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Ethanol elimination among different racial groups
Alcohol, Voi. 9, pp. 213-217, 1992
0741-8329/92 $5.00 + .00 Copyright © 1992 Pergamon Press Ltd.
Printed in the U.S.A. All rights reserved.
Ethanol Elimination Among Different Racial Groups B E R N A R D S E G A L *l A N D L A W R E N C E K. D U F F Y ~
*Department o f Health Sciences, University o f Alaska Anchorage, Anchorage, A K 99508 tInstitute o f Arctic Biology and Department o f Chemistry, University o f Alaska Fairbanks, Fairbanks, A K 99775-0180 Received 16 September 1991; Accepted 21 N o v e m b e r 1991 SEGAL, B. AND L. K. DUFFY. Ethanoleliminationamongdifferent racialgroups. ALCOHOL 9(3)213-217, 1992.This study examined the relationship between ethanol elimination and race, specifically exploring differences among Alaskan Natives, American Indians, and whites. Native Americans, believed to be of recent Asian origin, were expected to eliminate alcohol faster than whites. The data suggested that both Native American men and women eliminated alcohol faster than whites. A relationship was also found between age, gender, and rate of alcohol elimination. The implications of these findings were reviewed and specific needs for future research were noted. Alcohol
Ethanol elimination
Race
known, however, about the distribution frequency of the A L D H and ADH polymorphisms (or other genetic differences) in northern racial groups such as Alaskan Natives, who are believed to have an Oriental ancestry. Further studies are needed to assess the consistency of differences in ADH and ALDH genotypcs in different racial groups, and to determine the extent to which they differ across different racial groups. These studies are important with respect to groups who differ culturally and racially, but who may share a relatively recent common ancestry. This research, in anticipation of genetic studies, examined differences in reduction of blood alcohol levels among heavy drinkers of different racial groups. Because genetic differences could contribute to variations in alcohol elimination among these two racial groups, it was anticipated that Alaskan Natives would show a more rapid rate of alcohol reduction in comparison with whites (of presumed European ancestry).
SIGNIFICANT attention in recent years, in the form of family, twin, adoption, and other genetic studies, has been directed at the role that heredity plays in the etiology of alcoholism (1,6,13,16,19,32,35). The results of these studies have led to the discovery of different levels of alcohol sensitivity and varying pharmacological behavior among individuals of different racial groups (3,4,12,28,31,33,36,38). It has been shown, for example, that aldehyde dehydrogenase is a key enzyme in alcohol metabolism (5,18), and that the aldehyde dehydrogenase polymorphism provides the genetic base for facial flushing among Orientals (15). Although research results are mixed, it appears that people of Asian ancestry (Chinese and Japanese) metabolize alcohol to acetate more rapidly than non-Asians. This has been attributed to the presence in some Orientals of an atypical form of alcohol dehydrogenase (ADH) that metabolizes ethanol more efficiently to acetaldehyde than the normal form. Agarwal and Goedde (2) reported that about 50% of the Asians they studied showed an undue accumulation of acetaldehyde, seemingly attributable to the relatively inefficient or completely inefficient variant of aldehyde dehydrogenase (ALDH). The blocking of enzymatic degradation of acetaldehyde can result in unpleasant side effects after alcohol consumption, such as facial flushing, palpitations, muscle weakness, and headaches. This strong aversive reaction has been interpreted as protecting people with aldehyde dehydrogenase deficiency from becoming alcoholic (23,37). Research (36) has shown that the prevalence of the gene alleles for both atypical ADH and the inactive variant of A L D H are lower in alcoholic Chinese subjects than in nonalcoholic subjects. Little is
METHOD
This article conveys findings from an extended study of a diverse drinking population in Anchorage, AK. The data were derived from a comprehensive research and demonstration project enacted to attempt to intervene in the lifestyle of chronic homeless drinkers. Park of this project involved the establishment of a 2,4-hour sobering center [Sleep-off Center (SOC)] in which homeless street people, many of whom would be intoxicated, could find shelter. This report is based on data derived from this project during 1988 (30).
To whom requests for reprints should be addressed. 213
214
SEGAL AND DUFFY
Subjects All clients entering the SOC were logged in at their time of entry, which required that name, residential status, race, age, gender, entry time, date, referral source, condition on entry, and use of alcohol and other drugs be recorded. Upon departure, the date, time of leaving, and destination were documented. The intake log was maintained by staff members who were trained to elicit information from intoxicated clientele. In addition to the demographic data, an attempt was made to obtain an entry and exit blood alcohol level (BAL) on all clients using an Intoximeter IR 3000 Model breathalyzer, which requires that a deep breath be blown into a tube to obtain a reading. A comprehensive description of the client population is presented elsewhere (30). Briefly, a total of 22,282 multiple (or duplicated) entries to the SOC were made by 1749 unique (or unduplicated) persons (mean age 37.1 years). Of these individual cases, 81070 were male (n = 1416) and 19070 were female (n = 333). The racial composition was: white, 27.6°/0; Alaskan Native, 64.6070; Black, 2.4070; American Indian, 3.1070; Hispanic, 1.3 %; Asian Pacific 0.2 070; and other 0.9 %. The data for this study were derived from 632 cases (selected from a subject pool of 1749 unique cases), for whom entry and exit times and entry and exit BALs were complete, and who stayed at the SOC for a minimum of 1 hour on each entry. Many of these subjects had completed a questionnaire that assessed a wide array of information encompassing demographic data, drinking and drug-taking behavior, social functioning, economic and occupational data, and legal involvement. The interviews were obtained when they were sober. The subject pool, from which the data reported herein were derived, consisted of 531 men (mean age 37.4 years) and 101 women (mean age 38.8 years), whose entries to the SOC amounted to a collective total of 10,436 times, of which 9201 were by men and 1235 by women. Of these, 141 were white males, 21 were American Indian (from the lower 48 states), 80 were Athabascan Indian, 24 Tlingit/Halda Indian, 107 Yupik Eskimo, 102 Inupiat Eskimo, and 56 Aleut. Nine of the women were white, 20 were Athabascan Indian, 30 Yupik Eskimo, and 42 Inupiat Eskimo. The data were analyzed separately by gender to control for variations in body weight and physiological differences between men and women.
