent
High-inter-interviewer
variability
Food Records
Strengths
Weaknesses
Greater precision than
single 24-hour recall
Not memory reliant
Eating behavior may
change
Literate and numerate
dependent; requires
knowledge of portion
sizes
High client burden
Considered “actual”
intake
Food Frequency Questionnaire
Strengths
Weaknesses
Low client burden
Primarily provides qualitative
information
Quick and inexpensive
Literate and numerate dependent
Can examine specific
nutrients
Memory dependent
Considered “usual” intake Cognitively difficult since food
list not meal based
Easily standardized
Accuracy improves when
combined with other data
Direct Observation
Strengths
Weaknesses
Low client burden
Client unaware of
assessment
Not memory or literacy
dependent
High staff burden
Intrusive
Difficult to attain and
interpret
Does not represent usual
intake
Expensive
NCI Food
Frequency
Questionnaire
Food Diary
What’s wrong with this picture?
Weight Status and
Anthropometry
Anthropometry
 Involves obtaining physical
measurements of an
individual and relating them
to standards that reflect the
growth and development of
the individual
 Can be used in nutrition
assessment and evaluation
and monitoring
Height Measurement
 Standing: taken without shoes, feet flat,
heels together, legs straight
 Arm span: with arms at right angles,
distance from tip of the middle finger on the
right hand to tip of middle finger on the left;
does not change with age
 Knee height: can be used to measure stature
in those unable to stand; there are equations
to convert knee height to stature
Commonly Used Weight
Standards
 NHANES (%ile or IBW or DBW)
 Hamwi (% IBW or DBW)
 BMI
 % ABW/UBW (weight loss)
Hamwi
 Population: small group of people with
diabetes; desirable weight related to best
blood glucose control
 Advantage: Portable and easy to use
 Disadvantage: no evidence this is predictive
of morbidity/mortality in general or in
hospitalized population
Hamwi GJ. Changing dietary concepts. In: Donowski TS, ed. Diabetes
Mellitus: Diagnosis and Treatment. New York, NY: American Diabetes
Association, 1964;73-78.
Metropolitan Height/Weight Tables
 Population: 4.2 million mostly Caucasian
policy holders; upper socio-economic class.
 Advantages: desirable wt associated with
lowest morbidity/mortality in this population
 Disadvantages: may not apply to different
socio-economic classes; requires frame size
measurement and reference to a table; data
gathering methods poorly controlled; data
collected 1954-1972
NHANES DATA
 Population: U.S. Population over time;
generally percentiles <5 and >95 are
considered to be at risk. 50th percentile is
median
 Advantages: more rigorous data gathering
methodology; can be normed to age, sex,
race, socio-economic class etc.
 Disadvantages: Americans are growing
larger; median is not necessarily a healthy
weight
NIH BMI Classification
 Population: NHANES data has been
collected in general population; many RCT
use BMI to describe height-weight
relationships
 Advantage: Strong evidence from RCT and
epidemiological studies demonstrating
relationship between BMI classification
and risk for morbidity and mortality
 Disadvantage: Paucity of evidence showing
BMI predicts risk in an acute care
population
Calculating BMI (Quetelet Index)
 BMI = Weight (kg) divided by (height [m]2)
OR
 BMI = (Weight in Pounds
(Ht/in) x (Ht/in)
x 703
“Ideal” Body Weight vs “Usual”
Body Weight
 Ideal weight for height (IBW) from
standards like NHANES and Metropolitan
ht/wt tables (and Hamwi) is no longer
used—Hammond in K&M, p. 400
 However, IBW IS often used, whether
evidence-based or not
 Usual body weight is more useful in those
who are ill
What is “Desirable” Weight in Men?
