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Body Composition and Physical Performance 1992. Pp. 223-235. Washington, D.C. National Academy Press 14 Body Composition Measurement Accuracy, Validity, and Comparability foe! A. Grinker BACKGROUND Because estimates of body composition may vary as a function of gen- der, age, or ethnicity, their universal applicability needs to be considered with care. Current military standards include both gender- and age-specific norms. Are they sufficient? Are norms for older women more restrictive than for comparable men? Should norms be adjusted for race as well? Should norms be based not on total body composition, but on fat distribu- tion patterns? Finally, should performance rather than body composition be the major determinant? The substitution of tests of health and physical capacity is possible, such as submaximal treadmill test performance, blood pressure test to rule out hypertension, spirometry to check lung health, Cybex to check quadriceps strength, hand grip dynamometer for hand strength, and evaluation of endurance via field performance or mini mara- thon. Would these tests provide more information than arbitrary standards based on changing norms? How relevant is physical appearance to effective military service, and how well correlated are arbitrary standards of body composition with preferred physical appearance? To assess these questions, it is necessary to document a number of factors. The applicability of different methods of assessing body composi- tion can be compared in relationship to assumptions of universal applica- bility. Secular, gender, and age-related differences in body composition and fatness can be documented. Ethnic or racial differences both in body composition and in age-related effects can also be documented. 223

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224 JOEL A. GRINKER METHODS AND ASSUMPTIONS Is the two-compartment model (lean body mass ELBM] and body fat LBFi) still useful? Should the four-compartment model (LBM, BF, body water, and bone mineral) be used? How well do multiple anthropometric measures mirror body composition, body density, and ethnic, racial, and age-related differences in fat distribution or changes in bone density? Body composition can be measured directly by chemical analysis of animal or human carcasses or cadavers. Indirect measures include densito- metry via hydrostatic weighing; anthropometric measures of skinfolds/ circumferences; and the more recent procedures of isotope dilution, neutron activation analysis, and potassium-40 counting (Boring et al., 1962; Brozek and Henschel, 1961; Forbes and Hursh, 1963; Lukaski, 1987~. However, it is important to realize that the use of any indirect method of assessing human body composition results in errors of prediction. The usual errors range from 2.5 percent for predicting BF from densitometry to 3 to 9 per- cent by anthropometry (Lohman, 19811. An early comparison of ultrasonic and skinfold measurements to evaluate subcutaneous fat thickness and to predict total BF weight suggested that skinfolds were the more effective and less costly procedure (Borkan et al., 1982b). The prevalent use of anthropometric measures (that is, height, weight, skinfolds and circumferences, and associated nomograms) is based on ease of application, simplicity, and reasonable correspondence with other tech- niques. Skinfolds of major interest include biceps, triceps, subscapular, suprailiac, abdomen, thigh, and medial calf. However, systematic errors can be introduced if the differential compressibility of skinfolds with age and skinfold thickness are not controlled (Himes et al., 19791. This tech- nique depends on two assumptions: that selected skinfold thicknesses are representative of the total subcutaneous adipose tissue mass and that subcu- taneous adipose tissue has a known relationship with total BF. However, the relationships between skinfold thickness and total BF reportedly differ with ethnicity, gender, and age (Chumlea et al., 1984; Durnin and Womers- ley, 1974; Jones et al., 1976; Wilmore and Behnke, 1970; Yuhasz, 1962~. In addition, these measurements are highly susceptible to experimenter bias or error leading to wide variability among experimenters. Densitometry has generally been considered the gold standard or crite- rion against which other techniques have been validated (Lohman, 1984; Roche, 19871. This technique assumes the two-compartment model: fat and fat-free mass (FFM; lipid-free) (Behnke et al, 19421. Fat is assumed to have a constant density of 0.9, although interstitial muscle fat is slightly higher (Mendez et al., 1960; Morales et al., 1945~. However, the density of FFM is not constant (Lohman, 1986; Roche, 19871. Until middle age, bone mineral mass and muscle mass increase, and extracellular fluid decreases