significant differences existed between BAL rates and race. One-way analyses were first conducted separately for men and women, followed by a two-way ANOVA that tested for differences between race (white and Alaskan Native) and gender. Only cases with an alcohol elimination rate or ratio greater than zero were included to avoid obtaining a skewed rate distribution. The procedures were executed on a Digital Vax 8800 computer using a SPSS program (32). RESULTS
Male admission drinking levels, as reflected by multiple entry BALs on the same cases, ranged from 0.001 to a high of 0.434, with a mean entry BAL of 0.204 (SD = 0.053); on departure, exit BALs ranged from 0.002 to a high of 0.406, with a mean value of 0.094 (SD = 0.056). Female entry BALs, also representative of multiple entries on the same cases, ranged from 0.005-0.393, with a mean entry BAL of 0.212 (SD = 0.051). Exit female BALs ranged from 0.0020.370, with a mean exit BAL of 0.091 (SD = 0.958). Time at the SOC averaged 7.19 h (SD = 3.14) for men and 7.00 h for women (SD = 3.24).
Alcohol Elimination by Race A one-way ANOVA was used to test for differences between alcohol elimination rate (if greater than zero) and race as represented by membership in one of seven groups: white, American Indian, Athabascan Indian, Tlingit/Haida Indian, Yupik Eskimo, Inupiat Eskimo, and Aleut. The latter five groups are known as "Alaskan Natives"; all six nonwhite groups are collectively referred to as Native Americans. This analysis involved all cases with a minimum entry BAL of 0.01, a minimum exit BAL of 0.01, a minimum 1 hour stay, and an elimination rate greater than zero. Figure 1 shows the results of this analysis, which yielded a statistically significant difference, F(6, 9194) = 9.4816, p < 0.0000, among the groups. The mean rates for each group were: White, 0.0154 (SD = 0.0086), American Indian, 0.0167 (SD = 0.0093), Athabascan, 0.0177 (SD = 0.0110), Tlingit/ Haida, 0.0178 (SD = 0.0105), Yupik Eskimo, 0.0170 (SD =
Blood Alcohol Levels
A U!~oer Limit MeanRate [] Lower Limit •
Each client's length of time at the SOC was paired with the difference between his or her entry and departure blood alcohol level (gram 070). A rate of alcohol elimination was derived by dividing blood alcohol difference by time at the SOC. The following equation was used to calculate an ethanol elimination rate:
A
&
0018 m
/,
A
Z
$
o
0.017
•
o
o []
Rate (in g070/h) =
BALi. - BALout Time at SOC
The resulting statistic (rate) is an empirically derived index representing change in blood alcohol content that was independent of length of time at the SOC and independent of entry BALs. The time between BAL measurements for cases used in this study was never less than 1 hour. A minimum exit BAL of 0.01 was selected so that comparisons would be based on the early part of the elimination curve. Analysis of variance (ANOVA) was used to determine if
~
oo~6
A o
0.015 "--'-O White Arneric;nlndian
Yu~ik
Al;ut
Inu'piat
Athab~ascar~Tlinkit'/Haida
RACE
FIG. 1. Mean alcohol elimination rates by race for males with lower and upper confidence limits (p = 0.05). ANOVAF(6, 9194) = 9.48, p < 0.000, based on a minimum BALin of 0.01, a minimum BALout of .01, a minimum 1 h stay and an elimination rate > 0. Duncan Multiple Range Test showed that whites differed from groups at the .05 level.
ETHANOL ELIMINATION AMONG RACIAL GROUPS 0.0099), Inupiat Eskimo, 0.0176 (SD = 0.0103), and Aleut, 0.0173 (SD = 0.0108). The Duncan Multiple Range Test, which examines mean differences among pairwise comparisons, revealed that the mean rate for the six Native groups differed significantly (p < 0.05) from the mean rate for whites. Additionally, a test for homogeneity of variance (Bartlet-Box F-test) indicated that the seven groups showed a homogeneity of variance, F = 19.169,p < 0.000. Inspection of Fig. 1 shows that whites had the lowest mean alcohol elimination rate, followed by American Indians. The rates were higher for the Alaskan Native groups, with Tlingit/ Haida Indians showing the highest mean rate of alcohol elimination. These findings can be interpreted to indicate that Whites, in comparison with the Native groups, showed the slowest rate of alcohol elimination. (It should be noted that the results in Fig. 1 do not imply linearity, because the data on the abscissa are categorical.) A comparable analysis for women was precluded by small sample sizes for similar racial groups, hut by using fewer groups, a one-way ANOVA was applied to test for differences in rates of alcohol elimination between whites and three Alaskan Native groups: Athabascan, Yupik, and Inupiat Eskimo. Figure 2 conveys the findings from this comparison, based on a minimum of 5 hours at the SOC, a minimum entry BAL of 0.10, a minimum exit BAL of 0.01, and an elimination rate greater than 0. A significant difference was obtained, F(3,887) = 11.807, p < 0.000. The mean rates were: Whites, 0.0151 (n = 78); Athabascan, 0.0159 (n = 182); Yupik, 0.0172 (n = 198); and Inupiat, 0.0184 (n = 433). A planned orthogonal contrast analysis found that a linear combination of White women differed significantly, t(df = 420) = 78.93,p < 0.000, from Eskimo and Athabascan women. The results of the Duncan Multiple Range Test indicated that white and Athabascan women differed significantly (p < 0.05) from Inupiat and Yupik women. The variance among these groups was found to be homogeneous (Bartlet-Box, F = 15.517, p < 0.001).
