Skip To Content
Click for DHHS Home Page
Click for the SAMHSA Home Page
Click for the OAS Drug Abuse Statistics Home Page
Click for What's New
Click for Recent Reports and HighlightsClick for Information by Topic Click for OAS Data Systems and more Pubs Click for Data on Specific Drugs of Use Click for Short Reports and Facts Click for Frequently Asked Questions Click for Publications Click to send OAS Comments, Questions and Requests Click for OAS Home Page Click for Substance Abuse and Mental Health Services Administration Home Page Click to Search Our Site

Substance Abuse by Older Adults:  Estimates of Future Impact on the Treatment System

Table Of Contents

Chapter 7. National Longitudinal Alcohol Epidemiologic Survey (NLAES): Alcohol and Drug Use Across Age Groups

Frederic C. Blow,* Ph.D.
Kristen L. Barry, Ph.D.
Deborah E. Welsh, M.S.
Brenda M. Booth, Ph.D.

Abstract: Over the coming decades, the aging of the "baby boom" generation is likely to have an enormous impact on the need and demand for health care among older adults. Because little is known about the patterns of use of alcohol and other drugs or the rates of substance abuse or dependence across age cohorts, this study used data from the National Longitudinal Alcohol Epidemiologic Survey (NLAES), conducted in 1992 by the National Institute on Alcohol Abuse and Alcoholism (NIAAA), to determine rates of alcohol and other drug use and abuse by age cohort and gender. The baby boom generation was aged 28 to 46 at the time of data collection. NLAES was designed as a comprehensive survey of alcohol and other drug use, abuse, diagnosis, and treatment, as well as associated health conditions. A representative sample of 42,862 men and women aged 18 or older were sampled in the contiguous United States and the District of Columbia, with a response rate greater than 90 percent. Mean drinks/week for those who used alcohol were consistent with levels seen in other samples for similarly aged men and women, with the exception of the older ages, which were higher. Rates of alcohol abuse/dependence for both men and women were highest among young adults, dropping off substantially after age 64. Rates for drug abuse/dependence were by far the highest among young adults, trailing off rapidly in older age cohorts. The rate of marijuana use for both men and women in the baby boom generation remained higher than for any other drug. Results from this large, population-based national dataset suggest that there have been and will likely continue to be substantial changes in the patterns of substance use and abuse over different age cohorts, particularly among those born after World War II, that will have a dramatic impact on the content, focus, and delivery of specialized substance abuse prevention and interventions needed for adults in late life.

 

Introduction

With changes in the health care system and the growing population of older adults, primary disease prevention and efforts to promote healthy lifestyles in this group are gaining importance. The occurrence of a number of acute and chronic diseases in late life leads to the high utilization of health care among the elderly (Barry, 1997; Fuchs, 1999; Krop et al., 1998; Schneider & Guralnik, 1990; Waldo, Sonnefeld, McKusick, & Arnett, 1989). Many of these acute and chronic medical and psychiatric diseases are influenced by lifestyle choices and behaviors, such as the consumption of alcohol.

Because of the increased incidence of health care problems, older adults are more likely to seek health care on a regular or semiregular basis than younger adults (Fuchs, 1999; Krop et al., 1998; Schneider & Guralnik, 1990; Waldo et al., 1989). They are also more susceptible to the effects of alcohol. Combined with their increased risk of comorbid diseases and their use of prescription and over-the-counter medications, older adults may seek health care for a variety of conditions that are exacerbated by increased alcohol consumption. This is one of the primary reasons that systematic alcohol screening and intervention methods are particularly relevant to providing high-quality health care to the elderly. Older adults with alcohol problems are a special and vulnerable population who require elder-specific screening and intervention procedures focused on the unique issues associated with drinking in later life. As a group, this generation of adults (aged 65 or older) is less likely than younger cohorts to abuse illicit drugs. Problems related to alcohol use are by far the largest class of substance use problems seen in older adults today. However, as the "baby boom" generation reaches later life, providers may see a greater use of illicit drugs than in the current older cohort.

Heavier alcohol use is associated with a number of adverse health effects in this population. These include greater risk for harmful drug interactions, injury, depression, memory problems, liver disease, cardiovascular disease, cognitive changes, and sleep problems (Barry, 1997; Gambert & Katsoyannis, 1995; Liberto, Oslin, & Ruskin, 1992; Wetle, 1997). It has recently been suggested that screening and interventions that focus on lifestyle factors, including the use of alcohol, may be the most appropriate way to maximize health outcomes and minimize health care costs among older adults (Wetle, 1997).

Over the coming decades, the aging of the baby boomers is likely to have an enormous impact on the need and demand for health care among older adults (Day, 1996). Despite significant advances made over the last two decades—both in the understanding of the aging process, with its attendant health problems, and in the understanding and consequences of alcohol problems and alcoholism—little attention has been paid to the intersection of the fields of gerontology or geriatrics and alcohol studies. However, in recent years there has been an increased interest in alcohol and other substance abuse problems among the elderly and in the potential impact of the future explosion of the elderly population as the baby boom generation reaches old age.