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BODY COMPOSITION MEASUREMENT 225 within the FFM. In old age, these differences are reversed for bone mineral and muscle. The density of FFM is also increased with marked physical activity due to the greater percentage of bone mineral (Mendez and Keys, 1960; Morales et al., 19451. Negative estimates of percent BE for some athletes are probably due to a greater density of FFM than allowed in the usual calculations (Roche, 19871. Although the two-compartment model has been considered adequate for young White men, it is not as useful for different ages, women, other ethnic groups, or even the extremely active (Lohman, 1986; Parizkova, 1977; Roche, 1987; Womersley et al., 1976~. Because of variations in the density of the FFM the correct model requires assessment of total body water and skeletal mass, in addition to measurement of body density. Physical training may also alter the fat-free body mass, suggesting that the new gold standard include separate measures of water, muscle, and bone mineral content. Greater delineation of lean body components that is, total body nitrogen, total body water, potassium, and so on have emerged. Newer technologies such as photon absorptiometry and neutron activation analysis are among the more quantitative means of measuring mineral content. The technique of dual-energy x-ray absorptiometry (DEXA), although as yet unverified, holds promise for its ability to measure accurately total body as well as regional bone and soft tissue composition (Mazess et al., 1990; Peppier and Mazess, 1981). Measurement and Definitions in Body Composition The application of limits in allowable body composition in the military depends on several assumptions. The first and primary assumption is that a single arbitrary point on the continuum of body fatness represents a "revers- ible abnormality". Overfatness or obesity is assumed to be a distinct abnor- mality that can be treated. Treatments consist of various procedures to induce "temporary" weight loss. Another assumption is that patterns of fat distribution at specific ages are less important or critical to overall health than is absolute fatness. Also implicit in the application of restrictive age- specific standards is the assumption that overweight/obesity at all ages is equivalently associated with increased health risks and/or poorer perfor- mance. Definitions of overweight and obesity, however, are population specific and subject to pronounced secular influences. Application to indi- viduals may often be arbitrary or inappropriate. Second, reversal of over- weight or obesity may be not only difficult to maintain but may itself be correlated with increased health risks (Williamson and Levy, 19881. Estimates of the population prevalence of overweight or overfatness are dependent both on the criteria and the measures used (Bray, 1987; Garrow, 1983;Simopoulos and Van Itallie, 19841. Among the most commonly used

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226 JOEL A. GRINKER criteria are relative weights (adjusted for height and gender) corresponding to specific percentiles for a specific population, ideal body weight, or body mass index (BMI; typically, weight in kg per height in m24. One common external standard for overfatness is based on a BMI above 26 while a fre- quently employed standard of ideal body weight is based on the Metropoli- tan Life Insurance mortality results (1959, 19831. National Center for Health Statistics (NCHS) surveys reported that 29 percent of the 1960-1962 and 26 percent of the 1977 U.S. adult population were overweight based on the 1959 Metropolitan Life Insurance norms of ideal weight-for-height (NCHS, 1966, 19801. More direct measures of fatness such as those derived from the sum of various skinfolds have also been used in large population-based studies with criteria based on population distributions. Norms are based on data from national health surveys such as the National Health and Nutrition Evaluation Survey (NHANES) I or II or data from insurance companies. The use of even multiple skinfolds or nomograms based on skinfolds and circumferences poses several problems. In overweight and obese subjects, these measurements show poor reliability (Forbes, 19641. Skin thickness and skinfold compressibility vary as a function of age, site, and gender (Brozek and Kinzey, 1960; Clegg and Kent, 1967; Garn and Gorman, 1956; Himes et al., 1979; Lee and Ng, 1965; Martin et al., 1985; Ruiz et al., 1971; Millar and Stephens, 19871. Discrepancies in reports of the prevalence of obesity have also been the result of applying different criteria for defining obesity (for example, NHANES I versus NHANES II or Metropolitan Life Insurance norms for 1959 versus 1983~. In addition, differences in sampling (for example, ran- domized census tract selection versus random digit telephone dialing) or measurements (for example, telephone self-report versus direct measures) have produced differences in reported obesity prevalence. Average fatness and prevalence rates for