Methods To Assess Nutritional Status And Body Composition PDF

Methods to Assess NUT 602 Nutritional Status FALL 2024 & Body Composition  2 Outline Anthropometric Muscle mass and Nutritional status measures muscle strength ...

Methods to Assess NUT 602 Nutritional Status FALL 2024 & Body Composition  2 Outline Anthropometric Muscle mass and Nutritional status measures muscle strength  3 Components of Total Body Mass  4 Anthropometric Measures Height & Weight ➔ BMI Waist & Hip Circumference Skinfold Thickness Mid-Upper-Arm Circumference Mid-Upper-Arm Muscle Area Calf & Thigh Circumference Novel Markers  5 Body Weight Changes in hydration, recency r=0.96 for repeated of food intake & intended Among the most precise assessments at 1 year among weight change increase error biologic measurements, even adult women: first value based more than technical aspects with simple and imperfect on self-report; second value of weighing ➔ repeated conditions based on measurement using measurements over a period a bathroom-type scale of months  6 Height & Weight: Reported vs. Measured Tendency to underreport weight & overreport height (slight) ➔ BMI will be biased downward ➔ Slight systematic error Adults in NHANES III: mean self-reported BMI was lower than technician-measured BMI (25.07 vs. 25.52 kg/m2): underreporting of weight (-0.56 kg, 95% CI: -0.71, -0.41) & overreporting of height (0.76 cm, 95% CI: 0.64, 0.88) (McAdams, Van Dam, and Hu, 2007) Correlations between self-reported & measured BMI values were very high (r=0.95 for whites, 0.93 for blacks, and 0.90 for Mexican-Americans) Self-reported & measured BMI values were equally correlated with FBG (r=0.43), HDL-C (r=-0.53), and SBP (r=0.54)  7 Height & Weight: Reported vs. Measured  8 Height & Weight: Reported vs. Measured  9 Effect on BMI The BMI of a woman with a Measured Reported Height & Height & weight of 50 kg and a height of Weight Weight 1.65 m, would differ by 2.36% (95% CI 2.07–2.58%) if measured using self-reported data (Seijo et al) H=165 cm H = 165 +0.36 W = 55 kg W = 55 – 0.94 The difference between the two BMIs in this example is 2.24% BMI = 20.20 BMI = 19.75  10 BMI = Measure of Body Fatness Ideal 1. Accurate in assessing the amount of body fat measure 2. Precise with small measurement error of body 3. Predict risks of health consequences fatness 4. Possible to develop cut-points to separate individuals into groups of excess adiposity-related health risks 5. Accessible (simple, cheap, easy to use) 6. Acceptable to be used in epidemiologic studies  11 BMI = Measure of Body Fatness Strengths Limitations Associated with height in Has most of the features children Biologic differences Cheap, easily accessed between ethnic groups Low sensitivity compared Strong association with with obesity classification body fat and health risks based on %Body Fat & novel markers  12 BMI in Children  WHO growth standards to monitor growth for infants and children aged 0 to 5 years  CDC growth charts for children aged 5 years and older https://www.cdc.gov/growthcharts/who_charts.htm  13 BMI in Asian Populations  Different BMI cut-points recommended for some Asian and Pacific populations  2002 WHO Expert Consultation:  Proportion of Asian people with a high risk of T2D & CVD is substantial at BMI30 kg/m2; HR 0.85; 95% CI 0.64–1.14) NS associated with mortality BMI 25–35 kg/m2 (23.8–25.9%): lowest absolute rates of death at 10 years FU Beleigoli et al., 2012, plos one  18 BMI in Older Adults  19 Waist & Hip Circumference WC valid measure for identifying central adiposity Predictor of risk for CVD and T2D Different cut-offs or indices Ethnic groups for which WC may reflect more body fat at a BMI level ➔ Asians have higher % body fat at lower BMIs Waist & Hip Circumference 20  21 Skinfold Thickness  Measurements based on Strengths Limitations an assumption that subcutaneous fat is ~50% Inexpensive Training of personnel of total body fat Easy to measure Type of calipers  Indirectly predict % BF Appropriate selection of through population- equation specific (gender-specific, Not all fat is accessible to the calipers (intraabdominal/ age-specific) equations intramuscular) Distribution of subcutaneous fat varies over the body  22 Mid-Upper-Arm Muscle Area MAMA determined from MUAC & Triceps Skinfold Thickness Evaluation of overall muscle mass Midarm muscle circumference & muscle status % of standard measurement Muscle status category 50 Wasted 60 Below average - depleted 75 Average – marginal 100±20 Adequate >120 High muscle  23 Calf & Thigh Circumference Because of complexity & impracticality of using DXA ➔ NIA recommends CC to assess muscle mass & bone density CC better depicts body composition changes, reflecting lower extremity muscle loss & atrophy contributing to