Arizona strategic prevention framework state incentive grant: statewide epidemiological profile and problem areas

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Arizona Strategic Prevention
Framework State Incentive
Grant:
Statewide Epidemiological
Profile and Problem Areas
Submitted by the Epidemiology
Work Group
October 19, 2005
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Table of Contents
Summary
3
Epidemiology Work Group Members
10
1. Background and Purpose
11
2. Approach
12
3. Assessment of the Magnitude of Substance Abuse in Arizona 15
3.1 Mortality 15
3.2 Morbidity 16
3.3 Consumption Patterns and Other Consequences 20
3.4 Select Problem Indicators by Age 27
3.5 Select Problem Indicators by Geography 34
3.6 Arizona, United States, and Healthy People 2010 Comparisons
50
4. Risk and Protection
51
5. Assessment of Community Assets and Resources and Identification of
Gaps in Services and Capacity
54
6. Identification of Problem Areas 58
6.1 Problematic drinking 58
6.2 Youth illicit drug use 58
6.3 Geographic problem areas 59
6.4 Age problem areas
60
7. Data Concerns and Needs
64
Appendix A: Consequence and Consumption Indicators Considered 66
Appendix B: County Population Estimates, 2003 68
Appendix C: Community Health Analysis Area Profiles 69
Appendix D: Arizona, United States, and Healthy People 2010
Comparisons
196
Appendix E: Arizona Youth Survey Risk and Protective Factors 197
Appendix F: Arizona Social Indicator Study Risk Factors 198
Appendix G: Problem Priority Worksheet 200
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Summary
Background and Purpose. In the fall of 2004, the State of Arizona and the Governor’s
Office received a Strategic Prevention Framework State Incentive Grant from the Center
for Substance Abuse Prevention in the Substance Abuse and Mental Health Services
Administration. The State Incentive Grant provides $ 11.75 million over five years to
reduce substance use in Arizona. The Strategic Prevention Framework State Incentive
Grant requires a statewide needs assessment to direct funding to substance abuse related
problems in Arizona. This epidemiological profile informs the statewide needs
assessment by providing data on substance use consumption patterns and consequences.
Approach. To oversee the development of the report and its findings, an epidemiology
work group was formed. Members included grant partner agencies, representatives of
agencies with key data sets, public health experts and epidemiologists, community
representatives, and the State Incentive Grant’s evaluator. The work group was convened
and staffed by the Governor’s Office.
The work was conducted in two phases. First, an exhaustive list of potential indicators of
substance use consequence and consumption patterns was developed. The second phase
of the work consisted of analyzing available indicator data so that they could be
interpreted and funding priorities set among various consequences, consumption patterns,
and audiences. Once problem areas began to be identified, additional analyses were
conducted to inform the problem areas.
Problem Areas. The epidemiology work group identified problematic drinking and
youth illicit drug use as the state’s problem areas for State Incentive Grant funds.
Depending on the objective of the funded interventions, there are several possible age and
geographic audiences. The following table presents indicators, age and geographic
groups, and possible prevention objectives.
Problematic drinking is defined with four indicators: past month underage drinking, past
month underage binge drinking, past month adult binge drinking, and alcohol related car
crash injuries. Youth illicit drug use is defined by one indicator: past month any illicit
drug use. For each indicator two age groups are suggested: the age group experiencing
the highest rate of the problem and the age group immediately preceding this high rate
population. The high rate age group can be targeted to decrease reoccurrence or
avoidance of the problem. The age group preceding the high rate age group can be
targeted for avoidance of the problem. There are also two types of target geographies:
those counties or sub- county segments, referred to as community health analysis areas or
CHAAs, with high rates of the problem measured by the indicator and those counties
with a high occurrence of the problem measured by the indicator.
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Problem Areas: Problematic Drinking and Youth Illicit Drug Use
Indicator Target Age Target Geography Objectives
Problematic Drinking
Counties and health analysis areas with highest
rate of 8th to 12th grade drinking: Santa Cruz,
Mohave, Gila, Cochise, Douglas CHAA,
Globe/ Hayden CHAA, Kingman and Lake
Havasu City CHAA
8th - 12th
grade
students
Counties with highest occurrence of 8th to 12th
grade drinking: Maricopa, Pima
1. Increase age of
onset
2. Decrease past 30-
day day use
Counties and health analysis areas with highest
rate of 8th to 12th grade drinking: Santa Cruz,
Mohave, Gila, Cochise, Douglas CHAA,
Globe/ Hayden CHAA, Kingman and Lake
Havasu City CHAA
Past month
underage
drinking
Students in
grades
below the 8th
grade
Counties with highest occurrence of 8th to 12th
grade drinking: Maricopa, Pima
Increase age of onset
Counties and health analysis areas with highest
rates of 8th to 12th grade binge drinking: Santa
Cruz, Mohave, Gila, Cochise, Douglas CHAA,
Benson CHAA, Globe/ Hayden CHAA,
Williams CHAA
8th – 12th
grade
students
Counties with highest occurrence of 8th to 12th
grade binge drinking: Maricopa, Pima
1. Decrease past 30-
day day use
2. Decrease past
two- week binge
drinking
Counties with highest rates of 8th to 12th grade
binge drinking: Santa Cruz, Mohave, Gila,
Cochise
Past month
underage binge
drinking
Students in
grades
below the 8th
grade. Counties with highest occurrence of 8th to 12th
grade binge drinking: Maricopa, Pima
Increase age of onset
18- 25 year
olds
( highest
rate)
State level ( no data at sub- state level) Decrease past 30- day
day binge drinking
Past month
adult binge
drinking
< 18 year
olds
State level ( no data at sub- state level) 1. Decrease past
two- week binge
drinking
2. Increase age of
onset
Counties with highest rates of car crash injuries:
La Paz, Coconino, Apache
21 - 34 year
olds
Counties with highest occurrence of car crash
injuries: Maricopa, Pima
1. Decrease alcohol
related car crashes
2. Decrease past 30-
day day binge
drinking
Counties with highest rates of car crash injuries:
La Paz, Coconino, Apache
Alcohol related
car crash
injuries
< 21 year
olds
Counties with highest occurrence of car crash
injuries: Maricopa, Pima
1. Decrease past 30-
day day binge
drinking
2. Increase age of
onset
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Priority Problems: Problematic Drinking and Youth Illicit Drug Use
Youth Illicit Drug Use
Indicator Target Age Target Geography Objectives
Counties and health analysis areas with highest
rates of past month any drug use: Apache,
Graham, Coconino, Navajo, Page/ Fredonia
CHAA, Sedona CHAA, Flagstaff West CHAA,
Flagstaff East CHAA, Flagstaff Rural CHAA,
Winslow CHAA, Holbrook CHAA, Benson
CHAA, Navajo Nation CHAA, Hopi Nation
CHAA, Havasupai CHAA.
8th – 12th
grade
students
Counties with highest occurrence of past month
any drug use: Maricopa, Pima
1. Decrease past
month illicit drug
use
2. Increase age of
onset
Counties and health analysis areas with highest
rates of past month any drug use: Apache,
Graham, Coconino, Navajo, Page/ Fredonia
CHAA, Sedona CHAA, Flagstaff West CHAA,
Flagstaff East CHAA, Flagstaff Rural CHAA,
Winslow CHAA, Holbrook CHAA, Benson
CHAA, Navajo Nation CHAA, Hopi Nation
CHAA, Havasupai CHAA.
Past month any
illicit drug use1
Students in
grades
below the 8th
grade
Counties with highest occurrence of past month
any drug use: Maricopa, Pima
Increase age of onset
1 Any illicit drug generally includes all drugs with the exception of tobacco and alcohol. The specific drugs
that are included may vary according to the study that is used to measure drug use.
Key Findings
Magnitude of Substance Abuse: Consequences and Consumption
1. Probably the most severe consequence of substance use is death but deaths
associated with substance use are relatively small when compared to the five
leading causes of death in Arizona ( Table 3A). This suggests two things. First,
any intervention targeting death directly related to substance use would have little
affect on the state’s overall mortality. Second, because there are so few deaths
directly attributable to drugs and alcohol, measuring an intervention’s success on
this indicator would be difficult because there is so little to change.
2. The absolute numbers for substance use problems related to illness or injury
are much greater than the absolute numbers for deaths related to substance
use ( Table 3B). Almost half a million people report clinical dependence or abuse
of illicit drugs or alcohol. Over 100,000 people reported driving after having too
much to drink and 6,200 people were injured in alcohol related crashes. Focusing
on reducing substance use related injury and illness provides a much larger target
for intervention and would also reduce deaths related to substance use.
3. Consumption does not necessarily result in death or illness but some consumption
patterns such as binge drinking or illicit drug use predict health consequences
better than others due to the impairment following such use. Alcohol
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consumption and binge alcohol consumption affect more people, including
youth, than other substances ( Table 3E and 3F).
4. For youth, the estimated rates of illicit drug use in the past month for 12 to
17 year olds ( 123.6/ 1,000) are comparable to the estimated rates of binge
drinking in the past month for 12 to 17 year olds ( 117.52/ 1,000, Table 3N).
5. Methamphetamine is one of the least used drugs relative to alcohol, tobacco,
and marijuana. Inhalants and cocaine are used slightly more than
methamphetamine ( Tables 3G through 3J).
Substance Use and Age
6. Eighteen to twenty- five year olds have the highest rates of use for all
substances and the highest rates for alcohol or illicit drug dependence or
abuse ( Table 3N).
7. Twelfth grade has the highest percentage of students that have used alcohol
( 51.1 percent), tobacco ( 24.4 percent), and illicit drugs ( 25.1 percent) in the
past 30 days or have engaged in binge drinking in the past two weeks ( 32.4
percent, Table 3O). Eighth grade students report substantial amounts of
substance use in the past 30 days ( 25 percent have used alcohol and 18
percent have used an illicit drug).
8. Highest rates for a majority of the problem indicators such as substance
consumption, drug- related arrests, and alcohol related car crashes, cluster in
the 18 to 25 year old age group ( Figure 3A).
Substance Use and Geography
9. Cochise, Gila, Mohave, and Santa Cruz counties have the most problems
with 30- day youth alcohol use and past two- week youth binge drinking
( Table 3Y).
In some cases, data are available at smaller geographic segments referred to as
community health analysis areas ( Figures 3B and 3C). Within Cochise and Gila
counties the Douglas and Globe/ Hayden health analysis areas have higher
than average percentages of youth that report binge drinking and past 30-
day alcohol use. Within Cochise and Coconino counties, the Benson and
Williams health analysis areas report higher than average youth binge
drinking rates. Within Mohave county, the Kingman and Lake Havasu City
health analysis areas have higher than average percentages of past 30- day
youth alcohol use.
10. A geographic analysis was also conducted for youth illicit drug use ( Table 3Z).
Apache, Graham, Coconino, and Navajo counties have the most problems
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with illicit drug use among 8th, 10th, and 12th grade students. For past month
drug use among 8th through 12th grade students, the health analysis areas of
Page/ Fredonia, Flagstaff West, Flagstaff East, Flagstaff Rural, Winslow,
Holbrook, Benson, Navajo Nation, Hopi Nation and Havasupai have higher
than average percentages of drug use ( Figure 3D).
Risk and Protective Factors
11. Another way to assess substance abuse prevention need is to measure the
prevalence of characteristics that have been shown to predict substance use. A
high prevalence of these risk factors suggests a greater potential for developing
substance abuse problems and hence a greater need for prevention interventions.
Two studies measure Arizona’s counties’ predilection for substance abuse
problems: the Arizona Youth Survey and the Arizona Social Indicator Study
conducted by the Mel and Enid Zuckerman Arizona College of Public Health at
the University of Arizona. Based on the number of indicators that exceed a
normative standard, Yavapai, Mohave, and Gila counties are at the highest
risk for substance abuse problems as indicated in both the Arizona Youth
Survey and the Arizona Social Indicator Study. Maricopa and Yuma counties
have the lowest level of risk in both studies ( Tables 4A and 4B).
Community Resources and Service Gaps
12. To get a better sense of the gaps that might exist between the problems identified
and the prevention resources that the state allocates to those problems, an analysis
was conducted of current state funding as reported in the Arizona Drug and Gang
Prevention and Treatment Program Inventory ( Table 5A) and the funding’s
relationship to the problems being studied ( Table 3HH). For La Paz, Santa
Cruz, and Cochise counties, high per capita spending on substance abuse
prevention programs is congruent with high rates of problem behaviors. On
the other hand there is a discrepancy between low prevention per capita
funding and high problem rates for Navajo, Mohave, Gila, Apache,
Coconino, and Greenlee counties.
Data needs and considerations. In the course of the epidemiology work group’s work,
a variety of data and research needs were identified, some of which presented significant
gaps in our knowledge of substance abuse consumption and consequences in Arizona.
Adult prevalence survey. There is no study of adults that provides sub- state level
estimates for substance use and substance related consequences such as clinical
dependence or abuse. Such a survey should be conducted on a regular basis with a
sample large enough, at a minimum, to provide sub- county level estimates for Maricopa
and Pima counties and county level estimates for the rest of the state.
Proportion of health or social problems attributable to substance use. Throughout the
development of the epidemiological profile the question of the relationship of substance
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use to chronic diseases such as heart disease or social problems such as crime or school
dropout remained unanswered. In ensuing years of the State Incentive Grant, the
epidemiology work group can address this issue in two ways: first, by conducting a
literature review of studies that reliably measure the contribution of substance abuse to
these health and social problems and second, by conducting studies specific to Arizona’s
population.
Measures of the severity of substance use such as economic costs or years of productive
life lost. With the exception of instances of death or illness, this profile does not describe
or quantify the affect substance use has on the individual or society. The severity of
substance use in terms of economic costs, utilization of system resources, or years of
productive life lost due to substance use or its consequences should be considered. As
with proportion of health or social problems attributable to substance use, the
epidemiology work group can address this deficiency in subsequent years by conducting
reviews of pertinent studies that can be applied to Arizona’s population or by conducting
primary research with Arizona specific populations.
Resource inventory. In this report, resources and assets were defined as the annual
amount of public funding received by service providers in Arizona as reported in the
Arizona Drug and Gang Prevention and Treatment Program Inventory. Some important
dimensions of resource assessment, such as measures of program effectiveness or the
behavioral objectives that are targeted by the resources have yet to be included in this
data source. Resource assessments should continue to be performed on a regular basis
and include data on resources at the lowest geographic level possible ( closest to program
delivery). In addition, the design of future assessments should consider use of additional
measures and tools that provide feasible and reliable information to determine the effects
of resources on behavioral outcomes.