overweight/obesity can also vary markedly as a consequence of socioeconomic status (SES), age, race, and gender (Cronk and Roche, 1982; NCHS, 1986, 1987; Forman et al., 19864. Overweight and level of education or SES are inversely associated (Baecke et al., 1983; Forman et al., 1986; Garn and Clark, 1976; Garn, 1985; Moore et al., 1962; NCHS, 1980; Silverstone et al., 1969~. Within each of the four National Health and Education Surveys (NHES) surveys, even younger adults (18 to 35 years old; especially those above the median of the distribu- tion) had higher BMIs at progressively older ages (Harlan et al., 19881. The prevalence of overweight and obesity increases until individuals are approxi- mately 50 years of age, then levels and declines (Jeffrey et al., 1984; NCHS, 1966; Ross and Mirowsky, 1983; Stewart and Brook, 19831. Secular trends in the American population have been recognized in increased values in the criteria for defining obesity in the recent Metropoli

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BODY COMPOSITION MEASUREMENT 227 tan Life Insurance tables (1983) based on changes in measured fatness of sampled populations (eighty-fifth percentile) and risk. However, this latest version failed to include age as a variable, and consequently, the recom- mended weights are reported to be too liberal for young adults to accurately reflect total mortality for 40 year olds, and may be too restrictive even for 50 or 60 year olds (Andres et al., 19851. Obesity Prevalence, Age Effects and Weight Fluctuations Population Based Data Cross-sectional studies have documented differences in fatness as a function of gender, age, race, and secular influences (Abraham et al, 1983; Garn, 1985; NCHS, 1965, 1986, 1980; Malina et al., 1983; Wong and Trowbridge, 1984; Zillikens and Conway, 1990~. The U.S. population has reportedly gained weight over the last 2 decades, and the prevalence of obesity has increased (Simopoulos, 1987) even in childhood and adolescence (Dietz et al., 1985; Gortmaker et al., 19874. Overweight among adults of varying ages has increased within the last 10 years despite widespread health con- cerns and dieting (Fisher and Bennet, 19851. Recent statistics suggest that in 1986, 28.4 percent of U.S. adults 25 to 74 years of age were 20 percent or more overweight as judged by BMI greater than 27.8 for men and greater than 27.3 for women (NCHS, 19861. Cross-sectional studies in England, Canada, the United States, and Hol- land report that in both men and women, relative weight increases during adulthood, is maintained in middle age, and decreases in old age (Baecke et al., 1983;Bray, 1987;Jeffreyetal., 1984;Khosla and Lowe, 1968;Millar and Stephens, 1987; Montoye et al., 1965; NCHS, 1980; Rosenbaum et al., 1985; Stewart and Brook, 1983~. Although such associations between age and overweight could be due in part to a confusion between cohort and age effects possible in cross-sectional studies, data from prospective studies support these general findings. These longitudinal studies suggest age- related trends in relative weight (Friedlaender et al., 1977; Hsu et al., 1977; Kannel et al., 19791. Individual-Based Data At present, little is known about patterns of individual weight change within the population during adult years. When and to what extent does weight loss or gain occur? Is stability in BE related to pattern of fat distri- bution? It has recently been suggested that stability in body habitue may be related to a lower risk for chronic disease such as coronary heart disease (CHD) (Hamm et al., 19891. Whether the risk of other chronic diseases,

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228 .. JOEL A. GRINKER such as cancer or noninsulin dependent diabetes (NIDD) are also related to weight fluctuations is unknown. The few existing prospective studies sug- gest relative consistency in body weight patterns over time. (See, for exam- ple, Kramer et al., 1989.) Changes in weight, BMI, and skinfold thickness (triceps and subscapu- lar) were studied after intervals of 4 to 7 years in over 17,000 Finnish adults as part of a recent health survey (Rissanen et al., 19881. Average weight and BMI increased with age in men and women below age 50 at entry, changed little in men aged 50 to 70 (women aged 50 to 60), and declined at later ages. Both moderate overweight (BMI = 27.0 to 29.9 kg/m2) and severe overweight (BMI 2 30 kg/m2) increased in successive age cohorts of men and women until age 70. A relatively high proportion of Finnish adults, approximately 24.7 percent of all men and 33.7 percent of all wom- en were considered overweight, and 8.3 percent of men and 17.4 percent of women were estimated to be severely overweight. Small changes in individual weights were reported, with two-thirds of these Finnish participants maintaining their weight within 5 kg of their original weight classification (lean, normal, moderately overweight, or se- verely overweight). A weight