&

U.S. Department of Justice

Office of Justice Programs

National Institute of Justice

DEPARTMENT OF JUSTICE

OFF ICE OF JUSTICE PROGRAMS

BJA NI J OJJDP BJS OVC

XE CE UT VI E OFFICE OF THE PRESIDENT OF THE UNITED STA ET S

OFFICE OF NATIONAL D R UG CONTR OL POLICY

UNUM

E PLURIBUS

Executive Office of the President

Office of National Drug Control Policy

R e s e a r c h R e p o r t

Office of National

Drug Control Policy

National Institute

of Justice

Crack, Powder Cocaine, and

Heroin: Drug Purchase and Use

Patterns in Six U.S. Cities
Executive Office of the President

Office of National Drug Control Policy

Washington, DC 20503

Barry R. McCaffrey

Director

U. S. Department of Justice

Office of Justice Programs

810 Seventh Street N.W.

Washington, DC 20531

Janet Reno

Attorney General

U.S. Department of Justice

Raymond C. Fisher

Associate Attorney General

Laurie Robinson

Assistant Attorney General

Noël Brennan

Deputy Assistant Attorney General

Jeremy Travis

Director, National Institute of Justice

Department of Justice Response Center:

800–421–6770

Office of Justice Programs National Institute of Justice

World Wide Web Site: World Wide Web Site:

http://www.ojp.usdoj.gov http://www.ojp.usdoj.gov/nij

Office of National Drug Control Policy

World Wide Web Site:

http://www.whitehousedrugpolicy.gov
Crack, Powder Cocaine, and Heroin:

Drug Purchase and Use Patterns in

Six U.S. Cities

K. Jack Riley

A report on research conducted under the joint auspices of the

National Institute of Justice and the Office of National Drug Control Policy

December 1997
Office of National Drug Control Policy

Barry R. McCaffrey

Director

National Institute of Justice

Jeremy Travis

Director

K. Jack Riley, Ph.D., is director of the

Arrestee Drug Abuse Monitoring program

at the National Institute of Justice.

Opinions or points of view expressed in this document do not necessarily reflect the official

position of the U.S. Department of Justice or the Office of National Drug Control Policy.

The National Institute of Justice is a component of the Office of Justice Programs, which also

includes the Bureau of Justice Assistance, the Bureau of Justice Statistics, the Office of Juvenile

Justice and Delinquency Prevention, and the Office for the Victims of Crime.

NCJ 167265
iii

Contents

Acknowledgments....................................................................................................................... vii

Executive Summary.................................................................................................................... 1

Summary of User Findings

Summary of Purchase Patterns

Summary of Use Patterns

Study Methodology ..................................................................................................................... 3

Profile of Users............................................................................................................................ 6

Age

Living Arrangements

Sources of Income

Arrest Charges

Race and Drug Use

Purchase Patterns ....................................................................................................................... 14

Buyer-Seller Relations

Dealer Networks

Location of Purchases

Failed Transactions

Purchase Frequency

Guns and Drug Purchases

Use Patterns................................................................................................................................. 21

Three-Day Use

Daily Use

Duration of Use

Cessation of Use

Conclusions and Implications.................................................................................................... 24

Drug User Profile

Drug Purchase Patterns

Drug Use Patterns

Policy Implications

Notes............................................................................................................................................. 26

Appendix ..................................................................................................................................... 29
v

List of Tables

Table 1. Attrition of Participants in Main DUF........................................................................ 4

Table 2. Eligibility for Participation in Procurement Study, by Drug, Gender,

and Age Group............................................................................................................ 4

Table 3. Percentage of Eligible Arrestees Participating in Procurement Study, by Gender

and Age Group............................................................................................................ 5

Table 4. Number of Individuals Participating in Procurement Study, by Interview Type ....... 5

Table 5. Participants in Procurement Study, by Gender and Age Group ................................. 6

Table 6. Participants in Procurement Study, by Race .............................................................. 6

Table 7. Mean Age of Participants in Procurement Study, by Drug ........................................ 7

Table 8. Living Arrangements Prior to Arrest, as Percentage of Total Participants,

by Site and Drug ......................................................................................................... 8

Table 9. Main Sources of Income Prior to Arrest, by Site and Drug ....................................... 9

Table 10. Average Monthly Income in Manhattan, by Reported Primary Source of Income.... 10

Table 11. Arrest Charges of Study Participants.......................................................................... 11

Table 12. Drug Use by Race of Arrestees .................................................................................. 12

Table 13. Race of Arrestees by Category of Drug Use .............................................................. 13

Table 14. Percentage of Respondents Using a Main Source, by Drug ....................................... 14

Table 15. Percentage of Respondents Using a Main Source, by Race and Drug ....................... 14

Table 16. Contingency Table of Use of Main Source Among Crack Users, by Race................ 15

Table 17. Number of Dealers Known, by Drug Used ................................................................ 16

Table 18. Percentage of Respondents Typically Making Purchases Outdoors .......................... 17

Table 19. Percentage of Respondents Typically Making Purchases

In Their Own Neighborhoods ..................................................................................... 17

Table 20. Percentage of Respondents with Failed Purchase Transactions in the Past Year ...... 18

Table 21. Reasons Cited for Failed Transactions ....................................................................... 19

Table 22. Percentage Reporting a Drug Purchase in the Week Prior to Arrest .......................... 20

Table 23. Mean Number of Purchases Made in the Week Prior to Arrest ................................. 20

Table 24. Drug Test Results by Completed Addendum Interview............................................. 21

Table 25. Drug Test Results for General DUF Population......................................................... 22
vi

Table 26. Percentage Describing Themselves as Daily Users, by Drug Used ........................... 22

Table 27. Mean Number of Daily Uses Among Those Describing Themselves

as Daily Users ............................................................................................................. 23

Table 28. Mean Number of Past Week Uses Among Those Describing Themselves

as Not Daily Users ....................................................................................................... 23

Table 29. Percentage of Respondents Reporting 30 or More Consecutive Days of Use

In the 90 Days Prior to Arrest..................................................................................... 23

Table 30. Percentage of Respondents Reporting 30 or More Consecutive Days

Of Abstinence in the 90 Days Prior to Arrest............................................................. 24

Table 31. Motivations for Periods of Abstinence Among Manhattan Arrestees, by Drug ........ 24
vii

Acknowledgments

The National Institute of Justice (NIJ) and

the Office of National Drug Control Policy

(ONDCP) would like to acknowledge the

contributions of individuals and organizations whose efforts made this project possible. ONDCP provided the resources to

fund the project. NIJ provided staff resources and access to the Drug Use Forecasting (DUF) sites that participated in the

project. Staff of BOTEC Analysis Corporation—including Ann Marie Rocheleau,

Jennifer Jackson, and Andrew Lockwood

Chalsma—were key to designing the interview instrument, conducting training, and

preparing the data. Similarly, Rosalee

Copeland and Jeremy Yuan at Aspen Systems Corporation’s Applied Management

Sciences Group provided data runs and

cross-checks between addendum data and

DUF data. NIJ and ONDCP staff provided

thoughtful suggestions for the project and

helpful reviews of draft reports. In addition, two anonymous reviewers provided

valuable critiques of an early draft. Many

DUF site staff contributed to making this

project happen by collecting the data, and

their cooperation is greatly appreciated:

James Swartz, Scott Slomka, and Norm

Hamilton (Chicago); Bruce D. Johnson,

Tom Miller, Phyllis Curry, Elliott Quinones, and Diane Concepcion (Manhattan);

Diane Wiscarson (Portland, Oregon); Ed

Baca and James Daniels (San Antonio);

Susan Pennell and Ami Caldwell (San Diego); and LaVon Williams (Washington,

D.C.). Special thanks go out to Bruce D.

Johnson, Susan Pennell, and Ami Caldwell

for their work on developing the interview

instrument and the training curriculum.
1

Crack, Powder Cocaine, and Heroin: Drug

Purchase and Use Patterns in Six U.S. Cities

Executive Summary

This document presents information collected

from 2,056 recently arrested powder cocaine,

crack cocaine, and heroin users from Chicago;

Manhattan; Portland, Oregon; San Antonio; San

Diego; and Washington, D.C. It highlights information concerning where and how arrestees

obtained and used drugs. Researchers used a

survey with approximately 100 questions to gather

information on the proximity of drug purchases to

the buyer’s home and neighborhood; the buyer’s

relationship to the seller; the elapsed time, duration, and frequency of purchases; the size and

price of drug transactions; how income is generated for drug purchases; the presence of firearms

during drug transactions; quantities of drugs

typically used; the form of drug and mode of

administration; frequency of drug use and cessation; reasons for cessation; and polydrug use

patterns.

The analysis revealed significant differences

within and across drug types. Furthermore, within

a given drug type (such as crack) significant

differences existed across cities, across racial,

ethnic, or age groups, or across other such definable subgroups. Across drug types, there were

nearly always differences, no matter what demographic or summary measure was considered.

Unless otherwise specified, the results include

adult males and females but exclude juveniles.

Summary of User Findings

■ Crack users reported living in shelters or on the

streets more frequently than did other drug

users in most sites. About 11.5 percent of crack

users in Washington, D.C., and 8.5 percent in

Manhattan reported living in a shelter prior to

arrest; 16 percent of crack users in San Diego,

13 percent in Manhattan, and 12 percent in San

Antonio reported being on the streets prior to

arrest.

■ Substantial fractions of respondents across all

drug types reported that public assistance was

their primary source of income prior to arrest.

In some cities, certain drug users (such as

Manhattan crack users) were more likely to

report public assistance as their main form of

income than full- and part-time work combined.

■ White and Hispanic participants spread their

drug use relatively evenly across the powder,

crack, heroin, and combination heroin markets.

Black participants primarily used crack.

Summary of Purchase Patterns

■ Heroin and powder cocaine users were more

likely to report using a main source (a single

individual) than crack users.

■ For most drugs in most sites, white drug users

were more likely than black drug users to

report using a main source.

■ Respondents were most likely to report using a

main source who was of their own racial or

ethnic background, regardless of the drug

considered.

■ On average, crack users reported knowing

more dealers from whom they could make

purchases than did powder and heroin users.
2

■ A large majority of crack and heroin users

reported that they typically made purchases

outdoors. Smaller (though still large) fractions

of powder purchasers reported that they usually bought drugs outdoors.

■ Similarly, crack and heroin users were more

likely than powder users to report that they

usually made their purchases in their own

neighborhoods.

■ Users reported that substantial majorities of

indoor purchases were made in residences.

Powder users reported that they typically made

indoor purchases in places of business more

frequently than did other users.

■ Large fractions of respondents (although not a

majority in most cities or for most drugs)

reported being unable to complete a drug

purchase at least once in the year prior to

arrest. The inability to locate a dealer and the

dealer’s lack of supply were frequently offered

as explanations for failed purchase attempts. In

addition, large fractions of Manhattan respondents reported police activity as the reason for

their failed transactions.

■ Substantial majorities of respondents from all

drug use categories and all sites reported

making at least one purchase in the week

before arrest. Among these, powder users

recorded the lowest mean number of purchases

(ranging from 3 to 9); heroin and crack users

reported much higher mean numbers of purchases in the week prior to arrest (ranging from

6 to 15 for heroin and 6 to 14 for crack).

Summary of Use Patterns

■ Study participants were very likely to test

positive for drugs, indicating that they had

used narcotics in the 72 hours before arrest. In

all sites, 90 percent or more of the crack

respondents tested positive for cocaine, and

more than 75 percent of the heroin respondents

tested positive for opiates. In five out of six

sites, more than 70 percent of the powder

respondents tested positive for cocaine.

■ In most sites, substantial majorities of heroin

users described themselves as daily users. In

contrast, approximately 40 to 50 percent of

crack users and 10 to 40 percent of powder

users described themselves as daily users.

■ Among those describing themselves as daily

users, powder and crack users generally reported consuming their drug more times per

day than did heroin users.

■ Larger proportions of heroin users than of

powder or crack users reported daily or neardaily use in the 90 days prior to arrest.

■ A majority of powder users in Manhattan

claimed that periods of nonuse or abstinence in

the 90 days prior to arrest formed part of their

regular use patterns, and similar trends were

found in other sites. A plurality of crack and

heroin users also reported that their regular

patterns included periods of nonuse. Substantial fractions of Manhattan crack users reported

cost (“could not afford”) and being “tired of

[the drug] life” as an explanation for periods of

nonuse. Among heroin users in Manhattan,

more than one-third attributed a recent period

of abstinence to either being in treatment

programs (nearly 24 percent) or being incarcerated (nearly 12 percent).

In summary, these findings suggest that the powder, crack, and heroin markets differ substantially

from one another in a variety of ways, including

how users buy and consume the drugs. Detailed

information about drug habits and patterns would

be a valuable tool for local law enforcement

officials, service providers, and policymakers.

In terms of specific drugs and markets, crack

stands out for its significant exposure to law

enforcement intervention. Crack transactions are

more frequent than powder or heroin transactions

(in aggregate), and crack transactions are more
3

likely to take place under conditions that expose

users to risk of arrest (for example, outdoors,

where they are visible to law enforcement). In

addition, crack users also have more extensive

networks of dealers; these wider networks introduce additional risks, including the opportunity for

compromise by law enforcement.

