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Prevalence of alcohol, smoking and illicit drug use amongst people with Intellectual Disabilities: review

Adam Huxley*1, Martha Dalton2, Yvonne Y Y Tsui3, Karen P Hayhurst4

1 Division of Clinical Psychology, CGL, 140-142 Kings Cross Road, London, WC1X 9DS, UK

2 Department of Health and Social Care, Leeds LS2 7UE, UK

3 Warneford Hospital, Oxford Health NHS Foundation Trust, OX3 7JX, UK

4 Division of Psychology and Mental Health, University of Manchester, Manchester, M13 9PL, UK

Running head: Prevalence of Substance Use in Intellectual Disability

*Address for Correspondence: CGL, 140-142 Kings Cross Road, London, WC1X 9DS, UK [email protected]


Abstract

People with an intellectual disability (ID) make up an unknown proportion of those seeking substance use treatment. We reviewed existing evidence on prevalence estimates relating to tobacco use, drug and alcohol use, and misuse in ID. Ten electronic databases were searched to identify studies published 1980 to 2016 describing substance use and misuse prevalence estimates in ID. 39 studies were identified (UK, 13; US, 10; Australia, 4; Netherlands, 3; Sweden, 2; Belgium, 1; Finland, 1; India, 1; Ireland, 1; Serbia, 1; more than 1 country, 2). The review highlighted considerable methodological variance in the description and diagnosis of ID plus substantial between-study variation in how use, misuse and dependency were defined. Current alcohol use prevalence ranged from 1.9% to 55%; current tobacco use prevalence from 0% to 62.9%; and current cannabis use prevalence from 5% to 9.5%. The prevalence of substance use and misuse in ID is highly variable; studies included in this review were too heterogeneous to determine conclusively whether prevalence rates are higher, lower or equivalent in ID versus non-ID samples. The use of substances amongst people with ID requires greater consideration by researchers, service providers and commissioners.

Keywords: Alcohol dependence, tobacco dependence, intellectual disability, learning disability, substance dependence, review


Introduction

Intellectual disability (ID) is a lifelong syndrome, which includes a heterogeneous range of clinical conditions characterised by deficits in cognitive function prior to the acquisition of skills through learning (Salvador-Carulla & Bertelli, 2008). The overall prevalence rate of ID converges on approximately 2% of the population (England data: Emerson & Hatton, 2004; UK data: Emerson & Brigham, 2013).

The misuse of substances remains a prime political, social and health concern, contributing to premature mortality, crime and social and health inequalities (Whiteford et al., 2013) The World Health Organisation (WHO) estimates that 39 deaths per 100,000 can be attributed to drug and alcohol misuse, making it a global public health priority (WHO, 2014). Despite established widespread use in the general population, alcohol is a psychoactive substance with dependence-producing properties, which, when used problematically can contribute to premature mortality and harms across a number of social, psychological and physical domains. In 2012, 5.9% of all global deaths were attributed to alcohol consumption (WHO, 2014). Cigarette smoking accounts for 16% of all deaths in England (NHS Digital, 2016a) and is the primary causal factor in at least 30% of all cancer deaths (CDC, 2008). Tobacco use prevalence is higher than average amongst vulnerable and lower socio-economic groups, for example, prevalence amongst people who misuse substances is as high as 74% to 88% (Kalman, 1998). Illicit drug use refers to the use of a wide range of substances prohibited under law and including substances such as cannabis, powder cocaine, LSD and ecstasy, which are more commonly associated with a pattern of recreational use and others, such as heroin and crack cocaine, which are more commonly associated with chronic and dependent use (Hayhurst et al., 2015). Cannabis is by far the most widely cultivated, trafficked and misused illicit drug globally (WHO, 2014).

The use of substances amongst people with ID has not been of prime concern for health providers until recent times with prevalence rates believed to be low, in comparison with the general (non-ID) population (Huxley, Copello, & Day, 2005). More recent evidence, however, suggests that substance use and misuse is an emerging issue amongst this cohort (Day, Lampraki, Ridings, & Currell, 2016). It is believed that the closure of long-stay residential facilities across a number of countries, alongside greater integration in the community has led to greater access to alcohol and illicit drugs by people with ID.

Individuals with ID appear less likely to access health services and health promotion activities (Emerson & Baines, 2011) and are less likely to seek help if, for example, their alcohol use becomes problematic (Quintero, 2011). The interaction of alcohol with medication prescribed for comorbid health conditions can lead to specific complications in ID (Degenhardt, 2000; Quintero, 2011). Despite the recent emphasis on improving access to primary care services, including regular health checks and integration into mainstream healthcare provision, there is limited information on the prevalence of risk factors for poor health in ID (McClintock, Hall, & Oliver, 2003).

Substance misuse in ID, as in the non-ID population, can harm interpersonal relationships and negatively affect physical and mental health (Taggart, Huxley, & Baker, 2008). In addition, excessive alcohol consumption in ID carries risks to personal safety due to the association with impaired judgement and excessive risk taking. This can increase the potential for accidental injury, unplanned and unprotected sex, criminal behaviour and acts of violence (McGillivray & Moore, 2001; Taggart et al., 2008; Taylor et al., 2010).

Previous research points to potential substance use profiles in ID. For example, alcohol-using individuals with ID initiate use later in life than their (non-ID) peers (Quintero, 2011). Individuals with ID are more likely to smoke tobacco if they are higher functioning, do not use available ID services, live in less restrictive environments, are male, or have co-occurring substance use disorders (Emerson & Baines, 2011; Steinberg, Heimlich, & Williams, 2009). Possible reasons given for alcohol and tobacco use amongst people with ID include a desire to be like their non-ID counterparts and social and emotional influences (Kerr, Lawrence, Middleton, Fitzsimmons, & Darbyshire, 2017).