gain of 10 kg or more occurred in 9 percent of the men and 4 percent of the women, and a 10-kg weight loss occurred in only 2 percent of the men and 4 percent of the women. Both weight loss and weight gain occurred among overweight subjects. Weight loss was associated with old age and higher initial BMI, whereas weight gain was most common in young adults, even among those with high initial BMI. Men aged 20 to 29 at entry gained an average 3.3 kg/5 years. Weight gain was less common among older subjects. Among 40 to 69-year-old men, there were negligible changes, with 15 percent losing or gaining 5 kg. BMI increased until age 50 and decreased thereafter. Results from the normative aging study (NAS) (Borkan et al., 1983, 1986; P. Vokonos, Boston Veterans Administration, pers. com.) illustrate strong age, cohort, and secular effects in fatness among healthy male adult volunteers. During the 20 years of this study, the average weight reportedly increased until age 55, with subsequent stability and then reduction. Pat- terns of central fat distribution have been examined in a small group of selected subjects from the NAS using CAT scans. Great variability among individuals in the redistribution of fat with increased age leading to an uneven thinning of subcutaneous fat and increased intra-abdominal fat has been documented (Borkan et al., 1982a; Borkan and Norris, 1977; Mueller, 19821. Estimates of internal abdominal fat appear to be poorly correlated with overall estimates of fatness and not well correlated with estimates such as the waist-hip ratio (Shimokata et al., 1989~. Abdominal fat and internal depots have been closely associated with cardiovascular disease (CVD). Data from the NAS have also been used to assess the effects of weight

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BODY COMPOSITION MEASUREMENT 229 change and age on coronary disease risk factors (Borkan et al., 19861. Even after controlling for age, smoking status, initial weight, and initial levels of the risk factor, increases in weight were significantly related to increases in most risk factors (for example, cholesterol levels, fasting glucose, triglycer- ides). However, data from at least one other longitudinal study suggest a curvilinear relationship between fatness and mortality (Andres et al., 19851. Recently, several studies have focused on the potential deleterious con- sequences of weight changes and have reported greater morbidity and mor- tality solely as a consequence of weight fluctuations (Hamm et al., 1989; Hoffman and Kromhout, 19891. Recent reports from the MRFIT, Goteborg, and Framingham populations suggest an association between weight cycling (individual variations in body weight) and coronary heart disease and mortality, which are reportedly independent of BMI or age (Lissner et al., 1988, 1990, 1991~. Whether undiagnosed illness is also a factor is under discussion. The factors related to success or failure in dieting and thus in promoting weight stability such as gender, ethnicity, intentionality, use of exercise, degree and duration of overweight/fatness, and fat distri- bution patterns need to be clarified. The appropriateness of age-specific criteria, however, remains some- what controversial. With affluence, fatness increases regularly with age, but it is unclear whether this is biologically desirable or inevitable. Per- haps, as with losses in muscle mass and strength, adequate exercise and attention to diet can prevent age-associated increases in total fatness but not, perhaps, changes in fat distribution. Although certain preindustrial societies may not demonstrate age-related increase in weight (Dietz et al., 1989), the documentation of shifts in the pattern of fat distribution suggests that ideal body weight and body composition are in fact age dependent. Andres (1990) has argued persuasively that modest increases in weight with increasing age (10 pounds/decade) are associated with minimum mortality among healthy, insured individuals. However, many analyses of these epi- demiological data sets have included "healthy" smokers. A recent study (Must et al., 1991) reports data from NHANES I on persons ranging in age from childhood to 74 years during 1971 to 1974. Population- and race-specific percentiles of BMI for obesity and super- obesity were obtained. Significant variability as a function of age, gender, and race were reported. In women, racial differences in the eighty-fifth and ninety-fifth percentiles of BMI emerged in the teens and persisted into adulthood with a continued divergence with age. The BMI at the fiftieth percentile was also higher in Black women starting in the teen years. In men, Whites had greater BMI at the eighty-fifth percentile until age 35; afterwards BMIs for Black men were greater. Black men had greater BMIs at the ninety-fifth percentile throughout adulthood with a continued diver- gence with age.

