Spatial Patterns of Drug Use and Mental HealthOutcomes Among High School Studentsin Ontario, Canada

Wanrudee Isaranuwatchai & Claus Rinner &

Heather Hart & Angela Paglia-Boak & Robert Mann &

Kwame McKenzie

Published online: 16 October 2013# Springer Science+Business Media New York 2013

Introduction

Mental illness and addiction have been linked to the places where people live or work(Dohrenwend and Dohrenwend 1971; Faris and Dunham 1939; Freeman 1994; Kessler1979; March et al. 2008; O’Campo et al. 2009; Peterson et al. 2009; Silver et al. 2002;Wilson and Rosenberg 1992). An increasing number of studies have examined and confirmedthe impact of environment and community (e.g., neighbourhood socioeconomic status) onphysical health, mental health or substance abuse (Goldsmith et al. 1998; Hobin et al. 2012;McKenzie and Harpham 2006; O’Campo et al. 2009; Ross 2000; Rush et al. 2007; Silver et al.2002). As an integrated discipline, health geography investigates how the natural and socialenvironment influences people’s health. Spatial analysis has been widely used to examinehealth in relation to geographical locations. This approach can be used to identify priority healthtopics, distribute health resources, or place health facilities at optimal locations (Joseph andPhillips 1984; McLafferty and Grady 2004; Meade and Earickson 2000).

Within spatial analysis, mapping can be used to present geographically referenced data(Meade and Earickson 2000). In recent years, spatial analysis has been used to explain thedistribution of health and disease, particularly those that are contagious and infectious (Beckeret al. 1998; Crighton et al. 2007; Meade and Earickson 2000). The analysis of spatial patternsthrough mapping of a variable of interest (such as mental illness and disease rates) can yieldnew insight (Bell et al. 2006; MacEachren et al. 1998).

Int J Ment Health Addiction (2014) 12:312–320DOI 10.1007/s11469-013-9455-0

W. Isaranuwatchai (*) :K. McKenzieSocial Aetiology of Mental Illness (SAMI) Training Program, Centre for Addiction and Mental Health,455 Spadina Avenue, Suite 300, Toronto, Ontario M5S 2G8, Canadae-mail: wanrudee@isaranuwatchai.com

C. Rinner :H. HartDepartment of Geography, Ryerson University, 350 Victoria Street, Toronto, Ontario M5B 2K3, Canada

A. Paglia-Boak : R. MannSocial and Epidemiological Research Department, Centre for Addiction and Mental Health,33 Russell Street, Toronto, Ontario M5S 2S1, Canada

Spatial pattern analysis has been applied to mental health, substance abuse, and gamblingactivity (Chaix et al. 2001; Faris and Dunham 1939; Freeman 1994; Gilliland and Ross 2005;Hasselback et al. 1991; Latkin et al. 1998; March et al. 2008; Midford et al. 1998; Ross andTaylor 1998; Rush et al. 2007; Silver et al. 2002; Veldhuizen et al. 2007;Wilson and Rosenberg1992). Previous research has shown that drug use and mental health problems among highschool students are significant issues (Paglia-Boak et al. 2009, 2010). Studies also suggestedthat drug use or poor mental health could lead to other health problems (Brand et al. 2010;Faulkner et al. 2010).

The objective of this research was to document the spatial patterns of drug use and mentalhealth among high school students in the Province of Ontario, Canada, in order to enhancethe identification and understanding of mental health issues in particular areas. The OntarioStudent Drug Use and Health Survey (OSDUHS) is a province-wide survey collected every2 years since 1977 by the Centre for Addiction and Mental Health (CAMH) (Paglia-Boaket al. 2009, 2010). This survey is the longest ongoing school study of adolescents in Canada.A spatial perspective on drug use and mental health among high school students couldprovide useful information to health providers and policy-makers concerning health promo-tion and prevention among this important population.