Prevalence rates of substance use and misuse in ID have been described as difficult to ascertain and imprecise (Moore & Polsgrove, 1991) and prevalence estimates of co-occurring substance use disorder (SUD) and ID rely largely on single source studies performed in selected samples (VanDerNagel et al., 2014), typically within existing ID services rather than addiction services. For example, the prevalence of substance misuse in ID ranges from 0.5% to 25% for any substance, in clinic samples reported by Pezzoni and Kouimtsidis (2015). A recent population study in the Netherlands, using capture-recapture methodology, estimated that a very low rate (between 0.05% and 0.25%) of the total population of males over 30 years old had borderline ID and substance use (VanDerNagel et al., 2014). Existing evidence indicates that people with ID do smoke tobacco, and do use alcohol, but at lower rates than those observed in the non-ID population (Stavrakaki, 2002, Emerson & Turnbull, 2005). For misuse patterns, there is existing evidence that people with ID may also misuse alcohol and illicit drugs and overuse prescribed medications (Sturmey, Reyer, Lee, & Robek, 2003, McGillicuddy, 2006).

This initial glance at the literature suggests that data on the prevalence of substance use and misuse in ID is ambiguous. Robust evidence on patterns of harmful substance use behaviour is essential to the development of services that tackle unmet need in substance-using individuals with ID and to the tailoring of intervention programmes able to optimise treatment outcomes in this vulnerable population. We set out to (1) explore and summarise existing evidence on the prevalence of tobacco smoking, alcohol use and misuse, and illicit drug use and misuse amongst people with an ID; and (2) make recommendations for required research based on identified gaps and inconsistencies in the existing evidence base.

Methods

Study identification

Studies were identified via database searches, bibliography screening and citation mapping. The following electronic databases were searched: CINAHL (via Ebsco-Host), HMIC, BNI, Embase, Medline, PsycInfo, AMED, PsycArticles, Web of Science and Cochrane databases. Searches covered the time-period January 1980 to 1st June 2016. The search strategy used the following key terms, including variant spellings of ‘intellectual’, ‘disability’, ‘difficulty’, ‘learning’, ‘drugs’, ‘alcohol’, ‘tobacco’, ‘cigarettes’. No setting or geographical restrictions were applied but searches were limited to English language sources. Additional relevant studies were identified via organic backwards (manually searching the references of included papers) and forward (searching databases for relevant papers citing included papers) searches.

Inclusion and eligibility

Inclusion criteria were: (1) focus on intellectual disability; (2) focus on alcohol, and/or tobacco, and/or illicit drug use behaviour; and (3) publication in a peer-reviewed journal (findings reported in books, dissertations, or theses were not included). Case series studies were not considered and only studies reported in the English language were included. The inclusion criteria were applied to titles and abstracts by two reviewers working independently. The full text of retrieved articles was reviewed with inclusion also based on consensus between two reviewers. A third reviewer was available to resolve any disagreements over inclusions.

Data extraction and quality assessment

Demographic data, plus details of ID and comparison samples (where available), together with data on prevalence of tobacco smoking, alcohol use and misuse, and illicit drug use and misuse were extracted from included studies by two reviewers (KH and AH).

Methodological quality was assessed using a tool (Munn, Moola, Riitano, & Lisy, 2014) for use in systematic reviews addressing prevalence, which addresses issues of internal and external validity across different study designs. The tool considers: representativeness; appropriateness of recruitment; adequacy of sample size; description and reporting of study subjects and setting; adequacy of data; reliable and objective measurement; appropriate statistical analysis; and appropriate identification of subgroups accounting for confounding factors (Munn et al., 2014). A higher score (out of a maximum of 10) indicates better methodological quality. Included studies were reviewed independently and scored by two reviewers (AH and MD). The two reviewers discussed any discrepancies in ratings and a consensus rating was reached. Where consensus could not be reached on a particular item, a third reviewer provided a rating. Meta-analysis was not carried out due to the heterogeneity of included studies, resulting from variation in the criteria used to define ID and substance use/misuse.

Results

The literature search identified 131 studies following the removal of duplicates. Initial screening excluded the majority of these, with 75 full-text articles progressing to a more detailed examination and 39 selected for inclusion. Reasons for exclusion included ambiguity in the clinical rationale for establishing ID, no clear type of substance when defining substance use, or specific educational difficulties rather than global ID (see Figure 1). The majority of included studies estimated prevalence rates within a specific cohort of individuals with ID. The average quality assessment score was 6 (95% CI 5 to 7). Lower quality studies were characterised by unclear sample characteristics, no defined criteria for establishing use, misuse and dependency and a description of substance use in general terms without specifying the substance type.

[Figure 1 about here]

Prevalence of alcohol use in ID

Characteristics of included studies

Twenty-eight studies were included (Table 1). Studies were set in the UK (10: Chaplin, Gilvarry, & Tsakanikos, 2011; Emerson & Brigham, 2013; Hassiotis et al., 2008; 2011; Lindsay et al., 2013; Pezzoni & Kouimtsidis, 2015; Plant, McDermott, Chester, & Alexander, 2011; Robertson et al., 2000; Robertson, Emerson, Baines, & Hatton, 2014; Taggart, McLaughlin, Quinn, & Milligan, 2006), US (5: Gress & Boss, 1996; Krishef, 1986; McGillicuddy & Blane, 1999; Rimmer, Braddock, & Marks, 1995; Westermeyer, Phaobtong, & Neider, 1988), Australia (3: Haider, Ansari, Vaughan, Matters, & Emerson, 2013; McGillivray & Moore, 2001; McGillivray & Newton, 2016), Netherlands (3: Didden, Embregts, van der Toorn, & Laarhoven, 2009; VanDerNagel, Kiewik, Buitelaar, & DeJong, 2011; VanDerNagel et al., 2014), Belgium (1: Swerts et al., 2017), Finland (1: Männynsalo, Putkonen, Lindberg, & Kotilainen, 2009), Ireland (1: McGuire, Daly, & Smyth, 2007), Serbia (1: Žunić-Pavlović, Pavlović, & Glumbić, 2013), and Sweden (1: Nettelbladt, Göth, Bogren, & Mattisson, 2009). Two studies reported data from more than one country; one set in the US, Italy and Israel (Fortuna et al., 2016); the other across 14 European countries (Haveman et al., 2011).