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230 .. JOEL A. G8lNKER RESEARCH APPLICATIONS Data from routine physicals in the military should provide both pro- spective data as well as cross-sectional data. The incidence and prevalence of weight shifts or changes in body composition in the military population can be documented. The existence of long-term trends in weight/fatness stability or cycling in individuals differing in body habitue can be explored. Initial anthropometric measures and pattern of fat deposition as well as estimates of percent BE or BMI can be compared with routine periodic measures of body composition and the incidence or degree of weight fluctu- ations individually determined. Secular and generational trends as well as relative stability in weight and fatness can be explored among different ethnic and racial groups. Retrospective case-cohort analysis can also be performed to determine the overall pattern of weight fluctuation; the initial fatness patterns of subjects subsequently exceeding specific fatness criteria can be contrasted against the entry status of a random selection of all partic- ipants at entry (Sorensen and Sonne-Holm, 19881. Weight and fatness stability can be defined as weight plus 5 pounds of starting weight per year. Weight stability can also be estimated by the intraindividual variability in body weights or fat distribution patterns, that is, the coefficient of variation (CV) of at least three consecutive body weights taken at regular intervals (3 to 5 years). Weight change can be defined as at least a 5-kg loss or gain; and weight cycling can be defined as two or more weight changes within the last 15 years. Comparisons can be made among current weight, initial weight, and "cycled" weights. Current and prior anthro- pometric measures can be used to provide estimates and adjustments of body composition and fat deposition and to estimate gender, ethnic, race, and age effects. It would also be of interest to measure adipose tissue in selected subjects for lipolysis and conduct VO2max testing or measure total metabolic rate by doubly labeled water technique in selected subjects with high or low weight fluctuations. These data would allow estimates of individual differenc- es in rates of lipolysis or energy utilization. These latter relationships might begin to provide partial answers to the major question of the relationships among body composition, body fatness, and performance. SUMMARY The body composition criteria for entrance and for retention in the military services especially the Army, are not identical. Screening criteria are primarily based on weight/height for age with retention criteria based on body composition standards that are only moderately related to performance. This paper discussed several key issues of measurement which influence both the accuracy and the reliability of measures of body composition. Fur

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BODY COMPOSITION MEASUREMENT 231 ther research is necessary to examine the relationships among the various methods of measuring body composition and various performance criteria. Major issues that were addressed in this discussion of criteria included those related to validity or accuracy and precision as well as issues of reliability. These factors are related not only to technical measurement error but also to issues concerning stability in body composition in adult men and women and differences in body composition among various sub- groups for example, racial or ethnic. Body composition and the adequacy (validity and reliability) of measurements were discussed in relation to age, pattern of fat distribution, gender, and ethnic or racial differences. The prevalence and significance of weight shifts with aging or dieting were also discussed. Finally, the relationship between standards of body composition and performance in relation to differences among age, ethnic, and gender groups was addressed. Additional research should address these remaining issues: What should be used as the true "gold standard" in determining body composition? Is the two- or four-compartment model more useful? How accurate are the large scale screening techniques versus experiment- al procedures? How reliable? What are the correlations among measurements? What corrections in weight or fatness should be allowed for gender, race and ethnic origin? How should ethnic differences in fatness distribu- tion patterns be translated into body composition standards? How stable are the weights and body compositions of adults? Are age associated corrections desirable or necessary? If certain patterns of fat distribution (centripetal or abdominal depots) are more likely to occur with older age and be more closely linked with morbidity/mortality, should body composition recommendations and standards be differentially aimed at specific subgroups, i.e. especially men (and women) with centripetal fat distribution patterns? Should standards of acceptable weight/fatness be relaxed for women (or those meeting lower waist/hip ratios)? Since smoking (in women) is related to higher waist/hip ratios should fatness/appearance recommendations include restrictions on cigarettes? Standards of measurement (validity and reliability) must be considered along with issues of applicability to military needs. REFERENCES Abraham, S. and C. L. Campbell. 