0.020 Upper Limit 0,019 IJJ I" < n-
•
Mean Rate
D
Lower Limit
0.018 -
Z
o I-<
0~017 " &
3 0.016 "
A
0.015
•
0,014
[] i White
,..I i. D
i Ath~an
!
i
Yupik
Inupiat
RACE
FIG. 2. Mean alcohol elimination rates by race for women with lower and upper confidence limits (p = 0.05). ANOVA F(3, 887) = 11.81, p < 0.0000, based on a minimum stay of 5 h, a minimum BALin of .10, a minimum BALout of .01 and an elimination rate > 0. Duncan Multiple Range Test showed that Whites differed from the other groups at the .05 level.
215
Alcohol Elimination by Gender and Age A three-way ANOVA (based on a minimum time of 5 h, a minimum entry BAL of 0.10, a minimum exit BAL of 0.001, and an elimination rate greater than 0), tested for differences between rate of alcohol elimination, gender, and race: Whites (n = 1268), Indians (n = 1709), Eskimos (n = 387), and Aleuts (n = 748). A significant difference, F(9, 7518) = 15.315, p < 0.000, was obtained among racial groups (White mean = 0.0157, SD = 0.0060; Indian mean = 0.0158, SD = 0.0063; Eskimo mean = 0.0160, SD = 0.0060; Aleut mean = 0.0153, SD = 0.0064), indicating that alcohol elimination rates differed among the groups. Significant main effects were also found between gender, F(I, 7 5 1 8 ) = 66.489, p < 0.000 (male mean = 0.0154, SD = 0.0060; female mean = 0.0174, SD = 0.0061), which suggests that women eliminated alcohol more rapidly than men. No significant difference was found between age and alcohol elimination rates. Two significant two-way interaction effects were obtained. One was between race and gender, F(3, 7518) = 5.853, p < 0.001, the other between gender and age, F(15, 7518) = 3.381, p < 0.000. These interaction effects imply that, although different elimination rates were observed among the four racial groups, alcohol elimination differences cannot be accounted for by race alone. Both gender and age influence alcohol elimination rates. These two variables are examined in more detail next.
Length of Drinking and Alcohol Elimination Because age is apparently a factor in alcohol elimination, the role of this variable in relation to alcohol elimination was explored further by using an age-derived variable-length of drinking. Alcoholics or long-term drinkers have been reported to metabolize alcohol more quickly than shorter-term drinkers (22). Bivariate Pearson correlation coefficients were derived between length of drinking and the average rate (of alcohol elimination) per individual for the total sample, for males, females, and for white and Alaskan Native males and females. Length of drinking was derived from responses given to items on a questionnaire administered as part of the larger study that examined drinking behavior among public inebriates (30). Drinking behavior ranged from 1-55 years, with a mean of 20.5 years. Only those cases that had completed a questionnaire, and whose rates were derived, were included in this analysis (AT = 419). All the coefficients obtained were either zero or approximated zero. This led to the conclusion that there was either no relationship between these variables or that the relationship could be nonlinear. An examination of the scatterplots suggested that the relationships were nonlinear (or curvilinear). Using the BMDP 3R program (7), nonlinear functions were derived by the least squares method using a modified GausNewton algorithm that does not require the specification of derivatives. The results of the nonlinear regression analyses were all highly negative and statistically significant ( - 0 . 9 3 for all males, - 0 . 9 0 for all females, - 0 . 8 9 for white males, - 0 . 9 4 for Alaskan Native males, - 0 . 8 9 and - 0 . 8 9 for Alaskan Native females). The magnitude and direction of these correlations indicate that, as length of drinking increased, rates of ethanol elimination decreased, but in a nonlinear manner, suggesting that the change in rate occurred at a decreasing ratio, not as a fixed ratio, in relation to length of drinking. The finding that the rate of alcohol elimination decreased
216
SEGAL AND DUFFY
over time is incompatible with an expectation, based on the findings by Mufti (22), that long-term drinkers showed enhanced alcohol elimination. DISCUSSION This study, which is an antecedent to more in-depth studies of alcohol elimination in this population, is one of the first field studies that investigated ethanol elimination among different racial groups, specifically observing the rate of ethanol disappearance from the blood principally among Alaskan Natives. At present, there is very minimal knowledge of the biological aspects of alcoholism among Alaskan Natives, The study's findings suggest that ethanol was eliminated at different rates among the different racial groups in the study population, with Alaskan Natives specifically showing a higher rate of ethanol elimination in comparison to Whites and American Indians. An important implication of this finding of the faster rate of ethanol elimination shown by Alaskan Natives is a challenge to any assumption that they eliminate alcohol slower than other races. The results support the research expectation that Native Americans (of presumed Asian ancestry) showed a more rapid rate of alcohol elimination in comparison with Whites (of presumed European ancestry). Additionally, the finding that Native Americans, who are presumed to be of relatively recent Asian or Oriental ancestry, eliminated alcohol more rapidly than whites is consistent with the recent report by Thomasson et al. (36) that Orientals tended to eliminate ethanol more quickly than non-Orientals. The current research examined elimination rates for alcohol, and did not study metabolism because a lack of body weight data prevented the report of elimination rates as grams ethanol per hour per body weight. Future research on the same population will include measurements pertaining to body weight, malnutrition, obesity, liver dysfunction, and other variables that are specifically important for comparison with other studies. It can be assumed, however, that elimination of alcohol from the bloodstream is related to the metabolism of alcohol. With this assumption in mind, the study's finding contrasts with those of Fenna et al. (9), who reported that: "Natives [Canadian Eskimos and Indians] metabolize alcohol at a significantly slower rate than the whites" (p. 475), and with Bennion and Li's (4) finding of no difference in alcohol metabolism between American Indians and whites. The current findings are consistent with those of Farris and Jones (8), who found that an "American Indian group metabolized