Wt in Kg
Ht
(in)
62
64
66
68
70
72
Hamwi 1983 Metro
Ht/Wt
54
61
59
64
65
66
70
68
75
71
81
74
NHANES
I and II
68
71
75
78
81
84
BMI 20-25
(NIH)
50-62
53-66
56-71
60-75
63-79
67-84
Weight Status as a Predictor of
Morbidity and Mortality
 In young to middle aged adults, morbidity/
mortality is highest in the highest quintile of
BMI
 In the elderly, morbidity/mortality is highest
in the lowest quintile of BMI
 In most populations, there is a U-shaped
relationship between mortality and BMI
Weight Status as a Predictor of
Morbidity and Mortality
 McClave et al found that “marasmic PCM”
defined as <90% “IBW” was not predictive
of poor outcome in acute care pts receiving
TPN (JPEN16:337. 1002)
 Weight loss and unintentional weight loss is
strongly predictive of morbidity/mortality,
particularly in the elderly. It is unclear
whether this is a nutritional issue
Evaluation of Weight Loss
 Significant weight loss: 5% loss in 1 month;
7.5% loss in 3 months; 10% loss in 6
months
 Severe weight loss: >5% loss in 1 month;
7.5% loss in 3 months, >10% weight loss in
6 months
Blackburn GL et al. Nutritional and metabolic assessment of the
hospitalized patient. J Parent Ent Nutr 1:11, 1977
Evaluation of % Usual Body Wt
 85-90% of usual weight: mild malnutrition
 75-84% of usual weight: moderate
malnutrition
 <74% of usual weight: severe malnutrition
Buchman AL: Handbook of nutritional support, Baltimore, 1997, Williams
& Wilkins, cited in Hammond in Krause, p. 434
Weight Issues in Clinical Settings
 Accuracy and reproducibility of weights taken on
different scales and by different personnel
 Weights of critically ill patients may be
unavailable on admission; sometimes heights are
not measured
 Fluid status
 Accuracy of weight history data from patients and
family members
 Confounding factors (wheelchairs, splints, casts,
clothing, amputations)
 Question of dosing weight: actual, usual, ideal,
adjusted???
Anthropometrics in Pediatrics
 Recumbent length measurements used for children
younger than 2 or 3 years of age; recorded on
birth-to-36 month growth grids
 Standing heights of children age 2 or 3 should be
recorded on the 2-20 years growth grids
 Rate of length or height gain reflects long-term
nutritional adequacy
 Head circumference: used to evaluate growth in
children <3 years of age; usually detects
nonnutritional abnormalities
Weight in Pediatrics
 A more sensitive measure of nutritional
adequacy than height, and reflects recent
nutritional intake
 Provides crude evaluation of fat and muscle
stores
Measurement of the Length of
an Infant
Body Composition: Skinfold
Thickness (subcutaneous fat)
 Validity depends on measurement
technique and repetition over time
 Changes take 3 to 4 weeks
 Accuracy decreases with increasing
obesity
 Skinfold sites most reflective of body
fatness are over the triceps and the biceps,
below the scapula, suprailiac, and upper
thigh
Body Composition:
Circumference measurements
 Waist circumference: smallest area below
the ribcage and above the umbilicus;
measurements >40 for men and >35 for
women are risk factors for disease
 Mid arm circumference (MAC) in
combination with TSF can determine arm
muscle area (lean body mass)
Fatfold Measurements
Skinfold Calipers Measure Thickness of
Subcutaneous Fat in Millimeters
Courtesy Dorice Czajika-Narins, PhD
Other Methods of Body
Composition
 Underwater weighing
 Total body potassium
 Neutron activation analysis
 BIA: fat free mass and fat mass
 CT: subcutaneous and intraabdominal fat
 MRI: size of skeleton and internal organs;
abdominal fat
 DEXA: dual-energy x-ray absorptiometry;
bone mineral density and fat and boneless
lean tissue
Visceral Protein Status
Evaluation of Visceral Protein Status
 Affected by numerous other factors, including
hydration status, chronic illness, acute phase
response
 May have low sensitivity/specificity
 However, low serum albumin and acute phase
proteins are associated with increased
complications and length of stay in
hospitalized patients; probably an index of
severity of illness
Preoperative Albumin as a Predictor
of Risk in Elective Surgery Patients
 Retrospective review of 520 patients with
preoperative serum albumin measurements
 Preoperative albumin correlated inversely
with complications, length of stay,
postoperative stay, ICU stay, mortality, and
resumption of oral intake
 S. albumin levels <3.2 were predictive of
risk
– Kudsk et al, JPEN, 2003
Role of Visceral Protein Measurement in
Nutrition Screening and Assessment
 Low values in critically ill patients a
measure of severity of illness
 Is a valuable predictor of
morbidity/mortality in hospitalized and LTC
patients
 Can be used to identify elective surgery
patients who could benefit from nutrition
intervention
 Sequential measurements may reflect
changes/improvement of nutritional status
Nutrition-Focused Physical
Examination
 Physical signs: using inspection, palpation,
percussion, auscultation
 Immune function: skin testing and TLC; not
always useful for hospitalized patients
 Handgrip dynamometry: measures muscle
function; useful for serial measurements
 Biochemical analysis
Classifying Malnutrition
(determination of ICD-9 codes)
 Body weight
 Body fat
 Somatic and visceral protein stores
 Laboratory values
More Research Needed
 More data needed to evaluate sensitivity/
specificity of nursing screening systems
 More research needed to validate nutrition
assessment parameters in clinical settings
 More data needed to evaluate whether
nutrition intervention is helpful in patients
identified to us
 The Joint Commission requirements for
nutrition screening and assessment are critical
in keeping nutrition care front of mind among
nurses and administrators
Estimation of
Energy and Protein Needs
Harris-Benedict Equation
 Monograph in 1919 described results of indirect
calorimetry on 239 healthy men and women of
varying body sizes up to a BMI of 56 in men and
40 in women
 Predicts BMR (RMR) with systematic
overestimation of 5-15% (1)
 Random error greater in women than in men
 Stress and activity factors must be applied to
estimate total energy expenditure
1. Daly JM, Helmsfield SB, Head CA, et al. Human energy requirements : overestimation by
widely-used predictive equations. Am J. Clin Nutr 1985;42:1170-1174.