Child welfare and substance abuse. One of the original intents of the grant was to
address the substance abuse prevention needs of those families that are in the child
welfare system or communities that have high rates of child welfare involvement.
Unfortunately, reliable data on the co- occurrence of substance use and child welfare
involvement are not regularly collected. If the state wishes to pursue such interventions
in the future, the child welfare system should include a substance use assessment at the
appropriate client contact point so that reliable and representative data can be collected.
Sub- county data. The epidemiology work group continuously sought survey data at a
sub- county level or archival data that could be disaggregated to a sub- county level. In
most instances, survey and archival data are readily available at a county level but this
may not accurately describe the circumstances in a municipality or neighborhood. It is
recommended that survey samples provide sub- county estimates for Maricopa and Pima
counties given the high density of people and large proportion of Arizona’s population
living in those areas. Other sub- county samples should be decided as needed.
Geographic information systems. Analyzing data geographically requires that data
elements have an address attached to them. This was not always the case with the
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archival and survey data that were used for this report. The survey data that were used
was originally collected for county estimates thus making it problematic to develop
values at a sub- county level. If survey data are to be used in evaluating the outcome of
prevention efforts, then the surveys need to be at the level of prevention activity. If the
community is conducting the prevention intervention then surveys need to be conducted
in that community. It is recommended that community level information continue to be
provided for the measures that are identified as priorities.
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Epidemiology Work Group Members
Michelle Anderson
Administrative Office of the Courts
Steve Ballance
Criminal Justice Commission
Jeanne Brandner
Administrative Office of the Courts
Leslie Carlson
Pima Prevention Partnership
Jenny Chong University of Arizona, Mel and Enid Zuckerman Arizona
College of Public Health
Wes Kortuem Department of Health Services
Heather Dunn
Department of Health Services
Judith Fritsch
Department of Economic Security
Robin Harris University of Arizona, Mel and Enid Zuckerman Arizona
College of Public Health
Catherine Osborn
Department of Education
Richard Porter
Department of Health Services
Lisa Shumaker
Department of Health Services
Steve Sparks
Department of Economic Security
Wendy Wolfersteig
Arizona Prevention Resource Center, Arizona State University
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1. Background and Purpose
In the fall of 2004, the State of Arizona and the Governor’s Office received a Strategic
Prevention Framework State Incentive Grant from the federal Center for Substance
Abuse Prevention in the Substance Abuse and Mental Health Services Administration.
The State Incentive Grant provides $ 11.75 million over five years to reduce substance use
in Arizona.
The State Incentive Grant requires a statewide needs assessment to direct funding to
substance abuse related problems in Arizona. The needs assessment must include the
following:
1. Assessment of the magnitude of substance abuse and related mental health
disorders in the State of Arizona
2. Assessment of risk and protective factors associated with substance abuse and
related mental health disorders in the state
3. Assessment of community assets and resources
4. Identification of gaps in services and capacity
5. Assessment of readiness to act
6. Identification of priorities based on the epidemiological analyses, including the
identification of target communities to implement the Strategic Prevention
Framework
7. Specification of baseline data against which progress and outcomes of the
Strategic Prevention Framework can be measured.
This epidemiological profile informs the statewide needs assessment by providing data
and suggesting priorities as required in the items listed above. Information on item
number five, assessment of readiness to act, is not included in this report. It was decided
early in the State Incentive Grant’s implementation that this readiness assessment would
occur once potential priority communities were identified.
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2. Approach
To oversee the development of the report and its findings, an epidemiology work group
was formed. Members included grant partner agencies, representatives of agencies with
key data sets, public health experts and epidemiologists, community representatives, and
the State Incentive Grant’s evaluator. The work group was convened and staffed by the
Governor’s Office.
Eight meetings were conducted over a ten- month period in which work group members
decided on the approach, selected indicators of substance abuse consequences and
consumption, advised on data sets and analysis, reviewed findings, and decided on
problem areas. The Department of Health Services and the Criminal Justice Commission
provided geographic and other analyses of key data sets to support the work of the group.
The work was conducted in two phases. First, an exhaustive list of potential indicators of
substance use consequence and consumption patterns was developed. Consequence and
consumption indicators were compiled from an indicator database developed by the
Substance Abuse and Mental Health Services Administration, a list of indicators
compiled from other State Incentive Grant awardees, and indicators that members of the
epidemiology work group suggested. A search was conducted for data sets that could
provide information on the indicators or data sets that were related to substance abuse and
might provide additional indicators.
From the beginning, it was tacitly assumed that indicators that would eventually be used
must have data that are reliable, regularly collected, and readily accessible. The data
must be of sufficient quality to provide some certainty for the conclusions drawn from
them. The data must also be constantly updated, usually on a yearly or every other year
basis, and have a good chance of being collected into the near future or at least over the
five year life of the State Incentive Grant. Data should be available either in published
reports, on agency web sites, or through a single communication with the data set
manager. Data used for this report was archival or existed in surveys already completed;
no primary research was done to inform the report. A complete list of all the indicators
that were considered is provided in Appendix A.
Another decision made early in the process was to only look at indicators of consumption
or consequences directly related to substance use. The relationship between substance
use and other health or social problems has been recognized in public health. Excessive
drinking has been linked to liver cirrhosis, pancreatitis, and various cancers. Tobacco use
has been associated with cancer and cardiovascular disease. Illicit drug use is also related
to other health problems such as heart disease and HIV/ AIDS. Social problems like
crime and academic achievement are also affected by drug use. But, while the literature
suggests correlations between substance use and other health and social problems, the
proportion of these problems directly attributable to substance abuse in Arizona, also
known as attributable fractions, was not readily quantifiable or available from existing
sources. Two ot her concerns with attributable fractions influenced the decision to
only look at indicators with a direct relationship to substance use. First, even in studies
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where the effect of substance abuse on chronic illness or social problems is measured,
such effects may not be seen for many years or decades making it difficult to measure the
effects of the State Incentive Grant’s interventions. Second, several of the public health
experts and epidemiologists on the working group questioned the methods used to
calculate the proportion of a given problem that could be attributed to substance use.
It should be pointed out that this approach, starting with a search for indicators that can
describe the consequences of substance abuse and consumption patterns, defines
substance use problems in a particular way. Problems are determined by available data
as opposed to starting with a community concern and then finding data to inform the
extent of that concern. This approach may be problematic because only those
consequences for which data exist are included in the analysis. This approach also
narrowly restricts a problem or problem syndrome, such as drinking and driving, to a
specific indicator or set of indicators such as arrests for driving under the influence of
alcohol.
The second phase of the work consisted of analyzing available indicator data so that it
could be interpreted for the purposes of the State Incentive Grant. Specifically, substance
abuse consequence and consumption patterns and the populations implicated by these
consequences and consumption patterns needed to be identified and priorities set among
the various consequences, consumption patterns, and audiences. Once problem areas and
audiences were identified, State Incentive Grant funds could be allocated to interventions
to remediate these problems. Data from the first phase of the process were reviewed and
a problem area identification exercise was conducted to specify those problem areas that
the epidemiology work group considered most important. Once these preliminary
problem areas were noted, the data were reviewed and analyzed again to specifically
inform decisions that would be made for allocating State Incentive Grant funds.
Data were presented in absolute numbers and rates when rates were available or when
denominators were known for rate calculation. Absolute numbers provide a sense of the
number of people that are affected and the magnitude of the problem. Rates suggest if a
particular population may be disproportionately affected by the problem and therefore
more in need of attention. Populations affected by a particular indicator were defined and
analyzed by county or sub- county geography and by age when geographic or age data
were available.
In analyzing and interpreting indicators, magnitude of the problem in terms of number of
people or events and disproportional distribution of the problem in the population in
terms of rates were the only two methods used. With the exception of death or illness,
data on the severity of an indicator or problem or its effect on an individual or society
such as economic costs or productivity losses were not included in the analysis. This is a
weakness of the final analysis since such data might influence priority setting if, for
example, a drug has a low consumption rate relative to other drugs but its economic costs
far exceed those of drugs that have higher consumption rates.
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This report presents data on the indicators of substance abuse consequence and
consumption that the work group investigated. It also documents some of the processes
and proceedings of the work group. The report attempts to provide an overview of the
effects of substance use in the state but it also interprets the data for the specific purposes
of the State Incentive Grant. For this reason, after the initial data exposition, the report’s
analysis and findings largely address the needs of the State Incentive Grant. This means
that some data are presented that do not make their way into the final problem areas. It
also means that some very specific analyses are conducted on certain data sets and not on
other ones in order to better inform the final problem areas. The group’s final
interpretations in the form of findings are included throughout the report. The problem
areas that the group decided upon and a brief discussion of the problem area
identification process are included in section six: Identification of Problem Areas.
Sources for the data contained in the report are cited in different ways to make the data
presentation more readable. When possible, data sources are cited within the body of the
table in the title or next to the indicator. When this approach becomes unwieldy and
begins to clutter the table, footnotes are used instead. In general, the report or data set
from which the information is derived, the date of the report, and the agency that
authored the report or maintains the data are cited.
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3. Assessment of the Magnitude of Substance Abuse in Arizona
3.1 Mortality
Probably the most severe consequence of substance use is death. Table 3A presents the
number of deaths caused by substance use compared to the state’s five leading causes of
death. A brief explanation of the various substance abuse related mortality indicators
follows.
Table 3A: Five Leading Causes of Death Compared to Alcohol/ Drug Related
Mortality, Arizona, 2003.
Alcohol/ drug mortality
Drug induced deaths1 646
Alcohol induced deaths1 543
Alcohol related crash deaths2 470
Alcohol related crash deaths3 298
Drug related fatal crashes3 24
Alcohol related boating fatalities4 6
Five leading causes of death1
Disease of heart 10,649
Malignant Neoplasm ( cancer) 9,451
Chronic lower respiratory diseases 2,522
Cerebrovascular diseases 2,466
Accidents ( unintentional injury) 2,356
1 Arizona Health Status and Vital Statistics, 2003 data, Arizona Department of Health Services. Available
online: http:// www. azdhs. gov/ plan/ index. htm [ cited September 13, 2005].
2 Arizona: Toll of Motor Vehicle Crashes, 2003, National Highway Traffic Safety Administration.
Available online: http:// www. nhtsa. dot. gov/ stsi/. [ cited September 13, 2005]. Federal estimates differ
from state reports due to the estimation method used to classify fatal accidents for which alcohol
involvement is unknown.
3 2003 Arizona Crash Facts Summary, 2004, Arizona Department of Transportation. Available on- line:
http:// www. azdot. gov/ MVD/ statistics/ crash/ index. asp. [ cited September 13, 2005].
4 2003 Arizona Boating Safety Report, 2004. Arizona Game and Fish Department.
3.1.1 Drug and alcohol induced deaths. The Department of Health Services includes
poisoning by, misuse of, abuse of, or dependence on drugs, medication, and biological
substances other than alcohol in its drug induced death category. Accidental overdoses of
drugs, intentional self- poisoning and drug abuse are the three major categories for drug
related mortality. In 2003, there were 1,189 deaths attributed to alcohol and drugs.
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3.1.2 Alcohol and drug related crash deaths. The Department of Transportation
collects data on crashes and crash injuries and deaths. These include crashes in which the
driver had been impaired by drinking or had been under the influence of narcotic or
prescription drugs. In 2003 there were 298 alcohol related crash deaths and 24 drug
related crash deaths. The National Highway Traffic Safety Administration amends the
state agency’s statistics by estimating how many of the unclassified traffic deaths can be
attributed to alcohol. Their estimation method increases the Department of
Transportation’s figure to 470 alcohol related crash deaths in Arizona.
3.1.3 Alcohol related boating fatalities. The Arizona Game and Fish Department
reports on alcohol related accidents and fatalities on the state’s waterways. In 2003, there
were 6 alcohol related boating fatalities.
Finding: As seen in Table 3A, deaths associated with substance use are relatively
small when compared to the five leading causes of death in Arizona. This suggests
two things. First, any intervention targeting death directly related to substance use would
have little affect on the state’s overall mortality. Second, because there are so few deaths
directly attributable to drugs and alcohol, measuring an intervention’s success would be
difficult because there is so little to change.
3.2 Morbidity
In this report, morbidity refers to illnesses or injuries, both physical and psychological,
directly attributable to substance use. To give an idea of the extent of a particular illness
or type of injury, Table 3B ranks indicators according to the number of people
experiencing the problem or occurrences of the problem event. The indicators in Table
3B can be grouped into four domains: clinical dependence or abuse, drunk and drugged
driving and boating, hospital discharges and emergency department visits, and
HIV/ AIDS. Subsequent tables group the indicators and discuss each domain.
Finding: As seen in Table 3B, the absolute numbers for substance use problems
related to illness or injury are much greater than the absolute numbers for deaths
related to substance use. Focusing on reducing substance use related injury and
illness provides a much larger target for intervention and would also reduce deaths
related to substance use.
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Table 3B: Alcohol/ Drug Related Morbidity, Arizona, 2003 Unless Otherwise Noted.
Estimated number of people with past year dependence or abuse for any illicit drug
or alcohol, 2002 and 2003 averages1
488,000 ( 12 and
older)
Estimated number of persons driving in the past 30 days when they think they have
had too much to drink, 20042
132,034
Arrests for driving under the influence3 39,536
Non- dependent abuse of drugs related ED visits, ( July- December, 20034 30,298
Hospital discharges related to alcohol abuse, 20034 19,507
Hospital discharges related to drug dependence or drug abuse, 20034 19,102
Alcohol related crashes5 7,800
Alcohol related crash injuries5 6,215
Drug and alcohol dependence neuroses related ED visits, July- December, 20034 5,321
First listed diagnoses of nondependent abuse of drugs in ED visits, July- December,
20034
5,134
Number of families in Child Protective Services that were referred for substance
abuse treatment ( Families F. I. R. S. T), 20046
3,135
Drug and alcohol psychoses related ED visits, July- December, 20034 1,810
First listed diagnoses of alcohol dependence in ED visits, July- December, 2003 4 1,808
First listed diagnoses of drug psychoses in ED visits, July- December, 2003 4 678
Hospital discharges related to noxious influences ( narcotics, hallucinogens, and
cocaine) affecting the fetus, 20034
517
HIV infection or AIDS incidence with injecting drug use as the mode of
transmission, 1998- 20027
500
First listed diagnoses of alcohol psychoses in ED visits, July- December, 2003 4 484
Drug related crash injuries5 325
First listed diagnoses of drug dependence in ED visits, July- December, 2003 4 322
HIV infection and AIDS incidence with injecting drug use/ men who have sex with
men as mode of transmission, 1998- 20027
259
Alcohol related boating injuries8 140
1National Survey on Drug Use and Health, 2002 and 2003 averages. Substance Abuse and Mental Health
Services Administration. Available on- line: http:// oas. samhsa. gov/. [ cited September 13, 2005]
2 Behavioral Risk Factor Survey, personal communication, Arizona Department of Health Services. The
BRFS provides an estimated percentage of 3.2% for people reporting driving in the past 30 days when they
think they have had too much to drink. Population computed by using 2003 population estimates for
individuals 18 years old and older of 4,126,072.