When reviewing the results of this study, it is

important to remember that two design factors

prevent the patterns and characteristics exhibited

by study participants from being representative of

drug users in any other locations. First, these six

cities are distinguished by their high rates of

heroin use. Second, the population interviewed as

part of this project consisted entirely of individuals

who were arrested; it is likely that drug users who

have not been arrested engage in different drug use

and procurement patterns.

Even so, the results suggest that the arrestee

population is appropriate for exploring motivations

for drug use and the impact of policy interventions. With appropriate questions, arrestee interviews could explore such critical factors as deterrence, substitution of one drug for another, and the

interaction between policing operations and the

need for treatment services.

Study Methodology

In 1993 and 1994, the Office of National Drug

Control Policy (ONDCP) demonstrated that heroin

users could be interviewed to describe various

aspects of drug market activity, including the

length of time it takes heroin users to locate and

purchase the drug.1 Improving the understanding

of search costs more accurately portrayed the full

costs users pay for drugs and helped policymakers

identify factors that affect the availability of drugs.

In 1995 ONDCP, in collaboration with the National Institute of Justice (NIJ), extended this

analysis to include two additional drugs—powder

cocaine and crack cocaine. This new study, called

the procurement study, was executed as an addendum to NIJ’s Drug Use Forecasting (DUF) program2

 and sought to explore additional features of

drug market participation and use, both within and

across drug types and cities. While earlier market

studies involved developing separate data collection samples, the procurement study was fielded as

a supplement to the ongoing interviews of arrestees as part of the DUF program. The study was

exploratory and was intended to address the

practical and policy implications of different drug

market participation patterns. Although this study

cannot identify what policies work best in a given

drug market, it does provide important insights on

how drug markets differ and how drug users and

drug markets are affected by different circumstances.

The procurement study, which added 100 questions to the DUF interview, was implemented

quarterly for 1 year in six DUF sites (Chicago;

Manhattan; Portland, Oregon; San Antonio; San

Diego; and Washington, D.C.). These sites were

selected because they had consistently shown the

highest rates of heroin use among the DUF sites,

and they had substantial levels of cocaine use. It

was important to select cities with a high heroin

prevalence in order to ensure that the study included an adequate number of heroin users.3

The DUF interview consists of fewer than 30

questions and is currently implemented in 23 sites

nationwide. The questions generate major demographic and descriptive data, including age, gender, race or ethnicity, education, living arrangements, sources and amounts of income, marital

status, drug treatment history, self-assessment of

need for treatment, emergency room history, and

recent criminal behavior. At the end of the interview, respondents—all of whom are recent

arrestees—are asked to provide a urine specimen

that is tested for 10 drugs, in order to validate their

self-reported drug use.4 Since the drug-screening

assay cannot reliably detect most drugs beyond 72

hours after use, arrestees who have been incarcerated for more than 48 hours do not qualify for the

DUF interview. During the procurement study

period (third quarter of 1995 through second

quarter of 1996), more than 11,000 arrestees in the
4

six procurement study sites were asked to participate in the DUF interview. Of these, 8,981 agreed

to participate in the main DUF interview and to

provide a urine specimen. Table 1 provides a

summary of participation in the DUF by study city.

Eligibility for the procurement study was defined

as having completed the main DUF questionnaire

and having reported powder, crack, or heroin use

in the 30 days prior to arrest.5 Arrestees who

reported having used more than one type of drug

during the 30 days preceding arrest were eligible

for more than one interview.6 More than 2,900

individuals were eligible to participate in the

procurement study, potentially representing 3,603

completed interviews (see table 2).

Table 2. Eligibility for Participation in Procurement Study, by Drug, Gender, and Age Group

Powder Crack Heroin Heroin and Powder Heroin and Crack Total

M FJ M FJ M F J M F J M F J

Chicago 106 — — 130 — — 152 — — 37 — — 40 — — 465

Manhattan 182 95 — 265 201 — 191 109 — 81 46 — 65 60 — 1,295

Portland 105 79 3 95 89 1 100 85 4 57 51 0 26 32 1 728

San Antonio 52 24 10 22 8 10 43 19 4 18 11 2 3 2 2 230

San Diego 89 23 9 123 35 10 73 27 8 33 16 0 25 6 1 478

Washington, D.C. 37 16 0 120 62 1 58 41 1 21 11 0 24 14 1 407

Total 571 237 22 755 395 22 617 281 17 247 135 2 183 114 5 3,603

Note: A dash indicates data were not collected from that gender or age group at a given site.

Key: F = adult female, J = juvenile, M = adult male

A total of 2,056 drug users were interviewed for

the procurement study. Study interviews were

conducted with about 42 percent of the eligible

powder users, 70 percent of the eligible crack

users, and 52 percent of the eligible heroin users,

although there was substantial variation by site and

gender (see table 3). In addition, two separate

interviews were completed with about 63 percent

of the eligible heroin-and-powder users and 57

percent of the eligible heroin-and-crack users.

Table 3 summarizes eligible arrestees’ participation in the study. These differential rates are at

least partially explained by the fact that interviewers were instructed to attempt to interview crack

users first, followed by heroin users and powder

Table 1. Attrition of Participants in Main DUF

Approached Interviewed Provided Specimen Completeda(%)

Chicago 906 870 832 91.8

Manhattan 1,499 1,470 1,436 95.8

Portland 2,591 2,105 1,902 73.4

San Antonio 1,861 1,740 1,679 90.2

San Diego 1,986 1,801 1,593 80.2

Washington, D.C. 2,711 1,901 1,539 56.8

Total 11,554 9,887 8,981 77.7

a This column reflects the percentage of those who were approached who consented both to being interviewed and to providing a urine specimen.
5

users. Because previous studies provided an

overview of heroin markets, this research emphasized interviewing crack users.7

The procurement interview consisted of approximately 100 questions and collected data on both

drug purchase patterns and drug use patterns. The

purchase pattern questions addressed such issues

as the proximity of purchases to the buyer’s home

and neighborhood; the relationship between buyer

and seller; frequency of purchases; source of

income for drug purchases; and the presence of

firearms during drug transactions. Use pattern

questions focused on the amount of narcotics

typically used; frequency of use and cessation; and

polydrug use patterns.

Two-thirds (1,620) of the interviews were conducted with adult males; 785, with adult females.

Among juvenile participants, 49 were boys and 16

were girls.8 Of all these individuals, 350 completed

an interview only for powder, 821 only for crack,

and 471 only for heroin; 242 completed separate

instruments for both powder and heroin, and 172

completed separate instruments for both crack and

heroin. (These latter two groups are often referred

to as combination heroin users in the text.) Because some respondents completed more than one

form, there were actually 2,470 completed interview forms—993 for crack, 592 for powder, and

885 for heroin. Table 4 summarizes participation in

the study by site. Table 5 breaks this information

Table 3. Percentage of Eligible Arrestees Participating in Procurement Study, by Gender and Age Group

Powder Crack Heroin Heroin and Powder Heroin and Crack Total

M FJ M FJ M F J M F J M F J

Chicago 34 — — 68 — — 80 — — 14 — — 55 — — 59

Manhattan 43 28 — 67 69 — 37 33 — 78 67 — 65 78 — 55

Portland 40 33 67 69 58 0 49 42 50 77 59 100 35 41 0 52

San Antonio 29 50 100 64 38 20 63 53 0 78 72 100 67 50 50 63

San Diego 53 26 100 77 91 40 55 41 63 52 63 100 68 67 100 63

Washington, D.C. 30 25 * 77 90 0 55 76 0 33 36 100 38 29 0 62

Total 45 32 73 71 71 27 55 44 41 61 61 100 55 61 40 57

Note: A dash indicates data were not collected from that gender or age group at a given site. An asterisk indicates that there were no eligible (i.e., reporting past

30-day drug use) arrestees at the site.

Key: F = adult female, J = juvenile, M = adult male

Table 4. Number of Individuals Participating in Procurement Study, by Interview Type

Heroin and Heroin and Total Individuals

Powder Crack Heroin Powder Crack Interviewed

Chicago 36 89 122 5 22 274

Manhattan 105 316 106 94 89 710

Portland 70 118 87 78 22 375

San Antonio 61 19 37 25 4 146

San Diego 63 131 56 28 22 300

Washington, D.C. 15 148 63 12 13 251

Total 350 821 471 242 172 2,056
6

down by gender and adult/juvenile status, while

table 6 contains data on racial categories.

Profile of Users

Age

Table 7 summarizes information regarding the age

of individuals participating in the study (excluding

juveniles). In general, powder users were the

youngest group (although not in all sites). Also,

combination heroin users were generally the

oldest. Some of the differences in average age

were statistically significant at the site level. Age

differences can have practical significance, in that

they may signal different initiation rates. For

example, recent initiation into crack use has been

relatively low in a number of DUF sites, resulting

in an aging of the crack-using cohort in those cities.9

Living Arrangements

Primary living arrangements of the respondents

varied by site. A majority or strong plurality of

Chicago and Manhattan residents, regardless of

their drug use category, reported living in an

apartment in the 30 days prior to arrest. Overall,

more than 40 percent of the users of each drug

reported living in an apartment, although this

distribution is affected by the concentration of

apartment dwellers in Chicago and Manhattan. In

contrast, a majority or strong plurality of respondents in Portland, San Antonio, San Diego, and

Washington, D.C., reported living in a house. At

Table 5. Participants in Procurement Study, by Gender and Age Group

Powder Crack Heroin Heroin and Powder Heroin and Crack Total

M F J M FJ M F J M F J M FJ

Chicago 36 — — 89 — — 122 — — 5 — — 22 — — 274

Manhattan 78 27 — 177 139 — 70 36 — 63 31 — 42 47 — 710

Portland 42 26 2 66 52 0 49 36 2 44 30 4 9 13 0 375

San Antonio 31 12 18 14 3 2 27 10 0 14 8 3 2 1 1 146

San Diego 47 6 10 95 32 4 40 11 5 17 10 1 17 4 1 300

Washington, D.C. 11 4 0 92 56 0 32 31 0 7 4 1 9 4 0 251

Total 245 75 30 533 282 6 340 124 7 150 83 9 101 69 2 2,056

Note: A dash indicates data were not collected from that gender or age group at a given site.

Key: F = adult female, J = juvenile, M = adult male

Table 6. Participants in Procurement Study, by Race

Powder Crack Heroin Heroin and Powder Heroin and Crack Total

B W H O B WHO B W H O B W H O B W H O

Chicago 16 9 11 0 72 4 13 0 100 10 8 4 2 1 1 1 21 1 0 0 274

Manhattan 62 22 19 2 228 28 55 5 39 28 38 1 31 32 29 2 44 18 23 4 710

Portland 8 48 13 1 65 45 3 5 10 69 7 1 5 46 16 11 8 13 0 1 375

San Antonio 5 16 40 0 12 3 4 0 3 9 24 1 1 4 20 0 1 1 2 0 146

San Diego 5 19 37 2 92 21 17 1 4 26 25 1 4 14 9 1 6 10 6 0 300

Washington, D.C. 15 0 0 0 137 8 1 2 55 8 0 0 10 2 0 0 11 1 1 0 251

Total 111 114 120 5 606 109 93 13 211 150 102 8 53 99 75 15 91 44 32 5 2,056

Key: B = black, H = Hispanic, O = other, W = white
7

the city level, heroin users were the most likely to

report living in public housing, although the specific type of heroin use (heroin only, heroin and

powder, or heroin and crack) that was prevalent

among residents of public housing varied from city

to city.

Crack users typically reported living in shelters

more frequently than other drug users at the city

level. Overall, 7 percent of crack users lived in a

shelter for most of the 30 days prior to arrest,

including 11.5 percent in Washington and 8.5

percent in Manhattan. In Chicago and Portland,

combination heroin users reported living in shelters more frequently than crack users. Typically,

however, such situations involved relatively small

numbers of respondents. In the nonqualifying DUF

population (that is, those who did not report using

these drugs in the 30 days prior to arrest), less than

2 percent reported living in shelters immediately

before arrest.

Similar findings were evident with respect to those

respondents living on the streets. That is, crack

users typically reported being on the streets more

frequently than other drug users, although the rates

for combination heroin users were generally

comparable. Overall, San Diego reported the

highest street-living rate (16.5 percent across

drugs), a finding that may be largely attributable to

the area’s benevolent climate. The rate of street

living for procurement study participants was

substantially higher than the rate for the general

DUF population. Between 3 and 4 percent of the

nonqualifying DUF respondents reported living on

the streets prior to their arrest, compared to rates

that were three and four times higher in this study

population. Table 8 summarizes issues related to

living arrangements.

Sources of Income

A sizeable fraction of the respondents reported that

their main source of income was either full-time or

part-time work. San Antonio reported the highest

rate of employment (either part-time or full-time)

across drug use categories, 65 percent. Manhattan

reported the lowest rate of combined full- and parttime work, less than 28 percent. Generally, at the

site level, powder users were most likely to report

work as the primary source of their income (the

specific percentages varied by city). Table 9 presents information relating to income sources by

site and drug used.

Combined across drug categories, more Manhattan

participants reported public assistance as their

largest single source of income (more than 32

percent) than all forms of work combined (less

than 28 percent). In contrast, about 11 percent of

the San Antonio respondents reported public

assistance as their primary source of income.