Harris Benedict Equation (HBE)
 Men = 66.47 + (13.75 x wt in kg) + (5 x ht
in cm) – (6.76 x age)
 Women = 655.1 + (9.56 x wt in kg) + (1.85
x ht in cm) – (4.68 x age)
Stress Factors for Use with HBE
 Elective surgery
1.0 – 1.1 X BEE
 Multiple bone fx
1.1 – 1.3 X BEE
 Cancer
1.1 – 1.45 X BEE
 Fever
1.2 X BEE per 1C >37C
 Sepsis
1.2 – 1.4 X BEE
 Severe infection
1.2 – 1.6 X BEE
 Closed head injury
1.3 X BEE
 Infection with trauma 1.3 – 1.55 X BEE
Elwyn DH et al. Surg Clin N Am 1981;61:545-556; Souba WB et al. In Shils ME.
Modern Nutrition in Health and Disease, 9th ed. Baltimore, MD: Williams & Wilkins,
1999; Sax HC et al. In The ASPEN Nutrition Support Practice Manual Silver Springs,
MD: ASPEN, 1998, 1-5. Cited in ADA Manual of Clinical Dietetics, 6th edition.
Activity Factors for Use with REE
 Hospitalized and critical illness
 Chair or Bed-Bound
 Seated work with little movement and




little or no leisure activity
Seated work with requirement to move
but little strenuous leisure activity
Standing work
Strenuous work or highly active
leisure activity
30-60 minutes strenuous leisure
activity 4-5 times a week
1.05-1.1
1.2 x BEE
1.4-1.5 x BEE
1.6-1.7 x BEE
1.8-1.9 x BEE
2.0-2.4 x BEE
AF + .3
Shetty PS, Henry CJK, Black AE, et a. Energy requirements in adults: an update of
basal metabolic rate (BMR) and physical activity levels (PALs). Eur J. Clin Nutr
1996;50:S11-S23, Frankenfeld et al Crit Car Med 22;1796:1994
Dosing Weight
 The weight on which nutritional
calculations are based
 Must consider
– Fluid status
– Weight vs standard (IBW? SBW? Adjusted
wt?)
Adjusted Body Weight
 In common use for obese patients
 Rationale is that fat is less metabolically active
than lean tissue; thus using actual body weight in
an obese person will overpredict energy needs
 However, studies have shown that in very
overweight persons, calculating HBE using the
adjusted wt tends to make calculations less
accurate; underestimating total energy needs
Adjusted Body Weight
 [(ABW – IBW) * .25] + IBW
Alternative equation:
 [(ABW – IBW) * .50] + IBW
– Barak N, et al. Evaluation of stress factors and body weight
adjustments currently used to estimate energy expenditure in
hospitalized patients. JPEN 26:231-238, 2001.
What Weight Should We Use to
Calculate HBE in Obese Patients?
 Use Average of IBW/AW. Glynn CC, et al. JPEN
1999;23:147-154. Barak N at al. Evaluation of stress factors and body
weight adjustments currently used to estimate energy expenditure in
hospitalized patients. JPEN 26:231-238, 2002.
 Use actual weight in the HBE equation. Or
use obesity-specific equations. Ireton-Jones CS,
Turner WW. Actual or ideal body weight: which should be used to
predict energy expenditure? JADA 1991;91:193-195.
 Use the Mifflin-St. Jeor equation and actual
weight for healthy patients (Frankenfeld et al JADA
2003;103:1152-1159)
What Weight Should We Use to
Calculate HBE in Obese Patients?