3 Crime in Arizona 2003, 2004. Arizona Department of Public Safety. Available on- line:
http:// www. azdps. gov/ crimereport/ default. asp. [ cited September 13, 2005].
4 Hospital Discharge Database, 2003 data. Arizona Department of Health Services. Available online:
http:// www. azdhs. gov/ plan/ index. htm . [ cited September 13, 2005].
5 2003 Arizona Crash Facts Summary, 2004, Arizona Department of Transportation. Available on- line:
http:// www. azdot. gov/ MVD/ statistics/ crash/ index. asp. [ cited September 13, 2005].
6 Families FIRST, 2004 personal communication. Department of Economic Security.
7 Arizona Statistics, Office of HIV/ AIDS, Department of Health Services. Available on- line:
http:// www. azdhs. gov/ phs/ hiv/ pdf/ arizona. pdf. [ cited September 13, 2005].
8 2003 Arizona Boating Safety Report, 2004. Arizona Game and Fish Department.
3.2.1 Clinical dependence or abuse. Estimates for the number of people in Arizona that
have a clinical problem with dependence or abuse of alcohol or drugs are provided by the
National Survey on Drug Use and Health. Clinical dependence and abuse is measured
using criteria from the Diagnostic and Statistical Manual of Mental Disorders, 4th edition
and is diagnosed when alcohol or drug use is chronic or excessive enough to cause
behavioral, psychological, or lifestyle problems. Using data from the 2002 and 2003
18
survey, it is estimated that almost one- half million people in Arizona, ages 12 and older,
are dependent on or abuse alcohol and/ or drugs ( Table 3B).
3.2.2 Drunk and drugged driving and boating. Table 3C groups driving and boating
consequences together. The Department of Transportation reported 7,800 alcohol related
crashes causing 6,215 injuries. Another 325 injuries resulted from drug related crashes.
The Game and Fish Department reports 140 alcohol related boating injuries.
Even though drinking and driving is not an illness or injury in itself, this behavior is a
necessary antecedent to alcohol related injury or death and clearly increases the risk for
injury and death. For this reason, several different indicators that address the prevalence
of drinking and driving are included in this section.
According to the 2003 Behavioral Risk Factor Survey conducted by the Department of
Health Services, 105,859 people are estimated to have been driving in the past 30 days
when they thought they had too much to drink. Arrests for driving under the influence of
alcohol is another measure of the prevalence of this risky behavior. According to the
Department of Public Safety, there were 39,536 arrests in Arizona for driving under the
influence of alcohol in 2003. This figure should be interpreted cautiously since arrests
can be influenced by administrative decisions such as increased law enforcement activity
to identify drunk drivers.
Table 3C: Drunk and Drugged Driving and Boating, Arizona, 2003 Unless
Otherwise Noted.
Persons estimated to be driving in the past 30 days when they think they have
had too much to drink, 2004
105,859
Arrests for driving under the influence 39,536
Alcohol related crashes 7,800
Alcohol related crash injuries 6,215
Drug related crash injuries 325
Alcohol related boating injuries 140
Source: See sources for Table 3B.
3.2.3 Hospital and emergency department data. The Department of Health Services
maintains a database with information about hospital inpatient and emergency department
discharges. Under the uniform patient reporting system mandated by A. R. S. 36- 125.05,
all of Arizona's licensed, non- federal hospitals ( except for psychiatric hospitals) are
required to report a set of data to the Department of Health Services on a biannual basis,
on February 15th and August 15th each year. Each data set report includes inpatient and
emergency department hospital discharges for a six- month period by each hospital. The
Department currently collects approximately 2.2 million discharge records annually from
the state's 82 licensed hospitals. These data related to substance use are presented in
Table 3D.
When an admitted patient leaves a hospital or when an individual visits an emergency
department, up to nine diagnoses are recorded. Diagnoses are based on the International
19
Classification of Diseases, 9th Revision. Data are reported for drug and alcohol related
diagnoses that were listed as the primary or first diagnoses as well as drug and alcohol
related diagnoses that occurred in any of the nine diagnoses. The largest diagnoses
category related to substance use was for emergency department visits related to non-dependent
abuse of drugs. In a six- month period, 30,298 emergency department visits
had a mention of this diagnosis. Hospital discharges related to alcohol abuse ( 19,507)
and hospital discharges related to drug dependence or drug abuse ( 19,102) followed.
Diagnoses of alcohol and drug related neuroses or psychoses are much lower than
diagnoses of dependence or abuse. There were 5,321 visitors to emergency departments
that had a mention of drug or alcohol neuroses diagnoses in a six- month period and 1,810
visitors to emergency departments that had a mention of drug or alcohol psychoses
diagnoses.
Hospitals regularly test newborns for what are called noxious substances, i. e. narcotics,
hallucinogens, and cocaine. According to the hospital discharge database, there were 517
discharges of newborns that tested positive for such substances.
Table 3D: Hospital and Emergency Department Discharges and Visits Related to
Substance Use, Arizona.
Non- dependent abuse of drugs related ED visits ( July- December,
2003)
30,298
Hospital discharges related to alcohol abuse, 2003 19,507
Hospital discharges related to drug dependence or drug abuse, 2003 19,102
Drug and alcohol dependence neuroses related ED visits ( July-
December, 2003)
5,321
First listed diagnoses of nondependent abuse of drugs in ED visits
( July- December, 2003)
5,134
Drug and alcohol psychoses related ED visits, ( July- December, 2003) 1,810
First listed diagnoses of alcohol dependence in ED visits ( July-
December, 2003)
1,808
First listed diagnoses of drug psychoses in ED visits ( July- December,
2003)
678
Hospital discharges related to noxious influences affecting the fetus
( 2003), Narcotics, hallucinogens, and cocaine
517
First listed diagnoses of alcohol psychoses in ED visits ( July-
December, 2003)
484
First listed diagnoses of drug dependence in ED visits ( July-
December, 2003)
322
Source: See sources for Table 3B.
3.2.4 HIV/ AIDS. HIV infection as a direct result of substance use is relatively small
compared to other morbidity indicators. According to the Department of Health Services,
from 1998 to 2002, 500 cases of HIV infection were reported as a result of injection drug
use ( Table 3B). This increases to 759 cases when cases that also fall under the risk
category of men who have sex with men and inject drugs are added.
20
3.3 Consumption Patterns and Other Consequences
3.3.1 Alcohol and illicit drugs. Patterns of alcohol and illicit drug consumption and
other consequences of substance use not directly related to death or illness are discussed
in this section. Consumption does not necessarily result in death or illness but some
consumption patterns such as binge drinking or illicit drug use predict health
consequences better than others due to the impairment following such use. Other
consequences such as arrests for drug possession suggest a social cost in terms of
infringement of laws and behavioral norms.
Table 3E presents alcohol and drug use data for Arizona from the National Survey on
Drug Use and Health on a variety of substances. Alcohol, cigarette, and illicit drug use
estimates are provided for individuals, ages 12 and older, and alcohol use estimates are
provided for individuals 12 to 20 years old. While responsible alcohol consumption for
adults may not be a problem, binge drinking, defined as five or more drinks in one sitting,
often leads to impairment that can lead to injury or may be a marker for alcohol abuse or
dependence. Because alcohol use is illegal for those individuals under the age of 21, both
alcohol use and binge alcohol use present a potential problem for this age group. It is
estimated that approximately 20 percent of the state’s population, ages 12 and older, has
engaged in binge drinking in the past month.
Table 3E: Alcohol/ Drug Consumption, Arizona Estimates, 2002 and 2003 Averages.
Past month alcohol use ( 12 and older) 2,217,000
Past month cigarette use ( 12 and older) 1,215,000
Past month binge alcohol use ( 12 and older) 1,075,000
Past month illicit drug use ( 12 and older) 392,000
Underage alcohol use
Past month alcohol use ( averages 12 to 20) 204,000
Past month binge alcohol use ( 12 to 20) 136,000
Source: National Survey on Drug Use and Health, 2002 and 2003 averages. Substance Abuse and Mental
Health Services Administration. Available on- line: http:// oas. samhsa. gov/. [ cited September 13, 2005].
The Arizona Youth Survey that is conducted every other year among 8th, 10th, and 12th
grade students in Arizona schools provides another measure of youth substance use.
Alcohol and illicit drug use prevalence data from the Arizona Youth Survey is presented
in Table 3F. According to the Arizona Youth Survey estimates, 36 percent of 8th, 10th,
and 12th grade students have used alcohol in the past month and 23 percent have engaged
in binge drinking in the past two weeks. Twenty- one percent of students surveyed report
using an illicit drug in the past month.
The Arizona Youth Survey samples respondents based on grade and not age. For this
reason it is difficult to compare Arizona Youth Survey findings with those from the
National Survey on Drug Use and Health. Comparisons between the two surveys should
be done with caution.
21
Table 3F: Percentage of Students Reporting Various Substance Use by Grade, Arizona,
2004.
Grade 8 Grade 10 Grade 12 Total
Alcohol use, past 30 days 25.3 41.3 51.1 36.3
Binge drinking, past two weeks 16.0 25.1 32.5 22.7
Any illicit drug ( excludes alcohol and
tobacco), past 30 days
17.9 23.6 25.1 21.4
Cigarette use, past 30 days 10.7 17.7 24.4 16.1
Source: Arizona Youth Survey: State Report, 2004. Arizona Criminal Justice Commission. Available on-line:
http:// www. acjc. state. az. us/ publications/ publications. asp? ServId= 1000. [ cited September 13, 2005].
Finding: Of all substance use patterns measured, alcohol consumption and binge
alcohol consumption affect the most people, including youth.
3.3.2 Methamphetamine. Methamphetamine use and its consequences have been
widely discussed by law enforcement agencies, the media, and community and civic
groups. Because of the alarm raised by methamphetamine use, the epidemiology work
group analyzed this drug’s consumption and consequences separately.
Recent estimates of methamphetamine use in Arizona are not available from the National
Survey on Drug Use and Health. Representatives for the Survey stated that the sample of
people reporting using methamphetamine was too small to reliably develop estimates of
yearly, state level use. Data from several years of the Survey will be combined to provide
recent estimates in a forthcoming report. Table 3G presents lifetime, past year, and past
month illicit drug use including methamphetamine for Arizona based on 1999, 2000, and
2001 samples from the National Survey on Drug Use and Health.
Table 3G: Illicit Drug Use among Persons Aged 12 and Older, Arizona Percentage
Estimate, Averages Based on 1999, 2000, and 2001 Samples.
Lifetime Past Year Past Month
Marijuana and hashish 36.9 8.2 4.9
Cocaine 14.1 2.3 0.9
Heroin 1.6 0.2 0.2
Hallucinogens 13.4 1.7 0.5
Inhalants 8.9 1.0 0.3
Pain relievers 9.8 3.4 1.6
Tranquilizers 5.3 1.4 0.5
Methamphetamine 5.9 0.9 0.5
Sedatives 3.0 0.2 0.1
Source: National Survey on Drug Use and Health, 1999, 2000, and 2001 samples, personal communication.
Substance Abuse and Mental Health Services Administration.
Finding: The number of people using methamphetamine in Arizona is too small for
national surveys to develop reliable, current estimates of use in the population.
Based on past survey samples, methamphetamine use is much lower than
22
marijuana, cocaine, and non- medical pain reliever use. The past month use of
methamphetamine is similar to hallucinogens and inhalants use.
The Arizona Youth Survey provides a measure of methamphetamine use for 8th, 10th, and
12th grade students in Arizona. Table 3H presents the percentages of 8th, 10th, and 12th
grade students that are estimated to use a variety of alcohol and drugs in the past 30 days
and at any previous time in their life. In 2002, 2 percent of students were estimated to
have used methamphetamine in the past 30 days. In 2004, the question was modified and
collapsed methamphetamine in to the class of stimulants. 2.3 percent of students were
estimated to have use stimulants in the past 30 days.
Table 3H: Estimated Percents of 8th, 10th, and 12th Grade Students Using Alcohol,
Tobacco, and Other Drugs, Arizona, 2002 and 2004.
Lifetime 30- day day
2002 2004 2002 2004
Alcohol 69.2 63.3 46.4 36.3
Cigarettes 49.3 42.0 16.5 16.1
Smokeless Tobacco 10.9 10.6 4.8 3.4
Marijuana 38.8 31.3 20.5 13.8
Inhalants 10.9 11.8 4.1 3.9
Hallucinogens 7.4 4.6 2.6 2.0
Cocaine 8.0 6.8 3.3 2.5
Methamphetamine 5.9 5.51 2.0 2.31
Steroids 2.5 N/ A 1.2 N/ A
Heroin 2.9 2.1 1.3 0.7
Sedatives/ Barbituates 4.9 14.8 2.3 7.22
Ecstasy 8.3 3.8 3.1 0.9
Source: Arizona Youth Survey: State Report, 2004. Arizona Criminal Justice Commission. Available on-line:
http:// www. acjc. state. az. us/ publications/ publications. asp? ServId= 1000. [ cited September 13, 2005].
1 The category of “ Stimulants” was used in the 2004 survey and included “ amphetamines,” “ meth,”
“ crystal,” and “ crank” as examples.
2 Different drugs were included in 2002 survey so the 2004 value is not comparable.
Another data set that can be used to measure methamphetamine use come from the Youth
Risk Behavior Survey, a study conducted with a representative, school- based sample of
Arizona 9th through 12th grade students. As shown in Table 3I, 8.6 percent of students
reported using methamphetamine in their lifetime in 2003, which is considerably lower
than the percentage of students reporting lifetime alcohol, marijuana, cocaine, and
inhalant use.
23
Table 3I: Percentage of Students Reporting Lifetime Use of
Alcohol or Drugs, Arizona, 2003.
At least one drink of alcohol 78.4%
Marijuana 45.3%
Cocaine, any form 12.7%
Inhalants 12.6%
Methamphetamine 8.6%
Ecstasy 7.8%
Steroids 4.8%
Heroin 2.5%
Injecting illegal drugs 2.0%
Source: Youth Risk Behavior Surveillance System, Centers for Disease Control
and Prevention. Available online:
http:// www. cdc. gov/ HealthyYouth/ yrbs/ index. htm. [ cited September 13,
2005].
