Psychiatric Annals

Weight Gain After Adolescent Drug Addiction Treatment and Supervised Abstinence

Candace C Hodgkins, MA, LMCH; William S Jacobs, MD; Mark S Gold, MD

Abstract

DATA AND METHODS

Source of Data

This study was conducted at an adolescent residential substance abuse treatment center in a southeastern city in the United States. The facility is a 40-bed substance abuse treatment center for males and females, aged 13 to 18 years. This population of adolescents is referred to the program by three different means: self-referral, civil commitment by parents, or adjudicated by the court system. The clients are housed on the campus 24 hours a day, 7 days a week, with the average length of stay amounting to 5 and a half months. All information for this particular study was gathered from individual charts that are retained by the organization. Each client signs a consent form giving the organization permission to use data from the charts for research, with the understanding that all identifying information will be kept confidential. Because the lead researcher is an employee of this organization, the researcher was able to gather the data from each chart with the permission of the CEO. This research project was reviewed and approved by the University of Florida Institutional Review Board.

Analysis

There are a total of 93 charts for the months from August 1999 to July 2000 for both male and female clients. Thirtytwo charts were chosen randomly to create the sample population of charts to examine. Two were missing data; therefore, the final sample was 30 charts. The range of time between the admit date and July 1, 2000, is between 1 month and 1 1 months, with the largest cluster (13) grouped in May and June of 2000. For this design the available procedure for testing equality of mean weight gain is the dependent samples f test. For this study SPSS software was used for the statistical analysis. The significance is set at a = 0.05. Of this client population, 87.1% were male and 12.9% were female.

Results

The mean age in the total sample population is 15.9. Descriptive statistics are presented in Table 2. The mean July weight (JXJLWGT) of 165.97 pounds for clients appears to be larger than the mean admission weight (ADMWGT) of 150.78 pounds. The mean July BMJ (JULBMI) of 24.69 of clients appears to be larger than the mean admission BMI (ADMBMI) of 22.43. The mean July height (JULHGT) of 68.7 inches for clients appears to be close to the same as the mean admission height (ADMHGT) of 68.69 inches.

The results of the paired sample t test indicate a statistically significant difference between ADMWGT and JULWGT. The / = -9.003 (30), P < 0.05, P = .000. The results from the paired sample t test indicate a statistically significant difference between ADMBMI and JULBMI (r = -9.4 1 7 [30], P < 0.05, P = .000). The results from the paired sample / test indicate that there is not a statistically significant difference between ADMHGT and JULHGT (t = 0.311 [30], P > 0.05, P = 0.379). These results indicate that clients' weight and BMI increased between the time of entry into treatment and July 2000, and that clients' height showed no significant difference. At admission, 0.21 clients had a BMI greater than 25 but less than 30. At July 2000, 0.24 clients had a BMI greater than 25 but less than 30 and .07 clients had a BMI greater than 30 but less than 34.9.

DISCUSSION

Findings from this study suggest that there is significant weight increase while adolescents are residing in a supervised substance abuse treatment setting. This finding is particularly interesting due to the lack of increase in the height in this adolescent population during…

Alcohol and drug abuse, including tobacco, has been on the rise in the adolescent population for the past two decades, with a slight leveling off in 1991. The number of adolescents using alcohol and drugs in the United States is staggering. In 1992 the National Report on Substance Abuse reported that from 1962 to the mid-1980s there was a 48% increase in the number of individuals older than age 12 that had tried an illegal drug. Since the mid-80s, adolescent drug use has continued to increase. In the 1996 annual Monitoring the Future (MTF) Study, it was reported that 34% of high school seniors reported having been drunk in the past month, while one fifth of seniors and 10th graders had used marijuana in that same time period.2 In the 2001 annual MFT report, seniors who reported using alcohol on a daily basis increased from 2.9% to 3.6%, with seniors reporting being drunk in the last 30 days down to 30%.' Marijuana prevalence rates for use by seniors declined from 38.5% in 1997 to 37.0% in 2001. Overall use of illicit drugs remained stable between 2000 and 2001.