Although studies in this area are limited, prevalence estimates and typical characteristics of older problem drinkers have been reported (Adams, Barry, & Fleming, 1996; Center for Substance Abuse Treatment [CSAT], 1998; Robins & Regier, 1991). Specific treatment and intervention strategies for older adults who are alcohol dependent (Blow et al., 2000a) or at-risk drinkers (Fleming, Barry, Manwell, Johnson, & London, 1997) are beginning to be disseminated. At-risk or hazardous drinking can significantly affect a number of conditions in this age group (Fleming & Barry, 1992), including depressive symptoms (Coyne & Schwenk, 1997), as well as general health functioning (Blow, Walton, Chermack, Mudd, & Brower, 2000b). Depression has been linked to relapse in drinking and increased alcohol intake. Blow et al. (2000b) found a main effect of drinking status on general health, physical functioning, physical role functioning, pain, vitality, mental health, emotional role, and social functioning, controlling for race and gender, with low-risk drinkers scoring better than abstainers and better than hazardous drinkers. A focus on brief interventions with lifestyle factors, including the use of alcohol, may be one of the most appropriate methods to maximize health outcomes and minimize health care expenditures among older adults (Wetle, 1997).

 

Prevalence and Patterns of Substance Use among Older Individuals

In a large primary care clinical trial of at-risk and problem drinking that screened 17,695 primary care patients (Fleming et al., 1997), 15 to 20 percent of men and 8 to 10 percent of women drank at a risk or problem-drinking level (men: 15 or more drinks/week; women: 12 or more drinks/week). Prevalence estimates for older at-risk and problem drinking using community surveys have ranged from 1 to 15 percent (Adams et al., 1996; Gurland & Cross, 1982; Schuckit & Pastor, 1978). These rates vary widely depending on the definition of at-risk drinking, problem drinking, and alcohol abuse/dependence, as well as the methodology used to obtain samples. Several researchers have also questioned the accuracy of rates of alcohol problems for older adults because of the use of assessment instruments developed on younger hospitalized populations.

With the exception of a few studies, patterns of drinking among at-risk drinkers in older community-based populations have received little attention. Using data from the National Longitudinal Alcohol Epidemiologic Survey (NLAES)—a large epidemiological study that defined the parameters of alcohol use in the United States across the life span from adolescence to older adulthood—researchers (Grant, 1997; Grant et al., 1994a) found varying trajectories of problematic alcohol use across cohorts. The study provided new knowledge regarding changes over time in the diagnoses of alcohol abuse and dependence. Epidemiological data indicated that problem use declines with increasing age. However, there is some diagnostic stability in diagnoses into later life (Grant, 1997). Men were more likely to sustain a diagnosis of alcohol abuse or dependence over time than were women. Grant (1997) pointed out that the social structure, attitudes, and expectancies of each cohort make a difference in the extent to which members of that cohort engage in heavier drinking and experience more alcohol-related problems. The impact on health of untreated heavy drinking has been well described but may be even greater among the elderly, who are already at increased risk for many health problems, including harmful drug interactions, injury, depression, memory problems, liver disease, cardiovascular disease, cognitive changes, and sleep disturbance (Gambert & Katsoyannis, 1995; Liberto et al., 1992).

Symptoms of harmful drinking often are less visible among older adults because they can be masked by social, medical, or psychological conditions. In addition, sensitivity to and tolerance of ethanol may be affected by the physiological aging processes (Rosin & Glatt, 1971), as well as by health conditions common to old age (Baker, 1985). Drinking produces higher blood alcohol levels in older adults than in younger persons when comparable amounts of alcohol are consumed; many problems common among older people, such as chronic illness, poor nutrition, and polypharmacy, may be exacerbated by even small amounts of alcohol (Vestal et al., 1977). What might be considered light or moderate drinking for individuals in their 30s may have untoward health effects in an older person.

Even lesser rates of consumption, termed hazardous or harmful use, could result in increased risk of injury or health problems and may occur in a large proportion of patients coming into contact with health care professionals (Cyr & Wartman, 1988; Moore et al., 1989). Drinking at hazardous levels (over recommended limits) increases the risk of hypertension and may increase the risk of breast cancer and diabetes, among other medical conditions in this population. Furthermore, there is emerging evidence that problem drinking in late life affects a larger proportion of the elderly population than previously thought (CSAT, 1998; Williams & Debakey, 1992). Prevalence estimates of older problem drinking using community surveys have ranged from 1 to 10 percent (CSAT, 1998; Robins & Regier, 1991). These rates vary widely depending on the definition of alcohol abuse/dependence and the methodology used in obtaining samples. Several researchers have questioned the accuracy of rates of alcohol problems for older adults because of the use of assessment instruments developed on younger populations (CSAT, 1998).