Across cities, powder users generally reported

public assistance as their primary income source

Table 7. Mean Age of Participants in Procurement Study, by Drug

Powder Crack Heroin Heroin and Powder Heroin and Crack

(1) (2) (3) (4) (5)

Chicago 30.0 34.0 32.1 34.0 34.4

Manhattan 34.3 34.9 33.9 34.8 36.5

Portland 31.45 33.0 34.2 32.3 37.81

San Antonio 27.3 33.2 32.3 32.7 29.5

San Diego 29.02,3,4 34.61 34.91 37.41 33.6

Washington, D.C. 35.3 34.0 37.3 38.0 36.8

Notes: One-way analysis of variance, Bonferroni pairwise significance test. Superscripts indicate that the value differs significantly (p = .05) from the value in the

numbered column corresponding to the superscript number.
8

much less frequently than other drug users. Crack,

heroin, and combination heroin users reported

public assistance as their primary income source

with greater frequency than powder users.

A much larger fraction of women (31 percent)

mentioned public assistance as a main source of

income than of men (14 percent). In no city did

males report public assistance as a main source of

Table 8. Living Arrangements Prior to Arrest, as Percentage of Total Participants, by Site and Drug

Drug Used Living Arrangements (%)

Public Housing Private Apartment House Shelter Street

Chicago Powder 8.3 63.9 27.8 0.0 0.0

Crack 2.2 51.7 29.2 5.6 6.7

Heroin 4.9 57.4 32.0 0.8 3.3

Heroin and Powder 20.0 40.0 40.0 0.0 0.0

Heroin and Crack 9.1 13.6 13.6 9.1 0.0

Manhattan Powder 17.1 60.0 12.4 1.9 6.7

Crack 22.5 43.7 10.1 8.5 13.0

Heroin 24.5 50.9 11.3 5.7 3.8

Heroin and Powder 9.6 58.5 13.8 4.3 13.0

Heroin and Crack 20.2 52.8 10.1 7.9 7.9

Portland Powder 2.9 39.7 29.4 4.4 15.0

Crack 3.4 35.6 40.7 3.4 8.5

Heroin 2.4 38.8 44.7 1.2 9.4

Heroin and Powder 4.1 39.2 24.3 6.8 18.0

Heroin and Crack 4.5 31.8 54.5 4.5 0.0

San Antonio Powder 14.0 32.6 44.2 2.3 4.7

Crack 5.9 23.5 47.1 5.9 12.0

Heroin 16.7 19.4 47.2 0.0 14.0

Heroin and Powder 9.1 18.2 59.1 0.0 14.0

Heroin and Crack 0.0 33.3 33.3 0.0 33.0

San Diego Powder 0.0 34.0 50.9 0.0 11.0

Crack 0.0 49.6 23.6 2.4 16.0

Heroin 0.0 50.0 36.0 0.0 12.0

Heroin and Powder 0.0 37.0 44.4 0.0 19.0

Heroin and Crack 0.0 23.8 33.3 0.0 43.0

Washington, D.C. Powder 6.7 26.7 53.3 13.3 0.0

Crack 7.4 38.5 35.8 11.5 3.4

Heroin 9.5 41.3 41.3 6.3 1.6

Heroin and Powder 18.2 18.2 54.5 9.1 0.0

Heroin and Crack 7.7 38.5 38.5 7.7 7.7

Note: Not all responses fell into one of the five types of living arrangements shown here; therefore, percentages may not total 100.
9

income more frequently than females. Manhattan

had the highest percentage of both males (19 percent)

and females (37 percent) reporting public assistance

as their primary source of income, while San Antonio

had the lowest rate for males (4 percent) and Portland for females (19 percent).

Table 9. Main Sources of Income Prior to Arrest, by Site and Drug

Main Source of Income (%)

Public Work (Full- Drug Other Illegal

Assistance and Part-Time) Family Dealing Activities Other

Chicago Powder 5.6 61.1 5.6 13.9 0.0 13.9

Crack 17.1 57.3 7.3 9.8 0.0 8.5

Heroin 17.4 52.2 5.2 18.3 0.0 7.0

Heroin and Powder 0.0 50.0 25.0 25.0 0.0 0.0

Heroin and Crack 26.3 36.8 0.0 31.6 0.0 5.3

Manhattan Powder 25.0 39.1 4.3 19.6 2.2 9.8

Crack 35.5 26.7 10.8 13.9 6.0 7.2

Heroin 32.9 32.9 5.3 15.8 6.6 6.6

Heroin and Powder 34.6 24.7 3.7 18.5 8.6 9.9

Heroin and Crack 31.3 10.4 6.0 31.3 11.9 9.0

Portland Powder 13.1 39.3 6.6 11.5 9.8 19.7

Crack 20.4 43.7 8.7 7.8 9.7 9.7

Heroin 21.6 41.9 1.4 10.8 4.1 20.3

Heroin and Powder 11.7 31.7 3.3 33.3 6.7 13.3

Heroin and Crack 26.7 20.0 6.7 33.3 0.0 13.3

San Antonio Powder 12.2 78.0 2.4 0.0 2.4 4.9

Crack 18.8 56.3 0.0 0.0 6.3 18.8

Heroin 7.4 66.7 0.0 3.7 3.7 18.5

Heroin and Powder 26.7 33.3 13.3 0.0 20.0 6.7

Heroin and Crack 0.0 100.0 0.0 0.0 0.0 0.0

San Diego Powder 5.9 62.7 2.0 13.7 2.0 13.7

Crack 24.8 35.9 9.4 10.3 3.4 16.2

Heroin 20.4 46.9 8.2 8.2 0.0 16.3

Heroin and Powder 23.8 19.0 4.8 23.8 14.3 14.3

Heroin and Crack 20.0 33.3 0.0 26.7 0.0 20.0

Washington, D.C. Powder 21.4 57.1 0.0 14.3 0.0 7.1

Crack 18.0 51.1 7.9 2.9 2.9 17.3

Heroin 25.0 35.7 16.1 3.6 5.4 14.3

Heroin and Powder 16.7 33.3 16.7 16.7 0.0 16.7

Heroin and Crack 15.4 23.1 15.4 0.0 7.7 38.5

Note: Percentages may not total 100 due to rounding.
10

A large fraction of the respondents generated their

main income from illegal activities. The highest

rate of participation in illegal activities to provide

primary income was found in Manhattan and

Chicago (24 percent across drug categories) and

the lowest in Washington, D.C. (less than 8 percent). Prostitution was not counted in the “other

illegal” category, but was counted in “other.”

Among females, about 20 percent of combination

heroin-and-powder users and 10 percent of all

other drug users reported deriving the largest share

of their income from prostitution.

Table 10 shows average monthly incomes by

primary source category. That is, it shows the

average total income for the 30 days preceding

arrest, with the respondents grouped according to

the primary reported income source. These data

are limited to Manhattan because it is difficult to

reliably combine data across sites. Even though

Manhattan is not necessarily representative of the

other sites, it offers the advantage of having more

data than any other study location. The results

should not be generalized to other sites.

Approximately 20 percent of the respondents

reported no legal income; 55 percent reported no

illegal income; and the balance reported a combination of legal and illegal income. In Manhattan,

those who reported welfare and Supplemental

Security Income (SSI) as their major financial

resource had an average monthly income of $514

prior to arrest, ranging from $607 for heroin-andpowder users to $395 for powder users. Not all of

that money came from welfare and other public

sources; rather, that was the average total income

for people who reported public assistance as their

primary source of income. If median, rather than

average, incomes were used, the amounts would

drop, but the relative ranks would remain the same.

Arrest Charges

Participants in the procurement study were more

likely than nonparticipating DUF respondents to

have been arrested on drug charges (see table 11).

For many nondrug offenses, the percentages were

approximately equal in the two groups. However,

both violent and weapons offenders were represented less frequently in the procurement study

than in the DUF study. The higher rate at which

drug offenders were represented in the procurement study suggests that recent drug use is concentrated among drug offenders. An examination of

recent DUF statistics confirms that drug offenders

(and those arrested on prostitution charges) are

more likely than most other arrestees to test positive for cocaine and other drugs.10 A likely explaTable 10. Average Monthly Income in Manhattan, by Reported Primary Source of Income

Source of Income Procurement Study Participants DUF Participants

Heroin Heroin

Powder Crack Heroin and Powder and Crack

Welfare/SSI 395 452 536 607 583 462

Working Full Time 1,357 1,710 1,619 2,186 1,831 1,675

Working Part Time 736 883 2,000 3,437 900 1,006

Family 1,110 399 913 467 740 361

Other Legal Activities 6,087 917 1,667 1,507 n/a 1,767

Prostitution 1,500 2,093 3,360 1,871 2,500 3,112

Dealing Drugs 5,342 2,361 1,538 2,328 2,135 2,779

Other Illegal Activities 886 1,769 2,176 2,238 1,354 1,754

Key: n/a = data not available, SSI = Supplemental Security Income
11

nation for the overrepresentation of drug offenders

in the procurement study may be that recent use is

found disproportionately among drug offenders

and the study screened for recent use. Since drug

offenders participated in the procurement study

with disproportionate frequency, it is important to

examine whether such users have market participation characteristics that distinguish them from

other users. Thus, data for drug offenders and

nondrug offenders are reported separately in some

analyses.

Race and Drug Use

Tables 12 and 13 illustrate the intersection of race

and drugs in different ways. Table 12 shows

percentages by race within drug use categories.

Table 13 shows percentages by drug use category

within race. Both tables are divided into drug

offender and nondrug offender categories. This

division demonstrates the relative stability of drug

use across offense patterns and partially adjusts for

drug arrest practices that may disproportionately

affect certain groups in the cities.

Table 12 reveals that blacks generally constitute a

majority or plurality of users within all drug categories. For example, approximately 73 percent of

crack-using drug offenders and 72 percent of

crack-using nondrug offenders in Manhattan were

black. Table 12 also reveals that whites’ largest

share of a drug category’s population was generally among heroin users (however, in Portland,

whites were disproportionately represented among

powder cocaine users as well). Excluding Chicago

(because of the small number of whites interviewed), whites constituted anywhere from more

than 75 percent of the heroin population (Portland)

to 16 percent (Washington, D.C.).

Table 13 reveals that drug use is relatively evenly

spread across powder, crack, and heroin among

both whites and Hispanics. That is, approximately

equal proportions of whites can be found among

crack, powder, heroin, and combination users; a

similar pattern holds for Hispanics. Many deviations from this general pattern are shown in table

13, but these are usually accompanied by a small

number of observations.

In contrast, table 13 reveals that drug use among

blacks is highly concentrated in crack. In every city

but Chicago, more than 50 percent of the blacks

interviewed reported that they used crack. Generally, heroin was the drug next most frequently

reported by blacks. The concentration of black drug

use in crack appears regardless of whether the

individual was arrested on a drug offense or a

nondrug offense. Thus, even if arrest practices for

crack unduly result in excess arrests of blacks on

crack charges, the high rate of crack use among

black nondrug offenders indicates that something

other than drug arrest practices must be invoked to

explain drug use patterns among black arrestees.

Table 11. Arrest Charges of Study Participants

Arrest Charge Addendum DUF

Participants Participants

(%) (%)

Drug Possession 23.8 14.6

Larceny 17.8 15.3

Violent Offense 11.8 18.0

Drug Sale 9.9 7.1

Burglary 6.2 5.6

Vehicle Theft 3.0 3.7

Weapons Offense 2.0 4.1

Prostitution 1.5 1.1

Sex or Domestic Violence 1.2 0.6

Resisting Arrest 1.0 1.7

Other 21.9 28.2

Note: Percentages may not total 100 due to rounding.
12

Table 12. Drug Use by Race of Arrestees

Drug Offenders Only

N Powder Crack Heroin Heroin and Powder Heroin and Crack

Row % B W H O B W H O B W H O B W H O B W H O

Chicago 1 3 2 0 14 2 6 0 29 1 4 1 0 0 0 0 8 1 0 0

16.7 50.0 33.3 0 63.6 9.1 27.3 0 82.9 2.9 11.4 2.9 0000 88.9 11.1 0 0

Manhattan 9 7 7 0 74 12 15 0 9 8 12 1 8 12 8 0 14 8 9 1

39.1 30.4 30.4 0 73.3 11.9 14.9 0 30.0 26.7 40.0 3.3 28.6 42.9 28.6 0 43.8 25.0 28.1 3.1

Portland 7 14 6 0 23 15 1 1 3 24 5 0 1 15 10 5 3301

25.9 51.9 22.2 0 57.5 37.5 2.5 2.5 9.4 75.0 15.6 0 3.2 48.4 32.3 16.1 42.9 42.9 0 14.3

San Antonio 0 1 10 0 5100 1140 1030 0000

0 9.1 90.0 0 83.3 16.7 0 0 16.7 16.7 66.7 0 25.0 0 75.0 0 0000

San Diego 3 8 19 1 42 9 8 1 0 9 12 0 3330 1540

9.7 25.8 61.3 3.2 70.0 15.0 13.3 1.7 0 42.9 57.1 0 33.3 33.3 33.3 0 10.0 50.0 40.0 0