alcohol significantly faster than a group of C a u c a s i a n s . . . " (p. 8). Additionally, Agarwal and Goedde (3) noted that research showed that Indians and Alaskan Natives metabolize alcohol more rapidly than Caucasians. The findings also revealed that women eliminated ethanol more quickly than men. Segal (30) found that women tend to drink more heavily than men, which may contribute to the differences in alcohol loss between genders. Frezza et al. (10), however reported no significant differences in blood alcohol levels, AUC values, or "rates of elimination of ethanol between men and women after the intravenous administration of ethanol, even though we confirmed that the volume of ethanol distribution is lower in women. Thus, an additional mechanism must explain the large sex-related differences in blood ethanol concentrations after oral adminstration" (p. 97). Further research is clearly needed to explain this complex process. It is evident that further research is needed: specifically, controlled metabolic and genetic studies that address the findings in the current study. There is little knowledge about the frequency of genotypes for both alcohol and aldehyde dehydrogenase, particularly among Alaskan Natives. It remains to be determined if Alaskan Natives show ALDH or ADH genotypes similar to Orientals. The uniform negative nonlinear correlation coefficients revealed suggest that the rate of ethanol clearance slows down in long-term drinkers (i.e., chronic drinkers or alcoholics). This finding, in light of the elimination results pertaining to ethnicity, implies that although the process of alcohol elimination may slow down or be inhibited over time as a function of consistent drinking, the rate of alcohol elimination nevertheless differs among racial groups. Our findings are in keeping with those of Nuutinen et al. (24) who, in a study of chronic alcoholics, found a slower rate of alcohol oxidation among chronic drinkers, which they attributed to an impaired capacity to metabolize acetaldehyde. ACKNOWLEDGEMENTS Funded in part by a grant from NIAA/NIDA, No. RI8-AA07961 and an award from the Alaska-Siberian Medical Research Program, University of Alaska Anchorage. The assistance of Dr. T. -K. Li, Department of Medicine, Indiana University Medical Center, is greatly appreciated. We also appreciate the assistance provided by Victor J. Kapella, Systems Manager, Computing and Technical Services, University of Alaska Anchorage, for the extra services he provided.
REFERENCES 1. Anthenelli, R. M.; Schuckit, M. A. Genetic studies of alcoholism. Int. J. Addictions 25:81-94; 1990-1991. 2. Agarwal, D. P.; Goedde, H. W. Human aldehydrogenases: Their role in alcoholism. Alcoholism 6:517-523; 1989. 3. Agarwal, D. P.; Goedde, H. W. Pharmacogenetics of alcohol dehydrogenase (ADH). Pharmacol. Ther. 45:69-83; 1990. 4. Bennion, L. J.; Li, T. -K. Alcohol metabolism in American Indians and whites: Lack of racial differences in metabolic rate and lever alcohol dehydrogenase. New Engl. J. Med. 294:9-13; 1976. 5. Bosron, W. F.; Li, T. -K. Generic determinants of alcohol and aldehyde dehydrogenase and alcohol metabolism. Semin. Liver Dis. 1:179; 1981. 6. Cloninger, C. R. Recent advances in family studies of alcoholism. In Goedde, H. W.; Agarwal, D. P., eds. Genetics and alcoholism. New York: Liss; 1987:47-60. 7. Dixon, W. J.; Brown, M. B.; Engelman, L.; Hill, M. A.; Jenn-
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9. 10.
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rich, R. I. BMDP statistical software manual (vol. 2), Los Angeles: University of California Press; 1990. Farris, J. J.; Jones, B. M. Ethanol metabolism in male American Indians and Caucasians. Paper presented at the 8th Annual NCA-AMSA Medical-Scientific Sessionof the National Alcoholism Forum, San Diego, CA, May, 1977. Fenna, D.; Mix, L.; Schaefer, O.; Gilbert, J. A. L. Ethanol metabolism in various racial groups. Can. Med. Assoc. J. 105:472475; 1971. Frezza, M.; diPadova, C.; Pozzato, G.; Terpin, M.; Baraona, E.; Leiber, C. S. High blood alcohol levels in women: The role of decreased gastric alcohol dehydrogenaseactivity and first pass metabolism. New Engl. J. Med. 322:95-129; 1990. Goedde, W. H.; Agarwal, D. P. Pharmacogenetics of aldehyde dehydrogenase (ALDH). Pharmacol. Theory 45:345-371; 1990. Goedde, W. H.; Singh, S.; Agarwal, D. P.; Fritze, G.; Stapel,
ETHANOL
13. 14. 15. 16. 17.
18. 19. 20. 21. 22. 23.
24.
ELIMINATION
AMONG
RACIAL GROUPS
K.; Pail, Y, K. Genotyping of mitochondrial aldehyde dehydrogenase in blood samples using allele-specific oligonucleotides: Comparison with phenotyping in hair roots. Hum. Genet. 81: 305-307; 1989. Goodwin, D. W. Is alcoholism hereditary? 2nd ed. New York: Ballantine Books; 1988. Hannu, N.; Lindros, K. O.; Salaspuro, M. Determinants of blood acetaldehyde level during ethanol oxidation in chronic alcoholics. Alcoholism Clin. Exper. Res. 7:163-168; 1983. Harada, S.; Agarwal, D. P.; Goedde, W. H. Aldehyde dehydrogenase polymorphism and alcohol metabolism in alcoholics. Alcohol 2:391-396; 1985. Holden, C. Probing the complex genetics of alcoholism. Science 151:1630; 1991. Lieber, C. S.; Baraona, E.; Gordon, E. R.; Jauhonen, P.; Lebsack, M. E.; Pikkarainen, P. Elevation of acetaldehyde levels after chronic alcohol consumption: Pathogenesis and pathologic consequences. In: Hesselbrock, V. M.; Shaskan, E. G.; Meyes, R. E., eds. Biological/genetic factors in alcoholism. Rockville, MD: NIAAA; 1983:67-91. Li, T. -K. Enzymology of human alcohol metabolism. Advances in Enzymology 45:427; 1977. Li, T. -K.; Bosron, W. F. Genetic variability of enzymes of alcohol metabolism in humans. Ann. Emerg. Med. 15:997-1004; 1986. Lumeng, L.; Durant, P. J. Regulation of the formation of stable adducts between acetaldehyde and blood proteins. Alcohol 2:397; 1985. Myers, R. D. Tetrahydoisoquinolines in the brain: The basis of an animal model of alcoholism. Alcoholism: Clin. Exp. Res. 2: 145-154; 1978. Mufti, S. I. Ethanol metabolites as indicators of alcohol abuse. In: Watson, R. R. ed. Diagnosis of alcohol abuse. Boca Raton, FL: CRC Press; 1989:9-26. Nagoshi, C. T.; Dixon, L. K.; Johnson, R. C.; Yuen, S. H. L. Familial transmission of alcohol consumption and the flushing response to alcohol in three Oriental groups. J. Studies of Alcohol 49:261-267; 1988. Reed, T. E.; Kant, H. Bias in calculated rate of alcohol metabolism due to variation in relative amounts of adipose tissue. J. Studies on Alcohol 38:1773-1779; 1977.