 

Physical and Mental Health Consequences of Substance Abuse

The physical and mental health effects of hazardous drinking in young to middle adulthood (Willenbring, Johnson, & Tan, 1994) and old age (Blow et al., 2000a) have been studied separately in treatment populations, but only rarely in primary care samples (Fleming, Barry, Adams, Manwell, & Krecker, 2000; Fleming et al., 1997), or in population-based studies. In alcohol treatment samples, a greater number of concomitant problems have been noted in older adults, including more difficult alcohol withdrawal (Brower, Mudd, Blow, Young, & Hill, 1994), and worse physical health (Fleming & Barry, 1992). There has, however, been little work establishing differences in physical and mental health functioning across various age groups.

The potential interaction of medication and alcohol is of great concern for adults of all ages, particularly for older adults. For some younger and older individuals, any alcohol use at all combined with the use of specific over-the-counter or prescription medications can increase problematic consequences. Therefore, alcohol use recommendations for older adults are generally lower than those set for adults under 65 and are usually made on a case-by-case basis.

 

Substance Use and Abuse Across Age Cohorts

There is strong evidence that the use and misuse of alcohol and other drugs decline with advancing age (Grant, 1997; National Institute on Alcohol Abuse and Alcoholism [NIAAA], 1998). Grant (1997) noted that over the past century, there has been a shift to increasingly earlier ages for the onset of alcohol use and an increased likelihood of alcohol dependence among cohorts of drinkers. Grant (1997) also reported increasing convergence in the patterns of substance abuse/dependence of men and women over the last century. These findings, along with those from other recent studies (Johnstone, Leino, Ager, Ferrer, & Fillmore, 1996; Nelson, Heath, & Kessler, 1998; NIAAA, 1998), support the idea that there have been, and will likely continue to be, substantial changes in the patterns of substance use and abuse in different age cohorts, particularly among those born after World War II. Furthermore, these changes will have a dramatic impact on the content, focus, and delivery of specialized substance abuse prevention and interventions needed for adults in late life.

Population-based data on the amount of alcohol and drug use, as well as substance abuse and dependence, by gender and age cohort, are essential to understand the potential impact of the baby boom generation on the need and demand for substance abuse services. Grant (1997) used 1992 NLAES data to describe the cumulative probability of alcohol use and alcohol dependence by cohort, as well as the NIAAA (1998) monograph on NLAES. Grant also has published global information on the categories of drinkers by age grouping. Few details, however, have been described on the quantity of alcohol consumption among current drinkers, as well as other drug abuse/dependence. The purpose of this chapter is to explore in detail reported drinking amounts, and the rates of alcohol and other drug abuse and dependence, by gender and age cohort. Differences were expected by age cohort and gender on these key dimensions of alcohol and drug use and misuse.

 

Methods

 

Survey Specifics

NLAES was conducted in 1992 by the NIAAA to provide a comprehensive survey of alcohol use, abuse, diagnosis, treatment depression, and associated health conditions (Grant, 1997; NIAAA, 1998). A sample of 42,862 men and women aged 18 or older were sampled in the contiguous United States and the District of Columbia, with greater than a 90 percent response rate. Using a complex multistage stratified sampling frame developed by the U.S. Census Bureau, a cross-sectional survey of households was conducted with a large sample of individuals representative of the U.S. population. Oversampling of the black population was performed to secure adequate numbers for analytic purposes, and likewise for young adults between the ages of 18 and 29 at the household level to secure adequate numbers of this heavy alcohol- and substance-using subgroup. The NLAES design has been described in detail elsewhere (Grant, Peterson, Dawson, & Chou, 1994b; Massey, Moore, Parsons, & Tadros, 1989). No additional data were collected beyond 1992; therefore, all analyses are cross-sectional.

 

Data Sources

Data were obtained from the Alcohol Epidemiologic Data System (AEDS), operated by CSR, Inc., under contract from the NIAAA. All analyses were generated using SUrvey DAta ANalysis (SUDAAN) statistical software (Shah, Barnwell, Hunt, & LaVange, 1994).

 

Variables

Weekly Drinking Levels. Weekly drinking levels were calculated on the basis of two variables: how often an alcoholic beverage is consumed times the number of alcoholic beverages consumed on that occasion. Occasions and number of drinks were assessed in the NLAES dataset for beer, wine, and liquor. These estimates were converted to the number of days per week the person consumed alcohol. Abstainers were not included in Table  2 but are discussed in the Results section of this chapter.

Number of drinks of each type were assessed with one question: "What is the usual number of drinks of beer per usual drinking day? (when drinking size is less than 16 ounces)." Two other questions asked about beer sizes larger and smaller than these. A very small number of people answered the alternative item forms and thus were deleted from the analysis because (a) exact parallel items were unavailable for wine and liquor, and (b) using any size estimates inflated the extreme values of drinking and thus skewed the distribution and inflated the mean.

The algorithm for this variable was as follows:

Prescription and Illegal Drug Use. Levels of drug use were collected by asking about use in the past 12 months and ever in the lifetime. These items were worded to reflect that the drug was used by the subject without a physician's recommendation. Eight categories of drug use were assessed: sedatives, tranquilizers, painkillers, stimulants, marijuana, cocaine or crack cocaine, heroin, and methadone. The respondent answered "yes" or "no" to each item. Missing data were an issue with this variable. A decision was made to transform missing data to the "no" category to ensure that the estimates of drug use included all participants.