Washington, D.C. 1 0 0 0 28 6 0 0 21 4 0 0 3 0 0 0 2 0 1 0

100.0 0 0 0 82.4 17.6 0 0 84.0 16.0 0 0 100.0 0 0 0 66.7 0 33.3 0

Nondrug Offenders OnlyChicago 15 6 9 0 58 2 7 0 71 9 4 2 2 1 1 1 13 0 0 0

50.0 20.0 30.0 0 86.6 3.0 10.4 0 82.6 10.5 4.7 2.3 40.0 20.0 20.0 20.0 100.0 0 0 0

Manhattan 53 15 12 2 154 16 40 3 30 20 26 0 23 20 21 2 29 10 14 2

64.6 18.3 14.6 2.4 72.3 7.5 18.8 1.4 39.5 26.3 34.2 0 34.8 30.3 31.8 3.0 53.6 18.2 25.5 3.6

Portland 1 33 6 1 42 30 2 4 7 43 2 1 4 29 5 4 5 10 0 0

2.4 80.5 14.6 2.4 53.8 38.5 2.6 5.1 13.2 81.1 3.8 1.9 9.5 69.0 11.9 9.5 33.3 66.7 0 0

San Antonio 3 13 16 0 7 2 2 0 2 8 20 0 0 3 15 0 1 1 1 0

9.4 40.6 50.0 0 63.6 18.2 18.2 0 6.7 26.7 66.7 0 0 16.7 83.3 0 33.3 33.3 33.3 0

San Diego 2 9 11 0 49 11 7 0 4 15 10 1 1 11 5 1 5510

9.1 40.9 50.0 0 73.1 16.4 10.4 0 13.3 50.0 33.3 3.3 5.6 61.1 27.8 5.6 45.5 45.5 9.1 0

Washington, D.C. 14 0 0 0 109 2 1 2 34 4 0 0 6 2 0 0 10 1 0 0

100.0 0 0 0 95.6 1.8 0.9 1.8 89.5 10.5 0 0 75.0 25.0 0 0 90.9 9.1 0 0

Key: B = black, W = white, H = Hispanic, O = other
13

Table 13. Race of Arrestees by Category of Drug Use

Drug Offenders Only

Black White Hispanic Other

Powder Crack Heroin Heroin Heroin Powder Crack Heroin Heroin Heroin Powder Crack Heroin Heroin Heroin Powder Crack Heroin Heroin Heroin

N and and and and and and and and

Row % Powder Crack Powder Crack Powder Crack Powder Crack

Chicago 1 14 29 0 8 3 2 1 0 1 2 6 4 0 0 0 0 1 00

1.9 26.9 55.8 0 15.4 42.9 28.6 14.3 0 14.3 16.7 50.0 33.3 0000 100.0 0 0

Manhattan 9 74 9 8 14 7 12 8 12 8 7 15 12 8 9 0 0 1 01

7.9 64.9 7.9 7.0 12.3 14.9 25.5 17.0 25.5 17.0 13.7 29.4 23.5 15.7 17.6 0 0 50.0 0 50.0

Portland 7 23 3 1 3 14 15 24 15 3 6 1 5 10 0 0 1 0 5 1

18.9 62.2 8.1 2.7 8.1 19.7 21.1 33.8 21.1 4.2 27.3 4.5 22.7 45.5 0 0 14.3 0 71.4 14.3

San Antonio 0 5 1 1 0 1 1 1 0 0 10 0 4 3 0 0 0 0 0 0

0 71.4 14.3 14.3 0 33.3 33.3 33.3 0 0 58.8 0 23.5 17.6 0 0 0 0 00

San Diego 3 42 0 3 1 8 9 9 3 5 19 8 12 3 4 1 1 0 0 0

6.1 85.7 0 6.1 2.0 23.5 26.5 26.5 8.8 14.7 41.3 17.4 26.1 6.5 8.7 50.0 50.0 0 0 0

Washington, D.C. 1 28 21 3 2 0 6 4 0 0 0 0 0 0 1 0 0 0 00

1.8 50.9 38.2 5.5 3.6 0 60.0 40.0 000000 100.0 0 0 0 00

Nondrug Offenders OnlyChicago 15 58 71 2 13 6 2 9 1 0 9 7 4 1 0 0 0 2 10

9.4 36.5 44.7 1.3 8.2 33.3 11.1 50.0 5.6 0 42.9 33.3 19.0 4.8 0 0 0 66.7 33.3 0

Manhattan 53 154 30 23 29 15 16 20 20 10 12 40 26 21 14 2 3 0 22

18.3 53.3 10.4 8.0 10.0 18.5 19.8 24.7 24.7 12.3 10.6 35.4 23.0 18.6 12.4 22.2 33.3 0 22.2 22.2

Portland 1 42 7 4 5 33 30 43 29 10 6 2 2 5 0 1 4 1 40

1.7 71.2 11.9 6.8 8.5 22.8 20.7 29.7 20.0 6.9 40.0 13.3 13.3 33.3 0 10.0 40.0 10.0 40.0 0

San Antonio 3 7 2 0 1 13 2 8 3 1 16 2 20 15 1 0 0 0 0 0

23.1 53.8 15.4 0 7.7 48.1 7.4 29.6 11.1 3.7 29.7 3.7 37.0 27.8 1.9 0 0 0 00

San Diego 2 49 4 1 5 9 11 15 11 5 11 7 10 5 1 0 0 1 1 0

3.3 80.3 6.6 1.6 8.2 17.6 21.6 29.4 21.6 9.8 32.4 20.6 29.4 14.7 2.9 0 0 50.0 50.0 0

Washington, D.C. 14 109 34 6 10 0 2 4 2 1 0 1 0 0 0 0 2 0 00

8.1 63.0 19.7 3.5 5.8 0 22.2 44.4 22.2 11.1 0 100.0 0000 100.0 0 0 0
14

Purchase Patterns

Buyer-Seller Relations

Heroin users and powder cocaine users were more

likely to report using a main source—one seller

from whom the buyer regularly or usually purchases drugs—than were crack users. More than

47 percent of powder users and nearly 46 percent

of heroin users reported having a main source,

compared to less than 36 percent of crack users.

Site variations on use of a main source were

evident. Ignoring combination users, crack users

were the least likely to rely on a main source in

three of the six sites. In general, respondents in

Chicago, Manhattan, and Washington, D.C., were

the least likely to use a main source, regardless of

the drug they used. In Portland, powder cocaine

purchases were slightly less likely to involve a

main source than were crack cocaine purchases.

The frequency with which combination drug users

used main sources varied with the specific drug.

For example, heroin-and-crack users in Manhattan

had main sources for heroin in nearly 54 percent of

the cases, but for crack in less than 43 percent of

the cases. Table 14 presents findings about the use

of a main source at the site level.

Black drug users participating in this study were

generally least likely to use a main source for

obtaining their drugs (see table 15). Exceptions

Table 14. Percentage of Respondents Using a Main Source, by Drug

variable = cmnsrce Powder Crack Heroin Heroin and Powder Heroin and Crack

Heroin Powder Heroin Crack

(1) (2) (3) (4) (5) (6) (7)

Chicago 27.8 23.6 23.0 60.0 40.0 27.3 27.3

Manhattan 46.74 33.26,7 40.0 35.11 29.86 53.92,5 42.72

Portland 45.63 50.0 62.41 54.1 43.2 59.1 36.4

San Antonio 58.1 58.8 67.6 59.1 68.2 33.3 33.3

San Diego 49.04 44.13,4,5 72.52 85.21,2 77.82 66.7 57.1

Washington, D.C. 46.7 34.7 39.7 54.5 54.5 23.1 23.1

Notes: Pairwise chi-squared test. Superscripts indicate that the value differs significantly (p = .05) from the value in the numbered column corresponding to the

superscript number.

Table 15. Percentage of Respondents Using a Main Source, by Race and Drug

variable = cmnsrce Powder Crack Heroin

B W H B W H BWH

(1) (2) (3) (4) (5) (6) (7) (8) (9)

Chicago 43.8 33.3 n/a 19.46 25.0 46.24 23.0 20.0 37.5

Manhattan 43.5 63.6 42.1 32.5 39.3 34.5 30.8 50.0 40.5

Portland 37.5 48.9 41.7 44.66 57.86 100.04,5 30.08 70.17,9 28.68

San Antonio 66.7 50.0 61.5 66.7 33.3 50.0 33.38 100.07,9 62.58

San Diego 50.0 58.8 41.4 46.2 45.0 26.7 100.08,9 70.87 68.27

Washington, D.C. 46.7 n/a n/a 33.8 50.0 n/a 36.4 62.5 n/a

Notes: Pairwise chi-squared test. Superscripts indicate that the value differs significantly (p = .05) from the value in the numbered column corresponding to the

superscript number.

Key: B= black, H = Hispanic, n/a = not available, W = white
15

were found, but these were typically in situations

with a limited number of observations. (After

stratification by city, use of main source, drug, and

race, the cell sizes were often too small for significance testing.) In most cases, the rate of Hispanics

who relied on main sources fell between the rates

of blacks and whites; however, the individual site

samples included a relatively small number of

Hispanic participants. Table 15 does not report on

combination heroin users, because of limited data

in these categories.

Respondents who reported having a main source

were asked to identify the ethnicity of their main

source. Table 16, which is a contingency table,11

illustrates the interdependence of buyers’ and main

sources’ ethnicity for crack. (Because of the

complexity of the table and the relatively small

number of observations for drugs other than crack,

only crack sources are presented in table 16.) The

top line in every cell reports the observed number

of main sources by ethnicity; the middle row

reports the expected number of main sources by

ethnicity (calculated from the row and column

percentages multiplied by the cell population); and

the last row reports the difference between the

observed and expected, adjusted by the variation in

the data. Negative values for adjusted residuals

indicate that there were fewer observations in the

cell than if the row and column variables were

independent. If the cumulative deviations of

expected values from observed values are large,

then the hypothesis that the race of the buyer and

the race of the main source are independent of

each other can be rejected. In the case of crack, the

hypothesis of independence can be rejected for

each site. In other words, it is likely that there is an

interaction between the race of the buyer and the

race of the main source, and that the differences

between observed and expected values are not due

to chance.

To take some examples from table 16, the intersection of black main source with black buyer in

Manhattan shows that 42 black crack users reported a black main source, whereas 39.1 would

Table 16. Contingency Table of Use of Main Source

Among Crack Users, by Race

variable = cmnsreth Ethnicity of Reported Ethnicity

Respondent of Respondent’s

Observed (Buyer) Main Source

Expected

Adjusted Residuals Black White Hispanic

Chicago* Black 13.0 n/a 1.0

10.7 3.3

2.5 -2.5

White 0.0 n/a 1.0

0.8 0.2

-1.8 1.8

Hispanic 3.0 n/a 3.0

4.6 1.4

-1.8 1.8

Manhattan* Black 42.0 0.0 32.0

39.1 2.1 32.7

1.2 -2.8 -0.3

White 5.0 3.0 3.0

5.8 0.3 4.9

-0.5 5.1 1.1

Hispanic 0.0 0.0 10.0

0.5 0.0 8.0

-1.1 -0.2 1.1

Portland* Black 22.0 2.0 3.0

21.5 3.5 2.5

0.3 -1.2 0.5

White 18.0 5.0 2.0

19.2 3.1 2.2

-0.8 1.5 -0.2

Hispanic 2.0 0.0 0.0

1.5 0.3 0.2

0.8 -0.5 -0.5

San Diego* Black 19.0 2.0 19.0

18.1 1.5 20.4

0.6 0.8 -0.9

White 4.0 0.0 5.0

4.1 0.3 4.6

-0.1 -0.7 0.3

Hispanic 1.0 0.0 2.0

1.4 0.1 1.5

-0.4 -0.4 0.6

Washington, D.C.* Black 40.0 3.0 2.0

39.6 2.7 2.7

0.6 0.6 -1.4

White 4.0 0.0 0.0

3.5 0.2 0.2

0.8 -0.5 -0.5

Hispanic n/a n/a n/a

Key:* = Chi-squared test of independence, significant at p = .05. San Antonio

data are not reported because of insufficient observations.

n/a = insufficient observations to analyze cell
16

have been expected if no interaction had existed

and independence had prevailed. Thus, there was a

slightly disproportionate tendency for blacks to buy

crack from a black main source in Manhattan.

Reading down the diagonal for each site, it is

evident that a tendency to buy disproportionately

from a person of the same race existed in most sites

for most racial groups (these are shaded in black in

table 16). That is, the adjusted residuals down the

same race diagonal are usually positive. Some racial

or ethnic groups in some cities disproportionately

reported main sources of a different ethnicity,

although this occurred only in cases with small

numbers of observations. Manhattan’s powder

cocaine markets and Chicago’s heroin markets also

showed that buyers were disproportionately likely to

report using a main source of their own ethnicity.

All other markets had insufficient observations to

model the relationship.

Dealer Networks

Crack users reported having more extensive dealer

networks than powder users or heroin users.12 The

reported dealer structure for crack held up across all

sites; that is, in no site did the average number of

powder or heroin dealers exceed the average number of crack dealers. Note, however, that the differences in means did not test significantly across any

pairwise combinations in any of the sites. This is

primarily because the data on dealers known are not

normally distributed; rather, they are skewed with a

long righthand tail. When the dealer data are log

transformed, the distribution is approximately

normal and many pairwise differences are significant. Table 17 reflects log-transformed data. San

Antonio and Manhattan respondents generally

reported smaller dealer networks than the other

cities; Chicago and San Diego respondents, medium-sized networks; and Portland and Washington,

D.C., respondents had larger networks.