Youth are getting involved in the use of drugs and alcohol at a younger age, beginning at the ages of 10 to 13 with tobacco, beer, and wine drinking, then moving on to marijuana, cocaine, and club drugs.3·4 The 2000 MFT report cited 17% of 8th graders, 32% of 10th graders, and 38% of 12th graders using marijuana, which, along with tobacco and alcohol, is often called a "gateway drug" to other illicit drug use.5,6 Many youth become polysubstance abusers, with marijuana being the most widely used illicit drug. In recent years there has been a dramatic increase in the use of me illicit drug ecstasy (3,4methylenedioxymethylamphetamine), also known as a club drug because of its use at raves, party, and dance clubs where adolescents congregate for social interaction. Johnston et al. report that use of ecstasy in 8th graders, for past year use, rose from 1.7% in 1999 to 3.1% in 2000, while 10th graders use rose from 4.45% to 5.4%, and among 12th graders from 5.6% to 8.2%, making it a drug that is more frequently used by adolescents than cocaine.'

OBESITY PREVALENCE

Another alarming increase over die past 30 years is the prevalence of adult and adolescent obesity. Adolescent obesity is described by the Centers for Disease Control and Prevention as an epidemic responsible for dramatic increases in diabetes in children.1 The obesity literature suggests mat one in five of me child and adolescent population in me United States is overweight (body mass index [BMl] between 85th and 95th percentile) and one in four are at risk of becoming overweight.7,8 This is an alarming thought since youth from the ages of 10 to 19 represent 14.4% (39 257 000) of the U.S. population.9 Half of die current U.S. adult population (20 years and older) is overweight and one quarter suffers from obesity. That equates to 97.1 million adults being overweight and 39.8 million adults being obese.10 The prevalence of obesity in the United States among adolescents has led for calls for food restriction, exercise, less television watching, and bariatric surgery."

BODY MASS INDEX

Overweight is defined as an increase in weight relative to some standard. The three most common techniques for evaluating body weight are life insurance tables, relative weight (actual weight/ desirable weight multiplied by 100), and BMI. The standard definition of overweight is having a BMJ, which is calculated by weight in kilograms/height in meters squared, between the 85th and 95th percentile, with severe obesity being any BMl greater than the 95di percentile. For females and males, anytiiing greater than 30 BMI and greater man 25 BMT, respectively, is considered a health-related definition of obesity for the adolescent population.12 Body mass index was originally proposed by Quetelet more than 150 years ago but still correlates more closely with body fat composition than do other anhropometric relationships of height and weight. Body mass index remains the preferred measure in epidemiologic and population studies. Its chief limitation is tihat in me normal range (18.5 to 24.9) BMI is a poor guide to individual fat level because of the low correlation with actual body fat content. This limitation is also evident in extreme bodybuilders who, because of their large muscle mass, may have high BMI and low body fat content. However, with that exception, BMI above 25 and especially above 30, is an acceptable guide to the degree of excess fat and health risk (Table I).12

SUBSTANCE ABUSE AND EMOTIONAL PROBLEMS

Current research from Substance Abuse and Mental Health Services Administration (SAMHSA) reports there is a strong correlation between substance abuse and behavioral and emotional problems among youth.13 There is currently a significant coprevalence of adolescent substance use disorders with depression, anxiety, attentiondeficit/hyerpaetivity disorder, eating disorders, and childhood disruptive disorders but little current research on substance use and weight gain, obesity, or eating disorders.6 Those youth wim serious emotional problems were four times more likely than those with low levels of emotional problems to use illicit drugs, while those with behavioral problems were seven times as likely to use illicit drugs than those without significant behavioral problems. Weinberg et al. report mat drug use also clusters with delinquency, early sexual behavior and pregnancy.6 In a study done by Ross and Ivis, binge eaters were more likely to use all types of substances, with a high correlation existing with cannabis use.14

Table

TABLE 1

TABLE 1

Obesity in adolescence is as serious as the rise in adolescent substance abuse. Both issues are a major public health problem in the United States. The cost to society for health care related to these factors is extraordinary. Health care in die United States in 1993 cost $900 billion, while prevention and treatment cost a total of only $25 billion.15 Research shows that adolescents who are obese and those that are substance dependent have a propensity to continue these problems into adulthood. Weight in adolescence is a predictor of adult weight and later adverse health events, as substance abuse in adolescence is a predictor of substance abuse and dependence in adulthood.16

In recent studies, substance abuse and binge eating behaviors have been positively associated, presenting evidence tihat substance use is often times employed to alleviate feelings of low self-esteem and negative self-perception linked with binge eating, therefore reducing the tension caused by these thoughts and actions.17 Given that adolescence is an intensified period of selfconsciousness, where appearance and acceptance by peers are powerful influences on mood liability, it appears imperative that the addiction field address the issue of a possible correlation of weight gain and abstinence from drugs and alcohol.18 The time has come for intensified research regarding this possible correlation and determining whether it warrants inclusion as a treatment element.