Diagnosis of Alcohol Abuse and Dependence. One of the hallmarks of the NLAES dataset is that several alcohol consequences were assessed. These items paralleled the Diagnostic and Statistical Manual of Mental Disorders (DSM-III-R and DSM-IV) criteria for alcohol abuse and dependence (American Psychiatric Association [APA], 1987, 1994). Therefore, code was developed for each of these criteria to perform diagnoses for all participants. Diagnoses used in this chapter were based on DSM-IV criteria. If a subject was diagnosed with alcohol dependence, he or she was excluded from an alcohol abuse diagnosis according to the DSM-IV. A dichotomous variable was also constructed based on whether the subject scored positive on DSM-IV criteria in the past 12 months.

Diagnosis of Drug Abuse and Dependence. Development of variables and scoring schemes for drug abuse and dependence paralleled those used for alcohol abuse/dependence.

Depression Diagnosis. A simple algorithm was developed to score the depression items because of complexities in scoring used in the DSM-IV criteria for major depressive disorder. In the NLAES database, the DSM-IV criterion variables for depression did not have clear time frame references. Three items contributed to the diagnosis of depression: (a) periods of 2 or more weeks when the subject felt depressed most of the time; (b) number of separate periods of 2 or more weeks when the subject experienced low mood/not caring; and (c) whether all periods of depressed feelings occurred when ill, getting over illness, or after the death of someone close. Only if the answers to the first two items were yes and the answer to the third item 3 was no was a diagnosis of depression conferred.

Age Categories. Five-year age categories based on subject ages were constructed. Categories included younger than 24, 25 to 29, 30 to 34, 35 to 39, and so on up to age 105. Because NLAES assessed no one younger than 18, the lowest category had a range of 18 to 24. The age categories that most reflected the baby boom generation were the combined age groups of 25 through 34 and 35 through 44. Hence, results relating to this cohort are compilations of results in these two study age groups. The baby boom generation comprised approximately 57 percent of the sample (24,621 of 42,862).

 

Results

Age and race distribution by gender is listed in Table  1. Mean drinks/week were consistent with levels seen in the National Health and Nutrition Examination Survey (NHANES) for similarly aged men and women, with the exception of the older ages (Table  2). Generally, NLAES subjects older than 55 had higher mean drinks/week than those in the NHANES database with corresponding ages. Rates of alcohol abuse/dependence for both men and women were highest among young adults, decreasing substantially after age 60 (Table  2). For the baby boom generation, rates of alcohol abuse averaged approximately 8 to 12 percent for men and 3 to 5 percent for women, depending on age subcategory. Rates of alcohol dependence were from 4 to 7 percent in men and around 2 to 3 percent in women. Rates for drug abuse/dependence were by far highest among young adults, trailing off rapidly in older age groups.

Not surprisingly, the most commonly used illegal drug was marijuana (see Table  3 for lifetime use and Table  4 for current use). The rate of marijuana use for both men and women in the baby boom generation remained higher than for any other drug. Current use of prescription drugs (painkillers, stimulants, sedatives, tranquilizers) was very low for all age groups. Males in the baby boom generation, in particular, had lifetime stimulant use rates of around 8 to 9 percent, but low rates of current use. Older adults reported virtually no illegal drug use, and their use of prescription drugs, with the exception of sedatives, was similarly absent.

Few individuals, regardless of age, reported concurrent problems with alcohol and illegal drugs in the 12 months prior to sampling with none in the 55 or older age groups. In the baby boom generation, less than 1 percent of women and less than 2 percent of men reported concurrent alcohol and drug abuse or dependence. More common was the co-occurrence of alcohol abuse/dependence and depression, but rates were low across the age groups. These are consistent with data from the National Comorbidity Study (Kessler et al., 1994).

 

 

Table 1 Distribution of Age and Race, by Gender, from the NLAES Dataset

Age

N

(%)*

Race

White

Black

Native American

Asian

Other

N

%**

N

%

N

%

N

%

N

%

Men

< 24

2,323

(50.06)

1,836

79.36

338

13.17

24

1.46

72

3.41

53

2.60

25-34

4,099

(49.63)

3,366

80.47

464

11.73

31

0.90

156

4.43

82

2.47

35-44

3,862

(49.41)

3,207

83.10

445

11.11

22

0.61

106

2.96

82

2.21

45-54

2,438

(48.94)

2,031

84.99

300

9.64

13

0.65

64

3.16

30

1.57

55-64

2,082

(47.54)

1,760

87.00

259

8.93

9

0.47

30

2.31

24

1.28

65-74

1,808

(44.19)

1,550

88.45

204

7.85

6

0.32

27

2.30

21

1.08

75-84

995

(38.60)

862

90.15

112

7.11

2

0.18

10

1.46

9

1.10

85-94

204

(32.44)

175

87.76

25

8.29

1

0.34

2

2.73

1

0.89

> 95

8

(21.78)

7

93.46

1

6.54

0

0.00

0

0.00

0

0.00

Women

< 24

2,773

(49.94)