217 25. Rex, D. K.; Bosron, W. F.; Smialek, J. E.; Li, T. -K. Alcohol and aldehyde dehydrogenase isoenzymes in North American Indians. Alcoholism: Clin. Expel Res. 9:147-152; 1977. 26. Ross, D. H. Inhibition of high affinity calcium binding by salsol. Alcoholism. Clin. Exper. Res. 2:139-143; 1985. 27. Schuckit, M. A. Biological vulnerability to alcoholism. J. Consult. Clin. Psychol. 55:301-309; 1987. 28. Schuckit, M. A. Studies of populations at high risk for the future development of alcoholism. In: Goedde, H. W.; Agarwal, D. P. eds. Genetics and alcoholism. New York: Liss, 1987:51-59. 29. Segal, B. Drinking and Homelessness: A study of a street population. Drugs and Society 6; 1992. 30. Shibuya, A.; Yoshida, A. Genotypes of alcohol-metabolizing enzymes in Japanese with alcohol lever disease: A string association of the usual Caucasian-type aldehyde dehydrogenase gene (ALDH) with the disease. Am. J. Hum. Genet. 43:741-743; 1989. 31. Shuster, L. Genetics of responses to drugs of abuse. Int. J. Addictions 25T:57-79; 1990. 32. Singh, S.; Fritze, G.; Fang, B.; Harada, S.; Paik, Y. K.; Eckey, R.; Agarwal, D. P.; Goedde, W. H. Inheritance of mitochondrial aldehyde dehydrogenase: Genotyping in Chinese, Japanese and South Korean families reveals dominance of the mutant allele. Hum. Genet. 83:119-121; 1989. 33. SPSS: SPSS-X user's guide. 4th ed. Chicago, IL: SPSS; 1990. 34. Tabakoff, B.; Hoffman, P. L. Genetics and biological markers of risk for alcoholism. Public Health Reports 103:690-698; 1990. 35. Thomasson, H. R.; Edenberg, H. J.; Crabb, D. W.; Mai, X. -L.; Jermone, R. E.; Li, T. -K.; Wange, S. -P.; Lin, Y. -T.; Lu, R. -B.; Yin, S. -J. Alcohol and alcohol dehydrogenase genotypes and alcoholism in Chinese men. Am. J. Hum. Genet. 48:677; 1991. 36. Yoshida, A.; Wang, G.; Dave, V. Determination of genotypes of human liver aldehyde dehydrogenase ALDH2 locus. Am. J. Hum. Genet. 35:1107-1116; 1983. 37. Zeiner, A. R. Biological sensitivity to alcohol. Paper presented at the International Research Workshop, Long Beach, CA, October 1980.
0741-8329/92 $5.00 + .00 Copyright © 1992 Pergamon Press Ltd.
Printed in the U.S.A. All rights reserved.
Ethanol Elimination Among Different Racial Groups B E R N A R D S E G A L *l A N D L A W R E N C E K. D U F F Y ~
*Department o f Health Sciences, University o f Alaska Anchorage, Anchorage, A K 99508 tInstitute o f Arctic Biology and Department o f Chemistry, University o f Alaska Fairbanks, Fairbanks, A K 99775-0180 Received 16 September 1991; Accepted 21 N o v e m b e r 1991 SEGAL, B. AND L. K. DUFFY. Ethanoleliminationamongdifferent racialgroups. ALCOHOL 9(3)213-217, 1992.This study examined the relationship between ethanol elimination and race, specifically exploring differences among Alaskan Natives, American Indians, and whites. Native Americans, believed to be of recent Asian origin, were expected to eliminate alcohol faster than whites. The data suggested that both Native American men and women eliminated alcohol faster than whites. A relationship was also found between age, gender, and rate of alcohol elimination. The implications of these findings were reviewed and specific needs for future research were noted. Alcohol
Ethanol elimination
Race
known, however, about the distribution frequency of the A L D H and ADH polymorphisms (or other genetic differences) in northern racial groups such as Alaskan Natives, who are believed to have an Oriental ancestry. Further studies are needed to assess the consistency of differences in ADH and ALDH genotypcs in different racial groups, and to determine the extent to which they differ across different racial groups. These studies are important with respect to groups who differ culturally and racially, but who may share a relatively recent common ancestry. This research, in anticipation of genetic studies, examined differences in reduction of blood alcohol levels among heavy drinkers of different racial groups. Because genetic differences could contribute to variations in alcohol elimination among these two racial groups, it was anticipated that Alaskan Natives would show a more rapid rate of alcohol reduction in comparison with whites (of presumed European ancestry).