Table

TABLE 2Study Statistics

TABLE 2

Study Statistics

DATA AND METHODS

Source of Data

This study was conducted at an adolescent residential substance abuse treatment center in a southeastern city in the United States. The facility is a 40-bed substance abuse treatment center for males and females, aged 13 to 18 years. This population of adolescents is referred to the program by three different means: self-referral, civil commitment by parents, or adjudicated by the court system. The clients are housed on the campus 24 hours a day, 7 days a week, with the average length of stay amounting to 5 and a half months. All information for this particular study was gathered from individual charts that are retained by the organization. Each client signs a consent form giving the organization permission to use data from the charts for research, with the understanding that all identifying information will be kept confidential. Because the lead researcher is an employee of this organization, the researcher was able to gather the data from each chart with the permission of the CEO. This research project was reviewed and approved by the University of Florida Institutional Review Board.

Analysis

There are a total of 93 charts for the months from August 1999 to July 2000 for both male and female clients. Thirtytwo charts were chosen randomly to create the sample population of charts to examine. Two were missing data; therefore, the final sample was 30 charts. The range of time between the admit date and July 1, 2000, is between 1 month and 1 1 months, with the largest cluster (13) grouped in May and June of 2000. For this design the available procedure for testing equality of mean weight gain is the dependent samples f test. For this study SPSS software was used for the statistical analysis. The significance is set at a = 0.05. Of this client population, 87.1% were male and 12.9% were female.

Results

The mean age in the total sample population is 15.9. Descriptive statistics are presented in Table 2. The mean July weight (JXJLWGT) of 165.97 pounds for clients appears to be larger than the mean admission weight (ADMWGT) of 150.78 pounds. The mean July BMJ (JULBMI) of 24.69 of clients appears to be larger than the mean admission BMI (ADMBMI) of 22.43. The mean July height (JULHGT) of 68.7 inches for clients appears to be close to the same as the mean admission height (ADMHGT) of 68.69 inches.

The results of the paired sample t test indicate a statistically significant difference between ADMWGT and JULWGT. The / = -9.003 (30), P < 0.05, P = .000. The results from the paired sample t test indicate a statistically significant difference between ADMBMI and JULBMI (r = -9.4 1 7 [30], P < 0.05, P = .000). The results from the paired sample / test indicate that there is not a statistically significant difference between ADMHGT and JULHGT (t = 0.311 [30], P > 0.05, P = 0.379). These results indicate that clients' weight and BMI increased between the time of entry into treatment and July 2000, and that clients' height showed no significant difference. At admission, 0.21 clients had a BMI greater than 25 but less than 30. At July 2000, 0.24 clients had a BMI greater than 25 but less than 30 and .07 clients had a BMI greater than 30 but less than 34.9.

DISCUSSION

Findings from this study suggest that there is significant weight increase while adolescents are residing in a supervised substance abuse treatment setting. This finding is particularly interesting due to the lack of increase in the height in this adolescent population during the time of the research. The significant increase in the BMI validates the necessity of assessing the association of weight gain and abstinence from drugs and alcohol. An interesting finding from this research revealed that 0.21 of the clients in the study had a BMI greater than 25 and less than 30 on admittance to treatment, putting them in the overweight category. In July 2000, 0.24 clients had a BMI greater than 25 but less than 30, and 0.07% clients had a BMl greater than 30 but less than 34.9, putting that subset of clients in the obesity category.

Although comorbidity of substance abuse and eating disorders has gotten some attention in the past 10 years, there is still no clear empirical research on the specific characteristics linking the symptoms of eating disorders and substance use.19 Most of the eating disorder literature does not address the issues of overweight or obesity on the diagnostic continuum linked to substance use. In addition, the addiction field does not adequately address the issue of weight gain during abstinence from drugs and alcohol.

