NUT 112 Midterm 1

Nutriture

Too specific to know
A body's nutritional condition

Nutritional assessment

Collection and interpretation of information on:
1. Tissue nutrient reserves
2. Dietary factors affecting these reserves
3. Health and functional outcomes in relation to these reserves

Direct measures of nutritional assessment

1. Anthropometric and body composition tests (physical tests)
2. Biochemical (blood tests)
3. Clinical tests (bilateral edema tests)

Indirect measures of nutritional assesment

1. Dietary intake
2. Energy expenditure measurements

Why measure nutrient status

1. Measure health and risk of diseases
2. Diagnose diseases
3. Product development
4. Identify people who may need an intervention

Biomarker assessment

Test for distinct biological molecules in blood /body fluid/tissues that is a sign of a process/event/condition

Biomarker

A characteristic which can be objectively measured and evaluated as indicators of normal biological processes, pathogenic processes, and pharmacologic responses

Measuring biomarkers can determine...

1. *Exposure*: Determining nutrient condition in the body
2. *Status*: explaining how an individual's nutrient status compares to standard nutrient status
3. *Function*: identify role and interactions of specific nutritients
4. *Effect*: clarifying the direct and indirect affects of a nutrient or lack of nutrients

Dietary assessment

Observations or reports of food intake, conversion to nutrient intake, and comparison with recommended levels of consumption

Examples of dietary assessments

Food records, 24 hr dietary recall, food frequency questionnaire

Energy expenditure assessment

Measured or reported assessments of calories expended throughout the day. May also include measures of physical activity that are used to estimated calories expended during activity.

Examples of energy expenditure assessments

Direct calorimetry, indirect calorimetry, physical activity logs, accelerometers, heart rate monitors, or pedometers

Clinical assessment

Medical history and physical examination used to detect signs and symptoms of deficiency or excess. Includes the examination of the morphology of cells or the physical appearance of tissues whose integrity is affected by nutritional deficiency or excess

Examples of clinical assessments

Physical examinations of the surface of cornea (Vitamin A deficiency), Palpation of thyroid gland (iodine deficiency)

Nutritional screening

The process of identifying characteristics known to be associated with nutrition problems in order to identify those who are malnourished or at risk.

Purposes of nutritional screening (2)

1. Identify individuals for intervention
2. Calculate the prevalence of deficiency or excess in a population

How to evaluate nutritional screenings

Evaluate using cutoffs--\> cutoffs based on the relationship between nutritional assessment indices and low body stores, functional impairment, or clinical signs of deficiency

Progression to deficiency

1. Causes (Environmental conditions, reduced intake, malabsorption, excretion, increased requirements)
2. Adaption (Depletion of stores, metabolic alterations)
3. Consequences (Reduced growth/wasting, clinical changes)

Progression to excess

1. Causes (Environmental conditions, increased intake, reduced physical activity, reduced requirements)
2. Adaption (obesity, metabolic alterations)
3. Consequences (Clinical changes - obesity, diabetes, etc.)

Measurements of validity

1. Precision
2. Accuracy
3. Sensitivity
4. Specificity
5. Predicability

Types of Errors

Random error
Systematic error

Random errors

Errors that are due to chance alone and lead to measurements that are imprecise (does not affect accuracy) --\> increases standard deviation without affecting the mean

Systematic errors

Errors that cause the results to deviate from the true value in a consistent direction, reducing the accuracy of the measure (not the precision) --\> alters the mean/median but no affect on the standard deviation

Accuracy

How close a measurement is to the true value

--\> affected by systematic errors of bias of observer/instrument

Precision

The extent to which repeated measures provide similar results

--\> improved through quality control, training and standardizing protocols, and replicating measures

Coefficient of variation

Indicator of precision

CV\= SD/Mean x 100

Validity

The degree to which a method measures what you want it to measure

For a measure to be valid it must be

Accurate and precise --\> validity reduced by errors

Validity of nutritional screening

We cannot measure nutrient content directly (too expensive/invasive) --\> we use indicators of nutritional status to measure --\> the validity of thee test depend on how sensitive and specific the indicators are

Sensitivity

The proportion of *true cases* of disease which are *correctly classified* as such

Sensitivity equation

TP / (TP + FN)

Reasons for selecting a test with high sensitivity

If the disease has severe complications or high risk of mortality
if the disease has a treatment that is benign and/or low cost

*You'd rather be safe than sorry

Sensitivity increases or decreases with a lower cutoff value?

Increases

Lower cutoff\= easier to be diagnosed\= more people will be diagnosed \= more treatment

Specificity

The proportion of *non-cases* of disease which are *correctly classified* as such

Specificity equation

TN / (TN + FP)

Reasons for selecting a test with high specificity

Do not wish to treat people unnecessarily
if the disease has a treatment that is expensive or associated with adverse side effects

*Treatment is risky --\> don't want to subject everyone to it

Specificity increases or decreases with a lower cutoff value?

