Ethanol Clearance Rate as a Function of Age, Gender,
and Drinking Practices
H e rb e rt M oskow itz, D ary F io re n tin o , a n d M arcellin e B u rn s
Southern C alifornia Research Institute, Los Angeles, California, U.S.A.
A BSTRA CT
Accurate estim ation of ethanol clearance rate is often necessary in order to calculate a blood
alcohol concentration (BAC) at the time of an accident or arrest. To increase the precision of
such estim ates, the effects o f gender, drinking practice and age on ethanol clearance were
exam ined in a betw een-subjects factorial experiment. Subjects were dosed with alcohol for
peak BACs of 85 m g/dL or 105 mg/dL. They were breath tested frequently until their peak
BAC, and then at hour intervals on the descending BAC curve. U sing the post-peak BACs
(three or m ore) an ethanol clearance rate for each subject was calculated with a linear
regression analysis. Gender, drinking practice, and age were found to have statistically
significant effects on ethanol clearance rates.
IN T R O D U C T IO N
E stim ations of the rate of ethanol clearance are often used in forensic situations to predict a
BAC at the time o f an accident or arrest. W idm ark (1932) was among the first to quantify
ethanol clearance rates. He reported sim ilar mean rates betw een m ales and females.
Subsequently, other investigators reported that ethanol clearance rates vary as a function of
gender (Sutker et al., 1987; Thomasson, 1995; Cole-H arding et al., 1987), and drinking
practice (Sm ith et al., 1993; Jones et al., 1992; Jones, 1993). Although Cole-H arding reported
that age is not a reliable predictor o f ethanol m etabolism rates, age as a variable has not been
studied extensively.
This study exam ined the effects of age, gender, drinking practice, and their interactions, on
ethanol m etabolism rates.
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M ETH O D
Su b jects
Fifty-one healthy adults were recruited with advertisem ents in com m unity newspapers to
participate in an alcohol study as paid volunteer subjects (Ss). They were screened in term s of
health history, current health status, drug and alcohol use. As shown in Table 1, they were
grouped by gender, drinking category, and age (21 to 24, 25 to 50, 51 to 70). The Cahalan,
Cisin, and Crossley Q uantity-Frequency-Variability scale (1969) was used to classify Ss as
either light, m oderate, or heavy drinkers.
T ab le 1 : S u b je c t D istrib u tio n A cross E x p erim e n ta l C onditions
M ales
Fem ales
Age
Age
Age
Age
Age
Age
21-24
25-50
51-70
21-24
25-50
51-70
L ig h t D rin k e rs
n=l
n=
n=
6
n=3
n=
n=4
M o d e ra te
n= l
n=2
n= l
n=2
n=3
n=
n=3
n=4
n=
n=3
n=5
n=l
6
2
2
D rin k e rs
H eavy D rin k e rs
2
P ro c e d u re s.
On treatm ent days, Ss were transported by taxi between their residences and the laboratory. If
the Ss reported that they fulfilled the following criteria,
• No food intake within the preceding 4 hours
• No coffee, tea, or other stimulants intake within the preceding 4 hours
• No alcohol consum ption within the preceding 48 hours
• No illicit, prescription. OTC drug use during the preceding 7 days
• No current health problems,
The alcohol treatm ent was administered. The alcohol dose for m oderate and heavy drinkers,
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expected to produce a peak BAC of 105 mg/dL, was 2.06 g absolute alcohol per Kg o f body
water. Body water was estim ated on the basis o f each subject’s age, height, weight, and body
fram e size. Because light drinkers cannot tolerate the same am ount o f alcohol as m oderate
and heavy drinkers, their dose was reduced to 1.77 g absolute alcohol/K g o f body water. This
am ount was expected to produce a peak BAC o f 85 mg/dL.
The drinks were a m ixture of 80 proof vodka and orange juice. The alcohol-orange juice ratio
was 1:1.5 for heavy and m oderate drinkers and 1:2 for light drinkers. The total beverage was
given as three equal drinks at
1 0
-minute intervals for m oderate and heavy drinkers and at 15-
minute intervals for light drinkers. Subjects were instructed to pace their drinking evenly and to
com plete each drink within the allotted period. All subjects began their first drink betw een 8:00
and 9:00 am.
BACs were measured with breath specimens obtained with an Intoxilyzer 5000 at five minutes
intervals, beginning 15 minutes after completion o f drinking. After tw o consecutive descending
BAC readings, the sampling rate was reduced to two Intoxilyzer readings per hour. W hen a
S ’s BAC returned to zero, he/she was transported home by taxi.
C alcu latio n o f E th a n o l C lea ran c e R ates.
For each S, at least three BAC readings from the linear portion o f the clearance phase, i.e.,
between 7 0 mg/dL BAC (the point at which the absorption phase was judged to be complete)
and 3 0 m g/dL BAC were used to calculate the slope o f a best-fit straight line. For each S, an
individually calculated linear regression line was utilized to calculate the corresponding times
where the regression line indicated BACs o f 7 0 mg/dL ( t 7o mg/di.) and 3 0 mg/dL (t
30
mg/dr). The
clearance rate (P 6 o) for that individual was then calculated as follows:
p
-
70mg / dLBAC 30mg / dL B hC
t30mg/dL “ t70mg/dL
60
The analyses were performed utilizing the p 6 0 values as the basic response variable for each S.