2,013

75.75

544

15.23

35

1.57

99

4.41

82

3.05

25-34

5,721

(50.37)

4,349

79.30

1,045

14.13

42

0.82

152

3.19

133

2.56

35-44

5,137

(50.59)

4,053

81.02

806

12.86

34

0.75

149

3.58

95

1.79

45-54

3,063

(51.06)

2,446

83.58

471

11.16

28

0.90

73

2.66

45

1.71

55-64

2,776

(52.46)

2,279

85.66

412

10.53

14

0.46

33

1.70

38

1.66

65-74

2,944

(55.81)

2,502

88.64

386

8.89

8

0.31

17

0.88

31

1.27

75-84

2,037

(61.40)

1,760

89.71

238

7.96

6

0.33

15

0.99

18

1.01

85-94

562

(67.56)

501

90.14

53

7.95

3

0.56

1

0.40

4

0.95

> 95

30

(78.22)

25

87.59

4

10.42

1

1.99

0

0.00

0

0.00

* Weighted percentage for gender within each age group in the population.
** Weighted row percentage within each age group in the population, by race and gender.

 

Discussion

NLAES is one of the most comprehensive and representative national epidemiological surveys on alcohol and drugs available with a large (over 45,000) sample size.

Recent research has suggested that older adults have unique drinking patterns, alcohol-related consequences, and intervention/treatment needs. Because of this, early identification and secondary prevention of alcohol problems in later life are likely to require innovative approaches. With changes in the health care system to managed models of care, the time is right to move forward into a comprehensive system of alcohol interventions with older adults, considered one of the most vulnerable and the fastest growing segment of the U.S. population.

 

 

Table 2 Alcohol Use Rates, by Gender and Age Group, from the NLAES Dataset

Age

Drinks Per Week
(Drinkers Only)

Percent Alcohol Abuse
(Entire Sample)

Percent Alcohol Dependence
(Entire Sample)

Percent Drug Abuse
(Entire Sample)

Percent Drug Dependence
(Entire Sample)

Men

< 24

8.42 (1,382)*

15.78

12.52

4.94

2.90

25-34

7.86 (2,752)

12.66

7.08

2.96

1.02

35-44

7.12 (2,371)

7.97

4.02

1.35

0.69

45-54

8.09 (1,328)

6.13

2.84

0.50

0.12

55-64

8.66 (972)

2.79

2.09

0.00

0.03

65-74

7.93 (739)

1.48

0.62

0.00

0.00

75-84

7.13 (285)

0.34

0.40

0.12

0.00

85-94

6.77 (41)

2.39

0.00

0.00

0.00

> 95

6.12 (1)

0.00

0.00

0.00

0.00

Women

< 24

4.30 (1,132)

8.53

6.13

1.55

1.57

25-34

3.34 (2,476)

5.31

2.99

1.01

0.79

35-44

3.35 (2,098)

2.70

1.73

0.44

0.36

45-54

3.92 (1,046)

1.41

0.93

0.16

0.17

55-64

4.59 (7,626)

0.60

0.67

0.02

0.04

65-74

4.96 (575)

0.34

0.18

0.05

0.00

75-84

4.58 (233)

0.07

0.20

0.00

0.00

85-94

3.60 (46)

0.00

0.00

0.00

0.00

> 95

9.19 (2)

0.00

0.00

0.00

0.00

* Drinks per week category includes only those subjects who used alcohol; however, percentage estimates of abuse and dependence include the entire sample (drinkers and abstainers).

A limited number of public health strategies are available to identify and intervene with older adult at-risk and problem drinkers because many older adults are retired and some are isolated or have mobility problems. Because the majority of older adults are treated in primary care settings, this group of professionals has a unique opportunity to identify and help older adults who drink at risky levels. The availability of a range of prevention/intervention strategies for older adults—prevention/education for persons who are abstinent or low-risk drinkers, minimal advice, structured brief intervention protocols, and formalized treatment for older persons with alcohol abuse/dependence—provides the tools for health care providers to work with older adults across a spectrum of drinking patterns.

 

 