Location of Purchases

Most crack and heroin purchases were reportedly

made outdoors. For both drugs, a majority of

respondents in all sites (except the Portland crack

and San Diego heroin markets), reported making

their purchases outdoors. In contrast, powder

cocaine users typically reported making purchases

outdoors with less frequency than crack and heroin

users. Weather did not appear to be a significant

factor in determining the market’s predominant

structure. Cities with a warmer climate, such as

San Diego and San Antonio, exhibited trends that

were similar to the overall trend—even in these

two cities, crack purchases tended to be made

outdoors and powder purchases indoors. Only in

Portland did a majority of crack users (52.5 percent)

report typically making crack purchases indoors.

Two cities—Chicago and Washington, D.C.—can

be characterized as having primarily outdoor drug

markets. In those cities, more than 70 percent of

all transactions for most drugs were reported as

Table 17. Number of Dealers Known, by Drug Used

variable = log(cnumppl) Powder Crack Heroin Heroin and Powder Heroin and Crack

Heroin Powder Heroin Crack

(1) (2) (3) (4) (5) (6) (7)

Chicago 9.32,7 18.71 11.8 11.8 15.0 16.67 27.11,6

Manhattan 12.22,7 14.81,6 10.5 11.7 10.7 8.92,7 14.21,6

Portland 20.0 25.63 18.02,5 28.8 30.33 16.6 27.4

San Antonio 10.8 21.2 11.6 11.4 9.7 1.7 10.3

San Diego 9.22 25.51 9.6 12.0 11.4 18.0 23.4

Washington, D.C. 7.7 23.3 19.3 18.4 19.4 12.9 27.1

Notes: One-way analysis of variance, Bonferroni pairwise significance test. Superscripts indicate that the value differs significantly (p = .05) from the value in the

numbered column corresponding to the superscript number.
17

typically occurring outdoors. Table 18 provides a

summary of outdoor purchases, by drug type and site.

As shown in table 19, crack users were generally

likely to report making their purchases in their

own neighborhoods. (Respondents used their own

definitions of “neighborhood” when answering the

question.) In five of the six sites, a majority of

crack users reported usually making purchases in

their neighborhood, compared to a majority of

heroin users in four of the six sites and a majority

of powder users in two of the sites. The frequency

of crack purchases near the home ranged from

73.4 percent in Manhattan to 47.5 percent in

Portland.

Of purchases that took place indoors, the overwhelming majority occurred in a residence.

More than 85 percent of crack respondents and 88

percent of heroin respondents usually made indoor

purchases in residences. For crack, residencebased purchases ranged from 100 percent in San

Antonio to 78 percent in Manhattan. For heroin,

residence-based purchases ranged from 100 percent in San Antonio and Washington, D.C., to 71

percent in Manhattan. In contrast, powder cocaine

transactions, while still predominantly occurring in

residences, were more likely than heroin or crack

transactions to occur in businesses. Overall, about

22 percent of powder respondents reported usually

buying at a place of business, ranging from a low

of 12 percent in San Diego to a high of 38 percent

in Chicago. Manhattan, Chicago, and Washington

reported the highest rates of making purchases in

abandoned buildings, at least for heroin-only and

Table 18. Percentage of Respondents Typically Making Purchases Outdoors

variable = cbuynout Powder Crack Heroin Heroin and Powder Heroin and Crack

Heroin Powder Heroin Crack

(1) (2) (3) (4) (5) (6) (7)

Chicago 75.0 86.54 91.84 60.02,3,6,7 40.0 95.54 95.54

Manhattan 43.32,3,5,7 73.21 72.41 74.5 59.61 66.3 61.41

Portland 60.3 47.53,5 68.22 79.5 68.92 50.0 50.0

San Antonio 38.1 58.8 70.3 45.5 45.5 33.3 100.0

San Diego 46.0 65.9 45.1 59.3 63.0 50.0 61.9

Washington, D.C. 57.1 81.6 88.9 90.9 90.9 92.3 84.6

Notes: Pairwise chi-squared test. Superscripts indicate that the value differs significantly (p = .05) from the value in the numbered column corresponding to the

superscript number.

Table 19. Percentage of Respondents Typically Making Purchases in Their Own Neighborhoods

variable = cbuyhood Powder Crack Heroin Heroin and Powder Heroin and Crack

Heroin Powder Heroin Crack

(1) (2) (3) (4) (5) (6) (7)

Chicago 38.92,6 68.51 65.6 60.0 100.0 77.31 81.8

Manhattan 60.6 73.4 74.0 67.7 72.3 77.5 78.4

Portland 54.4 47.5 40.06 51.4 51.4 72.73 86.4

San Antonio 44.2 64.7 62.2 63.6 68.2 0.0 0.0

San Diego 42.3 62.2 58.8 74.1 66.7 55.0 66.7

Washington, D.C. 40.0 64.93 39.72 54.5 54.7 30.8 69.2

Notes: Pairwise chi-squared test. Superscripts indicate that the value differs significantly (p = .05) from the value in the numbered column corresponding to the

superscript number.
18

crack-only purchases. About 10 percent of Manhattan respondents reported regularly buying crack

and heroin in abandoned buildings, as did 9 percent of Chicago respondents and 7 percent of

Washington respondents.

By race and ethnic group, Hispanics and blacks

were more likely than whites to report that they

usually made their purchases outdoors. This result

usually held across drug type and across sites,

except in situations where there were a small

number of observations. Hispanics and blacks

were also more likely than whites to report making

the majority of their purchases in their own neighborhoods (again, across drug types and sites).

Failed Transactions

Respondents were asked to recall if they had

unsuccessfully attempted to purchase drugs in the

past year. The fraction of arrestees who had at least

one failed transaction varied substantially by drug

and by city. Overall, crack users (excluding combination users) were typically the most likely to have

reported a failed transaction at the site level (see

table 20). Generally, large fractions of users in

Manhattan failed to complete purchases, although

other sites had higher percentages for individual

markets. More than 40 percent of crack users in

Manhattan and San Diego and more than 55

percent in San Antonio, for example, reported

being unable to buy crack at least once during the

last year, despite having the willingness and the

money to do so.

Those who reported a failed transaction were

asked to recall why they were unable to complete

the transaction. The question was designed to get

them to recall a situation when external circumstances (other than their own lack of resources)

limited their ability to purchase drugs. Interviewers did not offer answers to the participants, but

rather coded responses into the best-fitting category. Respondents frequently ascribed their

failure to complete a transaction to their inability

to locate a dealer or to the dealer’s lack of supply

(see table 21, which excludes combination users).

In Manhattan, however, where police were aggressively enforcing quality-of-life statutes against

panhandling, drug dealing, fare beating, and other

crimes, 64 percent of crack users, 55 percent of

heroin users, and 38 percent of powder users

reported police activity as a factor in their failure

to obtain drugs. In contrast, the city with next

highest mention of police activity was Chicago,

where 18 percent of heroin users and 17 percent of

crack users cited such activity as a factor. Respondents in Washington, D.C., mentioned police

activity even less often: no respondents in the

powder market, only one (2.9 percent) in the crack

market, and three (16.7 percent) in the heroin

market. It should be noted, however, that the

overall percentage reporting failed transactions

was generally no higher in Manhattan than in the

other study sites. Thus, while police in Manhattan

were disproportionately named as a factor among

the subset of failed transactions, it cannot be

concluded that police activity caused the subset to

be any larger in Manhattan than in other study sites.

Table 20. Percentage of Respondents with Failed Purchase Transactions in the Past Year

variable = m12cocby Powder Crack Heroin Heroin and Powder Heroin and Crack

Heroin Powder Heroin Crack

Chicago 50.0 33.7 28.8 40.0 20.0 31.6 21.1

Manhattan 39.0 42.4 35.8 38.3 34.4 39.3 46.1

Portland 29.4 33.0 38.8 28.8 24.3 27.3 40.9

San Antonio 31.7 56.3 42.9 20.0 45.5 50.0 66.7

San Diego 25.0 41.6 25.5 29.6 46.2 47.6 47.6

Washington, D.C. 26.7 31.9 31.1 45.5 36.4 23.1 53.8
19

Another factor to note in table 21 is that a small

fraction of crack and heroin users reported high

prices as the reason for their failed transactions.

However, fairly large fractions of powder users

offered price as a motivation for failed transactions. Data on prices and purity indicated that

while a majority of crack users thought prices were

stable, a sizable minority perceived prices to be

increasing. Thus, even though some respondents

thought crack prices were increasing, the increases

were not cited as a barrier to purchasing the drug.

This information suggests that powder users may

be more sensitive to price changes than either

heroin users or crack users.

Purchase Frequency

Respondents were asked if they had purchased

drugs in the week prior to their arrest and interview. A large majority of respondents in each site

indicated that they had purchased drugs in the

previous week (see table 22). The low was in San

Diego, where 63 percent of the participants reported buying drugs, and the high was in Manhattan where nearly 91 percent reported making a

purchase in the 7 days before arrest. Overall,

Manhattan generally had the highest percentage of

arrestees reporting recent purchases (across drugs);

San Diego and Portland had the lowest. By drug

category at the site level, powder users were

usually less likely than others to report having

made a recent purchase.

Table 21. Reasons Cited for Failed Transactions

Percentage of Respondents Citing Reason for Failed Transaction

No Dealer Not Police Dealer Out Holiday Too Other

Reason Available Activity of Supply or Sunday Expensive

Chicago Powder 70.6 17.6 0.0 11.8 0.0 0.0 0.0

Crack 30.0 16.7 16.7 36.7 0.0 0.0 0.0

Heroin 34.4 25.0 18.8 6.3 6.3 3.1 6.3

Manhattan Powder 7.5 42.5 37.5 7.5 0.0 0.0 5.0

Crack 3.8 20.5 63.6 5.3 0.8 0.0 6.1

Heroin 5.3 26.3 55.3 5.3 0.0 0.0 7.9

Portland Powder 0.0 57.9 0.0 31.6 0.0 10.5 0.0

Crack 2.7 51.4 2.7 37.8 0.0 0.0 5.4

Heroin 6.1 45.5 9.1 33.3 3.0 0.0 3.0

San Antonio Powder 0.0 60.0 0.0 30.0 0.0 10.0 0.0

Crack 12.5 50.0 0.0 25.0 0.0 0.0 12.5

Heroin 0.0 36.4 0.0 63.6 0.0 0.0 0.0

San Diego Powder 0.0 69.2 0.0 23.1 0.0 7.7 0.0

Crack 6.4 29.8 8.5 46.8 2.1 2.1 4.3

Heroin 7.7 38.5 7.7 38.5 0.0 0.0 7.7

Washington, D.C. Powder 0.0 66.7 0.0 0.0 0.0 33.3 0.0

Crack 20.6 35.3 2.9 26.5 0.0 5.9 8.8

Heroin 5.6 55.6 16.7 22.2 0.0 0.0 0.0

Note: Percentages may not total 100 due to rounding.
20

Among those reporting having purchased drugs in

the 7 days prior to arrest, heroin users appeared to

have made the greatest number of purchases (see

table 23). In most sites, heroin users (or combination heroin users) had the highest number of mean

weekly purchases. In San Diego, however, while

combination heroin users reported the highest

number of mean weekly purchases, heroin-only

users reported the second lowest number. In

Manhattan and San Diego, crack users averaged

more purchases than heroin users in the week

preceding their arrest. Crack users typically reported

more weekly purchases than did powder users at the

site level, but the data were not statistically significant. Only in Portland did powder users report more

weekly purchases than crack users.

Guns and Drug Purchases

Respondents were asked if they carried a firearm

while purchasing drugs during the month preceding

Table 22. Percentage Reporting a Drug Purchase in the Week Prior to Arrest

variable =c7cocbuy Powder Crack Heroin Heroin and Powder Heroin and Crack

Heroin Powder Heroin Crack

Chicago 75.0 89.9 91.8 80.0 100.0 86.4 100.0

Manhattan 89.5 88.3 93.4 92.6 90.4 92.1 93.3

Portland 64.7 64.4 74.1 75.7 70.3 59.1 59.1

San Antonio 58.1 76.5 89.2 86.4 77.3 66.7 100.0

San Diego 30.2 68.5 60.8 88.9 70.4 61.9 76.2

Washington, D.C. 73.3 80.4 74.6 81.8 63.6 61.5 69.2

Table 23. Mean Number of Purchases Made in the Week Prior to Arrest

variable = c7buytme Powder Crack Heroin Heroin and Powder Heroin and Crack

Heroin Powder Heroin Crack

(1) (2) (3) (4) (5) (6) (7)

Chicago 6.63,6 6.9 10.21 7.8 5.0 12.01 9.2

Manhattan 4.2* 9.21 7.61 8.81 7.51 8.91 9.41

Portland 9.2 6.94,5 9.4 11.52 12.82 10.6 13.5

San Antonio 5.73,4 13.9 15.21 21.21 11.0 4.0 21.7

San Diego 4.14 12.34 6.44 19.81,2,3 15.6 7.5 12.0

Washington, D.C. 2.7 6.13 7.42 10.2 6.3 4.9 4.4

Notes: One-way analysis of variance, Bonferroni pairwise significance test. Superscripts indicate that the value differs significantly (p = .05) from the value in the

numbered column corresponding to the superscript number. An asterisk indicates significant difference from all other values in the row.

arrest. In four of the six sites, crack users were the

least likely to report carrying a weapon while

obtaining drugs. In these sites (Chicago, Manhattan, San Diego, and Washington, D.C.) between 3

and 6 percent of crack users reported carrying a gun

in the 30 days prior to arrest. In San Antonio and

Portland, heroin users were less likely than crack

users to report carrying a gun.