decreased mobility & risk of falling TC is an alternative marker of muscle mass & a predictor of risk for bone fracture Strong positive correlation of CC & TC to muscle mass (predict BMD & disability)  24 Anthropometric Measurements Benefits Limitations Time of day Low cost variance Variations in Ease of training location or sire of measurement Observational Non-invasive subjectivity 25  26 Novel Markers  AVI, WHtR, WC best predicted cardiometabolic abnormalities in a sample of Lebanese adults Abboud M, Haidar S, Mahboub N, Papandreou D, Rizk R (2023) Abdominal volume index, waist-to-height ratio, and waist circumference are optimal predictors of cardiometabolic abnormalities in a sample of Lebanese adults: A cross-sectional study. PLOS Glob Public Health 3(12): e0002726. https://doi.org/10.1371/journal.pgph.0002726  27 Muscle Mass DXA Bioelectrical impedance (BIA) ➔ Total body water ➔ estimate lean body mass & by difference from total body mass ➔ fat mass Advantages Does not require Ease of use in Cheap Portable extensive training research settings to operate  28 Nutritional Status Anthropometric & body composition measures for nutritional assessment Protein status Mid-arm-muscle circumference Grip strength Fat stores Triceps skinfold BMI BIA DXA Waist circumference Body water BIA Weight change Waist circumference  29 Nutritional Status Anthropometric & body composition measures Questionnaires  30 Muscle Strength  Assessment of nutritional status may include tests of muscle function  Handgrip strength (Dynanometer, commercially available)  Typical strength in healthy males is 40–50 kg; females 20–30 kg  May differ between dominant and non-dominant arms  Tends to decline in later years  Several protocols depending on posture, timing, number of repeats, use of dominant vs. non-dominant arms  Good predictor of health changes, morbidity & mortality in adults and children  Strong marker of nutritional status & frailty  31 Questionnaires to Assess Nutritional Status Hospital Community Computerized setting setting NRS-2002 MUST CONUT MNA MNA INFORNUT SGA, PG-SGA SNAQ NRI, GNRI GLIM criteria  32 Validated Malnutrition Screening Tools  Position of AND: Malnutrition 33 (Undernutrition) Screening Tools for Adults  Position of AND: Malnutrition 34 (Undernutrition) Screening Tools for Adults  35 SGA: Golden Standard  Subjective Global Assessment  Valid tool for the nutritional diagnosis of hospitalized clinical and surgical patients  Potential superiority of nutritional screening methods in the early detection of malnutrition (Da Silva Fink et al., 2015) https://nutritioncareincanada.ca/sites/default/uploads/files/SGA%20Tool%20EN%20BKWT_2017.pdf  36 MNA  Mini Nutritional Assessment  Validated nutrition screening and assessment tool  Can identify geriatric patients aged ≥65 years who are malnourished or at risk of malnutrition  Two forms: long and short forms https://www.mna-elderly.com/forms/mini/mna_mini_english.pdf  MNA 37  Functional, psychological, & cognitive parameters (not considered in MUST & NRS-2002) are probably more important risk factors for malnutrition than acute illness in geriatric long-term care inpatient settings  May account for the low predictive value of these tests  MNA-SF seems to combine the predictive capacity of the full version of the MNA with a sufficiently short time of administration  38 Appetite: AHSP, CNAQ, SNAQ AHSP Appetite Hunger and Sensory Perception Questionnaire 29-item multidomain: taste (14 items), smell (6 items), hunger (9items) 5-point Likert-type scale CNAQ Council on Nutrition Appetite Questionnaire 8-item single domain questionnaire 5-point Likert-type scale SNAQ Simplified Nutritional Appetite Questionnaire 4-item single domain  39 VALIDITY Considerations for RELIABILITY Choosing a Tool SENSITIVITY SPECIFICITY https://www.youtube.com/watch?v=psELBu7muNY  40 Validity vs. Reliability  Validity – extent to which a test measures what it is supposed to measure VS.  Reliability – consistency of a test or measure over a period, and between different participants  Inter-rater reliability – produces consistent results for the same subject regardless of the user  41 Validation Terms  Sensitivity – how likely is the test to detect presence of condition in someone with the condition?  Specificity – how likely is the test to detect the absence of a condition in someone without the condition?  42 MST  Malnutrition Screening Tool (MST) and Nutritional Screening Tool (NUTRISCORE)  Global Leadership Initiative of Malnutrition (GLIM) as reference standard  Sensitivity and specificity: MST: 75% and 94% vs. NUTRISCORE 45% and 97%  Area under ROC curves: MST: 0.90 for MST vs. NUTRISCORE: 0.85  MST has a significantly better diagnostic performance over NUTRISCORE  43 Take-home message