SIGNIFICANT attention in recent years, in the form of family, twin, adoption, and other genetic studies, has been directed at the role that heredity plays in the etiology of alcoholism (1,6,13,16,19,32,35). The results of these studies have led to the discovery of different levels of alcohol sensitivity and varying pharmacological behavior among individuals of different racial groups (3,4,12,28,31,33,36,38). It has been shown, for example, that aldehyde dehydrogenase is a key enzyme in alcohol metabolism (5,18), and that the aldehyde dehydrogenase polymorphism provides the genetic base for facial flushing among Orientals (15). Although research results are mixed, it appears that people of Asian ancestry (Chinese and Japanese) metabolize alcohol to acetate more rapidly than non-Asians. This has been attributed to the presence in some Orientals of an atypical form of alcohol dehydrogenase (ADH) that metabolizes ethanol more efficiently to acetaldehyde than the normal form. Agarwal and Goedde (2) reported that about 50% of the Asians they studied showed an undue accumulation of acetaldehyde, seemingly attributable to the relatively inefficient or completely inefficient variant of aldehyde dehydrogenase (ALDH). The blocking of enzymatic degradation of acetaldehyde can result in unpleasant side effects after alcohol consumption, such as facial flushing, palpitations, muscle weakness, and headaches. This strong aversive reaction has been interpreted as protecting people with aldehyde dehydrogenase deficiency from becoming alcoholic (23,37). Research (36) has shown that the prevalence of the gene alleles for both atypical ADH and the inactive variant of A L D H are lower in alcoholic Chinese subjects than in nonalcoholic subjects. Little is
METHOD
This article conveys findings from an extended study of a diverse drinking population in Anchorage, AK. The data were derived from a comprehensive research and demonstration project enacted to attempt to intervene in the lifestyle of chronic homeless drinkers. Park of this project involved the establishment of a 2,4-hour sobering center [Sleep-off Center (SOC)] in which homeless street people, many of whom would be intoxicated, could find shelter. This report is based on data derived from this project during 1988 (30).
To whom requests for reprints should be addressed. 213
214
SEGAL AND DUFFY
Subjects All clients entering the SOC were logged in at their time of entry, which required that name, residential status, race, age, gender, entry time, date, referral source, condition on entry, and use of alcohol and other drugs be recorded. Upon departure, the date, time of leaving, and destination were documented. The intake log was maintained by staff members who were trained to elicit information from intoxicated clientele. In addition to the demographic data, an attempt was made to obtain an entry and exit blood alcohol level (BAL) on all clients using an Intoximeter IR 3000 Model breathalyzer, which requires that a deep breath be blown into a tube to obtain a reading. A comprehensive description of the client population is presented elsewhere (30). Briefly, a total of 22,282 multiple (or duplicated) entries to the SOC were made by 1749 unique (or unduplicated) persons (mean age 37.1 years). Of these individual cases, 81070 were male (n = 1416) and 19070 were female (n = 333). The racial composition was: white, 27.6°/0; Alaskan Native, 64.6070; Black, 2.4070; American Indian, 3.1070; Hispanic, 1.3 %; Asian Pacific 0.2 070; and other 0.9 %. The data for this study were derived from 632 cases (selected from a subject pool of 1749 unique cases), for whom entry and exit times and entry and exit BALs were complete, and who stayed at the SOC for a minimum of 1 hour on each entry. Many of these subjects had completed a questionnaire that assessed a wide array of information encompassing demographic data, drinking and drug-taking behavior, social functioning, economic and occupational data, and legal involvement. The interviews were obtained when they were sober. The subject pool, from which the data reported herein were derived, consisted of 531 men (mean age 37.4 years) and 101 women (mean age 38.8 years), whose entries to the SOC amounted to a collective total of 10,436 times, of which 9201 were by men and 1235 by women. Of these, 141 were white males, 21 were American Indian (from the lower 48 states), 80 were Athabascan Indian, 24 Tlingit/Halda Indian, 107 Yupik Eskimo, 102 Inupiat Eskimo, and 56 Aleut. Nine of the women were white, 20 were Athabascan Indian, 30 Yupik Eskimo, and 42 Inupiat Eskimo. The data were analyzed separately by gender to control for variations in body weight and physiological differences between men and women.
significant differences existed between BAL rates and race. One-way analyses were first conducted separately for men and women, followed by a two-way ANOVA that tested for differences between race (white and Alaskan Native) and gender. Only cases with an alcohol elimination rate or ratio greater than zero were included to avoid obtaining a skewed rate distribution. The procedures were executed on a Digital Vax 8800 computer using a SPSS program (32). RESULTS
Male admission drinking levels, as reflected by multiple entry BALs on the same cases, ranged from 0.001 to a high of 0.434, with a mean entry BAL of 0.204 (SD = 0.053); on departure, exit BALs ranged from 0.002 to a high of 0.406, with a mean value of 0.094 (SD = 0.056). Female entry BALs, also representative of multiple entries on the same cases, ranged from 0.005-0.393, with a mean entry BAL of 0.212 (SD = 0.051). Exit female BALs ranged from 0.0020.370, with a mean exit BAL of 0.091 (SD = 0.958). Time at the SOC averaged 7.19 h (SD = 3.14) for men and 7.00 h for women (SD = 3.24).