Samples were predominantly majority male (not reported in 5 studies), ranging from 49% (McGillicuddy & Blane, 1999; Swerts et al., 2017) to 94% (Hassiotis et al., 2011) with a mean of 66% (SD 14). Mean age (not reported in 12 studies) was 35 years (SD 8) ranging from 15.6 (Žunić-Pavlović et al., 2013) to 47.5 years (Robertson et al., 2000). One study (Haveman et al., 2011) reported an upper age range of 90 years. Mean sample size was 346 (SD 492), ranging from 30 (McGillivray & Moore, 2001) to 2200 (VanDerNagel et al., 2014). One study (Nettelbladt et al., 2009) reported on a cohort with data collected from 1947; the most recent data collection date was 2012 (Emerson & Brigham, 2013). Seventeen studies did not report dates of data collection; the most recent of these was published in 2017 (Swerts et al., 2017). Ten studies reported alcohol prevalence data set against non-ID comparison groups (Emerson & Brigham, 2013; Fortuna et al., 2016; Gress & Boss, 1996; Haider et al., 2013; Hassiotis et al., 2008; 2011; McGillivray & Moore, 2001; McGuire et al., 2007; Robertson et al., 2000; 2014).

Studies used varied definitions of ID (see Table 1). Severity of ID (where reported) ranged from borderline/mild to profound, with IQ (where reported) ranging from 85 to less than 20. Six studies (Hassiotis et al., 2011; Lindsay et al., 2013; Männynsalo et al., 2009; McGillivray & Moore, 2001; McGillivray & Newton, 2016; Plant et al., 2011) reported on ID cohorts with criminal justice system involvement. The cohorts of 2 studies (Caplin et al., 2011; Pezzoni & Kouimtsidis, 2015) had comorbid mental health problems and 2 further cohorts (Taggart et al., 2006; Westermeyer et al., 1988) had defined substance use problems.

Findings of included studies

Prevalence of alcohol use was classified as: current; past-month; and lifetime across the categories of: use; heavy use; abuse; misuse; dependence; and alcohol use disorder. Current alcohol use prevalence ranged from 1.9% (daily drinking adults with ID: Haveman et al., 2011) to 55% (low alcohol-using male ID group: Robertson et al., 2000) with a mean of 23% (SD 17) across 17 cohorts. Past-month alcohol use prevalence ranged from 14% (adolescents with mild ID: Žunić-Pavlović et al., 2013) to 44.7% (severely behaviourally handicapped students: Gress & Boss, 1996) with a mean of 35% (SD 10) across 5 samples. Past-year/ lifetime alcohol use prevalence ranged from 52% (adults with ID: Krishef, 1986) to 100% (mild ID with DSM substance abuse: Westermeyer et al., 1988) with a mean of 81% (SD 19) across 6 cohorts.

Collapsing the high use, heavy use, abuse, misuse, dependence, and alcohol use disorder, the prevalence of current/ lifetime alcohol misuse ranged from 0% (age 30-39 yrs group: Fortuna et al., 2016) to 100% (substance users with ID: Taggart et al., 2006) with a mean of 22% (SD 26) across 18 samples.

Looking at comparisons, for current alcohol use, two studies report higher use prevalence in ID: adolescent offenders with ID vs. adolescent offenders without ID (McGillivray & Moore, 2001); and self-reported ID vs. no self-reported ID in the same survey (Robertson et al., 2014). Two studies reported lower use prevalence: proxy respondents for adults with ID vs. general population (Haider et al., 2013); and proxy reports by carers of adults with ID vs. a general population health survey (McGuire et al., 2007). One study reported similar use prevalence (students in special schools with ID vs. students in high school: Gress & Boss, 1996). For comparisons of alcohol misuse, two studies report higher prevalence in ID: parents with ID vs. parents with no ID (Emerson & Brigham, 2013); and AUDIT scores in adults with borderline ID vs. adults with no ID (Hassiotis et al., 2008); two studies report lower misuse prevalence: lifetime misuse in a study cohort vs. the general population (Fortuna et al., 2016); and an ID group vs. the general population (Robertson et al., 2000) and one study reported similar misuse prevalence (AUDIT score in prisoners with ID vs. prisoners with no ID: Hassiotis et al., 2011). See Table 1 for further details.

[Table 1 about here]

Prevalence of tobacco use in ID


Twenty-two studies were included (Table 2). Studies were set in the US (8: Gress & Boss, 1996; Havercamp, Scandlin, & Roth, 2004; Hymowitz, Jaffe, Gupta, & Feuerman, 1997; McDermott, Platt, & Krishnaswami, 1997; McGillicuddy & Blane, 1999; Rimmer et al., 1995; Westermeyer et al., 1988), UK (7: Emerson & Brigham, 2013; Emerson & Hatton, 2008; Pezzoni & Kouimtsidis, 2015; Robertson et al., 2000; 2014; Taylor, Standen, Cutajar, Fox, & Wilson, 2004; Whitaker & Hughes, 2003), Australia (2: Haider et al., 2013; Tracy & Hosken, 1997), Belgium (1: Swerts et al., 2017), Ireland (1: McGuire et al., 2007), Serbia (1: Žunić-Pavlović et al., 2013), and Sweden (1: Hemmingsson, Kriebel, Melin, Allebeck, & Lundberg, 2008). Two studies reported data from more than one country; one set in the US, Italy and Israel (Fortuna et al., 2016); the other across 14 European countries (Haveman et al., 2011).

Samples were predominantly majority male (not reported in 5 studies), ranging from 38% (McDermott et al, 1997) to 100% (Hemmingsson et al., 2008) with a mean of 59% (SD 13). Mean age (not reported in 10 studies) was 37 years (SD 8) ranging from 15.6 (Žunić-Pavlović et al., 2013) to 47.5 years (Robertson et al., 2000). One study (Haveman et al., 2011) reported an upper age range of 90 years. Mean sample size was 505 (SD 655), ranging from 36 (Tracy & Hosken, 1997) to 2898 (Emerson & Hatton, 2008). One study (Hemmingsson et al., 2008) reported on a cohort with data collected from 1969; the most recent data collection date was 2012 (Emerson & Brigham, 2013). Twelve studies did not report dates of data collection; the most recent of these was published in 2017 (Swerts et al., 2017). Twelve studies reported tobacco use prevalence data set against comparison groups (Emerson & Brigham, 2013; Fortuna et al., 2016; Gress & Boss, 1996; Haider et al., 2013; Haveman et al., 2011; Havercamp et al., 2004; Hemmingsson et al., 2008; McDermott et al., 1997; McGuire et al., 2007; Robertson et al., 2000; 2014; Westermeyer et al., 1988).