National estimates from the 2002 and 2003 National Survey on Drug Use and Health for
30- day day and lifetime methamphetamine use are presented in Table 3J. Nationally the
percentage of 12 to 17 year olds reporting using methamphetamine is below 2 percent.
Table 3J: Methamphetamine Use in Lifetime and Past 30 Days, U. S. Percentage
Estimates, 2002 and 2003 Averages.
Lifetime 30- day Day
2002 2003 2002 2003
12- 17 1.5 1.3 0.3 0.3
18- 25 5.7 5.2 0.5 0.6
26 and older 5.7 5.7. 0.2 0.2
Source: National Survey on Drug Use and Health, 2002 and 2003 averages. Substance Abuse and Mental
Health Services Administration.
Finding: Based on current measures of adult and youth substance use,
methamphetamine is one of the least used drugs relative to alcohol, tobacco, and
marijuana. Inhalants and cocaine are used slightly more than methamphetamine.
Another way to consider methamphetamine in addition to the number of people using the
drug is to look at its effects on health and other social systems such as criminal justice.
The federal Treatment Episode Data Set provides one measure of effect. The data set
reports on the primary substance for which a person was admitted into publicly funded
treatment. According to the data presented in Table 3K, amphetamines, including
methamphetamine, accounted for the second largest number of treatment admissions,
more than marijuana or alcohol as the sole drug of use. These data should be interpreted
with caution since it is not clear what proportion of amphetamines is accounted for by
methamphetamine. In addition, more than 50 percent of reported treatment admissions in
Arizona did not list a primary drug. These data might look very different were these
unknowns to be included.
24
Table 3K: Primary Substance Reported upon Treatment Admission, Numbers and Percentages, Arizona, 2003
Total Alcohol
only
Alcohol
with
Secon-dary
Drug
Cocaine
( smoked)
Cocaine
( other
route)
Mari-juana
Heroin Other
opiates
Hallu-cin-ogens
Amphet
- amines
Other
stim-ulants
Tran-quil-izers
Seda-tives
Inha-lants
Other/
Un-known
15,879 1,417 2,068 343 321 1,014 611 71 10 1,625 46 22 9 10 8,312
100.0% 8.9% 13.0% 2.2 2.0 6.4 3.8 0.4 0.1 10.2 0.3 0.1 0.1 0.1 52.3
Source: Treatment Episode Data Set, 2003 data. Substance Abuse and Mental Health Services Administration. Available online:
http:// wwwdasis. samhsa. gov/ webt/ quicklink/ AZ03. htm. [ cited September 13, 2005.
25
Finding: While the prevalence of methamphetamine use is low, the affect on the
publicly funded treatment system appears to be high in terms of number of
treatment admissions.
Other claims have been made about the effects of methamphetamine use on the child
welfare system, the criminal justice system, and the health care system. For example, the
media frequently reports on the increase in methamphetamine users in emergency rooms
or the disproportionate affect of methamphetamine use on crime and law enforcement
resources. This data would provide another measure of the severity of methamphetamine
use but was not available for this report.
3.3.3 Substance use and criminal justice. Table 3L presents data on a variety of
indicators related to substance use and the criminal justice system. It should be noted that
these data are subject to changes in enforcement and sentencing practice and therefore do
not necessarily reliably reflect the prevalence of substance use in the state.
Substance use that results in encounters with law enforcement, the courts, and corrections
is not directly related to death and illness. Its importance as a problem would be derived
from other criteria such as financial costs to government for processing and maintaining
offenders, burden on victims as a result of the drug offender’s behavior, and moral or
social costs related to violations of community norms.
Arrest data comes from the Crime in Arizona, 2003 report that is compiled by the state’s
Department of Public Safety from reports submitted by local law enforcement agencies.
Not all law enforcement agencies in the state submit data so arrests are underreported in
these figures. Sentencing data is provided by the Administrative Office of the Courts and
commitment data is provided by reports from the Department of Corrections and the
Department of Juvenile Corrections.
Finding: The burden of substance use on the criminal justice system is substantial
with more than 72,000 arrests reported for substance use related crimes. Driving
under the influence accounts for more than half these arrests. Arrests for driving
under the influence, arrests for drug possession, and the number of adults sentenced
to probation account for 83 percent of the criminal justice encounters.
26
Table 3L: Substance Use and Criminal Justice, Arizona, 2003 and 2004 as Noted.
Arrests for driving under the influence, 20031 39,536
Arrests for drug possession, 20031 27,866
Adults sentenced to probation for drug offenses, 20042 18,525
Arrests for drug sale or manufacturing, 20031 5,520
Adults sentenced to probation for DUI offenses, 20042 4,633
Commitments to Department of Corrections for dangerous drugs, 20033 3,330
Commitments to Department of Corrections for DWI, 20033 2,675
Juveniles with disposition of probation or intensive probation, 20044 1,698
Commitments to Department of Juvenile Corrections for drug offenses,
20035
126
1 Crime in Arizona 2003, 2004. Arizona Department of Public Safety. Available on- line:
http:// www. azdps. gov/ crimereport/ default. asp. [ cited September 13, 2005].
2 Arizona Adult Probation Population: Fiscal Year 2004, 2005. Adult Probation Services Division,
Administrative Office of the Courts. Available on- line:
http:// www. supreme. state. az. us/ apsd/ azprobpop. htm. [ cited September 13, 2005].
3 Annual Report Fiscal Year 2003, 2004. Arizona Department of Corrections. Available on- line:
http:// www. azcorrections. gov/ reports/ reports. htm. [ cited September 13, 2005].
4 Juveniles Processed in the Arizona Court System FY2004, 2005. Juvenile Justice Services Division,
Adminstrative Office of the Courts. Available on- line:
http:// www. supreme. state. az. us/ jjsd/ juvenilesproce/ Juveniles_ Processed_ FY04. pdf. [ cited September 13,
2005.
5 Creating a Difference for Arizona’s Youth: The Arizona Department of Juvenile Corrections
FY ‘ 04 Annual Performance Report, July 1, 2003 – June 30, 2004, 2005. Arizona Department of Juvenile
Corrections. Available on- line: http:// www. azdjc. gov/ AgencyInfo/ AnnualRpt04. pdf. [ cited September 13,
2005].
3.3.4 Substance use and education. Table 3M presents data on the number of
disciplinary actions that are taken as the result of the possession, use, or distribution of
alcohol, tobacco, or illegal drugs on Arizona’s school campuses, grades kindergarten
through 12. Disciplinary actions are of three types: expulsions or removals for at least
one year, suspensions or removal from school for 10 days or more but less than one year,
and transfers or placement in a specialized schools for disciplinary reasons for
at least one year.
As with arrests, disciplinary actions are not representative of the problems that drugs and
alcohol cause on school campus but are more a measure of the administrative response to
these substances as they are discovered on campuses. Still, the response is significant
with more than 4,000 instances of suspension, expulsion, and transfer reported in 2004 as
a result of alcohol, tobacco, or drugs.
27
Table 3M: Disciplinary Actions for Possession, Use, or Distribution of Alcohol, Illegal
Drugs, and Tobacco, Arizona, 2004.
Disciplinary action
Expulsion Suspension Transfer Total
Possession of alcohol 54 577 49 680
Possession, use, and
distribution of illegal drugs
327 2,380 330 3,037
Possession and use of tobacco 24 192 2 918
Source: Arizona Department of Education, 2004, personal communication.
3.4 Select Problem Indicators by Age
An analysis of problem indicators by age is meant to describe the age groups that are
experiencing the most substance abuse related problems and age groups that might
benefit the most by interventions.
Age breakdowns are provided for problem indicators that affect large numbers of people
and for which age data are available. Given the small number of deaths directly caused
by substance use, drug related mortality was not analyzed by age.
The data presented in this section points to the age group that experiences a particular
problem but do not describe when the antecedents to problem behaviors first appear or
the age at which the presence of the antecedents is most critical in forming the problem
behavior. The type of intervention will vary depending on how this age data is used.
Interventions that seek to prevent the occurrence of a problem behavior could target
individuals that are younger than those age groups with a high rate of the problem
behavior. An intervention could also target an age group with high rates of the problem
behavior with the intention of reaching individuals in that group that have not yet
engaged in the problem behavior. If the intervention sought to prevent a reoccurrence of
the problem behavior, age groups with high rates of the problem behavior could be
targeted.
3.4.1 Consumption. Table 3N presents substance use consumption data from the
National Survey on Drug Use and Health by age groups. Table 3O presents substance
use consumption data from the Arizona Youth Survey by 8th, 10th, and 12th grade levels.
28
Table 3N: Selected Drug Use and Alcohol or Illicit Drug Dependence or Abuse, Estimated
Numbers and Rates Per 1,000 People in Age Group in Arizona, 2002 and 2003 Averages.
12- 17 18- 25 26+
Number Rate Number Rate Number Rate
Alcohol or Illicit Drug
Dependence or Abuse
52,000 105.36 141,000 222.79 295,000 85.91
Alcohol Dependence or
Abuse
36,000 72.94 117,000 184.86 258,000 75.13
Past month illicit drug
use
61,000 123.60 114,000 180.12 217,000 63.19
Past month alcohol use 91,000 184.38 352,000 556.18 1,774,000 516.64
Past month binge
alcohol use
58,000 117.52 250,000 395.02 767,000 223.37
Past month cigarette
use
62,000 125.62 234,000 369.73 919,000 267.64
Source: National Survey on Drug Use and Health, 2002 and 2003 averages. Substance Abuse and Mental
Health Services Administration. Available on- line: http:// oas. samhsa. gov/. [ cited September 13, 2005]
Table 3O: Percentage of Students Reporting Various Substance Use by Grade, Arizona,
2004.
Grade 8 Grade 10 Grade 12 Total
Alcohol, past 30 days 25.3 41.3 51.1 36.3
Binge drinking, past two weeks 16.0 25.1 32.5 22.7
Cigarettes, past 30 days 10.7 17.7 24.4 16.1
Any illicit drug, past 30 days 17.9 23.6 25.1 21.4
Source: Arizona Youth Survey: State Report, 2004. Arizona Criminal Justice Commission. Available on-line:
http:// www. acjc. state. az. us/ publications/ publications. asp? ServId= 1000. [ cited September 13, 2005].
Finding: According to the estimates in Table 3N, 18 to 25 year olds have the highest
rates for all substance use including alcohol or illicit drug dependence or abuse and
past month binge alcohol use. Twelve to seventeen year olds have the second highest
rates for alcohol or illicit drug dependence or abuse and past month illicit drug use.
Finding: According to Table 3O, 12th grade has the highest percentage of students
that have used alcohol, tobacco, and illicit drugs in the past 30 days or have engaged
in binge drinking in the past two weeks.
Finding: Even though the 8th grade does not have the highest percentage of past 30-
day day substance users, the 8th grade has a substantial percentage of students
reporting alcohol or illicit drug use in the past 30 days, anywhere from 21 percent
for illicit drugs and 36 percent for alcohol use.
Finding: The estimated rate of 12 to 17 year olds using illicit drugs in the past 30
days ( 123.6/ 1,000) is higher than the estimated rate of 12 to 17 year olds who report
binge drinking in the past 30 days ( 117.52/ 1,000)
29
3.4.2. Hospital discharges and emergency department visits. Rates by age group for
hospital discharge and emergency department visits are presented in Tables 3P and 3Q.
Most drug- related emergency room visits and hospital discharges result from the non-dependent
abuse of drugs. According to the International Classification of Diseases,
Ninth Revision, Clinical Modification, the non- dependent abuse of drugs diagnosis
“ includes cases where a person, for whom no other diagnosis is possible, has come under
medical care because of the maladaptive effect of a drug on which he is not dependent
and that he has taken on his own initiative to the detriment of his health or social
functioning.” Alcohol and drug psychosis and dependence are rare in emergency
departments compared to non- dependent abuse of drugs.
Finding: Rates and absolute numbers for non- dependent abuse of drugs among
emergency department visits and hospital discharges are highest among 20- 44 year
olds.
Finding: Rates for most drug- related disorders diagnosed in emergency department
visits and hospital discharges are highest among 20- 44 year olds. Rates for drug
related disorder diagnoses are also relatively high in the 45- 64 year old age group.
Finding: For disorders related to alcohol, rates are highest among 45- 64 year olds
in both emergency department visits and hospital discharges. Rates of diagnoses for
alcohol abuse in hospital discharges remain high among those 65 and older.
30
Table 3P: Emergency Department Visits and Rates per 100,000 People in Age Group for Alcohol/ Drug Psychoses and Neuroses,
Arizona, July- December 2003.
< 15 15- 19 20- 44 45- 64 65+ Unknown
Visits Rate Visits Rate Visits Rate Visits Rate Visits Rate
Drug psychosis, all
mention
1
— 45 11.16 648 31.48 301 25.63 85
11.6 0
Alcohol psychosis, all
mentions
0 — 1 — 434 21.08 267 22.73 28
3.82 0
Drug dependence
neuroses, all mentions
2 51 12.65 1,001 48.63 454 38.66 63
8.59 0
Non- dependent abuse of
drugs, neuroses, all
mentions
285 22.58 2,457 609.54 18,762 911.61 7,332 624.43 1,449 197.75 13
Alcohol dependence
syndrome neuroses, all
mentions
7
.55 93 23.07 2,135 103.73 1,388 118.21 124 16.92 3
Source: Hospital Discharge Database, 2003 data. Arizona Department of Health Services. Available online: http:// www. azdhs. gov/ plan/ index. htm . [ cited
September 13, 2005].
Table 3Q: Hospital Discharges Related to Drug Dependence, Drug Abuse, and Alcohol Abuse and Rates per 100,000 People in
Specified Age Group, Arizona, 2003.
< 15 15- 19 20- 44 45- 64 65+ Unknown
Disch. Rate Disch. Rate Disch. Rate Disch. Rate Disch. Rate
Drug dependence, all
mentions
36 2.85 232 57.55 3,094 150.33 1,747 148.78 296 40.39 0
Nondependent abuse of
drugs, all mentions
114 9.03 1,159 287.53 9,000 437.29 3,159 269.03 225 30.7 1
Drug psychoses, all
mentions
57 4.51 131 32.49 1,099 53.39 880 74.94 1,249 170.45 0
Alcohol abuse 194 15.37 415 102.95 6,621 321.7 8,461 720.59 3,811 520.1 5
Source: Hospital Discharge Database, 2003 data. Arizona Department of Health Services. Available online: http:// www. azdhs. gov/ plan/ index. htm . [ cited
September 13, 2005].