Decreases

Lower cutoff\= easier to be diagnosed\= more people will be diagnosed \= less people diagnosed as non-cases \= get treatment even if they don't need it

How are sensitivity and specificity related

Inversely (increasing one decreases the other)

Positive predictive value (PPV)

The likelihood that a test correctly predicts the present of malnutrition or disease

Equation for PPV

TP / (TP + FP)

Negative predictive value (NPV)

The likelihood that a test correctly predicts the absence of malnutrition or disease

Equation for NPV

TN / (TN + FN)

Anthropometry

Measurement of body size, weight and proportions (ex: stature, weight, MUAC, etc.)

Use anthropometry to assess... (3)

1. Physical growth
2. Nutritional status
3. Body composition

Pros vs cons of anthropometry

*Pros:*
1. Techniques are simple, safe, inexpensive, and easy to train
2. Equipment is relatively inexpensive and portable

*Cons:*
1. Not specific to a particular deficiency or excess intaake
2. Not sensitive to recent changes
3. Must be interpreted in context of a reference population and/or knowledge of individual's history

Wasting

*Low weight‐for‐length or weight‐for‐height*
- strongly associated with increased risk of mortality and infectious illness.
- Suggests a severe, or acute problem.

Stunting

*Low height‐for‐age*
-Associated with increased risk of infectious illness, higher risk of mortality, poor cognitive development, low school performance, lower earnings among adults.
-Suggests a long‐term, chronic problem.

Overweight

*High weight‐ or BMI‐for‐age*
- Associated with greater risk of obesity in later life, increased risk of diabetes and other chronic disease

How do children grow?

In spurts during their sleep

Where does growth occur?

Growth plates in the long bones

Nutritional deficiencies that limit growth (7)

1. Vitamin D
2. Calcium
3. Zinc
4. Iodine
5. Protein
6. Energy
7. Excess nutrients

Health conditions that limit growth (6)

1. Frequent or chronic infections (esp. diarrheal disease)
2. Malabsorption conditions
3. Stress
4. Immune function
5. Inflammation
6. Growth hormone production

Stature

The measure of the distance from the crown of the head to the heel, either standing or lying down

How to measure stature of children

*Recumbent length:*

The Frankfort Plane

Placement of the head so that the objects line of sight is perpendicular to the base of the board

Weight

Measures total body mass of all body compartments (fat, bone, body water, muscle)

Head circumference

With head in a frankfort plane, measure just above the supraorbital ridges and over part of the occiput

--\> An indicator of brain size and development in infants
--\>Less prone to measurement errors than recumbent length

Mid-Upper Arm Circumference (MUAC)

Measured at the midpoint between the acromion process of scapuls and the ocecranon process

--\> Reflects the size of the muscle, adipose, and bone tissue.
--\> Low arm circumference may reflect wasting malnutrition

Random errors in anthropometry

1. Inconsistent measurement techniques
2. Instrument precision
3. Movement artifacts/subject positioning
4. Variations in the stomach/bladder/bowel contents
5. Prandial (right after a meal) variations

Systematic errors in anthropometry

1. Improper measurement technique
2. Equipment bias
3. Diurnal (different times of the day) variation

Anthropometric indices

Combinations of two measurements of body size or a measurement of body size and age--\> can be expressed as percentiles, percent of median in relation to reference data, or as z‐scores

Common anthropometric indices

1. BMI (only one that is used for both adults and children)
2. Weight-for-age (only for children)
3. Weight-for-length (only for children)
4. Height-for-age (only for children)
5. BMI-for-age (only for children)

Percentiles

Rank the position of an individual on a particular reference distribution.

BMI-for-age cutoff for *obese*

≥95th percentile

BMI-for-age cutoff for *overweight*

≥85th and

Weight-for-height/length cutoff for *wasting*

Height/length-for-age cutoff for *stunting*

Size vs Growth

*Size*
- Product of prior nutritional experience
- Doesn't reflect recent events
-Static measurement

*Growth*
- Changes in body size during an interval of time
- Reflects nutritional conditions during that time
- Requires measurement at more than one point in time (dynamic)

Growth velocity

Change in weight or height per unit time

Weight velocity \= (w2 ‐ w1) / (t2 ‐ t1)

Height velocity \= (h2 ‐ h1) / (t2 ‐ t1)

Growth charts

-Separate for boys and girls
-Two types: CDC charts and WHO charts

Most--\>Least sensitive anthropometric indicators of acute change in nutritional status