1980. Prevalence of severe obesity in adults in the United States. Am. J. Clin. Nutr. 33:364-369. Abraham, S., M. D. Carroll, M. R. Najjar, and F. Robinson. 1983. Obese and overweight adults in the United States. Vital and Health Statistics U.S. Department of Health and Human Services Publication No. (PHS) 83-1680, PHS NCHS Series 11. No. 230. Washington, D.C.: Government Printing Office.

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232 JOEL A. GRINDER Andres, R. 1990. Mortality and obesity: The rationale for age-specific height-weight tables. Pp.759-765 in Principles of Geriatric Medicine and Gerontology, 2d ea., W. R. Hazzard, R. Andres, E. L. Bierman, and J. P. Blass, eds. New York:McGraw-Hill. Andres, R., D. Elahi, J. D. Tobin, D. C. Muller, and L. Brant. 1985. Impact of age on weight goals. Ann. Int. Med. 103:1030-1033. Baecke, J. A. H., J. Burema, J. E. R. Frijters, J. G. A. J. Hautvast, and W. A. M. vender Wiel- Wetzels. 1983. Obesity in young Dutch adults: I, Socio-demographic variables end body mass index. Int. J. Obes. 7:1-12. Bell, B., C. L. Rose, and A. Damon. 1966. The Veterans Administration longitudinal study of healthy aging. Gerontologist 6:179- 184. Boling C. A., W. Taylor, C. Entemor, A. R. Behnke. 1962. Total exchangeable potassium and chloride and total body water in healthy men of varying fat content. J. Clin. Invest. 31: 1840- 1849. Borkan, G. A., and A. H. Norris. 1977. Fat distributions and the changing body dimensions of the adult male. Hum. Biol. 49:495-514. Borkan, G. A., S. G. Gerzof, A. H. Robbins, D. E. Hults, C. K. Silbert, and J. E. Silbert. 1982a. Assessment of abdominal fat content by computed tomography. Am. J. Clin. Nutr. 36: 172-177. Borkan, G. A., D. E. Hults, J. Cardarelli, and B. A. Burrows. 1982b. Comparison of ultrasound and skinfold measurements in assessment of subcutaneous and total fatness. Am. J. Phys. Anthropol. 58:307-313. Borkan, G.A., D. E. Hults, and R. J. Glynn. 1983. Role of longitudinal change and secular trend in age differences in male body dimensions. Hum. Biol. 55:629-641. Borkan, G.A., D. Sparrow, C. Wisniewski and P. S. Vokonas. 1986. Body weight and coronary disease risk: Patterns of risk factor change associated with long-term weight change. Am. J. Epidemiol. 124:410-419. Bray, G. A. 1987. Overweight is risking fate: Definition, classification, prevalence, and risks. Ann. N.Y. Acad. Sci.499: 14-28. Brozek, J. and Henschel A. eds. 1961. Proceedings of a Conference: Techniques for Measuring Body Composition.Washington, D.C.: National Academy of Sciences. Brozek, J., and Kinzey W. 1960. Age changes in skinfold compressibility. J. Gerontol. 15:45-51. Chumlea, W. C., A. R. Roche, P. Webb. 1984. Body size, subcutaneous fatness and total body fat in older adults. Int. J. Obes. 8:311-317. Clegg, E. J. and C. Kent. 1967. Skinfold compressibility in young adults. Hum. Biol. 39:418- 429. Cronk, C. E. and A. R. Roche. 1982. Race and sex-specific reference data for triceps and subscapular skinfolds and weight/height2. Am. J. Clin. Nutr. 35:347-354. Dietz, W. H., S. L. Gortmaker, and A. M. Sobol. 1985. Trends in the prevalence ofchildhood and adolescent obesity in the United States. Pediatr. Res. 19:198A. Dietz, W. H., Marino B., N. R. Peacock, and R. C. Bailey. 1989. Nutritional status of Ese Pygmies and Lese horticulturists. Am. J. Phys. Anthropol. 78:509-518. Durnin, J. V. G. A. and M. M. Rahaman. 1967. The assessment of the amount of body fat in the human body from measurement of skinfold thickness. Br. J. Nutr. 21:681-689. Durnin, J. V. G. A. and J. Womersley. 1974. Body fat assessed from total body density from skinfold thickness: Measurements on 481 men and women aged 16 to 72 years. Br. J. Nutr. 32:77-97. Fisher, K. D. and Bennett. 1985. Report of the scientific community's views on progress in attaining the PHS objectives for improved nutrition in 1990. Life Science Research Of- fice, Federation of American Societies for Experimental Biology, Bethesda, Md. Forbes, G. B. 1964. Lean body mass and fat in obese children. Pediatrics 34:308-314. Forbes, G. B., and J. B. Hursch. 1963. Age and sex trends in LBM calculated from K40 mea