Studies used varied definitions of ID (see Table 2). Severity of ID (where reported) ranged from borderline/mild to profound with IQ (where reported) ranging from 89 to less than 20. The cohorts of 2 studies (Hymowitz et al., 1997; Pezzoni & Kouimtsidis, 2015) were reported has having comorbid mental health problems.


Prevalence of tobacco use was defined as: current; past-month; lifetime; and chronic. Current tobacco use prevalence ranged from 0% (profound LD group: Taylor et al., 2004) to 62.9% (low IQ group (<74 to 89) with 12 years of education: Hemmingsson et al., 2008) with a mean of 18% (SD 19) across 30 cohorts. Past-month tobacco use prevalence ranged from 23% (mild/ moderate ID: McGillicuddy & Blane, 1999) to 48% (mild/ moderate ID: Swerts et al., 2017) with a mean of 32% (SD 9) across 6 cohorts. Lifetime tobacco use prevalence ranged from 35% (mild ID without DSM substance abuse: Westermeyer et al., 1988) to 82.5% (mild ID with DSM substance abuse: Westermeyer et al., 1988) with a mean of 61% (SD 23) across 4 cohorts.

Three studies reported a higher prevalence of tobacco use in ID compared with non-ID cohorts: parents with ID vs. parents with no ID (Emerson & Brigham, 2013); low IQ group (<74 to 89) vs. high IQ group (111 to >126) (Hemmingsson et al., 2008); and self-reported ID vs. no self-reported ID in a survey (Robertson et al., 2014). Two studies reported statistically comparable prevalence rates in ID vs. non-ID samples: students in special schools vs. students in high school (Gress & Boss, 1996); and a group with developmental disabilities vs. a group with no disabilities (Havercamp et al., 2004). Six studies found lower tobacco use prevalence in ID, when compared with non-ID, samples: autism cohort vs. the general population (Fortuna et al., 2016); proxy respondents for adults with ID vs. the general population (Haider et al., 2013); adults with ID vs. the general population (Haveman et al., 2011); ID community sample vs. Medicaid and privately-insured groups (McDermott et al., 1997); proxy reports by carers of adults with ID vs. a general population health survey (McGuire et al., 2007); and ID group vs. the general population (Robertson et al., 2000). See Table 2 for further details.


Prevalence of illicit drug use in ID


Twenty-one studies were included (Table 3). Studies were set in the UK (6: Chaplin et al., 2011; Emerson & Brigham, 2013; Hassiotis et al., 2008; 2011; Plant et al., 2011; Taggart et al., 2006), US (6: Gress & Boss, 1996; Larson, Lakin, & Huang, 2003; McDermott et al., 1997; McGillicuddy & Blane, 1999; Westermeyer et al., 1988; Westermeyer, Kemp, & Nugent, 1996), Netherlands (3: Didden et al., 2009; VanDerNagel et al., 2011; 2014), Australia (2: McGillivray & Moore, 2001; McGillivray & Newton, 2016), Belgium (1: Swerts et al., 2017), Finland (1: Männynsalo et al., 2009), India (1: Kishore, Nizamie, Nizamie, & Jahan, 2004), and Serbia (1: Žunić-Pavlović et al., 2013).

Samples were predominantly majority male (not reported in 4 studies), ranging from 38% (McDermott et al., 1997) to 94% (Hassiotis et al., 2011) with a mean of 69% male (SD 16). Mean age (not reported in 7 studies) was 32 years (SD 8) ranging from 15.6 (Žunić-Pavlović et al., 2013) to 45 years (Swerts et al., 2017). One study (Swerts et al., 2017) reported an upper age range of 77 years. Mean sample size was 301 (SD 527), ranging from 30 (McGillivray & Moore, 2001) to 2200 (VanDerNagel et al., 2014). One study (Larson et al., 2003) reported on a cohort with data collected in 1994; the most recent data collection date was 2012 (Emerson & Brigham, 2013). Sixteen studies did not report dates of data collection; the most recent of these was published in 2017 (Swerts et al., 2017). Six studies reported illicit drug prevalence data set against non-ID comparison groups (Emerson & Brigham, 2013; Gress & Boss, 1996; Hassiotis et al., 2008; 2011; Larson et al., 2003; McDermott et al., 1997).

Studies used varied definitions of ID (see Table 3). Severity of ID (where reported) ranged from borderline/mild to profound with IQ (where reported) ranging from 85 to less than 20. Five studies (Hassiotis et al., 2011; Männynsalo et al., 2009; McGillivray & Moore, 2001; McGillivray & Newton, 2016; Plant et al., 2011) reported on ID cohorts with criminal justice system involvement and the cohorts of 4 studies (Didden et al., 2009; Taggart et al., 2006; Westermeyer et al., 1988; 1996) had defined substance use problems.


Prevalence of illicit drug use. Classified by individual substance, time period of use, and dependence, creating a mostly inconsistent pattern of results from heterogeneous studies (see Table 3).

For cannabis: current use prevalence had a mean of 5% from 4 studies (SD 4, range 1.6% in adults with mild to moderate ID: Swerts et al., 2017 to 9.5% in the 70-85 IQ group: VanDerNagel et al., 2011); last month use prevalence was a mean of 16% from 3 cohorts (SD 2, range 13.8% in developmentally-handicapped students: Gress & Boss, 1996 to 17.8% in severely-behaviourally handicapped students: Gress & Boss, 1996); and last-year/ lifetime use prevalence was a mean of 38% from 4 studies (SD 31, range 4% in adolescents with mild ID: Žunić-Pavlović et al., 2013 to 67% in prisoners with ID: McGillivray & Newton, 2016).

Current opiate use prevalence was reported amongst 2 cohorts in the same study (0% in the 70-85 IQ group: VanDerNagel et al., 2011; and 2.3% in the 50-70 IQ group: VanDerNagel et al., 2011) with a mean of 1% (SD 2); last-year/ lifetime use prevalence was reported by two studies (1.6% in mild to moderate ID: Swerts et al., 2017) and 40% (prisoners with ID: McGillivray & Newton, 2016) with a mean of 21% (SD 27).

