Historically, understanding the associations between nutrients and development (of which aging processes comprise a major component) has been based on recognition that anthropometric measures are useful proxies of health status that vary from detection of the impact on health of the public attributable to improved feeding (as in the growth of infants) to selection of military recruits and to the progress of chronic disease. For most populations, detailed reference data are available, and these can be used for purposes as diverse as demonstration that a study sample is typical of the population from which it was drawn to surveillance of the general nutritional status of large populations (e.g., Hughes et al., 2004). However, caution is advised when applying such simple methods to underdeveloped countries where there may be many malnourished subjects, frequent recurrent disease (e.g., malaria), and other stressors. Exposure to these confounders may vary within a country from place to place and over time.
At first glance, anthropometric data appear robust and simple to use. Certainly, most reports in nutritional gerontology do not provide detailed methods for anthro-pometric data collection, yet caveats abound. First, it is important to include anthropometric data in descriptions of samples. Second, in old people, great care must be exercised to ensure that these data are reproducible, so some training will always be required to achieve this. It is also useful in old people, in addition to height, to record the demispan between outstretched fingers and the midpoint of the sternum. This measure agrees closely with maximum height achieved and can be used to allow for shrinkage in stature with age in old people. As in much nutrition research, many measures are not normally distributed, and transformations to approximate normality should be made by systematically reviewing which of the following yields the best result (by increasing adjustment): square root ( x), logarithmic, inverse square root (1/^/x), and inverse (1/x).
Studies on reliability of measures of height and weight suggest that a priori maximum acceptable values should be set for differences between observers. This becomes more important as more measures are added to a study (e.g., arm circumference, triceps skin fold, subscapular skin fold). Here, it is useful to provide an estimate of measurement error such as the technical error of measurement (TEM) from one or more observers.
Anthropometric indices are derived from two or more raw anthropometric measures. Examples include the body mass index (BMI), arm muscle area (AMA) and arm fat area (AFA), and waist-hip ratio. Together, these measures and composite indices provide a guide to under- and overnutrition in a sample. The extent of underweight is gauged by applying a criterion value (usually 16, 17, or 18.5) to BMI scores. So far, it is uncertain how BMI varies within samples of old people. A greater proportion of under- and overweight individuals die before or soon after entering old age, but subsequently, overweight individuals enjoy some advantages, with a better chance of surviving some illnesses, yet with a greater risk of falls and such (Ledikwe et al., 2003).
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