 ADA Pocket Guide to Nutritional Assessment.
Does not include adjusted body weight. Chicago: The
American Dietetic Association, 2004.
 ADA Nutrition Care Manual. Does not use
adjusted body weight. Online at www.nutritioncaremanual.org
 ADA Evidence Library cites maximal
underestimation of 42% to overestimation of 25%
when using HBE and adjusted body weight
REE Estimates Using Various
Equations Healthy Non Obese Pts
Mifflin-St. Jeor
Harris-Benedict
Actual BW
Owen
82% of estimates are accurate;
maximal underestimation 18%;
overestimation 15%
45-81% of estimates are accurate;
errors tend to be overestimates;
underestimation 23%; over 42%
73% of estimates are accurate;
errors tend to be underestimates;
max underestimation 24%;
overestimation 28%
REE Estimates Using Various
Equations Healthy Obese Pts
Mifflin-St.
Jeor
70% of estimates are accurate; errors
tend to be underestimates; max
underestimations 20%; over 15%
Harris38-64% of estimates are accurate;
Benedict
errors tend to be overestimates; max
Actual BW
underestimation 35%; over 57%
Harris26% of estimations are accurate;
Benedict
errors tend to be underestimates
Adjusted BW Max underestimation 42% to
overestimation 25%
ADA EAL NCP accessed 12-07
Recommendations for Predicting
RMR in Critically Ill Pts
 HBE should not be used to predict RMR in
critically ill patients (Grade I)
 Ireton-Jones 1997 should not be used to
predict RMR in critically ill patients (Grade
II)
 Ireton-Jones 1992 may be used to predict
RMR in critically ill pts but errors will
occur. (Grade III)
– ADA Evidence Analysis Library, 12-07
Ireton-Jones 1992 Equations
Spontaneously-breathing patients:
 IJEE (s) = 629 – 11(A) + 25(W) – 609 (O)
Ventilator-dependent patients:
 IJEE (v) = 1925 – 10(A) + 5(W) + 281 (S) +
292 (T) + 851 (B)
Frankenfield D, Smith JS, Cooney RN. Validation of 2
approaches to predicting resting metabolic rate in critically ill
patients. JPEN 2004;28(4):259-64.
Ireton-Jones Equations
Where:
 A = age in years
 W = weight (kg)
 O = presence of obesity >30% above IBW (0 =
absent, 1 = present)
 G = gender (female = 0, male = 1)
 T = diagnosis of trauma (absent = 0, present = 1)
 B = diagnosis of burn (absent = 0, present = 1)
 EEE = estimated energy expenditure
Advantages of Ireton-Jones
 Validated in hospitalized patients with
varying conditions (pancreatitis, diabetes,
trauma, burns)
 No need to apply stress factor
 Data are easily obtainable
Mifflin-St. Jeor
 Derived from data on 498 healthy subjects
(females=247, males=251) ages 19-78 years
 Included normal weight (n=264) and obese
(n=234) subjects
 REE (males) = 10 x wt (kg) + 6.25 x height
(cm) – 5 x age (years) + 5
 REE (females) = 10 x weight (kg) + 6.25 x
height (cm) – 5 x age (years) - 161
Mifflin-St. Jeor
 Best validated of predictive equations in
estimating REE in healthy patients
 Like HBE, studies were done in healthy
patients, so stress factors must be applied if
used in medical or surgical patients
Comparison of Prediction Equations with
Indirect Calorimetery in Critically Ill Patients
 Compared REE measurements by indirect
calorimetry with standard predictive equations
(Harris-Benedict, Ireton-Jones, Fusco,
Frankenfeld)
 None of the REEs predicted by the equations
correlated well with indirect calorimetry
 Mean REEs predicted by Ireton-Jones and
Frankenfield were not significantly different, but
had low correlation coefficients (r=.26 and r=.39,
respectively), meaning they predicted poorly in
individual patients
Flancbaum L, Choban PS, Sambucco S, Verducci J, Burge JC. Comparison of
indirect calorimetry, the Fick method, and prediction equations in estimating the
energy requirements of critically ill patients. Am J Clin Nutr 1999;69:461-6.