One study used stimulant use as a category, reporting a current use prevalence of 6.8% and 23.8% in 2 cohorts (IQ 50-70 and IQ 70-85, respectively: VanDerNagel et al., 2011) with a mean of 15% (SD 12). Other studies reported stimulant drug use individually. For amphetamines, mean last-month use prevalence was 5% (SD 2) from 3 cohorts in the same study (range 2.5% in students with a developmental handicap to 6.5% in specific learning disabled students: Gress & Boss, 1996); mean past-year/ lifetime use prevalence was 25% (SD 22) from 4 studies (range 3.3% in mild to moderate ID: Swerts et al., 2017) to 52% (prisoners with ID: McGillivray & Newton, 2016). For cocaine, mean current/ last-month use prevalence was 3% (SD 2) across 4 cohorts from 2 studies (range 1% in an ID group referred to mental health services: Chaplin et al., 2011) to 4.3% (specific learning disabled students: Gress & Boss, 1996); mean past-year/ lifetime use prevalence was 10% (SD 7) from 4 studies (range 3.3% in adolescent offenders with mild ID: McGillivray & Moore, 2001) to 20% (mild ID with substance abuse: Westermeyer et al., 1988). One study also reported a lifetime use prevalence of 0.8% for ecstasy (mild to moderate ID: Swerts et al., 2017).

Two studies considered illicit drug use in general, reporting last-month use of illicit drugs as 4% (mild to moderate ID: McGillicuddy & Blane, 1999) and lifetime drug use prevalence as 85% (prisoners with ID: Hassiotis et al., 2011).

Prevalence of illicit drug misuse. For individual illicit drugs, mean current cannabis misuse prevalence was 21% (SD 20) from 5 studies (range 1.6%: SUD in mild to borderline ID: VanDerNagel et al., 2014) to 51% (dependence in prisoners with ID: Hassiotis et al., 2011). Mean cocaine misuse prevalence was 3.5% (SD 3) from 3 studies (range 1.5%: DSM misuse in substance users with ID: Taggart et al., 2006 to 7%: ICD dependence in an inpatient forensic ID sample: Plant et al., 2011). Two studies reported opiate misuse prevalence with a mean of 6% (SD 8) (0.14% identified by staff in mild to borderline ID: VanDerNagel et al., 2014 and 11% ICD dependence in adults treated by a forensic service: Plant et al., 2011). Misuse prevalence of ecstasy (4%), amphetamine (1.5%) and solvents (1.5%) were reported in single cohorts from the same study (DSM misuse in substance users with ID: Taggart et al., 2006). A further single cohort had a misuse prevalence of 0.18% for benzodiazepines (identified by staff in mild to borderline ID: VanDerNagel et al., 2014). Two further studies reported stimulant misuse prevalence with a mean of 4% (SD 5) (0.59% identified by staff in mild to borderline ID: VanDerNagel et al., 2014 and 8% ICD dependence in adults treated by a forensic service: Plant et al., 2011).

Studies reporting the prevalence of current illicit drug misuse (in general) gave a mean of 16% (SD 23) from 9 studies (range 0.5% substance abuse determined by family physician: McDermott et al., 1997 to 68% DSM/ICD dependence in offenders with ID: Männynsalo et al., 2009). Rather than presenting illicit drug misuse prevalence, a further study reported that 6% of a treated substance-using cohort had ID (Westermeyer et al., 1996).

Comparisons. Two studies reported similar illicit drug use prevalence in ID and non-ID samples: no statistically significant differences on last-month use prevalence of cannabis, cocaine or amphetamine in ID students vs. non-ID students (Gress & Boss, 1996); and no statistically significant differences on lifetime drug use prevalence in prisoners with ID vs. non-ID prisoners (Hassiotis et al., 2011).

Five further studies compared illicit drug misuse prevalence between ID and non-ID samples: one reported a lower misuse prevalence rate in the ID group (0.5% substance abuse vs. 12.6% and 6.8% in two non-ID groups: McDermott et al., 1997). Four studies found higher misuse prevalence among ID versus non-ID samples: higher current drug abuse prevalence in parents with ID vs. parents with no ID (Emerson & Brigham, 2013); higher past-year prevalence of drug dependence in adults with borderline ID vs. adults without ID (Hassiotis et al., 2008); higher cannabis dependence prevalence in prisoners with ID vs. non-ID prisoners (Hassiotis et al., 2011); and higher rate of past-year substance misuse treatment receipt in adults with ID and developmental disabilities vs. adults with functional limitations but no ID (Larson et al., 2003). See Table 3 for further details.


Discussion

Summary

A systematic review of available literature identified relevant studies reporting the prevalence of tobacco smoking (n=22 studies); alcohol use and misuse (n=28); and illicit drug use and misuse (n=21) in people with an Intellectual Disability (ID). A wide range of prevalence data were reported from heterogeneous cohorts using varying definitions. Data point to a mean current alcohol use prevalence of 23% (SD 17) and misuse of 27% (SD 29). Tobacco smoking had a mean prevalence of 18% (SD 19). The highest mean prevalence rate of current illicit drug use was for the category of stimulants (15%, SD 12); the highest mean misuse prevalence rate was for cannabis (21%, SD 20).

Equivocal findings were observed in comparisons of ID with non-ID cohorts in the same study. It was impossible to derive conclusions as to whether prevalence rates were consistently higher, lower, or the same in ID versus non-ID samples. Review data suggest a lower prevalence of current alcohol use (vs. 62.5%; NHS Digital, 2016a), a higher prevalence of alcohol misuse (vs. 4.5%; NHS Digital, 2016a), and a similar prevalence of tobacco use (vs. 15.5%; NHS Digital, 2016b) in ID samples when compared with the general population, although studies were too heterogeneous to derive conclusive findings from pooling rates from included studies.