One possible link between these constructs exists in the substance abuse and eating disorder literature regarding selfesteem that may assist in the necessity to examine the association of weight gain and abstinence. In a longitudinal study on childhood obesity and self-esteem, me researcher examined 1520 children aged 9 to 11 years.20 Strauss found that selfesteem scores were not significantly different between obese and nonobese subjects in this age range. Yet by 13 to 14 years of age, significantly lower levels of self-esteem were observed in obese boys, obese Hispanic girls, and obese white girls as well as an increase in smoking and drinking alcohol. There are many initial external decisions that prompt the use of a drug, but once in the body the drug promotes continued drug-seeking behavior. The impact of drugs and alcohol on the brain is modulated by reinforcement and neuroadaptation that contribute to the process of addiction. The action of drugs in the brain can change the neural processes around the connections between the ventral tegmental area and the basal forebrain that contain the general reward circuitry. The mesolimbic dopamine system that connects these two areas is critical to the self-administration of psychomotor stimulants and has a crucial function in motivational behavior.21,22 Current studies regarding increases of the extracellular level of dopamine in the mesolimbic region, links this neurotransmitter to food ingestion as well as other drug self-administration. Both food and drugs are reported to be addictive or stimulating to the brain reward system.23

Our hypothesis is that if drugs Of abuse mimic natural rewards such as food or sex, we should expect drug taking to compete with them and drug abstinence to result in a rebound hyerphagia. Drugs are abused because of their action in the brain on neuronal receptors and neurotransmitters. The sites of action for most drugs of abuse have been at least partially demonstrated. Although there are different sites of action for different drugs of abuse, a final common pathway has been identified involving the mesolimbic frontocortical dopamine (MFD) system. This reward pathway mediates the reinforcement of behaviors essential to individual and species survival including eating and sex. Drugs of abuse evoke dopamine release in the reward pathway resulting in powerful and immediate positive reinforcement, essentially hijacking the brain. In addition to self-administration, anticipatory changes and learning associated with drugs of abuse have also been linked to dopamine and other neurotransmitter release in the nucleus accumbens in the MFD system.

Research is also developing that explores circuits that join the MFD system with the amygdala. The amygdala has important functions associated with emotion and memory.21 The brain attempts to adapt to the continued presence of the drug. Eating, anticipation of consuming food, and food reward may share neural pathways with drugs of abuse.23 Repeated exposure to this process accumulates to result in the behavioral abnormalities that characterize addiction.24

This new research in brain science, which examines the relationship of drugs of abuse and dopamine and other neurotransmitter release in the brain reward pathway, suggests that food and drugs of abuse have the same reinforcement and motivation purpose. Through repeated stimulation of the MFD reward system, the brain learns what is important for survival.25 Studies produced in tihe 1970s examined rats and rhesus monkeys deprived of food and found that the effects Of this deprivation on drug self-administration increased the degree of the reinforcement effects of the drugs. These drugs include alcohol, barbiturates, opiates, cocaine, amphetamine, and phencyclidine.33 Further research confirms these findings and also demonstrates that food deprivation increases drug selfadministration.26,27

To our knowledge, our study is the first to our knowledge to attempt to begin the process of further research of this extraordinary phenomenon. With the knowledge that addiction is a chronic relapsing disease, our treatment system needs to address how to support our adolescent clients in their recovery. We must ask ourselves if we are setting the stage for die adolescent client for future relapse by not paying attention to the variables that are causing this significant weight increase.

Alcohol and drug abuse has increased in adolescents, and young adults, at the same time as has overeating, under-exercising, and obesity. Drug use and obesity are considered the nation's major public health problems and the most common preventable causes of death and disability. Further research is warranted to examine what variables are associated wim the weight increase during abstinence from alcohol and drugs, what are the treatment implications that need to be examined, and what different protocols need to be developed to facilitate sustained recovery for the adolescent population. While this data supports the inclusion of dietary counseling* exercise, and weight management as part of a comprehensive addiction treatment program, further research is necessary to determine if overeating and weight gain after detoxification is due to a rebound after chronic appetite suppression or simply a response to drug withdrawal.

REFERENCES

1. Johnston LD, O'Malley PM, Bachman JG. Monitoring the Future National Results, on Adolescent Drug Use, 1975-1999 Volume I: Secondary School Students. Rockvüle, Md: US Department of Health and Human Services, National Institute on Drug Abuse; 2000. NIH publication 00-4802.

2. Johnston LD, O'Malley PM, Bachman JG. Monitoring the Future National Results on Adolescent Drug Use: Overview of Key Findings, 2000. Rockvüle, Md: US Department of Health and Human Services, National Institute on Drug Abuse; 2001. NIH publication 01-4923.

3. American Academy of Pediatrics, Committee on Substance Abuse. Alcohol use and abuse: a pediatric concern. Pediatrics. 2001;108:185-189.