Methods

The analysis was based on the 2009 cycle of the OSDUHS. The OSDUHS is a cross-sectional,biennial, full-probability survey of Ontario students in grades 7 through 12 in the public schoolsystem. The survey employs a stratified (region and school level), two-stage (school, class)cluster sample design. Since it covered a wide geographic area, the socio-economic character-istics of the sample are likely representative of the student population. The survey included aquestion about the educational attainment of the students’ parents, showing that over 50 % ofboth, mothers and fathers, had graduated from college or university. Our analysis used asubsample of 5,783 secondary school students (grades 9 to 12) sampled from 101 high schoolsand 366 classes. The participation rate was 66 % with loss due to absenteeism (15 %) andunreturned parental consent forms or parental refusal (19 %). This survey used self-administeredquestionnaires to promote anonymity. The 2009 OSDUHS protocol was approved by researchethics boards at CAMH and York University (which conducted the survey on CAMH’s behalf).Full details of the OSDUHS methodology can be found in elsewhere (Paglia-Boak et al. 2009,2010).

In 2006, the Ontario government established 14 Local Health Integration Networks (LHINs)as agencies that plan and fund health services, which are more closely aligned to local needs andpriorities in their designated geographical area. Due to the limited sample size in the 2009OSDUHS, three pairs of adjacent LHINs were merged resulting in the 11 units of analysis ofthis study: 1) Erie St. Clair and South West (merged); 2) Waterloo Wellington; 3) HamiltonNiagara Haldimand Brant; 4) Central West; 5) Mississauga Halton; 6) Toronto Central; 7)Central; 8) Central East and North Simcoe Muskoka (merged); 9) South East; 10) Champlain;and 11) North East and North West (merged).

The data of the 2009 OSDUHS were reported in population percentages and 95 % confi-dence intervals (CIs), which were weighted to accommodate for the complex survey samplingdesign (i.e., stratification and clustering). For the present study, 24 drug use and mental healthoutcomes were examined by LHIN (see Table 1 for a description of the outcomes). Populationpercentages and 95 % CIs were calculated for each LHIN area and for the province. Populationpercentage, therefore, referred to the proportion of study participants with a specified outcome

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Table 1 Drug use and mental health indicators examined in this study

Indicator Description

Past year cigarette use Smoking at least one cigarette daily or smoking occasionally during thepast 12 months. Those who smoked only a few puffs or less than onecigarette in the past 12 months were classified as non-smokers.

Past year alcohol use Consuming any alcohol during the past 12 months. Use includesconsumption on special occasions, but excludes sips just to try it.

Binge drinking Drinking 5 or more drinks on the same occasion once or more often duringthe past 4 weeks

Cannabis use Using cannabis (marijuana or hashish) once or more often during the past12 months. Those who reported that they did not know what cannabis iswere classified as non-users.

Opioid pain reliever use(NM)

Using a prescription opioid pain reliever (such as OxyContin, Percocet,Percodan, Tylenol #3, codeine) for non-medical purposes once or moreoften during the past 12 months. Those who reported that they did notknow what these drugs are, were classified as non-users.

Any NM use of a prescriptiondrug

Non-medical use of at least one of the following five prescription drugs ordrug classes once or more often during the past 12 months: OxyContin,other prescription opioid pain relievers, attention deficit hyperactivitydisorder (ADHD) drugs, other stimulants, or tranquillizers/sedatives(excluding Rohypnol)

Any illicit drug, includingNMprescription drug

Use of at least one of the following 24 drugs asked about in the 2009survey during the past 12 months: cannabis, glue, solvents, LysergicAcid Diethylamide or LSD, Phencyclidine or PCP, other hallucinogens,cocaine, crack, methamphetamine, crystal methamphetamine, heroin,ecstasy, Gamma-Hydroxybutyric acid or GHB, Rohypnol, ketamine,jimson weed, salvia divinorum, stimulants (NM), tranquillizers/sedatives (NM), OxyContin (NM), other prescription opioid painrelievers (NM), ADHD drugs (NM), over-the-counter sleepingmedication, or over-the-counter cough/cold medication

Hazardous/harmful drinking Scoring at least 8 of 40 (Likert scoring) on the World HealthOrganization’s Alcohol Use Disorders Identification Test (AUDIT)screen, which identifies the percentage drinking hazardously orharmfully. Hazardous drinking is a pattern of drinking that increases thelikelihood of future physical and mental health problems, includingdependence. Harmful drinking is a pattern that is already causing harms(e.g., injuries).