Limitations

Non-peer-reviewed published studies were not included; this omission could have introduced bias, although the inclusion of potentially less robust non-peer-reviewed data could have served to introduce even greater heterogeneity into the review. Meta-analysis was not used to pool prevalence data due to the obvious heterogeneity of included studies in definitions of ID used, together with varying definitions of substance use and misuse being applied.

This review did not include the overuse or misuse of prescribed medications, such as opiate painkillers, which would be a useful and informative separate review in this population. The rate of prescription of psychoactive medications for the management of challenging behaviours in ID remains an obvious concern with the potential for harmful patterns of use, which could develop into misuse behaviour.

The methodological quality of included studies was mixed with variation in criteria used to establish both the presence of ID and the use, misuse and dependence of substances. A number of the substance type categories for the prevalence of use and misuse were derived from a small number of cohorts. This means that caution needs to be attached to some figures, for example, lifetime use of illicit drugs of 85% in a single cohort (Hassiotis et al., 2011: prisoners with ID). More reliable data, pooled from a greater number of cohorts, characterises figures for the prevalence of current alcohol use (23% from 17 cohorts), alcohol misuse (27% from 18 cohorts) and current tobacco use prevalence (18% from 30 cohorts). Prevalence rates of illicit drug use appear similar or higher than general population rates but these categories were derived from a small number of cohorts and may be unrepresentative.

Studies were carried out across a large number of countries and represent findings reported over more than three decades. A variety of cohorts were examined in included studies, for example, prisoners (Hassiotis et al., 2011; McGillivray & Newton, 2016) and offenders (Lindsay et al., 2013; Männynsalo et al., 2009; McGillivray & Moore, 2001) with ID and cohorts with ID in receipt of psychiatric care (Chaplin et al. 2011; Hymowitz et al., 1997; Pezzoni & Kouimtsidis, 2015; Plant et al., 2011); in addition to community-based samples (Emerson & Brigham, 2013; Krishef, 1986; Nettelbladt et al., 2009); students in special education settings (Gress & Boss, 1996; Žunić-Pavlović et al., 2013) and groups with defined substance use problems (Taggart et al., 2006; Westermeyer et al., 1988). A wide range of ID was reported in included cohorts, ranging through the whole spectrum of difficulties, from borderline/mild to profound, with reported IQ from 85 to less than 20. Inherent difficulties pooling evidence from studies using varying definitions of ID has previously been highlighted as a common challenge (Day et al., 2016; Huxley et al., 2005).

Some studies used recognised diagnostic categories to assess substance use/ misuse prevalence rates, for example, DSM criteria (Nettelbladt et al., 2009), ICD criteria (Plant et al., 2011), or AUDIT score (Hassiotis et al., 2008). Others used proxy reports, for example, from carers (McGuire et al., 2007); support staff (VanDerNagel et al., 2011), clinicians (McDermott et al., 1997) or self-report (McGillivray & Moore (2001). Acceptable levels of agreement concordance between self-report and objective measures of drug use have been found in substance users (Darke, 1998) although the extent to which this holds for users with ID has not been explored in detail.

Interpretation

Research points to a prevalence of approximately 6% of treated substance users having ID (VanDerNagel et al., 2014; Westermeyer et al., 1996). This suggests a slight over-representation in treatment vs. general populations. One reason for this is that although substance use rates may be lower in ID compared with non-ID groups, the risk of developing a substance-related problem may be greater (Chapman & Wu, 2012; McGillicuddy, 2006). For example, others have concluded that signs of problematic use can develop in substance users with ID at lower doses than is seen in non-ID substance users (Westermeyer et al., 1988).

Studies included in this review point to a number of correlates of substance use and misuse in ID: being male (Chaplin et al., 2011; Taggart et al., 2006; Žunić-Pavlović et al., 2013); having a milder ID (Chaplin et al., 2011; McGillicuddy & Blane, 1999; Robertson et al., 2000; Taggart et al., 2006); having criminal justice system involvement (Chaplin et al., 2011); and having a mental health problem (Didden et al., 2009; Taggart et al., 2006). ID subgroups characterised by a combination of these factors appear to be at particular risk of problematic substance use, for example, predominantly male offenders with mild ID (McGillivray & Moore, 2001; Männynsalo et al., 2009) or predominantly male individuals with mild ID together with a psychiatric diagnosis (Pezzoni & Kouimtsidis, 2015). Setting also played a role, with people in less restrictive settings being more likely to smoke (Robertson et al., 2000; Taggart et al., 2006) and smokers also being more likely to live with someone who smoked than non-smokers (Whitaker & Hughes, 2003). Alcohol use, daily drinking and tobacco smoking were more common in older than younger age groups (Haveman et al., 2011; VanDerNagel et al., 2011) and interactions were observed between patterns of harmful behaviours, such as misusers of alcohol also smoking more cigarettes than users of alcohol (McGillicuddy & Blane, 1999).

Limited information was available on receipt of substance misuse or smoking cessation treatment by people with ID or on treatment outcomes in this group. Larson et al. (2003) reported that women with ID in their sample were 2.3 times less likely to have received services for alcohol or drug abuse than men. McGillivray and Moore (2001) highlighted that only 6.7% of their offender ID cohort had ever received treatment.

Future work

Integration of the evidence base on substance use in ID requires better reporting standards. As a minimum, ID status and the presence and severity of substance use/misuse need to accord with accepted definitions, e.g. ICD or DSM. Future work is required that focuses on two main areas: raising awareness of substance use and misuse in ID; and the evaluation of interventions tailored to the particular needs of this population. The prevalence of substance misuse may, indeed, be lower in ID compared with non-ID cohorts - this review has been unable to provide definitive conclusions - but the risk of developing a substance-related problem among ID substance users is comparatively high (McGillicuddy, 2006). The development of evidence-based messages to communicate the risks associated with substance use to individuals with ID could be evaluated via a pre/post knowledge test. Additionally, there is the need for awareness raising and training of healthcare professionals who may come into contact with those with ID about the potential for substance use related harms in this group.