31
3.4.3 Alcohol related car crashes. Table 3R presents age data for alcohol related crashes.
Finding: Drivers between the ages of 21 and 24 have the highest rates of alcohol related
injury and fatal car crashes. Drivers between the ages of 25 and 34 have the second highest
rate of injury and fatal crashes.
3.4.4 Drug and alcohol related arrests. Table 3S presents age data for drug related arrests,
including arrests for driving under the influence.
Finding: Arrest rates for driving under the influence are highest for 18 to 24 year olds.
Rates of arrests for driving under the influence continues to be problematic for drivers
between the ages of 25 and 44 when compared to other age groups.
Finding: Eighteen to twenty- four year olds have the highest rates for all drug related
arrests. Thirteen to seventeen year olds have the second highest arrest rate for drug
possession.
Figure 3A summarizes age- related data for various problem indicators. The ages at the top of the
figure are not continuous because they correspond to the age groupings provided by a particular
data set. Black cells indicate the ages that had the highest rates of the problem. Gray cells
indicate age groups that did not have the highest problem rate but were still experiencing
relatively high problem rates compared to other age groups. It should be noted that for student
substance use, data for college students or students above the 12th grade level are not
systematically collected.
Finding: Highest rates for a majority of the problem indicators cluster in the 18 to 25 year
old age group. In the case of hospital or emergency department discharges, the high rates
extend up to the age of 44.
Finding: One exception to the pattern of highest rates among 18 to 25 year olds is hospital
discharges with a diagnosis of alcohol abuse. In this case, the highest rates occur among
people ages 45 and older.
32
Table 3R: Age of Driver in Alcohol Related Crashes and Rates per 100,000 people in the Specified Age Group, Arizona, 2003.
15- 20 21- 24 25- 34 35- 44 45- 54 55+ No
report
Drivers Rate Drivers Rate Drivers Rate Drivers Rate Drivers Rate Drivers Rate
Drivers in fatal
crashes
30 6.44 41
12.75 70
8.7 51
6.48 36
5.19 28
2.27 5
Drivers in injury
crashes
479 102.83 685 210.17 1039 129.16 716 91.03 414 59.77 242 19.68 81
Source: 2003 Arizona Crash Facts Summary, 2004, Arizona Department of Transportation. Available on- line: http:// www. azdot. gov/ MVD/ statistics/ crash/ index. asp.
[ cited September 13, 2005].
Table 3S: Drug Related Arrests and Rates per 100,000 in the Specified Age Group, Arizona, 2003.
< 13 13- 17 18- 24 25- 29 30- 34 35- 39 40- 44 45+
Arrest Rate Arrest Rate Arrest Rate Arrest Rate Arrest Rate Arrest Rate Arrest Rate Arrest Rate
Arrests for drug
sale or
manufacturing
23 2.08 471 146.7 1,663 300.2 843 211.8 789 194.2 668 173.2 548 136.7 515 26.8
Arrests for drug
possession
217 19.6 4,653 1449.5 9,591 1731.5 3,452 867.2 2,833 697.2 2,651 687.4 2,127 530.6 2,342 121.9
Arrests for driving
under the
influence
5 — 607 189.1 11,703 2112.8 6,748 1695.2 5,433 1,337 4,278 1109.2 3,936 981.9 6,826 355.2
Source: Crime in Arizona 2003, 2004. Arizona Department of Public Safety. Available on- line: http:// www. azdps. gov/ crimereport/ default. asp. [ cited September 13,
2005].
33
Figure 3A: Comparison of Rates for Problem Indicators by Age Groups. ( Black cells represent highest rates, gray cells represent second or third highest
rates.)
Problem Age
12 13 15 16 17 18 19 20 21 24 25 34 44 45 64 65+
Student substance use1
Past month illicit drug and alcohol use2
Alcohol/ illicit drug dependence/ abuse2
DUI arrests3
Drug related arrests3
Drug possession arrests3
Drug/ alcohol ED visits4
Nondep. drug abuse ED4
Nondep. drug abuse HD4
Inj/ fatal alcohol related crashes5
Alcohol abuse HD4
1 Arizona Youth Survey: State Report, 2004. Arizona Criminal Justice Commission. Available on- line:
http:// www. acjc. state. az. us/ publications/ publications. asp? ServId= 1000. [ cited September 13, 2005].
2 National Survey on Drug Use and Health, 2002 and 2003 averages. Substance Abuse and Mental Health Services Administration. Available on- line:
http:// oas. samhsa. gov/. [ cited September 13, 2005]
3 Crime in Arizona 2003, 2004. Arizona Department of Public Safety. Available on- line: http:// www. azdps. gov/ crimereport/ default. asp. [ cited September 13,
2005].
4 Hospital Discharge Database, 2003 data. Arizona Department of Health Services. Available online: http:// www. azdhs. gov/ plan/ index. htm . [ cited September
13, 2005].
5 2003 Arizona Crash Facts Summary, 2004, Arizona Department of Transportation. Available on- line: http:// www. azdot. gov/ MVD/ statistics/ crash/ index. asp.
[ cited September 13, 2005].
34
3.5 Select Problem Indicators by Geography
This section presents data that are available at a sub- state level in order to determine
geographic areas that experience higher rates of substance use related problems. Several
issues should be considered in this type of analysis.
The size of the population of the county and the absolute number of substance use related
events should be taken into account. A county might have a high rate of the problem
compared to other counties but the county’s population and the number of people
experiencing the problem may be relatively small. An intervention may not be able to
achieve sizable reductions in an already small audience. Population estimates in 2003 for
each county are provided in Appendix B.
Looking at problems by county may mask high rates of problems in smaller geographic
areas. For example, Maricopa County is so big that one rate to describe all of its
constituent communities may understate a particular municipality’s problems.
The relationship between problem prevalence and intervention need should be
considered. A car crash may not occur in the same place that the person became
intoxicated or learned the behaviors that resulted in the car crash. Similarly, arrests may
occur in a particular zip code but the offender may have come from another geographic
area altogether. This is even more salient for prevention interventions where antecedents
to the actual problem may have developed years before the problem event and in a
different location.
Sub- state data for adult substance use prevalence are generally not available for Arizona.
One exception to this are data collected for the Report on the Status of College Student
Alcohol and Other Drug Use in Arizona. These data are taken from a 2004 study of
undergraduates at Arizona’s three state universities. According to the report, 77 percent
of undergraduates surveyed reported using alcohol during the school year and 22 percent
reported having used marijuana during the school year. These findings are derived from
a convenience sample of undergraduates and should be interpreted cautiously.
Tables 3T through 3W present county level data from the Arizona Youth Survey on past
30- day day alcohol use, past two- week binge alcohol use, past 30- day day cigarette use,
and past 30- day day illicit drug use for 8th, 10th, and 12th grade students.
35
Table 3T: Percentage of 8th, 10th, and 12th Grade Students Who Used Alcohol During the Past 30
Days, Arizona, 2004.
8th Grade 10th Grade 12th Grade
County % Rank % Rank % Rank Average Rank
State 25.3 41.3 51.1 39.2
Apache 18.8 13 38.5 12 47.2 11 34.8 13
Cochise 31.4 2 41.7 7 52.3 5 41.8 4
Coconino 24.5 10 43.2 4 47.3 10 38.3 9
Gila 29.2 5 39.8 10 58.5 3 42.5 3
Graham 26.8 7 40.5 9 44.1 13 37.1 11
Greenlee 32.3 1 39.7 11 48.6 8 40.2 5
LaPaz 30.1 3 42.7 6 37.9 15 36.9 12
Maricopa 24.5 10 41.5 8 52.1 6 39.4 7
Mohave 26.6 8 48.2 3 55.9 4 43.6 2
Navajo 19.8 12 35.1 14 40.9 14 31.9 14
Pima 27.7 6 38 13 48.4 9 38.0 10
Pinal 29.4 4 43.1 5 46.9 12 39.8 6
Santa Cruz 25.4 9 50.9 1 60.5 2 45.6 1
Yavapai 26.8 7 49 2 49.6 7 41.8 4
Yuma 22.5 11 32.1 15 61 1 38.5 8
Source: Arizona Youth Survey: State Report, 2004. Arizona Criminal Justice Commission. Available on-line:
http:// www. acjc. state. az. us/ publications/ publications. asp? ServId= 1000. [ cited September 13, 2005].
Table 3U: Percentage of 8th, 10th, and 12th Grade Students Who Reported Binge Drinking in Past
Two Weeks, Arizona, 2004.
8th Grade 10th Grade 12th Grade
County % Rank % Rank % Rank Avg. Rank
State 16 25.1 32.5 22.7
Apache 14.8 12 24.8 10 33.3 7 24.3 9
Cochise 20.7 4 25.8 7 34.4 4 27 3
Coconino 19.8 5 26.4 6 32.9 8 26.4 5
Gila 23.9 1 25.4 8 41.4 3 30.2 2
Graham 21 3 24.5 11 33.6 6 26.4 5
Greenlee 22.7 2 23 12 33.3 7 26.3 6
LaPaz 18.4 7 29.2 3 21.4 14 23 11
Maricopa 15.2 11 24.5 11 32.4 9 24.0 8
Mohave 17.3 9 27.9 4 33.7 5 26.3 6
Navajo 17.7 8 25.2 9 26.6 13 23.2 10
Pima 16.6 10 22.5 13 29.4 11 22.8 12
Pinal 18.6 6 27.1 5 27.9 12 24.5 7
Santa Cruz 17.7 8 34.6 1 43.6 1 32 1
Yavapai 13 14 29.7 2 30.8 10 24.5 7
Yuma 14.1 13 22.1 14 43.2 2 26.5 4
Source: Arizona Youth Survey: State Report, 2004. Arizona Criminal Justice Commission. Available on-line:
http:// www. acjc. state. az. us/ publications/ publications. asp? ServId= 1000. [ cited September 13, 2005].
36
Table 3V: Percentage of 8th, 10th, and 12th Grade Students Who Used Cigarettes During the Past
30 Days, Arizona, 2004.
8th Grade 10th Grade 12th Grade
County % Rank % Rank % Rank Avg. Rank
State 10.7 17.7 24.4 17.6
Apache 20.4 2 34.6 1 42.6 1 32.5 1
Cochise 14.9 7 14.6 12 23.3 10 17.6 11
Coconino 23.5 1 23.3 5 28.3 8 25.0 4
Gila 18.4 3 16.4 10 23.8 10 19.5 8
Graham 11.9 9 16.7 9 25.4 9 18.0 10
Greenlee 15.5 6 34.2 2 37.3 3 29 2
LaPaz 9.9 12 15.6 11 16.5 14 14 14
Maricopa 9.3 13 16.4 10 23 12 16.2 13
Mohave 10.4 11 18.1 8 29.7 5 19.4 9
Navajo 17.7 4 23.8 4 29.6 6 23.7 5
Pima 9.9 12 13.8 13 18.3 13 14 14
Pinal 15.6 5 20.8 7 23.5 11 20 7
Santa Cruz 14.1 8 30.6 3 35.5 4 26.7 3
Yavapai 9.3 13 23 6 38.5 2 23.6 6
Yuma 10.9 10 12 14 29.4 7 17.4 12
Source: Arizona Youth Survey: State Report, 2004. Arizona Criminal Justice Commission. Available on-line:
http:// www. acjc. state. az. us/ publications/ publications. asp? ServId= 1000. [ cited September 13, 2005].
Table 3W: Percentage of 8th, 10th, and 12th Grade Students Who Used Any Drug During the Past
30 Days, Arizona, 2004.
8th Grade 10th Grade 12th Grade
County % Rank % Rank % Rank Avg. Rank
State 17.9 23.6 25.1 22.2
Apache 24.3 3 34.1 1 36.4 1 31.6 1
Cochise 22.7 7 22.2 11 17.9 14 20.9 12
Coconino 27.1 2 28.1 3 28.2 5 27.8 3
Gila 23.5 5 22.1 12 25.6 7 23.7 7
Graham 27.4 1 27.8 5 29.6 2 28.3 2
Greenlee 18.5 10 26.8 6 25 9 23.4 9
LaPaz 18.8 9 22.3 10 10.7 15 17.3 15
Maricopa 16.1 13 22.2 11 25.2 8 21.2 11
Mohave 17.9 11 24.2 9 28.5 4 23.5 8
Navajo 23 6 28 4 29.4 3 26.8 4
Pima 21.2 8 24.4 8 23.7 12 23.1 10
Pinal 23.9 4 26.4 7 27 6 25.8 5
Santa Cruz 17.4 12 20.5 13 20.8 13 19.6 13
Yavapai 15.6 14 31.1 2 24.8 10 23.8 6
Yuma 14.3 15 17.7 14 23.8 11 18.6 14
Source: Arizona Youth Survey: State Report, 2004. Arizona Criminal Justice Commission. Available on-line:
http:// www. acjc. state. az. us/ publications/ publications. asp? ServId= 1000. [ cited September 13, 2005].
37
There is no single county that has consistently high consumption rates across all
indicators. However, a pattern can be discerned where particular counties appear more
frequently among those counties with the highest problem rates. Table 3X shows how
many times a county had one of the five highest percentages of use for each grade across
the four indicators. The same analysis was done for the alcohol indicators by themselves
and is shown in Table 3Y. An analysis of past 30- day day drug use by grade is provided
in Table 3Z. A single score was obtained by adding the number of times each county was
ranked in the top five in each grade category
Coconino, Apache, Gila, Mohave, and Santa Cruz counties had the highest sums
indicating that, across the three grade levels, they were most frequently ranked among the
five worst counties for the four problem indicators studied. When looking at just 30- day
alcohol use and past two- week binge alcohol consumption, Apache county drops out and
Cochise, Gila, Mohave, and Santa Cruz counties become the most problematic.
Finding: In looking at the combined effects of 30- day day alcohol use, past two-week
binge drinking, 30- day day cigarette use, and 30- day day illicit drug use,
Coconino, Apache, Gila, Mohave, and Santa Cruz counties are the most severely
affected.
Finding: Cochise, Gila, Mohave, and Santa Cruz counties have the most problems
with 30- day alcohol use and past two- week binge drinking.
Finding: Apache, Graham, Coconino, and Navajo counties have the most problems
with illicit drug use among 8th, 10th, and 12th grade students.
Table 3X: Number of Times a County Had One of the Five
Highest Percentages of Use for 30- day Day Alcohol, 30- day Day
Cigarette, 30- day Day Any Drug, and 30- day Day Binge
Drinking, by Grade.