Table 3 Lifetime Drug Use Rates, by Gender and Age Group, from the NLAES Dataset

Age

Marijuana

Cocaine

Heroin

Methadone

Painkillers

Stimulants

Sedatives

Tranquilizers

N

%

N

%

N

%

N

%

N

%

N

%

N

%

N

%

Men

< 24

513

22.87

118

4.92

8

0.26

11

0.42

79

3.23

124

5.22

49

1.93

66

2.63

25-34

1,276

29.79

415

9.71

29

0.69

26

0.61

226

5.46

356

8.46

219

5.17

235

5.56

35-44

1,124

27.29

321

7.59

65

1.73

36

0.89

170

4.29

363

9.30

206

4.96

197

5.08

45-54

242

8.82

51

1.76

17

0.71

8

0.37

60

2.40

80

2.97

50

1.79

49

1.92

55-64

46

1.69

6

0.28

2

0.06

0

0.00

12

0.58

18

0.72

13

0.58

12

0.55

65-74

2

0.59

2

0.11

2

0.06

1

0.03

7

0.40

5

0.30

6

0.28

1

0.03

75-84

1

0.05

0

0.00

0

0.00

0

0.00

3

0.19

1

0.11

2

0.17

7

0.52

85-94

2

2.11

0

0.00

0

0.00

0

0.00

0

0.00

0

0.00

0

0.00

0

0.00

> 95

0

0.00

0

0.00

0

0.00

0

0.00

0

0.00

0

0.00

0

0.00

0

0.00

Women

< 24

429

14.90

82

2.89

3

0.09

2

0.06

69

2.41

108

3.77

35

1.12

57

2.04

25-34

1,183

20.47

386

6.62

20

0.34

8

0.15

185

3.16

363

6.41

160

2.94

183

3.15

35-44

843

14.93

182

3.03

21

0.35

14

0.21

116

2.06

224

4.02

130

2.41

134

2.44

45-54

110

2.60

24

0.48

7

0.16

4

0.08

35

0.87

48

1.40

39

1.04

36

1.09

55-64

25

0.89

5

0.28

3

0.21

3

0.21

16

0.74

15

0.50

19

0.68

15

0.82

65-74

2

0.06

1

0.04

1

0.04

1

0.04

4

0.15

2

0.06

8

0.24

8

0.26

75-84

0

0.00

0

0.00

0

0.00

0

0.00

0

0.00

0

0.00

5

0.29

2

0.11

85-94

0

0.00

0

0.00

0

0.00

0

0.00

0

0.00

0

0.00

1

0.14

0

0.00

> 95

0

0.00

0

0.00

0

0.00

0

0.00

0

0.00

0

0.00

0

0.00

0

0.00

 

 

Table 4 Rates of Drug Use in the Past 12 Months, by Gender and Age Group, from the NLAES Dataset

Age

Marijuana

Cocaine

Heroin

Methadone

Painkillers

Stimulants

Sedatives

Tranquilizers

N

%

N

%

N

%

N

%

N

%

N

%

N

%

N

%

Men

< 24

305

13.76

37

1.55

0

0.00

1

0.02

30

1.30

35

1.50

10

0.39

17

0.55

25-34

401

9.00

82

1.72

2

0.04

3

0.09

41

0.84

45

0.94

14

0.25

46

1.05

35-44

227

5.00

44

0.90

5

0.12

2

0.04

31

0.76

10

0.26

10

0.18

36

0.92

45-54

35

1.21

6

0.13

2

0.06

1

0.04

7

0.25

1

0.02

4

0.11

7

0.18

55-64

10

0.24

0

0.00

0

0.00

0

0.00

7

0.32

0

0.00

4

0.22

2

0.05

65-74

2

0.18

0

0.00

0

0.00

0

0.00

1

0.06

0

0.00

2

0.08

0

0.00

75-84

1

0.05

0

0.00

0

0.00

0

0.00

2

0.12

0

0.00

1

0.06

3

0.24

85-94

1

0.34

0

0.00

0

0.00

0

0.00

0

0.00

0

0.00

0

0.00

0

0.00

> 95

0

0.00

0

0.00

0

0.00

0

0.00

0

0.00

0

0.00

0

0.00

0

0.00

Women

< 24

214

7.48

17

0.60

0

0.00

0

0.00

39

1.43

39

1.44

8

0.36

25

0.97

25-34

270

4.50

66

0.97

6

0.09

2

0.03

60

1.00

32

0.62

27

0.41

42

0.71

35-44

129

2.14

15

0.24

1

0.01

3

0.03

34

0.67

8

0.12

7

0.21

29

0.53

45-54

24

0.52

4

0.06

0

0.00

0

0.00

8

0.13

6

0.22

39

1.30

13

0.38

55-64

3

0.08

0

0.00

0

0.00

0

0.00

4

0.11

0

0.00

5

0.16

4

0.32

65-74

0

0.00

0

0.00

0

0.00

0

0.00

0

0.00

0

0.00

4

0.11

2

0.07

75-84

0

0.00

0

0.00

0

0.00

0

0.00

0

0.00

0

0.00

1

0.07

1

0.04

85-94

0

0.00

0

0.00

0

0.00

0

0.00

0

0.00

0

0.00

1

0.14

0

0.00

> 95

0

0.00

0

0.00

0

0.00

0

0.00

0

0.00

0

0.00

0

0.00

0

0.00

The major limitations of the dataset are that the study was conducted in 1992, and, while the initial intention of NLAES was to study individuals over time, only one wave was conducted. However, it remains one of the most representative and comprehensive datasets of its kind in the United States. It offers the opportunity to study specific cohorts at a point in their development and allows researchers to relate alcohol and drug findings from that time to newer data on the drug use of these cohorts as they age.

