NUTRITION IN SPORT

(Martin Jones) #1

33 ±14 years; mean weight, 56.5±11.5 kg), includ-
ing trained male athletes. Harris and Benedict
derived different equations for both men and
women:


Males: RMR=66.47+13.75 (wt) – 5 (ht)



  • 6.76 (age)


Females: RMR=655.1 9.56 (wt)+1.85 (ht)



  • 4.68 (age)

  • Owen et al.(1986); based on 44 lean and obese
    women, eight of whom were trained athletes
    (age range, 18–65 years; weight range, 48–
    143 kg), none of whom were menstruating
    during the study, and all of whom were weight
    stable for at least 1 month:


Active females: RMR=50.4+21.1 (wt)


Inactive females: RMR= 795 +7.18 (wt)



  • Owen et al.(1987); based on 60 lean and obese
    men (age range, 18–82 years; weight range,
    60–171 kg), none of whom were athletes, and all
    of whom were weight stable for at least 1 month:


Males: RMR= 290 +22.3 (LBM)


Males: RMR= 879 +10.2 (wt)



  • Mifflin et al.(1990); based on 498 healthy lean
    and obese subjects, 247 females and 251 males
    (age range, 18–78 years; weight range, 46–120 kg
    for women and 58–143 kg for men); no mention
    was made of physical activity level:


RMR=9.99 (wt)+6.25 (ht) – 4.92 (age)
+166 (sex; male=1, female=0) – 161



  • Cunningham (1980); based on 223 subjects, 120
    males and 103 females, from the Harris and
    Benedict data base. Cunningham eliminated 16
    males who were identified as trained athletes. In
    this study, LBM accounted for 70% of the vari-
    ability of RMR. LBM was not calculated in the
    Harris–Benedict equation, so Cunningham esti-
    mated LBM based on body mass and age:


RMR= 500 +22 (LBM)


Thompson and Manore (1996) found that for
both male and female athletes the Cunning-


476 practical issues


ham equation best predicted RMR, with the
Harris–Benedict equation being the next best
predictor. Because the Cunningham equa-
tion requires the measurement of FFM, the
Harris–Benedict equation will be easier to use in
settings where FFM cannot be measured.
Once RMR has been estimated, TDEE can then
be estimated by a variety of different factorial
methods. These methods vary in how labour
intensive they are to use and the level of respon-
dent burden. A detailed description of these
methods is given elsewhere (Food and Nutrition
Board 1989; Schutz & Jequier 1994; Montoye et al.
1996). The easiest method multiplies RMR by an
appropriate activity factor, with the resulting
value representing TDEE (Food and Nutrition
Board 1989). Another method estimates a general
activity factor (GAF) and a specific activity factor
(SAF). The GAF represents the energy expended
in doing everyday activities such as walking,
standing, driving, and watching television. The
SAF is the amount of activity expended in
specific exercises (e.g. running, swimming or
weight training) for a designated intensity and
amount of time. The SAF is calculated by multi-
plying the amount of time spent in an activity by
its energy requirement (Berning & Steen 1991;
Montoyeet al. 1996). The GAF and SAF are
then added together to get the total amount of
energy expended per day in activity. This value is
added to the estimated RMR value, then an addi-
tional 6–10% is added to represent the TEF. The
final number then represents the TDEE. This
method is relatively easy to use with athletes
who have specific training or exercise pro-
grammes and who already keep training logs.
TDEE can also be estimated by recording all
activities over a 24-h period and then calculating
the energy expended in each of these activities
(kJ · kg–1· min–1). The amount of energy expended
in each activity is then added and represents
TDEE. Many computer programs calculate
energy expenditure in this way. Regardless of the
method used, keep in mind that all values are
estimates. The accuracy of these values will
depend on a number of factors: the accuracy of
the activity records, the accuracy of the data base
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