Potential drug use problem Experiencing at least 2 of the 6 items on the “CRAFFT” screener, whichmeasures a potential drug use problem that may require treatment (past12 months time interval)

Passenger-driver usedalcohol

Being a passenger in a vehicle, at least once during the past 12 months,with a driver who had been drinking alcohol

Passenger-driver used drugs Being a passenger in a vehicle, at least once during the past 12 months,with a driver who had been using drugs

Poor self-rated physicalhealth

Rating one’s physical health as either “fair” or “poor”

Sedentary behaviour Watching TV and/or on a computer for 7 h or more per day, on average,during the 7 days before the survey

Overweight or obese Exceeding the age-by-sex specific body mass index cut-off values asestablished for children and adolescents and recommended by theInternational Obesity Task Force, based on self-reported height andweight

Medically-treated injury Having an injury that was treated by a doctor or nurse during the past12 months

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in each LHIN area (LHIN average) or in the province (province-wide average). Each outcomewas mapped to LHIN boundaries using the ArcMap 10 Geographic Information System (GIS)software. In order to identify and interpret regional spatial patterns, outcome values for eachLHIN were classified into three categories with reference to the province-wide average: 1)above the upper 95 % CI limit of the average (orange colour); 2) within the 95 % CI of theaverage (off-white colour); and 3) below the lower limit of the 95 % CI of the average (bluecolour). Each map therefore shows whether LHINs have a proportion of the specified outcomethat is above, below, or within the 95 % CI of the province-wide average. When a map of aspecified outcome shows a LHIN’s proportion above the upper limit of the province-wideaverage, a possible conclusion could be that the student population in this particular LHIN wasworse off regarding this outcome than the province-wide student population. Consequently, thisoutcome should be carefully monitored by the LHIN.

Results

Of the 24 outcomes, poor self-rated mental health was chosen as an example as illustrated in Fig. 1.The proportion of students who reported having poor mental health was above the province-wideaverage in northern and southwestern Ontario as well as in the Toronto Central LHIN.

The map in Fig. 2 summarizes the outcomes of all 24 outcomes of drug use and mentalhealth highlighting LHINs with greater proportions of negative outcomes (values above the

Table 1 (continued)

Indicator Description

Medical use of opioidpain relievers

Using a prescription opioid pain reliever for medical purposes during the past12 months

Poor self-rated mentalhealtha

Rating one’s mental or emotional health as either “fair” or “poor”

Psychological distress Experiencing at least 3 of the 12 items on the “General Health Questionnaire”(GHQ). The GHQ measures symptoms of anxiety, depression, and socialdysfunction over the past few weeks.

Delinquent behaviour Reporting at least 3 of the following 11 delinquent behaviours at least onceduring the past 12 months: vandalized property, theft of goods worth lessthan $50, theft of goods worth $50 or more, stole a car/joyriding, break andentering, sold cannabis, sold other drugs, ran away from home, assaultedsomeone (not a sibling), gang fighting, carried a weapon

School fights Being in one or more physical fights at school during the past 12 months

Bully victim Being bullied at school since September in any one of the following manners:verbally, physically, or being a victim of theft/vandalism

Bully perpetrator Bullying others at school since September in any one of the followingmanners:verbally, physically, or stealing/damaging something of theirs

Any gambling activity Having gambled money at 1 or more of 10 gambling activities asked about inthe survey during the past 12 months

Video gaming problem Experiencing at least 5 out of the 9 problems in the Problem Video Playing(PVP) scale, which measures problems with preoccupation, tolerance, anddisruption to school/family due to video gaming during the past 12 months

NM non-medical use, without a doctor’s prescriptiona Chosen as an example to illustrate in the paper

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province-wide average). The LHIN with the highest number of above-average outcomes(largest circle size) was the merged North East and North West LHIN, followed by themerged Erie St. Clair and South West LHIN, and Hamilton Niagara Haldimand Brant LHIN.In contrast, three LHINs had less than five outcomes above the province-wide average:Central West, Central, and the merged Central East and North Simcoe Muskoka.