The opportunity to take an early snapshot of alcohol and drug use, particularly for the large cohort that is now at midlife and approaching older adulthood, will help to inform the extent to which services will be needed to meet the alcohol and drug prevention, intervention, and treatment needs of the aging population. It remains to be seen whether the baby boom generation, as they age, will continue the pattern of alcohol and drug use exhibited in the NLAES data. If they do, one of the challenges will be addressing the needs of members of the aging population who are misusing alcohol and/or medications/drugs in the context of a managed care environment, where providers are expected to deliver quality medical care for a wide variety of health problems within greater time constraints. The NLAES dataset has helped to define the drug and alcohol issues for an aging America. The development of short, effective techniques to address substance use issues in the growing population of older adults is one of the current and future foci for the substance use field (CSAT, 1999). Innovative screening, intervention, and treatment methods for alcohol and drug misuse among older adults, if successfully implemented, are steps in the process of assuring that current and future generations have the opportunity for improved physical and emotional quality in their lives.

 

References

Adams, W. L., Barry, K. L., & Fleming, M. F. (1996). Screening for problem drinking in older primary care patients. Journal of the American Medical Association, 276, 1964-1967.

American Psychiatric Association. (1987). Diagnostic and statistical manual of mental disorders (3rd ed., rev.). Washington, DC: Author.

American Psychiatric Association. (1994). Diagnostic and statistical manual of mental disorders (4th ed.). Washington, DC: Author.

Baker, S. L. (1985). Substance abuse disorders in aging veterans. In E. Gottheil, K. A. Druley, T. E. Skoloda, & H. M. Waxman (Eds.), Combined problems of alcoholism, drug addiction and aging (pp. 303-311). Springfield, IL: Charles C Thomas.

Barry, K. L. (1997). Alcohol and drug abuse. In M. B. Mengel & W. L. Holleman (Eds.), Fundamentals of clinical practice: A textbook on the patient, doctor, and society. New York: Plenum Medical Book Company.

Blow, F. C., Walton, M. A., Barry, K. L., Coyne, J. C., Mudd, S. A., & Copeland, L. A. (2000a). The relationship between alcohol problems and health functioning of older adults in primary care settings. Journal of the American Geriatrics Society, 48, 769-774.

Blow, F. C., Walton, M. A., Chermack, S. T., Mudd, S. A., & Brower, K. J. (2000b). Older adult treatment outcome following elder-specific inpatient alcoholism treatment. Journal of Substance Abuse Treatment, 19, 67-75.

Brower, K. J., Mudd, S., Blow, F. C., Young, J. P., & Hill, E. M. (1994). Severity and treatment of alcohol withdrawal in elderly versus younger patients. Alcoholism: Clinical and Experimental Research, 18, 196-201.

Center for Substance Abuse Treatment. (1998). Substance abuse among older adults (DHHS Publication No. SMA 98-3179, Treatment Improvement Protocol [TIP] Series 26; available at http://www.health.org/govpubs/BKD250/). Rockville MD: Author.

Center for Substance Abuse Treatment. (1999). Brief interventions and brief therapies for substance abuse (DHHS Publication No. SMA 99-3353, Treatment Improvement Protocol [TIP] Series 34; available at http://hstat.nlm.nih.gov/). Rockville, MD: Author.

Coyne, J. C., & Schwenk, T. L. (1997). The relationship of distress to mood disturbance in primary care and psychiatric populations. Journal of Consulting and Clinical Psychology, 65, 161-168.

Cyr, M. G., & Wartman, S. A. (1988). The effectiveness of routine screening questions in the detection of alcoholism. Journal of the American Medical Association, 259, 51-54.

Day, J. C. (1996, February). Population projections of the United States by age, sex, race, and Hispanic origin: 1995 to 2050 (Report No. P25-1130, U.S. Current Population Report; available at http://www.census.gov/prod/1/pop/p25-1130/ [last revised April 13, 1999]). Washington, DC: U.S. Bureau of the Census.

Fleming, M. F., & Barry, K. L. (Eds.). (1992). Addictive disorders. St. Louis, MO: Mosby Yearbook Medical Publishers.

Fleming, M. F., Barry, K. L., Adams, W., Manwell, L. B., & Krecker, M. (2000). Guiding older adult lifestyles (Project GOAL): The effectiveness of brief physician advice for alcohol problems in older adults. Manuscript submitted to the Annals of Internal Medicine.

Fleming, M. F., Barry, K. L., Manwell, L. B., Johnson, K., & London, R. (1997). Brief physician advice for problem alcohol drinkers: A randomized controlled trial in community-based primary care practices. Journal of the American Medical Association, 277, 1039-1045.

Fuchs, V. R. (1999). Health care for the elderly: How much? Who will pay for it? Health Affairs, 18, 11-21.

Gambert, S. R., & Katsoyannis, K. K. (1995). Alcohol-related medical disorders of older heavy drinkers. In T. Beresford & E. Gomberg (Eds.), Alcohol and aging (pp. 70-81). New York: Oxford University Press.

Grant, B. F. (1997). Prevalence and correlates of alcohol use and DSM-IV alcohol dependence in the United States: Results of the National Longitudinal Alcohol Epidemiologic Survey. Journal of Studies on Alcohol, 58, 464-473.

Grant, B. F., Harford, T. C., Dawson, D. A., Chou, P., DuFour, M., & Pickering, R. (1994a). Prevalence of DSM-IV alcohol abuse and dependence: United States, 1992 (NIAAA's Epidemiologic Bulletin No. 35). Alcohol Health and Research World, 18, 243-248.