Overall, San Antonio arrestees reported the highest

rate of carrying guns (12.4 percent). More than 8

percent of the respondents from each type of drug

market in San Antonio reported carrying firearms.

In contrast, Washington had the lowest overall rate,

with only 4.1 percent of arrestees in that city

reporting that they had carried a gun during drug

purchases in the 30 days before arrest.

In general, larger fractions of powder users reported carrying firearms than users of other drugs,

particularly when excluding combination users. In
21

three sites (Chicago, San Antonio, and San Diego),

combination users were more likely to report

carrying a gun than powder users, but these findings were based on fewer than 20 observations for

the combination use categories. Several factors

may plausibly explain the differences in gun

possession across drug markets. First, powder

cocaine users are more likely to make their purchases indoors (table 18) and more likely to travel

(table 19); both activities may increase the perceived need to carry a firearm. Second, powder

users may have greater cause to protect themselves

if they more frequently buy larger quantities and

carry more cash. On the other hand, powder users

are also more likely to have a main source from

whom they regularly purchase drugs; such a

relationship would probably reduce their inclination to carry a weapon. In contrast, crack users

may be more reluctant to admit carrying a firearm

than other drug users because of the severe penalties associated with possession of small amounts

of crack and the fear that a gun charge could lead

to even worse legal consequences.

Use Patterns

Three-Day Use

Participants in the procurement study were very

likely to test positive for drugs. Respondents to

the crack addendum were more likely to test

positive for cocaine than respondents to the

heroin or powder cocaine addenda were to test

positive for those drugs. The DUF interview is

accompanied by a drug test that is capable of

detecting recent drug use (within approximately 3

days). Overall, more than 90 percent of those

completing a crack interview tested positive for

cocaine, and more than 80 percent of those

completing a heroin interview tested positive for

opiates. Generally, combination heroin-andcrack users were more likely to test positive for

cocaine than for opiates, while combination

heroin-and-powder users were about equally

likely to test positive for opiates and for cocaine.

These findings are detailed in table 24.

For comparison purposes, table 25 shows the

percentage of positive drug tests for the corresponding general DUF populations in the study

sites. In general, while relatively large fractions of

the general arrestee population tested positive for

drugs, the procurement study population was

substantially more likely to have consumed drugs

recently. Note that table 25 classifies DUF respondents only by drug test results, not by completed

interview instruments; thus, this table has no

category for crack.

Table 24. Drug Test Results by Completed Addendum Interview

Percentage of Addendum Respondents Testing Positive for Corresponding Drug

Powder Crack Heroin Heroin and Powder Heroin and Crack

Heroin Powder Heroin Crack

Chicago 80.0 89.5 91.2 80.0 60.0 52.4 81.0

Manhattan 94.2 96.8 87.4 75.5 91.5 64.0 93.0

Portland 72.6 92.0 81.1 70.8 77.8 71.4 85.7

San Antonio 79.5 93.8 77.8 90.9 90.9 33.3 100.0

San Diego 53.3 90.0 78.7 88.0 84.0 42.1 84.2

Washington, D.C. 83.3 94.3 86.4 90.0 90.0 63.6 90.9

Note: Drug tests cannot distinguish between powder cocaine and crack cocaine. Percentages in those columns represent those individuals testing positive for

cocaine.
22

Daily Use

In each site, heroin users were more likely than

powder or crack users to describe themselves as

daily users. In addition, combination heroin users

(heroin with either crack or powder) reported

being daily users of both drugs with greater frequency than powder-only and crack-only users. In

contrast, powder users were less likely than any

other respondents to consider themselves daily

users. These findings are detailed in table 26.

Those who identified themselves as daily users

were asked to report the number of times they used

the drug in an average day. Generally, cocaine

users—both powder and crack—reported a larger

number of daily uses than heroin users (see table 27).

Among those who did not define themselves as

daily users, a different pattern emerged. These

individuals reported less use per week (on average)

than daily users reported per day (see table 28).

Remember, however, that those who considered

themselves daily users (including large fractions of

crack, heroin, and combination users) are not

included in table 28.

Duration of Use

Information on the duration of drug use provides

valuable insights into drug problems. Changes in

the frequency of use, for example, may indicate

intensification of an epidemic, concentration of

use, or diffusion of use into a different pool of

users. Similarly, differences in use patterns across

drugs may point to the severity of a drug’s addiction profile. The procurement interview asked

arrestees about a variety of different aspects of

drug use in an effort to discern some of these

distinctions.

Perhaps not surprisingly, heroin users reported the

longest periods of sustained use (see table 29). In

the 90 days preceding arrest, larger fractions of

heroin users than of powder or crack users reported daily or near-daily use. In addition, large

fractions of combination heroin users reported

daily or near-daily use for both heroin and cocaine.

These findings suggest that few of the heroin

Table 25. Drug Test Results for General DUF

Population

Percentage Testing Positive

Cocaine

Cocaine Heroin and Heroin

Chicago 48.9 22.2 15.5

Manhattan 63.3 20.9 16.4

Portland 25.5 12.6 8.1

San Antonio 21.7 9.1 5.7

San Diego 21.3 6.9 3.9

Washington, D.C. 26.8 7.4 5.8

Table 26. Percentage Describing Themselves as Daily Users, by Drug Used

variable = cocdaily Powder Crack Heroin Heroin and Powder Heroin and Crack

Heroin Powder Heroin Crack

(1) (2) (3) (4) (5) (6) (7)

Chicago 16.72, 3 32.21 69.71 40.0 40.0 54.5 45.5

Manhattan 31.4* 52.51,3,4,5,7 70.81,2 81.91,2 71.31,2 71.91 62.91,2

Portland 32.85 41.95 48.2 68.9 50.01,2 54.5 57.1

San Antonio 19.03,5 50.0 75.71 81.8 50.01 33.3 66.7

San Diego 9.6* 43.71,5 49.01,5 88.91,5 44.41,2,3,4,6 57.11,5 47.61

Washington, D.C. 40.0 43.53 67.72,6 81.8 36.46 46.23,5 16.7

Notes: Pairwise chi-squared test. Superscripts indicate that the value differs significantly (p = .05) from the value in the numbered column corresponding to the

superscript number. An asterisk indicates that the value differs significantly from all other values in the row.
23

respondents in the sample, relative to powder-only

and crack-only users, have a casual habit and that

polydrug users may have complicated drug use

patterns.

Cessation of Use

Drug cessation periods can also be informative, as

they may indicate what disrupts drug use patterns.

Powder users appear to be the most likely to have

Table 27. Mean Number of Daily Uses Among Those Describing Themselves as Daily Users

variable = c7daily Powder Crack Heroin Heroin and Powder Heroin and Crack

Heroin Powder Heroin Crack

(1) (2) (3) (4) (5) (6) (7)

Chicago 10.52,3,6,7 3.81 3.41 4.0 6.5 3.31 4.61

Manhattan 5.4 7.23,4,5,6 3.12,7 3.92 3.92 3.92 6.43

Portland 9.92,3,6,7 5.31 4.01,5 4.8 7.93 2.81 5.31

San Antonio 7.0 4.2 6.2 6.1 6.8 1.0 4.0

San Diego 6.8 7.7 2.8 4.2 6.2 2.5 6.7

Washington, D.C. 3.57 4.47 2.87 2.97 2.87 2.77 13.5*

Notes: One-way analysis of variance. Bonferroni pairwise significance test. Superscripts indicate that the value differs significantly (p = .05) from the value in the

numbered column corresponding to the superscript number. An asterisk indicates that the value differs significantly from all other values in the row.

Table 28. Mean Number of Past Week Uses Among Those Describing Themselves as Not Daily Users

variable = c7numtme Powder Crack Heroin Heroin and Powder Heroin and Crack

Heroin Powder Heroin Crack

(1) (2) (3) (4) (5) (6) (7)

Chicago 2.6 3.3 3.4 4.3 4.7 2.3 5.1

Manhattan 2.07 3.7 2.1 3.4 2.2 2.2 5.21

Portland 2.5 2.7 2.3 4.0 4.7 0.8 3.4

San Antonio 7.0 2.0 5.4 0.8 2.3 0.5 3.0

San Diego 8.6 2.3 1.8 0.0 4.8 1.0 3.2

Washington, D.C. 1.3 1.8 2.0 3.0 2.0 1.3 2.9

Notes: One-way analysis of variance, Bonferroni pairwise significance test. Superscripts indicate that the value differs significantly (p = .05) from the value in the

numbered column corresponding to the superscript number.

Table 29. Percentage of Respondents Reporting 30 or More Consecutive Days of Use

In the 90 Days Prior to Arrest

variable = m3cocuse Powder Crack Heroin Heroin and Powder Heroin and Crack

Heroin Powder Heroin Crack

Chicago 2.8 13.5 42.2 60.0 60.0 36.3 18.2

Manhattan 24.8 36.6 66.6 78.5 64.6 59.7 51.2

Portland 14.7 19.1 42.8 61.1 36.7 54.6 38.0

San Antonio 7.0 0.0 40.5 61.9 23.8 0.0 33.3

San Diego 5.7 14.4 33.4 74.1 39.7 28.6 14.3

Washington, D.C. 13.4 8.9 49.2 54.6 36.4 30.8 30.8
24

use patterns that include extended periods of

nonuse. From one-quarter to two-thirds of the

powder users reported a monthlong period of

nonuse in the 90 days prior to arrest, compared to

one-quarter to one-third of crack users and less

than one-quarter of heroin users. From table 30, it

is clear that only a relatively small fraction of

heroin users have use patterns that include extended (1 month or longer) periods of nonuse.

Users were asked to explain why they went as long

as they did without using drugs. Among powder,

crack, and heroin users in Manhattan, 57 percent

of powder users reported that they were not daily

users and that their regular consumption pattern

included periods of nonuse. (See table 31. Findings in other sites were generally comparable but

are not presented.) The next most common motivation among powder users in Manhattan was

“could not afford” (9.5 percent), followed by

“wanted to change” (8 percent). Similar patterns

were found among crack users and heroin users;

27 percent of the former and 31 percent of the

latter reported that their regular patterns included

periods of nonuse. The next most common responses among crack users for periods of nonuse

were “could not afford” (20 percent) and “tired of

[the drug] life” (19 percent). Among heroin users,

the most frequent explanations after regular use

pattern were “in treatment” (24 percent) and

“jailed/incarcerated” (12 percent).

Among the data that stand out in table 31 is that no

arrestees cited lack of drug availability as a factor

in determining their use patterns, and only one

crack arrestee reported drug testing as a factor

influencing periods of nonuse. Six percent of crack

users and 12 percent of heroin users cited jail and

incarceration as affecting their use patterns.

Conclusions and Implications

Drug User Profile

Evidence from the drug procurement study indicates that respondents face multiple risks in their

lives. They reported relatively high rates of living

on the streets and in shelters, even in comparison

Table 30. Percentage of Respondents Reporting 30 or More Consecutive Days of Abstinence

In the 90 Days Prior to Arrest

variable = m3coctm2 Powder Crack Heroin Heroin and Powder Heroin and Crack

Heroin Powder Heroin Crack

Chicago 36.1 27.4 9.3 20.0 0.0 31.8 13.6

Manhattan 28.3 31.4 13.3 9.9 15.6 20.5 17.5

Portland 43.3 35.3 25.3 13.9 31.4 31.8 19.0

San Antonio 58.5 31.3 6.3 5.0 31.6 100.0 33.3

San Diego 66.7 36.4 40.0 7.7 38.5 28.6 47.6

Washington, D.C. 57.1 31.4 18.3 0.0 18.2 54.5 23.1

Table 31. Motivations for Periods of Abstinence

Among Manhattan Arrestees, by Drug

variable =m3cocwhy Percentage Citing Reason

Powder Crack Heroin

Tired of [the Drug] Life 7.1 18.8 7.1

Wanted to Change 8.3 8.7 9.5

Could Not Afford 9.5 19.7 4.8

In Treatment 7.1 6.9 23.8

Because of Family 0.0 2.8 7.1

Switched to Other Drug 0.0 1.4 0.0

Jailed/Incarcerated 1.2 5.5 11.9

Drug Testing 0.0 0.5 0.0

Hard to Find 0.0 0.0 0.0

Health Reasons 6.0 6.0 2.4

Stigma 1.2 0.9 0.0

Not a Daily or Dependent User 57.1 27.1 31.0

Other 2.4 0.9 2.4
25

to the general arrestee population in their communities. In addition, substantial fractions of respondents reported that public assistance or drug

dealing and other illegal activities were their

primary form of income. The findings also suggested that while study participants were likely to

report frequent drug use and very likely to test

positive for drug use, they were also in contact

with institutions that provide other services, such

as temporary shelter, permanent housing, and

financial assistance. Drug-using arrestees’ contact

with such institutions should be studied carefully

from the perspective of how these institutions might

appropriately and effectively use their resources to

address the problems of substance abuse.