Few studies have examined the effectiveness of either standard or tailored treatment for substance use or misuse in ID (McGillicuddy, 2006). There are limited specialist services for substance users with ID and typically generic adult services are accessed. Specifically for tobacco smoking, cessation programmes with an emphasis on health education and nicotine replacement therapies (NRT) may be more effective in ID (Chester, Green, & Alexander, 2011; Tracy & Hosken, 1997) but are not routinely offered. Specialist ID addiction services have the potential to remove perceived barriers to access for those seeking treatment, whilst addressing unmet need in this patient population. A service reconfiguration, comprising joint working between specialist substance misuse and ID services would promote successful integration of services for this cohort and could improve outcomes. In particular, interventions tailored to meet the needs of ID subgroups at highest risk of problematic substance misuse require evaluation. Such specialist interventions should focus on males with mild ID together with CJS involvement and/or mental health conditions.

Tailored interventions need to take account of cognitive difficulties and their impact on understanding and interpreting health messages (Hemmingsson et al., 2008). Kouimtsidis et al. (2017) have recently published the EBI-LD manual for extended brief intervention for alcohol misuse specifically for adults with mild to moderate intellectual disabilities living in the community. Substance use may reduce anxiety and tension in ID (Wills & Hirky, 1996) pointing to the possible under-diagnosis of mental health problems and potential benefits from strategies to improve coping in this group. Long-term follow-up data on treatment received, treatment outcomes and post-treatment function would be informative.

Conclusion

This review highlights the lack of quality prevalence data amongst this cohort. One explanation is the limited numbers of people with ID accessing substance misuse treatment. From the available evidence it is clear that people with ID do use substances. The evidence is consistent with the conclusion that people with intellectual disabilities have access to, and use, substances problematically; particularly certain ID subgroups. The uncertainty about what types of substance are used, the severity of use and subsequent dependency rates is unlikely to be resolved by examination of the studies presented here. There is sufficient evidence to consider substance use as a health concern amongst people with ID. Future longitudinal studies are needed to estimate prevalence rates, protective factors and risk factors for substance use in ID, such as the wider determinants of poor health in this group (Robertson et al., 2014), together with treatment outcomes and factors associated with successful treatment.

Funding sources

This research did not receive any specific grant from funding agencies in the public, commercial, or not-for-profit sectors.

Declaration of interest

Karen P. Hayhurst has received grant research funding from Change, Grow, Live (CGL), a third-sector provider of substance misuse services. Other authors declare no interests.

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DRAFT

DRAFT

Table 1. Included studies: prevalence of alcohol use.

Study

Country

Study Population

(Sample size & Description)

Age (years)

Gender

Comparison Group

Findings

Study dates

Quality rating4

Chaplin et al. (2011)

UK

N=115

Definition: ICD-10 - ID referred to specialist mental health services

M=40 (SD 13)

64% Male

None

11% (13/115) current recreational alcohol use

6% current heavy alcohol use

Definition: DSM-IV recreational/occasional & heavy/continuous

Not reported published in 2011

7

Didden et al. (2009)

Netherlands

N=39

Definition: mild to borderline ID admitted for treatment of behavioural/ emotional problems

SU group IQ Mean 70 (48-80)

Non SU group IQ Mean 68 (48-84)

M=30

Range 21–46

Not reported

None for prevalence data

11/39 (28%) alcohol abuse

Definition: >14 units for Fs/ > 21 units for Ms per week

1995-2005

6

Emerson & Brigham (2013)

UK

Data collected in 3 PCTs1 covering 46,023 households with a child under 5 – size of sample with ID not reported

Definition: learning difficulties that required or still require additional educational support

Not reported

Not reported

Parents with no ID and a child under 5

14% current alcohol abuse vs. 7% without ID (single parent with ID)

12% current alcohol abuse vs. 1% without ID

(2 parents with ID)

Statistical analysis of differences between groups not presented

Definition: not reported

2008-2012

6

Fortuna et al. (2016)

US, Italy & Israel

N=255

Definition: confirmed upon manual chart abstraction. Autism Spectrum Disorder 50% had ID (IQ<70)

M=34

75% Male

General population

0.9% vs. 11.9% (lifetime) alcohol misuse (18-29yrs: p<0.001)

0% vs. 15.1% (lifetime) alcohol misuse (30-39yrs: p<0.001)

1.4% vs.18.2% (lifetime) alcohol misuse (>40yrs: p<0.001)

Definition: time in life when drank 4 or more alcoholic drinks almost every day


5

Gress & Boss (1996)

US

N=371

Definition: in receipt of special education - severely behaviourally handicapped (SBH), specific learning disabled (SLD) and developmentally handicapped (DH) and “regular students”)

Not reported – students in special schools

Not reported

N=3743 not in special education

39.5% (SLD) & 35.5% (DH) & 44.7% (SBH) vs. 46% (High School students: no sig differences between groups) alcohol use last 30 days


5

Haider et al. (2013)

Australia

N=897

Definition: adults with ID: proxy respondents - previously sought assistance (26% mild; 47% mod; 22% severe; 5% profound ID

M=38

55.5% Male

N=34,168 (general population)

People with ID statistically more likely to abstain from alcohol (65.8% vs 18% general population)

2009

6

Hassiotis et al. (2008)

UK

N=1040

Definition: DSM IV IQ range between 1 & 2 SDs below the mean (70–84). Adults with borderline ID

25% 16-24

35% 25-44

40% 45-74

52% Male

N=7410 adults without ID

Greater alcohol dependence = combined AUDIT2 & SAD-Q3 score = 9.5% for borderline ID group vs. 6.4% (p<0.01)

Definition: AUDIT score of 10 or more, dependence over last 6m

2000

8


UK

N=170

Definition: IQ ≤ 65. Prisoners with ID

38% 16-20

41% 21-29

15% 30-39

5% 40+

94% Male

N=2630 (prisoners with no ID)

No statistically significant differences between groups on AUDIT score (32.9% score of 16+ vs. 31.2%, p=0.7)


8

Haveman et al. (2011)

14 European countries

N=1,253

Definition: adults with ID: mild 22.7%; moderate 28.2%; severe 20.7%; profound 11.8%; NK 16.6%

M=41

Range 19-90

51% Male

None

9.8% drink at least 1 day per week

1.9% drink every day

2005-2008

8

Krishef (1986)

US

N=214

Definition: adults with ID - “mentally retarded persons in the community” (no further details)