Alcohol Elimination by Race A one-way ANOVA was used to test for differences between alcohol elimination rate (if greater than zero) and race as represented by membership in one of seven groups: white, American Indian, Athabascan Indian, Tlingit/Haida Indian, Yupik Eskimo, Inupiat Eskimo, and Aleut. The latter five groups are known as "Alaskan Natives"; all six nonwhite groups are collectively referred to as Native Americans. This analysis involved all cases with a minimum entry BAL of 0.01, a minimum exit BAL of 0.01, a minimum 1 hour stay, and an elimination rate greater than zero. Figure 1 shows the results of this analysis, which yielded a statistically significant difference, F(6, 9194) = 9.4816, p < 0.0000, among the groups. The mean rates for each group were: White, 0.0154 (SD = 0.0086), American Indian, 0.0167 (SD = 0.0093), Athabascan, 0.0177 (SD = 0.0110), Tlingit/ Haida, 0.0178 (SD = 0.0105), Yupik Eskimo, 0.0170 (SD =
Blood Alcohol Levels
A U!~oer Limit MeanRate [] Lower Limit •
Each client's length of time at the SOC was paired with the difference between his or her entry and departure blood alcohol level (gram 070). A rate of alcohol elimination was derived by dividing blood alcohol difference by time at the SOC. The following equation was used to calculate an ethanol elimination rate:
A
&
0018 m
/,
A
Z
$
o
0.017
•
o
o []
Rate (in g070/h) =
BALi. - BALout Time at SOC
The resulting statistic (rate) is an empirically derived index representing change in blood alcohol content that was independent of length of time at the SOC and independent of entry BALs. The time between BAL measurements for cases used in this study was never less than 1 hour. A minimum exit BAL of 0.01 was selected so that comparisons would be based on the early part of the elimination curve. Analysis of variance (ANOVA) was used to determine if
~
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A o
0.015 "--'-O White Arneric;nlndian
Yu~ik
Al;ut
Inu'piat
Athab~ascar~Tlinkit'/Haida
RACE
FIG. 1. Mean alcohol elimination rates by race for males with lower and upper confidence limits (p = 0.05). ANOVAF(6, 9194) = 9.48, p < 0.000, based on a minimum BALin of 0.01, a minimum BALout of .01, a minimum 1 h stay and an elimination rate > 0. Duncan Multiple Range Test showed that whites differed from groups at the .05 level.
ETHANOL ELIMINATION AMONG RACIAL GROUPS 0.0099), Inupiat Eskimo, 0.0176 (SD = 0.0103), and Aleut, 0.0173 (SD = 0.0108). The Duncan Multiple Range Test, which examines mean differences among pairwise comparisons, revealed that the mean rate for the six Native groups differed significantly (p < 0.05) from the mean rate for whites. Additionally, a test for homogeneity of variance (Bartlet-Box F-test) indicated that the seven groups showed a homogeneity of variance, F = 19.169,p < 0.000. Inspection of Fig. 1 shows that whites had the lowest mean alcohol elimination rate, followed by American Indians. The rates were higher for the Alaskan Native groups, with Tlingit/ Haida Indians showing the highest mean rate of alcohol elimination. These findings can be interpreted to indicate that Whites, in comparison with the Native groups, showed the slowest rate of alcohol elimination. (It should be noted that the results in Fig. 1 do not imply linearity, because the data on the abscissa are categorical.) A comparable analysis for women was precluded by small sample sizes for similar racial groups, hut by using fewer groups, a one-way ANOVA was applied to test for differences in rates of alcohol elimination between whites and three Alaskan Native groups: Athabascan, Yupik, and Inupiat Eskimo. Figure 2 conveys the findings from this comparison, based on a minimum of 5 hours at the SOC, a minimum entry BAL of 0.10, a minimum exit BAL of 0.01, and an elimination rate greater than 0. A significant difference was obtained, F(3,887) = 11.807, p < 0.000. The mean rates were: Whites, 0.0151 (n = 78); Athabascan, 0.0159 (n = 182); Yupik, 0.0172 (n = 198); and Inupiat, 0.0184 (n = 433). A planned orthogonal contrast analysis found that a linear combination of White women differed significantly, t(df = 420) = 78.93,p < 0.000, from Eskimo and Athabascan women. The results of the Duncan Multiple Range Test indicated that white and Athabascan women differed significantly (p < 0.05) from Inupiat and Yupik women. The variance among these groups was found to be homogeneous (Bartlet-Box, F = 15.517, p < 0.001).
0.020 Upper Limit 0,019 IJJ I" < n-
•
Mean Rate
D
Lower Limit
0.018 -
Z
o I-<
0~017 " &
3 0.016 "
A
0.015
•
0,014
[] i White
,..I i. D
i Ath~an
!
i
Yupik
Inupiat
RACE
FIG. 2. Mean alcohol elimination rates by race for women with lower and upper confidence limits (p = 0.05). ANOVA F(3, 887) = 11.81, p < 0.0000, based on a minimum stay of 5 h, a minimum BALin of .10, a minimum BALout of .01 and an elimination rate > 0. Duncan Multiple Range Test showed that Whites differed from the other groups at the .05 level.
215
Alcohol Elimination by Gender and Age A three-way ANOVA (based on a minimum time of 5 h, a minimum entry BAL of 0.10, a minimum exit BAL of 0.001, and an elimination rate greater than 0), tested for differences between rate of alcohol elimination, gender, and race: Whites (n = 1268), Indians (n = 1709), Eskimos (n = 387), and Aleuts (n = 748). A significant difference, F(9, 7518) = 15.315, p < 0.000, was obtained among racial groups (White mean = 0.0157, SD = 0.0060; Indian mean = 0.0158, SD = 0.0063; Eskimo mean = 0.0160, SD = 0.0060; Aleut mean = 0.0153, SD = 0.0064), indicating that alcohol elimination rates differed among the groups. Significant main effects were also found between gender, F(I, 7 5 1 8 ) = 66.489, p < 0.000 (male mean = 0.0154, SD = 0.0060; female mean = 0.0174, SD = 0.0061), which suggests that women eliminated alcohol more rapidly than men. No significant difference was found between age and alcohol elimination rates. Two significant two-way interaction effects were obtained. One was between race and gender, F(3, 7518) = 5.853, p < 0.001, the other between gender and age, F(15, 7518) = 3.381, p < 0.000. These interaction effects imply that, although different elimination rates were observed among the four racial groups, alcohol elimination differences cannot be accounted for by race alone. Both gender and age influence alcohol elimination rates. These two variables are examined in more detail next.