Fig. 1 Grouping of Local Health Integration Networks (LHINs) into one of the three categories: 1) proportionof students with poor mental health above the upper 95 % confidence interval of the province-wide average(orange colour); 2) proportion of the outcome within the 95 % confidence interval of the province-wideaverage (off-white colour); and 3) proportion of students with poor mental health below the lower 95 %confidence interval of the province-wide average (blue colour)

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Discussion

Visual analysis revealed regional clusters of LHINs with elevated levels of drug use andmental health problems in the north and in the southwest of the province, including the

Fig. 2 This figure summarizes the number of drug use or mental health outcomes which were above the upper95 % confidence interval, within the range of the interval, or below the lower limit of the 95 % confidenceinterval of the province-wide average. As the number of outcomes above the upper interval of the province-wide average increases, the orange part of the circle becomes bigger, and the size of the circle also becomeslarger. For example, a LHIN that had 14 outcomes above the province-wide average would have a biggercircle than a LHIN that has only 2 outcomes above the province-wide average

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Toronto Central LHIN. Additionally, LHINs with positive outcomes were identified sur-rounding the City of Toronto and in the southeast of the province. Policies and programs inthese LHINs could be examined to see if any might be linked to the positive outcomes, andwhether they could be applied to other LHINs.

Using LHINs as units of analysis in a spatial pattern analysis provided more detailedpatterns of drug use and mental health outcomes than previous studies. Specifically, inthe OSDUHS report (Paglia-Boak et al. 2009, 2010), regions in Ontario were groupedinto only four regions: 1) City of Toronto (including the Greater Toronto Area); 2)Northern Ontario (Parry Sound district, Nipissing District and farther north); 3) WesternOntario (Peel District, Dufferin County, and farther west); and 4) Eastern Ontario(Simcoe County, York County and farther east). The patterns of drug use and mentalhealth outcomes found from categorizing regions into 4 groups differed from the moredetailed patterns for the 11 LHINs in the present paper. For example, the Greater TorontoArea reported the highest proportion of high school students with poor mental healthamong the four large regions. However, our detailed analysis showed that only theToronto Central LHIN reported a higher proportion of students with poor mental healththan the province-wide average, whereas the other LHINs of the Toronto group (i.e.,Central West, Mississauga Halton, and Central) reported proportions of poor mentalhealth at or below the province-wide average. Moreover, the other LHINs of theToronto group had only a few outcomes above the province-wide average. In contrast,the Toronto LHIN had eight outcomes above the province-wide average. LHIN-basedmapping enabled the detection of these important spatial patterns, which might have beenoverlooked in non-spatial analyses.

The limitations of this study must be kept in mind when interpreting the results. Thesample size of 11 LHIN areas was too small to apply statistical tests to confirm spatialclustering. A general spatial trend of drug use and mental health problems was difficult toidentify due to the coarse geographic detail. In addition, some LHINs had lower sample sizesand thus were merged within the OSDUHS. Results for these merged LHINs might concealpatterns specific to each individual LHIN. Future research may consider collecting data atsmaller units of analysis (e.g., public health units or groups of postal codes) in order to allowfor the use of spatial statistics.

Conclusions

This brief communication presents spatial patterns of drug use and mental health outcomesamong high school students in Ontario by LHIN areas. This approach illustrates how carto-graphic mapping can be used to gain insight into the spatial patterns of drug use and mentalhealth outcomes and to provide spatially explicit summaries of health surveys such asOSDUHS. Thematic maps identified drug use and mental health issues among high schoolstudents that should be monitored within each LHIN. The visualization of the number of above-average outcomes could help health planners in the LHINs to develop response strategies tothese issues.

This brief report is an example of how a visual spatial analysis may be used as a tool topresent research findings from a geographic perspective. Furthermore, maps can be effectivetools for knowledge translation to health-care providers and policy-makers. Although the useof GIS in public health is becoming increasingly widespread, we did not find comparableexamples of exploratory mapping of student drug use and mental health patterns, whichattests to the importance of this study.

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