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R E SU L T S
A 2X3X3 betw een-subjects factorial ANOVA was perform ed to determ ine w hether ethanol
clearance rates varied as a function of gender , drinking practice, and age.
The ANOVA indicated statistically significant differences in clearance rates betw een females
(18.4 m g/dL/h) and m ales (15.3 mg/dL/h) F(2, 32) = 5.97, p = 0.020; light (15.7 m g/dL/h),
m oderate (18 m g/dL/h), and heavy drinkers (17.5 m g/dL/h), F(2,33) = 3.52, p = 0.040; ages
21-24 (15 m g/dL/h), ages 25-50 (16.7 m g/dL/h), ages 51-70 (17.5 m g/dL/h), F(2,33), p =
0.007. Figures 1 illustrates differences in clearance rates as a function o f gender, drinking
practice, and age.
No statistically significant interactions between gender, drinking practice, and age were
found. Because o f the lim ited and uneven num ber of Ss in treatm ent cells, however, these
results may be due to a Type II error. The cell means and standard deviations for all
conditions are reported in Table 2.
F ig u re 1 : H o u rly E th a n o l C lea ran c e R ates as a fun ctio n o f G e n d e r, D rin k in g G ro u p ,
a n d Age.
So
£cs
£16
Males
Females
Gender
Light
Moderate
Heavy
Drinking Practice
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21-24
25-50
Age Group
51-70
Table 2 : H ourly Ethanol Clearance Rates (m g/dL/h) A cross Experim ental Conditions
Males
Females
Age
Age
Age
Age
Age
Age
21-24
25-50
51-70
21-24
25-50
51-70
n=l
n=6
n=6
n=3
n=2
n=4
Drinkers
12 ± 0
14 ± 2
15 ± 4
13 ± 1
16 ± 3
22 ±3
Moderate
n=l
n=2
n=l
n=2
n=3
n=2
Drinkers
19 ± 0
16 ± 0
19 ± 0
15 ±3
18 ± 1
22 ± 2
n=3
n=4
n=2
n=3
n=5
n=l
14 ± 1
16 ± 2
18 ±3
17 ± 3
20 ±5
20 ± 0
Light
Heavy
Drinkers
DISCUSSION
In general, the results support and extend previously-reported findings. Fem ales were found
to have higher average ethanol clearance rates than males. Consistent with findings by Sutker
et al. and C ole-H arding, female rates were also found to be m ore variable than m ale rates.
Findings by Sm ith et al., Jones et al., and Jones indicating that drinking practices affect
clearance rate were also supported. M oderate and heavy drinkers cleared alcohol at a faster
rate than light drinkers.
Age also had a direct effect on clearance rate. All drinking groups, including light drinkers,
show ed increased clearance rates as a function o f age.
The absence o f statistically significant interactions between the three variables is perhaps
attributable to small and uneven cell sizes within the factorial matrix. Future studies will
address these lim itations by assem bling additional Ss until each cell will have at least seven
Ss. The resulting increase in pow er will make it less likely that a Type II error will occur, and
will allow for evaluations o f the possible interactions.
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R EFEREN CES
Cahalan, D., Cisin, I.H., & Crossley, H.M. (1969) American Drinking Practices. Connecticut:
College & University Press.
Cole-H arding, S., & W ilson J.R. (1987). Ethanol metabolism in men and women. Journal of
Studies on A lcohol. 48(41. 380-387.
Jones, A.W. (1993). Disappearance rate of ethanol from the blood of hum an subjects:
Im plications in forensic toxicology. Journal of Forensic Science. 38(11. 104-118.
Jones, A.W ., & Sternebring, B. (1992). Kinetics o f ethanol and m ethanol in alcoholics during
detoxification. Alcohol & A lcoholism . 27(6), 641-647.
Sm ith, G.D., Shaw, L.J., Maini, P.K., W ard, R.J., Peters, T.J., & M urray, J.D. (1993).
M athem atical m odeling o f ethanol metabolism in norm al subjects and chronic alcohol
m isusers. Alcohol & A lcoholism . 28(11. 25-35.
Sutker, P.B., Goist, K. C., Allain A.N., & Bugg, F. (1987). Acute alcohol intoxication: Sex
com parisons on M ood Measures. Alcoholism Clinical and Experim ental R esearch. U ( 6 ), 507512.
T hom asson, H.R. (1995). Gender differences in alcohol m etabolism . In M. Galanter (Ed.),
Recent Developm ent in Alcoholism . Volume 12: W omen and Alcoholism (pp. 163-179).
New York, NY: Plenum Press.
W idm ark, E.M .P. (1932). Die theoretischen Grundlagen und die praktische Verwendbarkeit
der
gerichtlich-m edizinischen
Alkoholbestim mung
M edicolegal Alcohol Determ ination].
[Principles
and
Applications
of
Fortschritte der naturw issenschaftlichen Forschung,
Heft 11, E. A bderhalden, Ed., Urban und Schwarzenberg, Berlin-W ien.
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