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BODY COMPOSITION MEASUREMENT 233 surements: With a note on the theoretical basis for the procedure. Ann. N.Y. Acad. Sci. 110:255-263. Forman, M.R., F. L. Trowbridge, E. M. Gentry, J. S. Marks, and G. C. Hogelin. 1986. Over- weight adults in the United States: The behavioral risk factor surveys. Am. J. Clin. Nutr. 44:410-416. Friedlaender, J. S., P. T. Costa, R. Bosse, E. Ellis, J. G. Rhoads, and H. W. Stoudt. 1977. Longitudinal physique changes among healthy white veterans at Boston. Hum. Biol. 49: 541 -558. Garn, S. M. 1985. Continuities and changes in fatness from infancy through adulthood. Curr. Probl. Pediatr. 15: 1 -47. Garn, S. M., and D. C. Clark. 1976. Trends in fatness and the origins of obesity. Pediatrics. 57:443-456. Garn, S. M., and E. L. Gorman. 1956. Comparison of pinch-caliper and tele-roentgenogram- metric measurements of subcutaneous fat. Hum. Biol. 28:407-413. Garrow, J. S. 1983. Indices of adiposity. Nutr. Abst. Rev. 53:697-708. Gortmaker, S. L., W. H. Dietz, A. M. Sobol, and C. A. Wehler. 1987. Increasing pediatric obesity in the United States. Am. J. Dis. Child. 141:535-540. Hamm, P., R. B. Shekelle, and J. Stamler. 1989. Large fluctuations in body weight during young adulthood and twenty-five year risk of coronary death in men. Am. J. Epidemiol. 129:312-318. Harlan, W. R., J. R. Landis, K. M. Flegal, C. S. Davis and M. E. Miller. 1988. Secular trends in body mass in the United States. Am. J. Epidemiol. 128:1065-1074. Himes, J. H., A. F. Roche, and R. M. Siervogel. 1979. Compressibility of skinfolds and the measurement of subcutaneous fatness. Am. J. Clin. Nutr. 32:1734-1740. Hoffman, M. D. A. F., and D. Kromhout. 1989. Changes in body mass index in relation to myocardial infarction (the Zutphen-study). Int. J. Obes. (abstr.) 13:25. Hsu P. H., F. A. L. Mattewson, and S. W. Rabkin. 1977. Blood pressure and body mass index patterns a longitudinal study. J. Chron. Dis. 30:93- 113. Jeffrey, R.W., A. R. Folsam, R. V. Luepker, D. R. Jacobs, R. F. Gillum, H. L. Taylor, and H. Blackburn. 1984. Prevalence of overweight and weight loss behavior in a metropol- itan adult population: The Minnesota heart-survey experience. Am. J. Public Health 74(4): 349-352. Jones, P. R. M., H. Bharadwaj, M. E. Bhatia, and M. S. Malhotra. 1976. Differences between ethnic groups in the relationship of skinfold thickness to body density. Pp. 373-376 in Selected Topics in Environmental Biology. B. Bhatia, G. S. Chhina, and B. Singh, eds. New Delhi: Interprint Publications. Kannel, W. B., T. Gordon, and W. P. Castelli. 1979. Obesity, lipids, and glucose intolerance. The Framingham Study. Am. J. Clin. Nutr. 32:1238-1245. Khosla, T., and C. R. Lowe. 1968. Height and weight of British men. Lancet i:742-745. Kramer, R. W., R. W. Jeffrey, J. L. Forster, and M. K. Snell. 1989. Long-term follow-up of behavioral treatment for obesity: Patterns of weight regain among men and women. Int. J. Obes. 13:123-136. Lee, M. M. and C. K. Ng. 1965. Postmortem studies of skinfold caliper measurement and actual thickness of skin and subcutaneous tissue. Hum. Biol. 37:91-103. Lissner, L., G. Collins, S. N. Blair, and K. D. Brownell. 1988. Weight fluctuation and mortality in the MRFIT population. Abstract, Soc. Epidemiol. Res. (abstr.) Birmingham, Alabama. Lissner, L., R. Andres, D. C. Muller, and H. Shimokata. 1990. Body weight fluctuation in men: Metabolic rate, health, and longevity. Int. J. Obes. 14:373-383. Lissner, L., P. Odell, R. D'Agostino, J. Stokes, B. Kreger, A. Belanger, and K. Brownell. 1991. Variability of body weight and health outcome in the Framingham population. N. England J. Med. 1324: 1839- 1844.

OCR for page 223
234 JOEL A. GRINKER Lohman, T. G. 1981. Skinfolds and body density and their relation to body fatness: A review. Hum. Biol. 53:181-225. Lohman, T. G. 1984. Research progress in validation of laboratory methods of assessing body composition. Med. Sci. Sports Exerc. 16:596-605. Lohman, T. G. 1986. Applicability of body composition techniques and constants for children and youths. Exerc. Sport Sci. Rev. 14:325-357. Lukaski, H. C. 1987. Methods for the assessment of human body composition: Traditional and new. Am. J. Clin. Nutr. 46:537-556. Malina, R. M., B. B. Little, M. P. Stern, S. P. Gaskill, and H. P. Hazuda. 1983. Ethnic and social class differences in selected anthropometric characteristics of Mexican American and Anglo adults: The San Antonio heart study. Hum. Biol. 55:867-883. Martin, A. D., W. D. Ross, D. T. Drinkwater, and J. P. Clarys. 1985. Prediction of body fat by skinfold caliper: Assumptions and cadaver evidence. Int. J. Obes. 9:(suppl.)31-39. Mazess, R. B., H. S. garden, J. P. Bisek, and J. Hanson. 1990. Dual-energy x-ray absorptiom- etry for total-body and regional bone-mineral and soft-tissue composition. Am. J. Clin. Nutr. 51:1106-1112. Mendez, J., and A. Keys. 1960. Density and composition of mammalian muscle. Metabolism 9: 184-188. Mendez, J., A. Keys, J. T. Anderson, and Grande F. 1960. Density of fat and bone mineral of mammalian body. Metabolism 9:472-477. Metropolitan Life Insurance Company. 1959. New weight standards for men and women. Stat. Bull. 40:1-4. Metropolitan Life Insurance Company. 1983. 1983 Metropolitan height and weight tables. Stat. Bull. 64:2-9. Millar, W. J., and T. S. Stephens. 