Validation of Equations for RMR
in Obese and Non-obese People
 Subjects: 130 non-hospitalized volunteers grouped
by degree of obesity (BMI 18.8 to 96.8)
 Resting metabolic rate determined using indirect
calorimetry was compared with Harris-Benedict,
Harris-Benedict with adjusted body wt in obese
persons, Mifflin-St. Jeor, and Owen equations
 Main outcome was % of subjects whose calculated
metabolic rate differed more than 10% from
measured values
Frankenfield DC, Rose WA, Smith JS, Cooney RN. Validation of several established
equations for resting metabolic rate in obese and nonobese people. J Am Diet Assoc
2003;103:1152-1159
Results
 Calculated RMR was 10% different from
measured in 22% of subjects using Mifflin;
33% using Harris-Benedict; 35% using the
Owen equation; and 74% in obese subjects
using adjusted body wt (vs 36% in obese
subjects using actual wt)
 Mifflin-St. Jeor was accurate in the largest
percentage of non-obese and obese healthy
individuals
Frankenfield DC, Rose WA, Smith JS, Cooney RN. Validation of several established
equations for resting metabolic rate in obese and nonobese people. J Am Diet Assoc
2003;103:1152-1159
Penn State Equation
 RMR = RMR (healthy) (0.85) + Ve(33) +
Tmax(175) – 6433
 Where RMR = RMR calculated using Harris
Benedict equation and actual body weight, Ve is
minute ventilation in L/min, and Tmax is
maximum body temperature in the previous 24
hours in degrees Centigrade
 ADVANTAGE: does not require the application of
stress factors; usually does not require activity
factor unless the patient is seizing or unusually
active; found to be highly correlated with MEE in
validation studies
– Frankenfeld DC et al. Validation of two approaches to predicting resting metabolic
rate in critically ill patients. J Parent Ent Nutr 2004;28:259.
In-Class Use of Predictive Equations
for EEE and REE
 Use actual body weight in calculations in
class
 Use Mifflin-St. Jeor plus activity factors, if
applicable, in ambulatory patients
 Use Harris-Benedict with actual weight in
hospitalized, stressed patients. Apply stress
factors and very small activity factor (1.05
to 1.1)
– ADA Nutrition Care Manual, www.nutritioncaremanual.org, accessed 1-06
In-Class Use of Predictive Equations
for EEE and REE
 Use Ireton-Jones 1992 in patients with
burns and trauma where Penn State data not
available
 Use Penn State equation in the ICU where
minute ventilation and temperature are
available
Indirect Calorimetry
 Better estimate in critically ill
hypermetabolic patient
 The “gold standard” in estimating energy
needs in critical care
 Can be used in both mechanically ventilated
and spontaneously breathing patients
(ventilated patients most accurate)
 Equipment is expensive and not readily
available in many facilities
Indirect Calorimetry
 Requires appropriate calibration of
equipment, attainment of a steady state for
measurement, and appropriate timing of
measurement
 Requires interpretation by trained clinician
 Inaccurate in patients requiring inspired
oxygen (FiO2>60%), and with air leaks via
the entrotracheal tube cuff, chest tubes or
bronchopleural fistula
 RQ should be within physiological range of
.67 to 1.3
Indications for Indirect Calorimetry
 Patients with altered body composition
(underweight, obese, limb amputation, peripheral
edema, ascites)
 Difficulty weaning from mechanical ventilation
 Patients s/p organ transplant
 Patients with sepsis or hypercatabolic states
(pancreatitis, trauma, burns, ARDS)
 Failure to respond to standard nutrition support
Malone AM. Methods of assessing energy expenditure in the intensive
care unit. Nutr Clin Pract 17:21-28, 2002.
Estimation of Protein Needs
 Adult maintenance:
0.8-1 g/kg
 Older adults: 1 g/kg
 Predialysis: 0.6-0.8
based on GFR
 Hemodialysis: 1.1-1.4
g/kg
 PD: 1.2-1.5 g/kg
 Short bowel
syndrome: 1.5-2 g/kg
 Cancer 1-1.2 g/kg
 Cancer cachexia 1.2-
1.5 g/kg
 Obesity, stressed: 1.52 g/kg IBW
 Pregnancy: + 10 g/day
 Critical illness: 1.5-2
g/kg
 Major Surgery: 1.0-1.5
g/kg (Cresci, p. 101)
See Chart in ADA Pocket Guide to Nutrition Assessment, p. 159
Estimation of Protein Needs
 Use actual weight in estimating protein
needs
 Use lower end of range in obese patients
(BMI>30)
Clinical Standards of Care
 Providers in a community or health care
organization should develop evidence-based
standards for care delivery
 This promotes consistency among providers
and improved quality of care
 Review University of Akron Nutritional
Standards of Care