8th 10th 12th Sum all
grades
Coconino 3 3 1 7
Apache 2 2 2 6
Gila 4 0 2 6
Mohave 0 2 4 6
Santa Cruz 0 3 3 6
Pinal 3 2 0 5
Cochise 2 0 2 4
Graham 2 1 1 4
Greenlee 2 1 1 4
Navajo 1 2 1 4
Yavapai 0 3 1 4
LaPaz 1 1 0 2
Yuma 0 0 2 2
Maricopa 0 0 0 0
Pima 0 0 0 0
38
Table 3Y: Number of Times a County Had One of the Five
Highest Percentages of Use for 30- day Day Alcohol and 30- day
Day Binge Drinking, by Grade.
8th 10th 12th Sum all
grades
Cochise 2 0 2 4
Gila 2 0 2 4
Mohave 0 2 2 4
Santa Cruz 0 2 2 4
Pinal 1 2 0 3
Coconino 1 1 0 2
Greenlee 2 0 0 2
LaPaz 1 1 0 2
Yavapai 0 2 0 2
Yuma 0 0 2 2
Graham 1 0 0 1
Apache 0 0 0 0
Maricopa 0 0 0 0
Navajo 0 0 0 0
Pima 0 0 0 0
Table 3Z: Number of Times a County Had One of the Five
Highest Percentages of Use for 30- day Day Drug Use, by Grade.
8th 10th 12th Sum all
grades
Coconino 1 1 1 3
Graham 1 1 1 3
Apache 1 1 1 3
Navajo 0 1 1 2
Gila 1 0 0 1
Mohave 0 0 1 1
Pinal 1 0 0 1
Yavapai 0 1 0 1
Santa Cruz 0 0 0 0
Cochise 0 0 0 0
Greenlee 0 0 0 0
LaPaz 0 0 0 0
Yuma 0 0 0 0
Maricopa 0 0 0 0
Pima 0 0 0 0
The Arizona Youth Survey can also provide some sub- county level data for select areas
and indicators. Figures 3B through 3D show data for the percent of students reporting
binge drinking in the last two weeks, the percent of youth reporting alcohol use in the last
30 days, and the percent of students reporting illicit drug use in the past 30 days by
39
community health analysis area. The community health analysis area is a geographic
segment used by the Department of Health Services for public health surveillance. The
community health analysis area is large enough to provide a population size meaningful
for statistical analysis but small enough to capture geographic variations and maintain a
sense of community or neighborhood. Appendix C contains individual profiles of all 126
community health analysis areas. The profiles are composed of 14 demographic
elements, 10 risk factor elements, and 8 consumption indicators. Not all data contained
in the community health analysis profiles were used for this report but they should
provide a wealth of information for further program planning at the health analysis area
level. Maps that visualize the data at the community health analysis area for each of the
10 risk factor elements and 8 consumption indicators of Arizona are also available by
contacting the Governor’s Division for Substance Abuse Policy.
The maps in Figures 3B through 3D report data on the percent of 8th, 10th, and 12th grade
students who used alcohol in the past 30 days; the percent of 8th, 10th, and 12th grade
students who reported binge drinking in the past two weeks; and the percent of 8th, 10th,
and 12th grade students who used any drug in the past 30 days. Data is categorized by
standard deviation; the higher the standard deviation, the greater the problem in a
community health analysis area relative to other areas.
For both the binge drinking and the last 30- day alcohol use indicators, the high problem
counties of Cochise, Gila, and Mohave can be further segmented into community health
analysis areas with higher than average rates. In Cochise county, the Douglas health
analysis area has a high percent of binge drinking and past 30- day alcohol use. The
Benson health analysis area shows a high percent of binge drinking. In Gila county, the
Globe/ Hayden health analysis area has a higher percentage of both binge drinking and
past 30- day alcohol use than surrounding health analysis areas. In Mohave county, the
Kingman and Lake Havasu City health analysis areas have higher than average
percentages of past 30- day alcohol use.
Interestingly, Coconino county did not rank as problematic on the alcohol indicators but
the health analysis area data finds that the Williams health analysis area within Coconino
county has a high percentage of 8th, 10th, and 12th grade students who report binge
drinking in the past two weeks.
For past 30- day drug use, Coconino county can be further segmented into health analysis
areas with higher than average drug use including Page/ Fredonia, Flagstaff West,
Flagstaff East, and Flagstaff Rural. Navajo county contains the Winslow and Holbrook
health analysis areas, both with higher than average drug use. Cochise county does not
appear in the list of most problematic counties for drug use but its Benson health analysis
area is higher than average for youth drug use. The community health analysis areas that
comprise the portion of the Navajo reservation within Arizona, the Hopi reservation, and
the Havasupai reservation have higher than average past 30- day drug use.
40
Figure 3B
41
Figure 3C
42
Figure 3D
43
Finding: Within Cochise and Gila counties the Douglas and Globe/ Hayden health
analysis areas have higher than average percentages of youth that report binge
drinking and past 30- day alcohol use. Within Cochise and Coconino counties, the
Benson and Williams health analysis areas report higher than average youth binge
drinking. Within Mohave county, the Kingman and Lake Havasu City health
analysis areas have higher than average percentages of past 30- day youth alcohol
use.
Finding: For past month drug use among 8th through 12th grade students, the health
analysis areas of Page/ Fredonia, Flagstaff West, Flagstaff East, Flagstaff Rural,
Winslon, Holbrook, Benson, Navajo Nation, Hopi Nation and Havasupai have
higher than average percentages of drug use.
Given the amount of information contained in the Arizona Youth Survey and other
sources, another analysis was conducted for community health analysis areas using
composite measures. Composite measures provide a single score obtained by adding the
z- scores of the constituent, single measures. A z- score is a statistic derived from the
standard deviation. A z- score allows for comparisons to be made across a range of
different measures. A high score on the composite measure was interpreted to reflect a
larger problem.
An alcohol and drug score were obtained and used for informing state problem areas.
The constituent measures for each score is provided below.
Alcohol score:
1. Percent of youth in the 8th, 10th, and 12th grades who used alcohol in last 30 days
2. Percent of youth in the 8th, 10th, and 12th grades who engaged in binge drinking in
last 2 weeks
3. Average age of first use for alcohol among 8th, 10th, and 12th, grade students
Drug score:
1. Percent of youth in the 8th, 10th, and 12th grades who used any drug in last 30 days
2. Percent of 8th, 10th, and 12th grade students who perceive drug use as not risky
3. Average age of first use for marijuana among 8th, 10th, and 12th grade students
4. Average age of first use for methamphetamine among 8th, 10th, and 12th grade
students
5. Percent of 8th, 10th, and 12th grade students with attitudes favorable to drug use
6. Rate of school suspensions related to drug use per 1,000 children, 14- 18 years old
Table 3AA presents those community health analysis areas with scores of 4 and higher on
the alcohol and drug composite measure.
44
Table 3AA: Community Health Analysis Areas with High Scores on Composite
Alcohol and Drug Measures.
Community health analysis area Score
Alcohol Score
Globe/ Hayden 6
Douglas 5
Flagstaff West 4
Kingman 4
Lake Havasu City 4
Drug Score
Flagstaff West 8
Cordes Junction 6
Flagstaff Rural 5
Lake Havasu City 5
Marana 5
Yavapai Co. S/ Bagdad 5
Tohono O’Odam Nation 4
St. Johns 4
It should be noted that in some cases health analysis areas in counties that are high on
single consumption measures do not appear in the most problematic health analysis areas
for the composite measures. Santa Cruz county is problematic for youth alcohol use but
its constituent health analysis areas do not appear as problematic in the composite
measures. Similarly Graham and Pinal counties are problematic on the single measure of
past 30- day youth illicit drug use but their constituent health analysis areas do not appear
in the list of problematic health analysis areas for the composite measure of drug use.
This anomaly arises when the additional measures that comprise the composite score
have low or negative values signifying lower levels of a particular problem indicator.
When these lower or negative values are added to the high single measure values, the
resulting score is lowered. Santa Cruz may be problematic in underage past month
drinking and binge drinking but it has a high age of onset, a beneficial attribute with a
negative standard deviation that lowers the total score.
Finding: The most problematic health analysis areas based on the composite alcohol
and drug scores are Globe/ Hayden, Douglas, Flagstaff West, Kingman, Lake
Havasu City, Cordes Junction, Flagstaff Rural, Marana, Yavapai County S/ Bagdad,
Tohono’Odam Nation, and St. Johns.
Tables 3BB through 3GG display data on those consequence indicators for which sub-state
data exists: alcohol- related car crash injuries and fatalities; hospital discharges and
emergency department visits; drug related arrests; disciplinary actions related to alcohol,
tobacco or drugs in kindergarten through 12th grades; and alcohol and drug juvenile
offenses referred to the court.
45
Table 3BB: Alcohol – Related Motor Vehicle Crashes and Rates per 10,000 People in
Specified County, Arizona, 2003.
Total crashes Persons killed Persons injured
Crashes Rate Persons Rate Persons Rate
Apache 110 15.5 14 1.9 141 19.9
Cochise 106 8.4 10 0.7 78 6.1
Coconino 241 18.6 8 0.6 186 14.4
Gila 69 12.8 2 — 72 13.4
Graham 26 7.5 1 — 15 4.3
Greenlee 2 — 0 — 2 —
La Paz 39 18.8 5 — 38 18.3
Maricopa 5,016 14.7 136 .4 3,890 11.4
Mohave 258 15.1 22 1.2 206 12.0
Navajo 135 13.0 20 1.9 127 12.2
Pima 1076 11.8 28 .3 881 9.6
Pinal 265 13.1 23 1.1 241 11.9
Santa Cruz 32 7.8 2 17 4.1
Yavapai 258 13.8 19 1.0 222 11.8
Yuma 198 11.3 9 .5 135 7.7
Source: Arizona Department of Transportation, personal communication.
Table 3CC: Hospital Discharges and Rates per 10,000 People in Specified County, Arizona,
2003.
Alcohol abuse Drug dependence/ abuse Fetus/
noxious
influences
Discharges Rate Discharges Rate Discharges
Apache 181 25.6 61 8.6 1
Cochise 328 25.9 193 15.2 1
Coconino 376 29.1 263 20.3 4
Gila 271 50.6 149 27.8 3
Graham 85 24.6 55 15.9 0
Greenlee 21 24.4 9 10.4 1
La Paz 99 47.7 56 27.0 0
Maricopa 10,419 30.6 10,869 31.9 362
Mohave 610 35.7 293 17.1 1
Navajo 515 49.6 235 22.6 7
Pima 4,025 44.1 5,033 55.2 95
Pinal 998 49.5 793 39.3 28
Santa Cruz 95 23.2 67 16.3 1
Yavapai 606 32.4 427 22.8 4
Yuma 596 34.0 297 16.9 5
Unknown 282 — 302 — 4
Source: Hospital Discharge Database, 2003 data. Arizona Department of Health Services. Available
online: http:// www. azdhs. gov/ plan/ index. htm . [ cited September 13, 2005].
46
Table 3DD: Emergency Department Visits with Mentions of Drug or Alcohol Disorders and
Rates Per 10,000 people in Specified County for Select Disorders, Arizona, July to
December 2003.
Alcohol
psychoses
Drug
psychoses
Drug
dependence
Nondependent
abuse of drugs
Alcohol
dependence
Visits Rate Visits Rate
Apache 28 11 13 205 29 99 14
Cochise 16 23 40 851 67.4 116 9.1
Coconino 59 29 37 490 38 882 68.4
Gila 11 36 23 189 35.2 35 6.5
Graham 3 11 20 139 40.3 10 2.8
Greenlee 0 0 1 12 13.9 2 —
La Paz 0 2 3 59 28.4 1 —
Maricopa 310 446 568 15,691 46.1 1,001 2.9
Mohave 31 43 113 496 29.0 126 7.3
Navajo 25 26 19 583 56.1 224 21.5
Pima 152 333 553 8,792 96.5 864 9.4
Pinal 10 36 46 693 34.3 68 3.3
Santa Cruz 5 10 18 121 29.5 12 2.9
Yavapai 45 42 60 667 35.6 148 7.9
Yuma 21 17 31 817 46.6 76 4.3
Unknown 14 15 26 493 86
Source: Hospital Discharge Database, 2003 data. Arizona Department of Health Services. Available
online: http:// www. azdhs. gov/ plan/ index. htm . [ cited September 13, 2005].
Table 3EE: Arrests and Rates Per 10,000 people in Specified County, Arizona, 2003.
DUI Drug possession Drug sale/
manufacturing
Arrests Rate Arrests Rate Arrests Rate
Apache 66 9 115 16.2 61 8.6
Cochise 785 62 689 54.6 143 11.3
Coconino 1,152 89.3 863 66.9 111 8.6
Gila1 249 46.4 131 24.4 17 3.1
Graham 97 28 140 40.5 2 —
Greenlee2 73 84.9 51 59.3 12 13.9
La Paz 224 108 169 81.5 25 12.0
Maricopa3 27,537 81.0 12,423 36.5 3,409 10.
Mohave 634 37.1 1,034 60.5 150 8.7
Navajo 544 52.4 321 30.9 48 4.6
Pima4 5,126 56.2 9,202 101.0 1,041 11.4
Pinal5 1,075 53.3 726 36.0 136 6.7
Santa Cruz 266 65.0 126 30.8 0 —
Yavapai6 1,375 73.5 864 46.2 302 16.1
Yuma 333 19.0 1,012 57.8 63 3.5
Source: Crime in Arizona 2003, 2004. Arizona Department of Public Safety. Available on- line:
http:// www. azdps. gov/ crimereport/ default. asp. [ cited September 13, 2005].
1 Hayden and Miami police departments did not provide complete data
2 Clifton police department did not provide complete data
3 Avondale and Surprise police departments did not provide complete data
4 Sahuarita police department did not provide complete data
5 Eloy, Florence, and Superior police departments did not provide complete data
6 Chino Valley police department did not provide complete data
47
Table 3FF: Alcohol and Drug Juvenile Offenses, July 1, 2003 to June 30, 2004.
Alcohol Related Drug Related Totals
Outcome Outcome
Juveniles Offenses Diverted Court
involved
Open Juveniles Offenses Diverted Court
Involved
Open Undup. # of
Juveniles
Alcohol &
Drug Offs.