Drug Purchase Patterns

Crack was more likely to be purchased under

circumstances that exposed the buyers (and sellers)

to law enforcement risks. A typical crack user in

the procurement study made numerous purchases

in a week, although not as many as a typical heroin

user. Crack and heroin purchases were both very

likely to take place outdoors, where they were

more visible (table 18). In addition, crack buyers

were less likely to buy from a main source than

were other drug users (table 14) and more likely to

have a large circle of dealers from whom to buy.

These large networks could introduce additional

exposure risks. There may also be an interaction

effect; that is, the combination of buying outdoors

from a stranger relatively close to one’s residence

(crack markets) poses different hazards than

buying outdoors from a stranger or main source in

a location farther from one’s residence (heroin

markets). These elements, in isolation or combination, may expose individuals participating in

crack transactions to greater risk than individuals

participating in transactions for other drugs. A

cumulative effect also results in elevated risk of

arrest for crack users: The relative size of the

heroin and crack markets means that there are

more crack transactions than heroin transactions to

observe. Cumulatively, then, these characteristics

may expose crack users to greater visibility and

greater risk.

The issue of risks and exposure has particular

relevance for the black arrestee population. Black

respondents were more likely than whites and

Hispanics to participate in crack markets in ways

that apparently increased risks. For example, if law

enforcement officials focus their efforts against

outdoor crack markets that are concentrated in

certain neighborhoods—a reasonable policing

strategy—this approach may disproportionately

affect blacks. The disproportionate impact will

arise because blacks are more likely than whites

and Hispanics to make their purchases outdoors

and are more likely to make them in their own

neighborhoods. Whites and Hispanics, on the other

hand, are more likely to travel away from their

neighborhoods to make their purchases and are

more likely to make them indoors. As a result,

drug transactions conducted by blacks may be

more visible to law enforcement, thus subjecting

blacks to greater risk for drug-related arrests.

Drug Use Patterns

Participants in the procurement study were very

likely to test positive for drugs. In addition,

substantial fractions of heroin and crack users

were likely to describe themselves as daily or

dependent users. Among those describing themselves as daily users, most respondents reported

consuming drugs more than once daily. Respondents also reported a variety of motivations for

periods of nonuse. Powder cocaine users were

most likely to report that their regular use pattern

included periods of nonuse, but heroin and crack

users also reported such patterns of intentional

nonuse. In addition, substantial fractions cited

other reasons for nonuse, including the cost of

drugs, being tired of the consequences of drug use,

and being in treatment programs or in jail.

These findings may be encouraging, because they

indicate that service providers may have a window

of opportunity for intervention; they also identify
26

influences over drug use patterns that policymakers may be able to manipulate or supplement.

These findings suggest that a more careful and

detailed examination of the factors influencing

arrestees’ drug use patterns would be beneficial.

Policy Implications

Analysis of the findings reveals that the powder,

crack, and heroin markets differ substantially from

one another in a variety of ways, including purchase and use practices. To the extent that drugusing arrestees are a particular problem in many

communities, the findings also suggest that detailed information about local drug habits and

patterns would be a valuable tool for law enforcement authorities, service providers, and policymakers. Further refinements of the interview

instrument, for example, could provide information that would be useful for local policy evaluations, impact analyses, and prevalence monitoring.

The data also suggest that it is possible to tap into

the DUF pool to explore motivations for drug use

and policy interventions that interrupt drug markets. A more specific set of questions could explore such critical factors as deterrence, substitution of one drug for another, and the interaction

between policing operations and perceived need

for treatment services. Of particular interest would

be whether there are differences in deterrence and

cessation motivations across drug markets. For

example, the findings presented here suggest that

powder users, when they temporarily stop using

cocaine, are motivated by factors over which they

generally have more control, including the perceived need to improve their circumstances. Crack

and heroin users, in contrast, are more likely to be

motivated to stop drug use by factors associated

with the consequences of consumption. Given

these apparent differences in motivations, it should

be possible to design questions to explore what set

of deterrents would work against what types of

users.

NOTES

1. Mark A.R. Kleiman and Ann Marie Rocheleau,

1993, “Measuring Heroin Availability: A Demonstration Program,” report prepared for the Office

of National Drug Control Policy by BOTEC

Analysis Corporation, September; David A.

Boyum and Ann Marie Rocheleau, 1994a, “Heroin

Users in Three Cities,” report prepared for the

Office of National Drug Control Policy by

BOTEC Analysis Corporation, August; David A.

Boyum and Ann Marie Rocheleau, 1994b, “Heroin

Availability in New York, San Diego, and Chicago,” report prepared for the Office of National

Drug Control Policy by BOTEC Analysis Corporation, August.

2. The DUF program is now known as the Arrestee Drug Abuse Monitoring (ADAM) program.

It is being expanded to 75 cities nationwide.

3. As a followup to the crack, powder cocaine, and

heroin addendum, NIJ awarded a DUF Challenge

Grant to the San Diego Association of Governments (SANDAG) to conduct similar research into

methamphetamine markets. Using a similar interview instrument, SANDAG began collecting data

in five sites (Los Angeles; Phoenix; Portland,

Oregon; San Diego; and San Jose) in October

1996. Findings from the methamphetamine study

will be available in 1998.

4. The 10 drugs are cocaine, opiates, marijuana,

PCP, methadone, benzodiazepines, methaqualone,

propoxyphene, barbiturates, and amphetamines.

Powder cocaine cannot be distinguished from

crack cocaine in the test. Samples that test positive

for amphetamines are subjected to gas chromatography analysis to eliminate false positives caused

by use of over-the-counter medications.

5. Note that these figures understate the number of

individuals eligible and overstate the completion

rate. Respondents screened into the procurement

study by self-reporting drug use in the 30 days

prior to arrest; however, self-reported data on drug

use consistently understate actual use.
27

6. The reporting convention for the tables in this

document parallels the number of forms that the

individual completed. For example, individuals

completing only a powder cocaine interview are

reported under “powder” in the tables, while those

completing both heroin and powder cocaine

interviews (or heroin and crack interviews) are

reported under “heroin and powder” (or “heroin

and crack”). Where drug-specific, rather than

individual-specific, factors are of interest, the data

from the “heroin and powder” and “heroin and

crack” categories are reported separately. Many of

the tables have a variable name printed in the

upper left corner. The interview question corresponding to the variable can be found in the

appendix. Tables without a variable name in the

upper left corner are either summary tables or are

derived from the main DUF instrument.

7. Kleiman and Rocheleau 1993; Boyum and

Rocheleau 1994a; Boyum and Rocheleau 1994b.

8. Given the small number of juveniles participating in the study, they are dropped from all analyses

and only included in the summary participation

tables in this section (tables 1–6).

9. Andrew Lang Golub and Bruce Johnson, 1997,

Crack’s Decline: Some Surprises Across the

United States. Washington, D.C.: U.S. Department

of Justice, National Institute of Justice.

10. National Institute of Justice, 1997, 1996 Drug

Use Forecasting Annual Report on Adult and

Juvenile Arrestees. Washington, D.C.: U.S. Department of Justice, National Institute of Justice.

11. Contingency means dependence, so a contingency table reflects how one characteristic (arrayed in a row) affects another characteristic

(arrayed in a column). If the characteristics are

independent of each other, then the percentage

found in any given cell should be approximately

equal to the product of the corresponding row and

column percentages. If one characteristic depends,

to some extent or another, on the other characteristic then the cell percentage will differ from the

row-column product.

12. A cluster of 101 individuals reported knowing

exactly 100 dealers. In addition, 33 respondents

reported knowing more than 100 dealers from

whom they could buy. Omitting values greater

than 100, one-third of which were greater than

500, reduces the variable means but does not

change the relative rankings.
29

Appendix: Addendum Interview Instrument

The following interview instrument was used for

both powder cocaine and crack cocaine respondents.

Powder and crack respondents were distinguished by

question 1.B, the COC_CRK variable. A similar

instrument, differing only in certain screening questions and response categories, was used with heroin

respondents. Data were segregated into three separate files (crack, powder cocaine, and heroin) and

merged with the corresponding main DUF data. The

segregated data files were then merged into a master

data file that contained a data record for each completed interview.

The complete addendum coding catalog, along

with separate and merged data files, will be

archived at the Inter-University Consortium for

Political and Social Research at the University

of Michigan. Interested analysts can also find

complete 1995 and 1996 Drug Use Forecasting

(DUF) files there. DUF files may be useful for

conducting additional analyses on differences

between addendum and nonaddendum respondents.
31

DUF COCAINE/CRACK AND HEROIN ADDENDUM

INTMO INTDAY INTYR ID

DATE: ____ /____ /____ I.D. # ____ ____ ____ ____

SITE: 1–NEW YORK 2–WASHINGTON 3–PORTLAND 4–SAN DIEGO 11–CHICAGO 19–SAN ANTONIO

I. COCAINE/CRACK SECTION

INTERVIEWERS: REFER BACK TO THE QUESTION ON THE DRUG GRID THAT STATES, “How many days did you use (NAME

DRUG) in the past 30 days?” THIS QUESTION IS CURRENTLY NUMBER 15 IN THE ADULT, AND 14 IN THE JUVENILE, DUF

QUESTIONNAIRES. IF ARRESTEE SAID HE/SHE USED COCAINE/CRACK IN THE PAST 30 DAYS, ASK THE FOLLOWING

QUESTIONS. IF ARRESTEE HAS NOT USED COCAINE/CRACK IN THE PAST 30 DAYS, GO TO THE HEROIN QUESTIONS (IF

APPLICABLE), BEGINNING WITH QUESTION 1.

READ: Now I want to ask you some more detailed questions about how you buy and use cocaine/crack. Remember, everything you tell

me is still confidential. It is important for this study that we get accurate and honest information. If there is a question you do not want to

answer, please let me know.

1. How do you use cocaine/crack? (READ ALL CHOICES, CIRCLE ALL THAT APPLY)

1. Snort powder

CUSESNRT

2. Inject cocaine powder alone

CUSEINJ

3. Inject cocaine powder in combination with:_____________

CUSECMBH (in combination with heroin)

CUSECMBO (in combination with other drugs)

4. Freebase powder

CUSEFBAS

5. Smoke crack

CUSESMOK

6. Smoke crack laced with:____________________________

CUSESMKM (marijuana)

CUSESMKC (crack)

CUSESMKO (other)

7. Other (SPECIFY):_________________________________

CUEOTHR

(IF MORE THAN ONE METHOD IS GIVEN, ASK A)

A. Which method do you most often use? (WRITE IN CODE NUMBER FROM ABOVE)

CUSEOFTN

METHOD_________

B. BASED UPON THE ANSWER IN A (AND IF NECESSARY #15 (CIRCLE ONE)

ON THE DRUG GRID) WE WILL BE ASKING THE REST OF 1. Cocaine Powder (GO TO QUESTION 2)

THE QUESTIONS IN THIS SECTION ABOUT: 2. Crack (ASK C)

COC_CRK

(IF B IS CRACK, ASK C)
32

C. What term do you use to refer to the crack that you smoke? (CIRCLE ALL THAT APPLY)

1. Crack

CTRMCRCK

2. Rock

CTRMROCK

3. Readyrock

CTRMRRCK

4. Freebase

CTRMFBAS

5. Base

CTRMBASE

6. Other (SPECIFY):_________________________________

CTRMOTHER

DEPENDING ON THE TYPE THEY SAY THEY USE MOST OFTEN IN QUESTION 1, PLEASE USE EITHER THE WORD

“COCAINE” OR SUBSTITUTE THE TERM THEY USE TO REFER TO “CRACK” THROUGHOUT THE REST OF THE INTERVIEW

WHERE YOU SEE “COCAINE/CRACK.” YOU CAN ALSO SUBSTITUTE LOCAL JARGON FOR THE WORDS “BUY” OR

“OBTAIN” DRUGS.

2. Do you usually buy/obtain cocaine/crack in the neighborhood (CIRCLE ONE)

where you live? 1. No

CBUYHOOD 2. Yes

3. Do you usually buy/obtain cocaine/crack indoors or outdoors? (CIRCLE ONE)

CBUYNOUT 1. Indoors (ASK A)

2. Outdoors (GO TO QUESTION 4)

A. Do you usually buy/obtain at a: (READ ALL, CIRCLE ONE)

CBUYAT 1. Residence?

2. Business?

3. Abandoned building?

4. Other? (SPECIFY):________________________________

4. How many people do you know that you could buy/obtain cocaine/

crack from today if you had the money or means and they had the

cocaine/crack?

CNUMPPL _________ # OF PEOPLE (NO RANGES)

5. How many different cocaine/crack dealers have you bought/

obtained cocaine/crack from in the past seven days?