Grant, B. F., Peterson A., Dawson, D. S., & Chou, S. P. (1994b). Source and accuracy statement for the National Longitudinal Alcohol Epidemiologic Survey. Rockville, MD: National Institute on Alcohol Abuse and Alcoholism.

Gurland, B. J., & Cross, P. S. (1982). Epidemiology of psychopathology in old age: Some implications for clinical services. Psychiatric Clinics of North America, 5, 11-26.

Johnstone, B. M., Leino, E. V., Ager, C. R., Ferrer, H., & Fillmore, K. M. (1996). Determinants of life-course variation in the frequency of alcohol consumption: Meta-analysis of studies from the collaborative alcohol-related longitudinal project. Journal of Studies on Alcohol, 57, 494-506.

Kessler, R. C., McGonagle, K. A., Zhao, S., Nelson, C. B., Hughes, M., Eshleman, S., Wittchen, H. U., & Kendler, K. S. (1994). Lifetime and 12-month prevalence of DSM-III-R psychiatric disorders in the United States: Results from the National Comorbidity Survey. Archives of General Psychiatry, 51, 8-19.

Krop, J. S., Powe, N. R., Weller, W. E., Shaffer, T. J., Saudek, C. D., & Anderson, G. F. (1998). Patterns of expenditures and use of services among older adults with diabetes: Implications for the transition to capitated managed care. Diabetes Care, 21, 747-752.

Liberto, J. G., Oslin, D. W., & Ruskin, P. E. (1992). Alcoholism in older persons: A review of the literature. Hospital & Community Psychiatry, 43, 975-984.

Massey, J., Moore, T., Parsons, R., & Tadros, W. (1989). Design and estimation from the National Health Interview Survey, 1985-1994. Hyattsville, MD: National Center for Health Statistics.

Moore, R. D., Bone, L. R., Geller, G., Mamon, J. A., Stokes, E. J., & Levine, D. M. (1989). Prevalence, detection, and treatment of alcoholism in hospitalized patients. Journal of the American Medical Association, 261, 403-407.

National Institute on Alcohol Abuse and Alcoholism. (1998, November). Drinking in the United States: Main findings from the 1992 National Longitudinal Alcohol Epidemiologic Survey (NLAES) (NIH Publication No. 99-3519, U.S. Alcohol Epidemiologic Data Reference Manual, Vol. 6; also available at http://www.niaaa.nih.gov/publications/manual-text.htm). Rockville, MD: Author.

Nelson, C. B., Heath, A. C., & Kessler, R. C. (1998). Temporal progression of alcohol dependence symptoms in the U.S. household population: Results from the National Comorbidity Survey. Journal of Consulting and Clinical Psychology, 66, 474-483.

Robins, L. N., & Regier, D. A. (Eds.). (1991). Psychiatric disorders in America: The Epidemiological Catchment Area Study. New York: The Free Press.

Rosin, A. J., & Glatt, M. M. (1971). Alcohol excess in the elderly. Quarterly Journal of Studies on Alcohol, 32, 53-59.

Schneider, E. L., & Guralnick, J. M. (1990). The aging of America: Impact on health care costs. Journal of the American Medical Association, 263, 2335-2340.

Schuckit, M. A., & Pastor, P. A. Jr. (1978). The elderly as a unique population: Alcoholism. Alcoholism: Clinical and Experimental Research, 2, 31-38.

Shah, B. V.; Barnwell, B. G.; Hunt, P. N., & LaVange, L. M. (1994). SUDAAN user's manual: Release 6.4. Research Triangle Park, NC: RTI.

Vestal, R. E., McGuire, E. A., Tobin, J. D., Andres, R., Norris, A. H., & Mezey, E. (1977). Aging and ethanol metabolism. Clinical Pharmacology and Therapeutics, 21, 343-354.

Waldo, D. R., Sonnefeld, S. T., McKusick, D. R., & Arnett, R. H. III. (1989). Health expenditures by age group, 1977 and 1987. Health Care Financing Review, 10, 111-120.

Wetle, T. (1997). Living longer, aging better: Aging research comes of age. Journal of the American Medical Association, 278, 1376-1377.

Willenbring, M. L., Johnson, S. B., & Tan, E. (1994). Characteristics of male medical patients referred for alcoholism treatment. Journal of Substance Abuse Treatment, 11, 259-265.

Williams, G. D., & Debakey, S. F. (1992). Changes in levels of alcohol consumption: United States, 1983-1988. British Journal of Addiction, 87, 643-648.

____________

* To whom correspondence should be sent at University of Michigan, Department of Psychiatry, 400 E. Eisenhower Parkway, Suite A, Ann Arbor, MI 48108. Telephone: 734-930-5139. E-mail: fredblow@umich.edu. Opinions in this chapter do not reflect the opinions of the Department of Veterans Affairs, The University of Michigan, or The University of Arkansas for Medical Sciences.

Top Of PageTable Of Contents

This page was last updated on June 16, 2008.