Offs. per
Juvenile
Apache 56 79 31 45 3 39 54 0 39 15 87 133 1.53
Cochise 189 260 167 73 20 460 500 191 269 52 652 1,043 1.60
Coconino 500 689 337 285 67 302 354 74 228 52 652 1,043 1.60
Gila 131 147 72 34 41 150 231 24 126 81 240 378 1.58
Graham 86 109 27 78 4 107 115 24 83 8 135 224 1.66
Greenlee 24 28 5 14 9 19 19 0 19 0 32 47 1.47
La Paz 26 28 12 12 4 34 38 2 32 4 48 66 1.38
Maricopa 3,209 4,393 802 2,468 1,123 3,463 4,934 886 2,577 1,471 5,764 9,327 1.62
Mohave 196 220 18 190 12 401 465 84 317 64 461 685 1.49
Navajo 302 405 58 196 151 279 406 75 204 127 468 811 1.73
Pima 1,110 1,366 761 404 201 2,664 3,245 1,168 1,496 581 2,740 4,611 1.68
Pinal 166 211 55 100 56 417 569 144 273 152 470 780 1.66
Santa
Cruz
89 108 30 65 13 184 193 35 149 9 167 301 1.80
Yavapai 339 405 200 164 41 458 535 209 249 77 583 940 1.61
Yuma 225 261 132 110 19 492 524 116 376 32 478 785 1.64
Totals 6,648 8,709 2,707 4,238 1,764 9,469 12,182 3,032 6,437 2,713 12,750 20,891
Source: Juvenile Justice Services Division, Administrative Office of the Courts, personal communication.
48
Table 3GG: Numbers and Rates of Disciplinary Actions ( Expulsions, Suspensions, and Tranfers) per
1,000 Students Enrolled in Specified County, Arizona, 2004, Department of Education
Possession and use
of alcohol
Possession, use,
and distribution of
illegal drugs
Possession and use
of tobacco
Total
Number Rate Number Rate Number Rate Number Rate
Apache 23 1.51 117 7.68 58 3.8 198 13.0
Cochise 8 .34 66 2.84 1 -- 75 3.22
Coconino 46 2.09 72 3.27 5 .23 123 5.59
Gila 2 -- 15 1.79 0 -- 17 2.03
Graham 0 -- 21 2.51 0 -- 21 2.51
Greenlee 0 -- 1 -- 0 -- 1 --
Maricopa 284 .47 1464 2.45 52 .09 1800 3.01
Mohave 13 .54 98 4.05 10 .41 121 5.0
Navajo 91 3.85 164 6.93 8 .34 263 11.11
Pima 154 1.09 735 5.22 44 .31 399 2.83
Pinal 14 .47 115 3.83 7 .23 136 4.53
Santa Cruz 2 -- 17 1.71 3 -- 22 2.21
Yavapai 20 .66 78 2.58 28 .93 126 4.17
Yuma 23 .67 72 2.10 2 -- 97 2.83
La Paz 0 -- 2 -- 0 -- 2 --
Source: Arizona Department of Education, personal communication.
-- Numbers too low to compute rates
Table 3FF presents data on the number of drug and alcohol related juvenile offenses
referred to Arizona’s court system and the disposition of these referrals. A juvenile can
be diverted from formal court involvement ( diversion) or placed under official court
oversight and ordered to a variety of consequences or programs ( court involvement).
Open cases are those that are still awaiting court action.
As with the youth consumption data, there is no one particular county that is consistently
implicated as being the most problematic. However there does emerge a pattern of
counties that present more frequently with high rates of problem behaviors. Table 3HH
lists those counties that have the five worst rates for the indicators presented in Tables
3BB through 3GG.
Finding: La Paz and Pima counties had one of the five worst rates for six of the nine
problem indicators. Coconino county had one of the five worst rates for five of the
nine problem indicators. Maricopa and Navajo counties had one of the five worst
rates for four of the nine problem indicators.
49
Table 3HH: Counties with the Five Highest Rates for Select Problem Indicators.
Crashes Alcohol abuse
discharges
Drug
dependence
discharges
Nondependent
abuse of drugs
ED
Alcohol
dependence
ED
DUI arrests Drug
possession
Drug sale/
manufacturing
arrest
Disciplinary
actions
La Paz Gila Pima Pima Coconino La Paz Pima Yavapai Apache
Coconino Navajo Pinal Cochise Navajo Coconino La Paz Greenlee Navajo
Apache Pinal Maricopa Navajo Apache Greenlee Coconino La Paz Coconino
Mohave La Paz Gila Yuma Pima Maricopa Mohave Pima Mohave
Maricopa Pima La Paz Maricopa Cochise Yavapai Greenlee Cochise Pinal
50
3.6 Arizona, United States, and Healthy People 2010 Comparisons
One way to gauge the severity or magnitude of Arizona’s substance abuse problems is to
compare Arizona’s data with the data of other jurisdictions. The table in Appendix D
compares percentages or rates between Arizona and the U. S. on problem indicators for
which national data exist in a readily available form. Also included in the table are
targets for a variety of substance abuse indicators from the Healthy People 2010
initiative, a program of the Department of Health and Human Services. According to its
website, “ Healthy People 2010 is a comprehensive set of disease prevention and health
promotion objectives for the Nation to achieve over the first decade of the new century.
Created by scientists both inside and outside of Government, it identifies a wide range of
public health priorities and specific, measurable objectives.” The address for the
Healthy People 2010 website is http:// www. healthypeople. gov/.
The Healthy People 2010 targets are included as statements of acceptable levels of
substance abuse related consumption patterns and consequences. Targets were set
through consultation with the work groups that developed Healthy People 2010. Work
groups used a variety of methods to set targets including retention of year 2000 targets,
statistical procedures using current rates to project targets, and expert judgment.
The epidemiology work group did not use the comparisons in their deliberations but they
are provided here as another way to understand substance use consequence and
consumption data.
51
4. Risk and Protection
Another way to assess substance abuse prevention need is to measure the prevalence of
characteristics that have been shown to predict substance use. A high prevalence of these
risk factors suggests a greater potential for developing substance abuse problems and
hence a greater need for prevention interventions.
Two studies measure Arizona’s counties predilection for substance abuse problems: the
Arizona Youth Survey and the Arizona Social Indicator Study conducted by the Mel and
Enid Zuckerman Arizona College of Public Health at the University of Arizona.
In addition to measuring substance abuse consumption patterns among Arizona’s high
school aged youth, the Arizona Youth Survey also measures a variety of risk and
protective factors at an individual, family, school, and community level. Data on these
factors are obtained by questioning youth in a written survey. These risk and protective
factors are listed in Appendix E. The Arizona Social Indicator Study collects and
analyzes community level data from archival sources. The community level indicators
are listed in Appendix F. Arizona Social Indicator Study data used in this analysis are
data for the year 2001.
Upon initial analysis it was discovered that the level of risk for any one county varies
across the range of indicators in both the Arizona Youth Survey and the Social Indicator
Study. Given this complexity, relative risk for the Social Indicators Study was gauged by
assessing what percent of a county’s indicators exceeded the mean of all the state’s
counties for that particular indicator. The results of this analysis are presented in Table
4A. Counties are ranked by the percentage of indicators that are worse than the mean of
the counties.
Studies similar to the Arizona Youth Survey are conducted in other states. Combining the
results of these studies provides a multi- state norm to which other states can be
compared. Table 4B shows how many of a county’s risk indicators measured by the
Arizona Youth Survey exceed the multi- state norm in each of the four risk domains and
across all domains. Counties are ranked by the number of risk indicators that are worse
than the multi- state norm.
52
Table 4A: Number and Percentage of a County’s Risk Indicators Exceeding the Mean
of Arizona’s Counties, 2000 and 2001 Data.
County Number of indicators Number of times the
county rate exceeds the
mean of the counties
Percentage of times the
county rate exceeds the
mean of the counties
Gila 30 27 90
Coconino 30 16 53
Mohave 30 16 53
Yavapai 30 15 50
Cochise 30 14 47
Santa Cruz 30 14 47
Navajo 30 13 43
Pima 30 13 43
Pinal 30 13 43
La Paz 30 12 40
Graham 30 11 37
Apache 30 10 33
Greenlee 29 8 28
Yuma 30 7 23
Maricopa 25 5 20
Source: Arizona Social Indicator Study: Risk Monitoring Report for 2000 & 2001, 2004. Mel and Enid
Zuckerman Arizona College of Public Health, University of Arizona.
Table 4B: Number of Risk Indicators Worse than the Multi- State Norm, Arizona,
2004.
Total
Community
Total
Family
Total
School
Total Peer/
Individual
Total Above
State Norm
Yavapai 15 12 4 25 56
Mohave 13 12 6 21 52
Pinal 14 8 3 23 48
Gila 15 8 4 19 46
Greenlee 10 9 5 22 46
Cochise 14 8 4 17 43
Graham 15 9 4 15 43
Coconino 11 6 3 21 41
Pima 12 7 4 17 40
Apache 8 6 3 22 39
Navajo 11 5 3 20 39
La Paz 12 9 3 14 38
Santa Cruz 10 8 3 17 38
Yuma 9 8 4 17 38
Maricopa 7 4 4 16 31
Source: Arizona Youth Survey: State Report, 2004. Arizona Criminal Justice Commission. Available on-line:
http:// www. acjc. state. az. us/ publications/ publications. asp? ServId= 1000. [ cited September 13, 2005].
53
Three counties, Yavapai, Mohave, and Gila, have the most indicators that exceed the
mean of the counties in the Social Indicator Study or the multi- state norm in the Arizona
Youth Survey. Maricopa and Yuma counties have the fewest indicators that exceed the
state or multi- state norm. Other counties’ rankings vary in between these two extremes.
Finding: Yavapai, Mohave, and Gila counties are at the highest risk for substance
abuse problems as indicated in both the Arizona Youth Survey and the Arizona
Social Indicator Study. Maricopa and Yuma counties have the lowest level of risk in
both surveys.
54
5. Assessment of Community Assets and Resources and Identification of Gaps in
Services and Capacity
To get a better sense of the gaps that might exist between the problems identified and the
prevention resources that the state allocates to those problems, an analysis was conducted
of current state funding as reported in the Arizona Drug and Gang Prevention and
Treatment Program Inventory and the funding’s relationship to geographic and age
defined problems. Such an analysis can provide another perspective on where resources
should be allocated to address the state’s most pressing substance abuse related problems.
The Arizona Drug and Gang Prevention and Treatment Program Inventory is an annual
assessment of publicly funded substance abuse prevention and treatment services in
Arizona. The inventory captures state and federal funds that are administered by state
agencies. Federal funds that are contracted or granted directly to agencies and funds
from private institutions such as private foundations or United Ways are not included in
the Program Inventory. Among other things, the Program Inventory reports on the
amount of funding going to prevention services, the number and age of people being
served, and the geographic location of services. Table 5A presents these data and ranks
counties by per capita spending on prevention services. Per capita prevention spending
will be used as the measure of resources going to communities to address substance abuse
prevention needs.
It should be noted that funds reported by agencies are not always assigned to the
geographical location where services are provided but rather to the geographic location of
the administrative office. This may affect the accuracy of county figures if the
administrative office is located outside of the county in which services are actually
provided.
55
Table 5A: Total Prevention Spending and Per Capita Prevention Spending by County,
Arizona, Arizona Drug and Gang Prevention and Treatment Program Inventory,
2003. 1
COUNTY SUM FUNDS
2003 Population
Estimate Per Capita Funds
La Paz $ 247,310 20,715 $ 11.94
Cochise $ 1,027,997 126,160 $ 8.15
Pinal $ 1,292,995 201,565 $ 6.41
Santa Cruz $ 257,035 40,890 $ 6.29
Pima $ 5,204,319 910,950 $ 5.71
Yuma $ 960,144 175,045 $ 5.49
Yavapai $ 918,189 186,885 $ 4.91
Maricopa $ 16,557,457 3,396,875 $ 4.87
Navajo $ 338,788 103,790 $ 3.26
Graham $ 99,795 34,490 $ 2.89
Gila $ 154,660 53,555 $ 2.88
Coconino $ 317,575 128,925 $ 2.46
Mohave $ 385,400 170,805 $ 2.26
Apache $ 151,595 70,625 $ 2.15
Greenlee $ 15,874 8,595 $ 1.85
Total Prevention $ 27,929,133 5,629,870 $ 4.96
Source: 2003 Arizona Drug and Gang Prevention and Treatment Program Inventory, 2004, personal
communication. Arizona Drug and Gang Prevention Resource Center, Arizona State University. The
analysis does not include Tobacco Education and Prevention Program funds totaling $ 22,345,294. These
funds were not disaggregated by county.
There are several congruencies and discrepancies when counties with high rates of
particular problems are compared to county per capita spending on substance abuse
prevention. La Paz, Cochise, and Santa Cruz counties have some of the highest per
capita prevention spending. La Paz county also has high rates of alcohol related crashes;
crash injuries; hospital discharges for alcohol abuse and drug dependence; and arrests for
drug possession, driving under the influence, and drug sales and manufacturing. Cochise
county has high rates of underage drinking and underage binge drinking, emergency
department visits for nondependent abuse of drugs and alcohol dependence, and arrests
for drug sales and manufacturing. Santa Cruz county has high rates of underage drinking
and underage binge drinking.
On the other hand, Navajo, Mohave, Gila, Apache, Coconino, and Greenlee counties
have lower per capita spending on prevention but high rates of consequences in one or
more of the consequence indicators presented in Table 3HH.
Finding: A gap exists between problems and prevention spending for Navajo,
Mohave, Gila, Apache, Coconino, and Greenlee counties.
56
Another comparison can be made using data on the age groups affected by substance
abuse and Program Inventory data. As seen in Figure 3A, 18 to 25 years olds experience
the highest rates in several indicator areas suggesting that primary prevention efforts
should be targeted to age groups younger than 18. Table 5B shows the distribution of
prevention funding in Arizona by age group. The majority of prevention funding, 55
percent, is serving youth under the age of 18.
Finding: Funding for substance abuse prevention is evenly distributed between
youth and adult audiences.
Several problems with using per capita prevention spending to assess prevention
resources should be noted. Per capita spending does not indicate the effectiveness of the
services that are being delivered. It is possible that smaller amounts of funds could be
spent on more effective interventions thereby creating a larger prevention effect than
larger amounts of money that are spent on less effective services. It is also not known
from available data if the prevention funds are addressing those consequence or
consumption indicators identified in this profile. So, while large amounts of prevention
funding may be going to a particular geographic area, those funds may not be affecting
problem areas of concern to the State Incentive Grant. Finally, prevention funding may
change dramatically from year to year as grants and contracts expire or new ones are
awarded. This makes it difficult to reliably measure gaps between funding and services.
57
Table 5B: Prevention Participant Age Groups by County, Arizona, 2003.