CNUMBDLRS _________ # of DEALERS (NO RANGES)

6. What type of connections do you use? (READ ALL CHOICES AND CIRCLE ALL THAT APPLY)

1. Street connection

CCONSTRT

2. House connection

CCONHOUS

3. Phone connection

CCONPHON

4. Through a beeper

CCONBEEP

5. Crack house

CCONCHSE

6. Other (SPECIFY):_________________________________

CCONBUSN

CCONFRND

CCONOTHR

(IF MORE THAN ONE METHOD IS GIVEN, ASK A)
33

A. What type of connection do you most often use? (WRITE IN CODE NUMBER FROM ABOVE)

CCONOFTN

CONNECTION _________

7. Do you have a main source—one dealer you most often buy/obtain (CIRCLE ONE)

cocaine/crack from? 1. No (GO TO QUESTION 8)

CMNSRCE 2. Yes (ASK A through F)

A. How long have you used this source? (PUT IN NUMBER AND CIRCLE TIME PERIOD)

CMNSRTIM _________ # OF DAYS / WEEKS / MONTHS / YEARS

B. What type of connection is this main source? (READ ALL, CIRCLE ONE)

CMNSRCON 1. Street connection

2. House connection

3. Phone connection

4. Through a beeper

5. Crack house

6. Other (SPECIFY):_________________________________

C. Does this main source live in your neighborhood? (CIRCLE ONE)

CMNSRHD 1. No

2. Yes

D. Do you purchase/obtain other drugs from this main source? (CIRCLE ONE)

CMNSRDRG 1. No

2. Yes (SPECIFY DRUG(S)):__________________________

E. What do you usually do if your main source is not around? (CIRCLE ALL THAT APPLY)

1. Go to someone else

CMNSRELS

2. Get it through a friend

CMNSFRD

3. Use other drugs

CMNSRODR

4. Will not buy

CMNSRNO

5. Other (SPECIFY):_________________________________

CMNSROTH

F. What is the ethnicity of your main source? (CIRCLE ONE)

CMNSRETH 1. Black (not Hispanic)

2. White (not Hispanic)

3. Hispanic

4. American Indian/Alaskan Native

5. Asian/Pacific Islander

6. Other (SPECIFY):_________________________________

8. In the past 12 months, was there a time when you had the money, (CIRCLE ONE)

but you couldn’t buy/obtain cocaine/crack? 1. No (GO TO QUESTION 9)

M12COCBY 2. Yes (ASK A THROUGH C)

A. How long ago was the last time? (PUT IN NUMBER AND CIRCLE TIME PERIOD)

M12COCT2 _________ # OF DAYS / WEEKS / MONTHS AGO
34

B. What was the reason you couldn’t buy/obtain cocaine/crack? (CIRCLE ONE)

M12COCRN 1. No reason

2. Dealer not available

3. Police activity hot

4. Dealer out of cocaine/crack

5. Holiday/Sunday

6. Dealer charging too much money

7. Other (SPECIFY):_________________________________

C. How did you get through the experience? (CIRCLE ONE)

M12COCEP 1. Didn’t do anything/didn’t use

2. Used/bought another drug

3. Found another connection

4. Other (SPECIFY):_________________________________

9. During the last 3 months, what is the most consecutive days in a

row you used cocaine/crack?

M3COCDAY _________ # OF DAYS

(PROBE: HOW MANY DAYS DID YOU USE COCAINE/

CRACK WITHOUT A BREAK?)

10. During the last 3 months, what is the longest time you went (PUT IN NUMBER AND CIRCLE TIME PERIOD)

without using cocaine/crack? _________ # OF DAYS / WEEKS / MONTHS

M3COCTM2 (IF ANSWER IS “0” GO TO QUESTION 11)

A. Why did you go that long without using cocaine/crack? (CIRCLE ONE. PROBE FOR MOST SPECIFIC ANSWER. IF

M3COCWHY TWO SPECIFIC ANSWERS ARE GIVEN, PROBE FOR

 MOST IMPORTANT ONE.)

1. Tired of life associated with cocaine/crack (passive answer)

2. Wanted to change/improve life (active answer)

3. Couldn’t afford cocaine/crack

4. In treatment

5. Because of my family/kids

6. Switched to other drug

7. Jailed/incarcerated

8. Subjected to drug testing

9. Cocaine/crack is hard to find

10. Health reasons

11. Stigma of cocaine/crack use

12. Not a daily or dependent user/that is my regular use pattern

13. Other (SPECIFY):_________________________________

11. A. In the past 30 days did you get cocaine/crack for free (did not (CIRCLE ONE)

pay money for it)? 1. No (GO TO B)

C30COCFR 2. Yes (ASK SUBQUESTION)
35

–Who gave you cocaine/crack for free in the past 30 days? (READ ALL AND CIRCLE ALL THAT APPLY)

1. Dealer

C30DEALR

2. Friend

C30FRND

3. Spouse/lover

C30SPOUS

4. Other relative/family member

C30FAMLY

5. Co-worker

C30COWKR

6. Other (SPECIFY):_________________________________

C30OTHR

B. In the past 30 days did you get cocaine/crack by participating (CIRCLE ONE)

in drug-related activities, for example, selling or holding drugs, 1. No

finding buyers, etc.? 2. Yes

C30ACTIV

C. In the past 30 days did you get cocaine/crack by trading sex (CIRCLE ONE)

for it? 1. No

C30TRDSX 2. Yes

D. In the past 30 days did you get cocaine/crack by trading (CIRCLE ONE)

something else for it? 1. No

C30TRELS 2. Yes

E. In the past 30 days did you get cocaine/crack by stealing it? (CIRCLE ONE)

C30STEAL 1. No

2. Yes

12. How do you usually get the money you need to buy cocaine/crack? (READ ALL AND CIRCLE ALL THAT APPLY)

1. Through legal means (legal job, welfare, savings)

CMNYLEGL

2. Steal

C30STEAL

3. Prostitution/sex work

CMNYSEX

4. Deal/sell drugs/help sell drugs

CMNYDRUG

5. Rob someone

CMNYROB

6. Borrow/ask for money

CMNYBORR

7. Work at illegal job (other than dealing drugs)

CMNYILGL

8. Don’t spend money on drugs

CMNYODR

9. Other (SPECIFY):_________________________________

CMNYOTH
36

13. ASK THIS QUESTION ONLY IF PARTICIPANT IN #11B OR

#12(4) SAID THEY PARTICIPATED IN DRUG-RELATED

ACTIVITIES TO GET MONEY FOR COCAINE/CRACK OR

GET THE DRUG ITSELF. IF NO DRUG-RELATED ACTIVITY

WAS REPORTED, GO TO QUESTION 14.

In the past 30 days, did you participate in any of the following (READ EACH ACTIVITY AND CIRCLE ONE FOR THAT

drug-related activities to get money for cocaine/crack or get the ACTIVITY)

drug directly?

A. Sold drugs to street dealer? 1. No

CACTDLR 2. Yes

B. Sold drugs to another person using drugs (not a dealer)? 1. No

CACTNODL 2. Yes

C. Steering and/or finding buyers? 1. No

CACTBUYR 2. Yes

D. Acting as a middleman? 1. No

CACTMDMN 2. Yes

E. Holding drugs or money? 1. No

CACTHOLD 2. Yes

F. Providing street security? 1. No

CACTSEC 2. Yes

G. Cutting, packaging or cooking drugs? 1. No

CACTPKG 2. Yes

H. Providing space for using drugs? 1. No

CACTSPAC 2. Yes

I. Selling or renting pipes/works/rigs or other paraphernalia? 1. No

CACTPARA 2. Yes

J. Any other activities not mentioned? 1. No

CACTOTHR 2. Yes, (SPECIFY):__________________________________

14. A. In the past 30 days, did you own a gun? (CIRCLE ONE)

C30GUN 1. No

2. Yes

B. In the past 30 days, have you carried a gun while you were (CIRCLE ONE)

obtaining cocaine/crack? 1. No

C30GUNOB 2. Yes

15. (IF QUESTION #1B IS COCAINE POWDER) How much ________ # OF GRAMS

cocaine powder do you usually use each time you get high? ___________________________________ SPECIFY OTHER

COCUSEGR DESCRIPTION
37

(IF QUESTION #1B IS CRACK) Crack is packaged in different ways. (READ ALL CHOICES, CIRCLE ALL THAT APPLY)

In the past 30 days have you purchased/obtained it: 1. In vials

CRKVIAL

2. In plastic baggies or zip lock baggies

CRKBAG

3. Wrapped in tin foil

CRKFOIL

4. By the rock - no packaging

CRKROCK

5. In other packaging (SPECIFY):_______________________

CRKPKOT

(IF MORE THAN ONE METHOD IS GIVEN, ASK A)

A. Which type of packaging do you usually purchase/obtain crack (WRITE IN CODE NUMBER FROM ABOVE)

in?

PACKAGING _________

CRKPKAGE

B. How much is in a typical _________________ (SPECIFY _________ # of GRAMS

ANSWER GIVEN IN A)? CRKGRAMS

_________ # of ROCKS

CRKROCKS

___________________________________ SPECIFY OTHER

DESCRIPTION

C. How much crack do you usually use each time you get high? (PUT IN QUANTITY AND CIRCLE TYPE OF PACKAGING)

CRKUSEUT QUANTITY: ________ # OF

CRKUSEQT

1. Vials

2. Plastic baggies or zip lock baggies

3. Tin foil packets

4. Rocks

5. Other packaging (SPECIFY):_________________________

16. Would you consider yourself a daily cocaine/crack user? (CIRCLE ONE AND ASK ONLY RELEVANT FOLLOW-UP

COCDAILY QUESTIONS)

1. No (ASK C ONLY)

2. Yes (ASK A & B ONLY)

A. During the past seven days, how often did you use cocaine/

crack on a typical day?

C7DAILY _________ # OF TIMES PER DAY

B. In the past seven days how many days were there that you did

not use any cocaine/crack?

C7NOTUSE _________ # OF DAYS DIDN’T USE

C. How many times did you use cocaine/crack during the past

seven days?

C7NUMTME _________ # OF TIMES USED IN PAST SEVEN DAYS
38

17. Compared to a year ago, what, if any, changes have you noticed (CIRCLE ONE)

about the purity of the cocaine/crack you’re using? 1. Purity is lower now

COCPURTY 2. Purity is the same now

3. Purity is higher now

4. N/A

18. Compared to a year ago, what, if any, changes have you noticed (CIRCLE ONE)

about the price you pay for cocaine/crack? 1. Price is lower now

COCPRICE 2. Price is the same now

3. Price is higher now

4. N/A

19. (IF QUESTION #1B IS COCAINE POWDER) The last time that ________ # of GRAMS

you purchased cocaine, how much did you buy? ___________________________________ SPECIFY OTHER

COCBUYGR DESCRIPTION

(IF QUESTION #1B IS CRACK) The last time that you purchased (PUT IN quantity AND CIRCLE TYPE OF PACKAGING)

crack, how much did you buy? QUANTITY: ________ # OF

CRKBUYUT 1. Vials

CRKBUYQT 2. Plastic baggies or zip lock baggies

3. Tin foil packets

4. Rocks

5. Other packaging (SPECIFY):_________________________

20. How much did you pay for that amount?

COCBUYPY $ ________________

21. Have you purchased cocaine/crack in the past seven days? (CIRCLE ONE)

C7COCBUY 1. No (ASK A, WHICH COMPLETES COCAINE SECTION)

2. Yes (GO TO QUESTION 22)

A. IF NO PURCHASE IN PAST SEVEN DAYS ASK: How

 many weeks ago did you last purchase cocaine/crack? _________ # of WEEKS (COCAINE SECTION

C7WKSAGO COMPLETED)

22. How many times did you buy cocaine/crack in the past seven days?

C7BUYTME _________ # times per seven days

23. During the past seven days, what was the total amount of money

you spent for the cocaine/crack you purchased?

C7BUYMNY $ _________ TOTAL SPENT PAST SEVEN DAYS

24. The last time you bought cocaine/crack, do you remember approx- (PUT IN NUMBER AND CIRCLE AM OR PM)

imately what time it was when you had the money in hand and you

made your first move toward buying it?

CTIMEMNY ____:____ AM / PM

25. Do you remember approximately what time it was when you

actually bought the cocaine/crack?

CTIMEBUY ____:____ AM / PM
39

26. (USING QUESTIONS 24 AND 25, CALCULATE IN HOURS (MAKE SURE THE # OF MINUTES GIVEN JIVES WITH

AND MINUTES HOW LONG IT TOOK TO PURCHASE THE THE TIMES GIVEN IN 24 AND 25. IF NOT, PURSUE

COCAINE/CRACK. THEN CONFIRM THIS SEARCH TIME QUESTIONING UNTIL BOTH TIMES MAKE SENSE. IF

WITH PARTICIPANT) SO, ASK A AND B)

So it took you __________ minutes to buy cocaine/crack from the

time you had the money in hand until you actually purchased the

cocaine/crack?

CMINSRCH ________ MINUTES OF TOTAL SEARCH TIME

A. Of the total number of minutes it took you to buy cocaine/

crack, how much of that time did you spend traveling to where

you bought the cocaine/crack?

CMINTRVL ________ MINUTES TRAVELING

B. How much of that time did you spend waiting for the dealer to

show up or get back to you?

CMINWAIT ________ MINUTES WAITING

(CONTINUE WITH HEROIN SECTION IF APPLICABLE)
For more information on the National Institute of Justice, please contact:

National Criminal Justice Reference Service

Box 6000

Rockville, MD 20849–6000

800–851–3420

e-mail: askncjrs@ncjrs.org

You can view or obtain an electronic version of this document from the

NIJ World Wide Web site.

To access the site, go to http://www.ojp.usdoj.gov/nij

If you have any questions, call or e-mail NCJRS.