Length of Drinking and Alcohol Elimination Because age is apparently a factor in alcohol elimination, the role of this variable in relation to alcohol elimination was explored further by using an age-derived variable-length of drinking. Alcoholics or long-term drinkers have been reported to metabolize alcohol more quickly than shorter-term drinkers (22). Bivariate Pearson correlation coefficients were derived between length of drinking and the average rate (of alcohol elimination) per individual for the total sample, for males, females, and for white and Alaskan Native males and females. Length of drinking was derived from responses given to items on a questionnaire administered as part of the larger study that examined drinking behavior among public inebriates (30). Drinking behavior ranged from 1-55 years, with a mean of 20.5 years. Only those cases that had completed a questionnaire, and whose rates were derived, were included in this analysis (AT = 419). All the coefficients obtained were either zero or approximated zero. This led to the conclusion that there was either no relationship between these variables or that the relationship could be nonlinear. An examination of the scatterplots suggested that the relationships were nonlinear (or curvilinear). Using the BMDP 3R program (7), nonlinear functions were derived by the least squares method using a modified GausNewton algorithm that does not require the specification of derivatives. The results of the nonlinear regression analyses were all highly negative and statistically significant ( - 0 . 9 3 for all males, - 0 . 9 0 for all females, - 0 . 8 9 for white males, - 0 . 9 4 for Alaskan Native males, - 0 . 8 9 and - 0 . 8 9 for Alaskan Native females). The magnitude and direction of these correlations indicate that, as length of drinking increased, rates of ethanol elimination decreased, but in a nonlinear manner, suggesting that the change in rate occurred at a decreasing ratio, not as a fixed ratio, in relation to length of drinking. The finding that the rate of alcohol elimination decreased
216
SEGAL AND DUFFY
over time is incompatible with an expectation, based on the findings by Mufti (22), that long-term drinkers showed enhanced alcohol elimination. DISCUSSION This study, which is an antecedent to more in-depth studies of alcohol elimination in this population, is one of the first field studies that investigated ethanol elimination among different racial groups, specifically observing the rate of ethanol disappearance from the blood principally among Alaskan Natives. At present, there is very minimal knowledge of the biological aspects of alcoholism among Alaskan Natives, The study's findings suggest that ethanol was eliminated at different rates among the different racial groups in the study population, with Alaskan Natives specifically showing a higher rate of ethanol elimination in comparison to Whites and American Indians. An important implication of this finding of the faster rate of ethanol elimination shown by Alaskan Natives is a challenge to any assumption that they eliminate alcohol slower than other races. The results support the research expectation that Native Americans (of presumed Asian ancestry) showed a more rapid rate of alcohol elimination in comparison with Whites (of presumed European ancestry). Additionally, the finding that Native Americans, who are presumed to be of relatively recent Asian or Oriental ancestry, eliminated alcohol more rapidly than whites is consistent with the recent report by Thomasson et al. (36) that Orientals tended to eliminate ethanol more quickly than non-Orientals. The current research examined elimination rates for alcohol, and did not study metabolism because a lack of body weight data prevented the report of elimination rates as grams ethanol per hour per body weight. Future research on the same population will include measurements pertaining to body weight, malnutrition, obesity, liver dysfunction, and other variables that are specifically important for comparison with other studies. It can be assumed, however, that elimination of alcohol from the bloodstream is related to the metabolism of alcohol. With this assumption in mind, the study's finding contrasts with those of Fenna et al. (9), who reported that: "Natives [Canadian Eskimos and Indians] metabolize alcohol at a significantly slower rate than the whites" (p. 475), and with Bennion and Li's (4) finding of no difference in alcohol metabolism between American Indians and whites. The current findings are consistent with those of Farris and Jones (8), who found that an "American Indian group metabolized
alcohol significantly faster than a group of C a u c a s i a n s . . . " (p. 8). Additionally, Agarwal and Goedde (3) noted that research showed that Indians and Alaskan Natives metabolize alcohol more rapidly than Caucasians. The findings also revealed that women eliminated ethanol more quickly than men. Segal (30) found that women tend to drink more heavily than men, which may contribute to the differences in alcohol loss between genders. Frezza et al. (10), however reported no significant differences in blood alcohol levels, AUC values, or "rates of elimination of ethanol between men and women after the intravenous administration of ethanol, even though we confirmed that the volume of ethanol distribution is lower in women. Thus, an additional mechanism must explain the large sex-related differences in blood ethanol concentrations after oral adminstration" (p. 97). Further research is clearly needed to explain this complex process. It is evident that further research is needed: specifically, controlled metabolic and genetic studies that address the findings in the current study. There is little knowledge about the frequency of genotypes for both alcohol and aldehyde dehydrogenase, particularly among Alaskan Natives. It remains to be determined if Alaskan Natives show ALDH or ADH genotypes similar to Orientals. The uniform negative nonlinear correlation coefficients revealed suggest that the rate of ethanol clearance slows down in long-term drinkers (i.e., chronic drinkers or alcoholics). This finding, in light of the elimination results pertaining to ethnicity, implies that although the process of alcohol elimination may slow down or be inhibited over time as a function of consistent drinking, the rate of alcohol elimination nevertheless differs among racial groups. Our findings are in keeping with those of Nuutinen et al. (24) who, in a study of chronic alcoholics, found a slower rate of alcohol oxidation among chronic drinkers, which they attributed to an impaired capacity to metabolize acetaldehyde. ACKNOWLEDGEMENTS Funded in part by a grant from NIAA/NIDA, No. RI8-AA07961 and an award from the Alaska-Siberian Medical Research Program, University of Alaska Anchorage. The assistance of Dr. T. -K. Li, Department of Medicine, Indiana University Medical Center, is greatly appreciated. We also appreciate the assistance provided by Victor J. Kapella, Systems Manager, Computing and Technical Services, University of Alaska Anchorage, for the extra services he provided.
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ETHANOL
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ELIMINATION
AMONG
RACIAL GROUPS
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