COUNTY
0- 4
( Pre- K)
5- 11
( K- 5)
12- 14 ( 6-
8
grades)
15- 17
( High
School)
18- 20
Years
21- 24
Years
25- 44
Years
45- 64
Years
65+
Years
Unknown
Adults
Unknown
Youths
Grand
Total
Cochise 110 2,512 2,991 5,870 301 810 606 284 176 1,434 1931 17,025
Coconino 15 61 8 57 80 0 221
Gila 223 1025 2044 10 230 26 50 3,608
Graham 122 122
La Paz 14 184 260 126 4 1 20 3 612
Maricopa 2,405 26,896 13,949 3,521 532 1,387 7,349 2,506 3,416 35,238 6,095 103,294
Mohave 3 15 32 13 758 821
Navajo 30 242 86 358 29 85 85 915
Pima 568 1,523 2,898 1,932 1,757 1,591 3,858 2,307 1,608 3,522 465 22,029
Pinal 321 3,230 2,628 2,506 147 205 2,014 773 1,539 0 0 13,363
Santa Cruz 8 25 22 2 23 5 85
Yavapai 0 105 2 41 197 289 845 71 0 0 0 1,550
Yuma 80 666 1,598 1,287 90 29 641 336 312 597 3,257 8,893
Grand Total 3,536 35,606 25,474 17,748 3,070 4,335 15,445 6,528 7,077 41,078 12,641 172,538
95,005, including unknown youths ( 55%) 77,533, including unknown adults ( 45%)
Source: 2003 Arizona Drug and Gang Prevention and Treatment Program Inventory, 2004, personal communication. Arizona Drug and Gang Prevention
Resource Center, Arizona State University.
58
6. Identification of Problem Areas
To assist the work group with the difficult task of selecting problem areas from among
the myriad problem indicators, a worksheet was developed that listed each problem
indicator and asked work group members to rate each indicator according to five criteria:
magnitude, severity, amenability to change, capacity to address the problem, and
sensitivity of the indicator to record changes brought about by State Incentive Grant
interventions. The criteria were presented as a series of statements. Work group
members were asked to rate each indicator on a scale of 1 to 3 with three indicating the
highest level of agreement with the statement. If they felt they did not have enough
information on the indicator for a specific criterion, work group members could mark the
indicator with a question mark. Three different versions of the worksheets that listed the
indicators in different orders were sent to work group members. The worksheet is
included in Appendix G.
The worksheet was to be used to start discussions about what problems should be
addressed with State Incentive Grant funds; it was not to be used to make final decisions
about priorities. It should also be noted that with the exception of the magnitude
criterion, there were no data presented that could inform the other criteria. For this
reason, all ratings, with the exception of ratings in relationship to magnitude, are based
on professional knowledge and experience.
6.1 Problematic drinking
The worksheet exercise suggested that several indicators were important to the group:
1. Arrests for driving under the influence
2. Past month underage drinking
3. Past month underage binge drinking
4. Past month binge drinking for those 12 and older
5. Past year clinical dependence or abuse of illicit drugs and alcohol
6. Alcohol related crash injuries
Based on the worksheet results and subsequent discussions, the work group developed a
problem area called “ problematic drinking.” This problem area included both underage
individuals and adults and was defined according to the following indicators:
1. Past month drinking, 8th through 12th grades
2. Past two- week binge drinking, 8th through 12th grades
3. Past month binge drinking, 18 years old and older
4. Alcohol related crash injuries
Originally, arrests for driving under the influence of alcohol was another indicator that
was part of the cluster; however, due to its susceptibility to enforcement and reporting
practices, it was dropped.
6.2 Youth illicit drug use
In subsequent discussion in the epidemiology work group, another problem area was
proposed, drug use by youth and adults. The proposal was made to address what was
59
considered an important problem in Arizona and to provide another option for
intervention and change efforts. As seen in Table 3N, the estimated rates of 12 to 17 year
olds who have used illicit drugs in the past 30 days is higher than the estimated rates of
12 to 17 year olds who report binge drinking in the past 30 days. If binge drinking was
included as a problem indicator for State Incentive Grant funds, then, given the almost
equal magnitude of the problem and the fact that illicit drug use like binge drinking can
lead to impairment, it could be argued that illicit drug use among youth could also be a
problem area. The same cannot be said for adult drug use. According to the Arizona
estimates presented by the National Survey on Drug Use and Health, the percentage of
18- 25 year olds using illicit drugs in the past month is 18.88% compared to 41.43% that
report binge drinking in the past month. For adults 26 and older, 6.53% report using
illicit drugs in the past month compared to 23.04% that report binge drinking in the past
month. For adults, the occurrence of binge drinking is much more problematic than illicit
drug use.
These data and rationales were presented to the epidemiology work group who
subsequently approved a second problem area of youth drug use defined by the single
indicator, past 30- day day any drug use ( does not include alcohol or tobacco) among 8th
through 12th grade students.
6.3 Geographic problem areas
Between the problematic drinking and youth drug use indicators, the risk and protective
factor studies, and the resource assessment, many geographic areas have been suggested
as geographic areas for targeting State Incentive Grant resources. Table 6A lists these
indicators of potential problems and the counties with high rates of the problem, high risk
as measured by risk factors, or low resources. County data does not exist for the
indicator, past month adult binge drinking.
Table 6A: Counties that Rank High in Problem Rates and Risk and Low in Resources*
Underage
drinking
Underage
binge
drinking
Alcohol
related
crashes
Youth
drug use
Social
Indicators
high risk
Arizona
Youth
Survey
high risk
Low per
capita
prevention
spending
Santa Cruz X X X
Mohave X X X X X
Gila X X X X X
Cochise X X
La Paz X
Coconino X X X X
Apache X X X
Yavapai X X
Greenlee X
Graham X
Navajo X
* If a county is not listed, it did not rank high or low enough in the indicator area to be included.
Finding: Mohave and Gila counties appear as priorities in five of the seven
indicators. Coconino county appears as a problem area in four of the seven
indicators.
60
Community health analysis areas can refine geographic targets for underage drinking,
underage binge drinking, and youth drug use. The community health analysis areas with
high alcohol composite scores and higher than average percentages of past 30- day day
alcohol use and past two- week binge drinking are presented in Table 6B.
Table 6B: Community Health Analysis Areas with High Alcohol Composite
Scores or Higher than Average Percentages of Past 30- day Day Alcohol Use and
Past Two- week Binge Drinking
Composite Alcohol Score Single measure past 30-
day day alcohol use
Single measure past two-week
binge drinking
Douglas Douglas Douglas
Globe/ Hayden Globe/ Hayden Globe/ Hayden
Kingman Kingman
Lake Havasu City Lake Havasu City
Flagstaff W est
Benson CHAA,
Williams CHAA
The community health analysis areas with high drug composite scores and higher than
average percentages of past 30- day day illicit drug use are presented in Table 6C.
Table 6C: Community Health Analysis Areas with High Drug Composite Scores or
Higher than Average Percentages of Past 30- day Day Drug Use.
Composite drug score Single measure past 30- day day drug use
Flagstaff West Flagstaff West
Flagstaff Rural Flagstaff Rural
Lake Havasu City
Marana
Cordes Junction
Yavapai Co. S/ Bagdad
Tohono O’Odam Nation
St. Johns
Page/ Fredonia
Flagstaff East
Sedona
Winslow
Holbrook
6.4 Age problem areas
Data on the age of people affected by the various consequence and consumption
indicators consistently suggests two age groups depending on the objective of the
intervention that is to be funded. For most indicators, rates of consumption or
consequences peaked among 18 to 25 year olds. For some indicators, rates among age
61
groups bracketing the 18 to 25 year olds were also relatively high and might be
considered as part of the target range for intervention.
While youth under the age of 18 do not present with the highest rates of the problems that
were analyzed, if the objective of interventions is to prevent the onset of consumption or
problem behaviors, this age group should be targeted.
If the intervention’s objective is to prevent the onset of consumption or problem
behaviors within a population already experiencing high rates of problems or to prevent
the reoccurrence of a problem behavior, 18 to 25 year olds and for some indicators, the
age groups with second or third highest rates, should be targeted.
6.4 Problem areas
Given the complexity of the information presented so far, the following table is meant to
provide a sense of how the data might be used for prevention intervention planning.
Table 6D presents possible indicators, geographically and age defined audiences, and the
objectives that interventions might address. Target geographies were selected based on
two criteria. First, they have high rates of the problem indicator or high alcohol or drug
composite scores. Second, they have a high occurrence of the problem indicator.
62
Problem Areas: Problematic Drinking and Youth Illicit Drug Use
Indicator Target Age Target Geography Objectives
Problematic Drinking
Counties and health analysis areas with highest
rate of 8th to 12th grade drinking: Santa Cruz,
Mohave, Gila, Cochise, Douglas CHAA,
Globe/ Hayden CHAA, Kingman and Lake
Havasu City CHAA
8th - 12th
grade
students
Counties with highest occurrence of 8th to 12th
grade drinking: Maricopa, Pima
1. Increase age of
onset
2. Decrease past 30-
day day use
Counties and health analysis areas with highest
rate of 8th to 12th grade drinking: Santa Cruz,
Mohave, Gila, Cochise, Douglas CHAA,
Globe/ Hayden CHAA, Kingman and Lake
Havasu City CHAA
Past month
underage
drinking
Students in
grades
below the 8th
grade
Counties with highest occurrence of 8th to 12th
grade drinking: Maricopa, Pima
Increase age of onset
Counties and health analysis areas with highest
rates of 8th to 12th grade binge drinking: Santa
Cruz, Mohave, Gila, Cochise, Douglas CHAA,
Benson CHAA, Globe/ Hayden CHAA,
Williams CHAA
8th – 12th
grade
students
Counties with highest occurrence of 8th to 12th
grade binge drinking: Maricopa, Pima
1. Decrease past 30-
day day use
2. Decrease past
two- week binge
drinking
Counties with highest rates of 8th to 12th grade
binge drinking: Santa Cruz, Mohave, Gila,
Cochise
Past month
underage binge
drinking
Students in
grades
below the 8th
grade. Counties with highest occurrence of 8th to 12th
grade binge drinking: Maricopa, Pima
Increase age of onset
18- 25 year
olds
( highest
rate)
State level ( no data at sub- state level) Decrease past 30- day
day binge drinking
Past month
adult binge
drinking
< 18 year
olds
State level ( no data at sub- state level) 1. Decrease past
two- week binge
drinking
2. Increase age of
onset
Counties with highest rates of car crash injuries:
La Paz, Coconino, Apache
21 - 34 year
olds
Counties with highest occurrence of car crash
injuries: Maricopa, Pima
1. Decrease alcohol
related car crashes
2. Decrease past 30-
day day binge
drinking
Counties with highest rates of car crash injuries:
La Paz, Coconino, Apache
Alcohol related
car crash
injuries
< 21 year
olds
Counties with highest occurrence of car crash
injuries: Maricopa, Pima
1. Decrease past 30-
day day binge
drinking
2. Increase age of
onset
63
Priority Problems: Problematic Drinking and Youth Illicit Drug Use
Youth Illicit Drug Use
Indicator Target Age Target Geography Objectives
Counties and health analysis areas with highest
rates of past month any drug use: Apache,
Graham, Coconino, Navajo, Page/ Fredonia
CHAA, Sedona CHAA, Flagstaff West CHAA,
Flagstaff East CHAA, Flagstaff Rural CHAA,
Winslow CHAA, Holbrook CHAA, Benson
CHAA, Navajo Nation CHAA, Hopi Nation
CHAA, Havasupai CHAA.
8th – 12th
grade
students
Counties with highest occurrence of past month
any drug use: Maricopa, Pima
1. Decrease past
month illicit drug
use
2. Increase age of
onset
Counties and health analysis areas with highest
rates of past month any drug use: Apache,
Graham, Coconino, Navajo, Page/ Fredonia
CHAA, Sedona CHAA, Flagstaff West CHAA,
Flagstaff East CHAA, Flagstaff Rural CHAA,
Winslow CHAA, Holbrook CHAA, Benson
CHAA, Navajo Nation CHAA, Hopi Nation
CHAA, Havasupai CHAA.
Past month any
illicit drug use1
Students in
grades
below the 8th
grade
Counties with highest occurrence of past month
any drug use: Maricopa, Pima
Increase age of onset
1 Any illicit drug generally includes all drugs with the exception of tobacco and alcohol. The specific drugs
that are included may vary according to the study that is used to measure drug use.
64
7. Data Concerns and Needs
In the course of the epidemiology work group’s efforts, a variety of data and research
needs were identified, some of which presented significant gaps in our knowledge of
substance abuse consumption and consequences in Arizona.
Adult prevalence survey
There is no study of adults that provides sub- state level estimates for substance use and
substance related consequences such as clinical dependence or abuse. National studies
provide state level estimates but their sample size is too small to provide any estimates at
a lower geographic level. The Department of Health Services conducted a population
based telephone survey in 1996 that investigated substance use consumption and
substance related consequences among adults ages 18 to 64. This survey or a survey like
it should be conducted on a biennial basis. State agencies with the mandate or burden of
addressing substance use or its consequences, the Department of Health Services or the
Administrative Office of the Courts, for example, should be involved with the
development and planning of the survey. The survey sample should be large enough, at a
minimum, to provide sub- county level estimates for Maricopa and Pima counties and
county level estimates for the other counties.
Proportion of health or social problems attributable to substance use
Throughout the development of the epidemiological profile the question of the
relationship of substance use to chronic diseases such as heart disease or social problems
such as crime or school dropout remained unanswered. The work group acknowledged
that these relationships do exist and are an essential contribution to a robust profile of the
effects of substance use in Arizona. In ensuing years of the State Incentive Grant, the
epidemiology work group can address this issue in two ways: first, by conducting a
literature review of studies that reliably measure the contribution of substance abuse to
these health and social problems and second, by conducting studies specific to Arizona’s
population provided that resources are available for such a study.
Measures of the severity of substance use such as economic costs or years of
productive life lost
This profile provides information about the extent of substance use and the occurrence of
substance use related consequences in Arizona but, with the exception of instances of
death or illness, does not describe or quantify the effect substance use has on the
individual or society. The severity of substance use is another factor to consider when
setting priorities among consequence and consumption indicators because it is possible
that certain consequences or drugs exert a heavier toll than others. Often severity is
measured by indicators such as economic costs, utilization of system resources, or years
of productive life lost due to substance use or its consequences. The epidemiology work
group can address this deficiency in subsequent years by conducting reviews of pertinent
studies that can be applied to Arizona’s population or by conducting primary research
with Arizona specific populations provided that resources are available for such a study.
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Resource inventory
In this report, resources and assets were defined as the annual amount of public funding
received by service providers in Arizona as reported in the Arizona Drug and Gang
Prevention