1987. The prevalence of overweight and obesity in Britain, Canada, and United States. Am. J. Public Health. 77:38-41. Montoye, H. J., F. H. Epstein, and M. D. Kjelsberg. 1965. The measurement of body fatness. A study in a total community. Am. J. Clin. Nutr. 16:417-427. Moore, M. E., A. J. Stunkard, and L. Srole. 1962. Obesity, social class, and mental illness. J. Am. Med. Assoc. 181(11):138-142. Morales, M. F., E. N. Rathburn, R. E. Smith, and N. Oace. 1945. Studies on body composition. II. Theoretical considerations regarding the major body tissue components with sug- gestions for application to man. J. Biol. Chem. 156:677-684. Mueller, W. H. 1982. The changes with age of the anatomical distribution of fat. Soc. Sci. Med. 16:191-196. Must, A., G. E. Dallal, and W. H. Dietz. 1991. Reference data for obesity: 85th and 95th percentiles of body mass index (wt/ht2) and triceps skinfold. Am. J. Clin. Nutri. 53:839- 846. National Center for Health Statistics. 1965. Weight, height and selected body dimensions of adults, United States, 1960-1962. Vital and Health Statistics Series 11. Washington, D.C.: U.S. Department of Health, Education and Welfare (HRA) 76-1074. National Center for Health Statistics. 1966. Weight by height and age of adults, United States, 1960-1962. Vital and Health Statistics Series 1, No. 14. Washington, D.C.: U.S. Depart- ment of Health, Education and Welfare. National Center for Health Statistics. 1980. Health practice among adults: U.S., 1977. Advance data from vital and health statistics. PHS No. 64. Washington, D.C.: U.S. Department of Health, Education and Welfare. National Center for Health Statistics. 1986. Health, United States, 1986. Department of Health and Human Services Publication No. (PHS) 87-1232. Public Health Service. Washington, D.C.: U.S. Government Printing Office. National Center for Health Statistics. 1987. Anthropometric reference data and prevalence of

OCR for page 223
BODY COMPOSlTlON MEASUREMENT 235 overweight, United States, 1976-1980. Vital and Health Statistics Series 11. Washington, D.C.: U.S. Department of Health, Education and Welfare. Parizkova, J. 1977. Body Fat and Physical Fitness, The Hague: Marrinus Nijhoff By/Medical Division. Peppler, W. W., and R. B. Mazess. 1981. Total body mineral and lean body mass by dual- photon absorptiometry. I. Theory and measurement procedure. Calcif. Tissue Int. 33:353- 359. Rissanen, A., M. Heliovaara, and A. Aromaa. 1988. Overweight and anthropometric changes in adulthood: A prospective study of 17,000 Finns. Int. J. Obes. 12:391-401. Roche, A. F. 1987. Some aspects of the criterion methods for the measurement of body compo- sition. Hum. Biol. 59(2):209-220. Rosenbaum, S., R. K. Skinner, I. B. Knight, and J. S. Garrow. 1985. A survey of heights and weights of adults in Great Britain. Ann. Hum. Biol. 12:115-127. Ross, C. D., and J. Mirowsky. 1983. Social epidemiology of overweight: A substantive and methodological investigation. J. Health Soc. Behav. 24:288-298. Ruiz, L., J. R. T. Colley, and P. J. S. Hamilton. 1971. Measurement of triceps skinfold thick- ness. An investigation of sources of variation. Brit. J. Prev. Soc. Med. 25:165-167. Shimokata, H., J. D. Tobin, D. C. Muller, D. Elahi, P. J. Coon and R. Andres. 1989. Studies in the distribution of body fat: Effects of age, sex, and obesity. J. Gerontol. 44:M66-73. Silverstone, J. T., R. P. Gordon, and A. J. Stunkard. 1969. Social factors in obesity in London. Practitioner 202:682-688. Simopoulos, A. P. 1987. Characteristics of obesity: An overview. In Human Obesity, R. J. Wurtman and J. J. Wurtman, eds. Ann. of N.Y. Acad. Sci. 499:4-13. Simopoulos, A. P. and T. B. Van Ittallie. 1984. Body weight, health, and longevity. Ann. Intern. Med. 100:285-295. Sorensen, T. I. A. and A. Sonne-Holm. 1988. Risk in childhood of development of severe adult obesity: retrospective, population-based case-cohort study. Am. J. Epidemiol. 127:104- 113. Stewart, A. L., and R. H. Brook. 1983. Effects of being overweight. Am. J. Public Health 73:171 - 178. Williamson, P. S., and B. T. Levy. 1988. Long-term body weight fluctuation in an overweight population. Int. J. Obes. 12:579-583. Wilmore, J. H., and A. R. Behnke. 1970. An anthropometric estimation of body density and lean body weight in young women. Am. J. Clin. Nutr. 23:267-274. Womersley, J., J. V. G. A. Durnin, K. Boddy, M. Mahaffy. 1976. Influence of muscular development, obesity, and age on the fat-free mass of adults. J. Appl. Physiol. 41:223- 229. Wong, F. L. and F. L. Trowbridge. 1984. Nutrition surveys and surveillance: Their application to clinical practice. Clin. Nutr. 3:94-99. Yuhasz, M. S. 1962. The Effects of Sports Training on Body Fat in Man with Prediction of Optimal Body Weight. Urbana, Ill.: University of Illinois Press. Zillikens, M. C. and J. M. Conway. 1990. Anthropometry in Blacks: Applicability of general- ized skinfold equations and differences in fat patterning between Blacks and Whites. Am. J. Clin. Nutr. 52:45-51.

OCR for page 223