1. Weight velocity (most)
2. Weight-for-length
3. Arm circumference
4. Skinfold thickness
5. Weight-for-age
6. Length-for-age (least)

Growth Reference

- Data on the characteristics of a well defined population
- Indicate "what is", not necessarily what "should be"
- CDC growth reference

Growth standard

- Data on the characteristics of a selected population
- Indicate "what should be", not necessarily "what is"
- Implies something desirable, thus requiring a value judgment
- WHO growth standards

CDC Growth Reference

-Growth charts for children 0-20 yrs
- Data from NHES and NHANES (1963‐1994) in the USA, published in 2000
- 5 cross‐sectional rounds of data collection over 30 years
- Data from newer NHANES was excluded for older children because of growing
obesity epidemic
• Contain info on breast fed vs non‐breast fed infants

WHO Growth Standards

- Growth charts for children 0 - 5 years - Data collected in 6 countries, published in 2006
- Based on "prescriptive" feeding practices and risk factor (Exclusively breastfed 0‐4 mo, complementary food introduced at 4‐6 mo, continued breastfeeding \> 12 mo, all mothers were non‐smoking, all families had good access to health care)
• Longitudinal data collected on children from birth to 2 years and cross‐sectional data collected on children from 2 to 5 years

WHO growth chart data is collected from?

1. Norway
2. Brazil
3. Ghana
4. India
5. Omen
6. USA

Which chart to use for children in USA 0-2, 2-5, and 5-20 years old?

0-2 y: WHO
2-5 y: CDC
5-20 y: CDC

Which chart to use for children outside of the USA 0-2, 2-5, and 5-20 years old?

0-2 y: WHO
2-5 y: WHO
5-20 y: WHO or country specific charts

Z-Score

Express an anthropometric value as the number of standard deviations (or Z‐scores) below or above the reference median

Z-Score Equation

Z-Score\= actual - expected / SD of expected

Stunting cutoffs (z-scores)

Normal height: \>-1
Mildly stunted: -2 to -1
Moderately stunted: -3 to -2
Severely stunted: < -3

Underweight cutoffs (z-scores)

Normal weight: \>-1
Mildly underweight: -2 to -1
Moderately underweight: -3 to -2
Severely underweight: < -3

Wasting cutoffs (z-score)

Normal: \>-1
Mildly wasted: -2 to -1
Moderately wasted: -3 to -2
Severely wasted: < -3

MUAC cutoffs

Normal: \>12.5 cm
Moderately wasting: 11.5-12.5 cm
Severe wasting: < 11.5cm

Marasmus

Severe wasting --\> Bones, ribs, spine protrude, loose baggy skin

Kwashiorkor

Severe malnutrition--\> Bilateral pitting edema, protruded belly, scaly skin, thin or brittle reddish hair, loss of hair, loss of appetite, irritability

Malnutrition risks in children

- 1.6 times the risk of death compared to children of normal weight‐for‐length
-Most of this risk is due to deaths from infectious causes, such as respiratory infections or diarrhea

Signs of severe acute malnutrition in children

- Weight‐for‐height z‐score

Factors attributing to Marasmus or Kwashiorkor

- Acute food shortage, such as in famine, extreme drought, severe food insecurity
- Persistent or severe diarrhea
- Other infections or chronic diseases, such as HIV, tuberculosis, or cancer

How many children are affected by malnutrition (globally)

\>156 million children

Famine still threatens which 5 countries

1. Yemen
2. Ethiopia
3. South Sudan
4. Nigeria
5. Somalia

5 major components of body weight

1. Extracellular water
2. Intracellular water
3. Minerals
4. Proteins
5. Fat

When major components are too low...

Low minerals: osteoporosis, osteopenia, rickets
Low protein: sarcopenia, wasting, cachexia
Low fat: wasting cachexia

When major components are too high...

High extracellular water: edema
High fat: obesity

Fat Mass vs Fat-Free Mass

*Fat Free Mass (FFM)*: measures all residual, lipid‐free tissues and extra cellular materials (water, muscle, bone, connective tissues, and internal organs)

*Fat Mass*: measures the sum of all the adipose tissue depots

Obesity

Abnormally elevated adiposity

Body Mass Index

A measure of weight in relation to height
that is used to screen for risk of obesity

BMI \= weight (kg) / height (m)^2

BMI cutoffs for adults

Underweight < 18.5

Normal 18.5 ‐24.9

Overweight 25 - 29.9

Obese≥ 30.0

BMI cutoffs for classes of obesity

Class I Obese 30 ‐35

Class II Obese 35-40

Class III Obese (morbid obesity) \>40

Waist circumference

- Measures of central obesity
- Highly correlated to BMI, percent body fat, subcutaneous and intra‐
abdominal fat
- A stronger predictor of diabetes risk than BMI