4. Johnson PB, Boles SM, Kleber HD. The relationship between adolescent smoking and drinking and likelihood estimates of illicit drug use. i Addictiv Dis. 2000;19:75-81.

5. Lai S, Lai H, Page JB, McCoy CB. The association between cigarette smoking and drug abuse in the United States. J Addict Dis. 2000;19:11-24.

6. Weinberg NZ, Rahdert E, Colliver JD. Adolescent substance abuse; a review of the past 10 yeais. J Am Acad Child Adolese Psychiatry. 1998;37:252-261.

7. Diete W. Childhood obesity. In: Shils ME, Shike M, Olson JA, Ross CA, eds. Modern Nutrition in Health and Disease. 9th ed. Baltimore, Md: Lippincott Williams and Wilkins; 1999:1071-1080.

8. Youth Risk Behavioral Surveillance. Atlanta, GA: Centers for Disease Control; 2000.

9. CSAT. Substance Abuse in Brief: Successful Treatment for Adolescents. Bethesda, Md: US Department of Health and Human Services, National Clearinghouse for Alcohol and Drug Information; January 2000.

10. Flegal KM, Carroll MD, Kuczmarski RJ, Johnson CL. Overweight and obesity in the United States: prevalence and trends, 1960-1994. Int J Obes Relat Metab Disord, 1998;22:39-47.

11. Yanovski JA. Intensive therapies for pediatric obesity. Ped Clin Nor Amer. 2001;48:1041-1053.

12. Bray GA, Bouchard C, James WP. Definitions and proposed current classification of obesity. In: Bray GA, Bouchard C, James WP, eds. Handbook of Obesity. New York, Ny: Marcel Dekker; 1997:31-41.

13. SAMHSA study links behavior problems, alcohol use. Brown University Digest of Addiction Theory and Application. 2000;19:5-6.

14. Ross HE, Ivis F. Binge eating and substance use among male and female adolescents. Inter } Eat Dis. 1999;26:245-260.

15. Miller NS, Gold MS. Comorbid cigarette and alcohol addiction: Episemiology and treatment. J Addict Dis. 1998;17:55-66.

16. Whitaker RC, Wright JA, Pepe MS. Predicting obesity in young adulthood from childhood and parental weight. N Engl J Med. 1997;337:869-873.

17. Krahn DD, Kurth C, Demitrack M, et al. The relationship of dieting severity and bulimic behaviors to alcohol and other drug use in young women. J Subst Abuse. 1992;4:341-353.

18. Nowinski J. Substance Abuse in Adolescents and Young Adults. New York: W. W. Norton & Company; 1990.

19. Wolfe WL, Maisto SA. The relationship between eating disorders and substance use: moving beyond co-prevalence research. Clin Psychology Reu. 2000;20:617-631.

20. Strauss RS. Childhood obesity and selfesteem. Pediatrics. 2000;105:1-15.

21. Roberts AJ, Koob GF. The neurobiology of addiction: An overview. Alcohol Health Res World. 1997;21:101-106.

22. Tenth Special Report to the United States Congress on Alcohol and Health. Alcohol, the brain, and behavior, mechanisms of addiction. Alcohol Research & Health. 2000;24:12-15.

23. Gold MS, Johnson C, Stennie K. In: Lowenstein JH, Ruiz P, Millman RB, Langrod JD, eds. Eating Disorders in Substance Abuse: A Comprehensive Textbook. 9th ed. Baltimore, Md: Lippincott Williams and Wilkins; 1997:319-330.

24. Nestler EJ. Neuroadaptation in Addiction. In: Graham AW, Schultz TK, eds. Principles of Addiction Medicine. 2nd ed. Chevy Chase, Md: American Society of Addiction Medicine; 1998:57-72.

25. Brown J, Bullock D, Grossberg S. How the basal ganglia use parallel excitatory and inhibitory learning pathways to selectively respond to unexpected rewarding cues. J Neurosci. 1999;19:10502-10511.

26. Gosnell BA, Krahn DD. Taste and Diet Preferences as Predictors of Drug SelfAdministration. Washington, DC: US Department of Health and Human Services, National Institute on Drug Abuse; 2001:154-175.

27. Krahn DD, Gosnell BA. Fat-preferring rats consume more alcohol than carbohydratepreferring rats. Alcohol. 1991;8:313-316.

TABLE 1

TABLE 2

Study Statistics

10.3928/0048-5713-20030201-07

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