Mean not presented

86% 18-45

54% Male


52% lifetime alcohol prevalence

25% current drinkers

1984

4

Lindsay et al. (2013)

UK

N=477

Definition: referred to forensic ID services: IQ 70 + 2 standard errors

Not reported

Not reported

None

20.8% history of alcohol abuse (range from 9.6% in community services to 49.5% in low/med secure services)

Definition: recorded in case notes (no further details)

5.9% (overall) alcohol-related crime

2001/02

6

Männynsalo et al. (2009)

Finland

N=44

Definition: offenders with ID: mild ID IQ 51-75: 84%; moderate ID IQ 36-50: 14%, severe 2%

M=35 (SD 13)

Range 17-69

82% Male

None

45% diagnosis of alcohol abuse/dependence

Definition: DSM and ICD

1996-2006

7

McGillicuddy & Blane (1999)

US

N=122

Definition: “mental retardation” (mild/moderate ID) mean IQ: 64

M=27

49% Male

None

39% past month alcohol use


8

McGillivray & Moore (2001)

Australia

N=30

Definition: adolescent offenders with mild ID: clients of the State-wide Forensic Program in Victoria, Australia. Mild ID not defined

M=30

Range 20-46

90% Male

N=30 (matched non-offending adolescents with mild ID) M=31.1yrs

26.7% prevalence of daily alcohol use (just beer) vs. 3.3% non-offenders (p<0.05)

Definition: 12m period prior to programme

Not reported published 2001

4

McGillivray & Newton (2016)

Australia

N=33

Definition: prisoners with ID: “established diagnosis if ID”: no further details

M=27.5

Range 19-47

91% Male

None

94% past 12m alcohol use

57.6% alcohol dependence

Definition: 12m period prior to sentence; dependence: 16+ on AUDIT


8

McGuire et al. (2007)

Ireland

N=157

Definition: proxy reports from main carers of adults with ID: diagnostic data from the National Intellectual Disability Database (NIDD): 14% mild IQ 50-69; 64% mod IQ 35-49; 13% Sev IQ 20-34; 9% profound IQ <20

M=37 (SD 12)

53.5% Male

General population health survey

10.3% daily to weekly alcohol consumption vs. 74.3% 1-3 times per week general population

Definition: proxy reports from carers


6

Nettelbladt et al. (2009)

Sweden

N=52

Definition: community ID sample: DSM. 58% mild (50-70); 27% mod (35-55); 13% severe/profound (20-40/<20); 2% NK

Median 61

Range 42-82

63% Male

No comparison for substance use

1.9% prevalence of alcohol abuse

Definition: DSM-IV diagnosis

1947-1997

7

Pezzoni & Kouimtsidis (2015)

UK

N=40

Definition: mild ID with a psych diagnosis +/or behaviour problems: community ID team providing secondary care services

Mean not reported

Range 22-60

75% Male

None

22.5% past year alcohol use disorder

Definition: score of >8 on AUDIT

2009-2010

8

Plant et al. (2011)

UK

N=74

Definition: inpatient forensic service for ID ICD-10 – no further details

Median=29

Range 18‐57

73% Male


41% harmful use/dependence on alcohol

Definition: ICD-10


8

Rimmer et al. (1995)

US

N=329

Definition: diagnosis of mild to severe mental retardation IQ up to 75 across different settings

Mean not reported

Range 17-70

56.5% Male

None

<5% consumption of alcohol

Definition: proxy completion


4

Robertson et al. (2000)

UK

N=500

Definition: people with ID in residential settings (35%-47% autism) no details re IQ

M=40; 45.5; 47.5 (3 groups)

59%; 60%; 62% Male (3 groups)

General population (only for high alcohol use)

Males 27%; 50%; 55% low alcohol use

Males 0% high use vs. 30% in gen pop

Females 4%; 18%; 24% low alcohol use

Females 0% high use vs. 15% in gen pop

Definition: low use 1-10 units/week for Males; 1-7 units/week for Females. High use >21 units/weeks for Males; >14 units/week for Females


8


UK

N=520

Definition: self-reported long-term intellectual impairments coexisting with low self-reported educational attainment

Mean not reported

Range 16–49

Not reported

no ID in same sample

9.4% self-reported daily alcohol use vs. 4.7% (no ID) p<0.01

Wave 1 2009-2011; dates of wave 2 not reported published in 2014

8

Swerts et al. (2017)

Belgium

N=123

Definition: American Association on Intellectual and Developmental Disabilities (AAIDD) mild (90%) to moderate (10%) ID (IQ<70) receiving support from independent living services

M=45 (SD 12)

Range 22-77

49% Male


92.7% lifetime prevalence of alcohol

45.5% current alcohol use

11% of current (N=45) drinkers alcohol dependent

Definition: informant reports. Current=past month. Dependence ≥ 20 on AUDIT


8

Taggart et al. (2006)

UK

N=67

Definition: substance users with IDs (borderline 16.4%; mild 58.2%; moderate 25.6% ICD-10 criteria)

Not reported

61% Male

none

100% alcohol misuse

Definition: proxy reports using DSM-IV criteria


8

VanDerNagel et al. (2011)

Netherlands

N=86

Definition: mild or borderline ID IQ 50-85 - case reports of most recent instances of substance use problems - proxy data provided by staff

M=30 (SD 12) of 86 case reports

81% Male (of 86 case reports)


Alcohol use: 32.6% (total sample); 19% (IQ 70-85); 45.5% (IQ 50-70) p=0.009

Definition: proxy data provided by staff


6

VanDerNagel et al. (2014)

Netherlands

N=2200

Definition: people with ID attending services mild to borderline IQ 50-85

M=38 (SD 13.5)

N=88 with SUD

76% Male

None

3% of ID sample had alcohol use disorder

Definition: identified by staff


7

Westermeyer et al. (1988)

US

N=40

Definition: mild ID “mentally retarded” IQ 50-70 with substance abuse (DSM-III)

M=32.2 (SD 7.2)

Range 19-48

67.5% Male

N=40 matched controls with mild ID but without substance use

100% lifetime prevalence of alcohol use vs. 85% ID but no substance use


7

Žunić-Pavlović et al. (2013)

Serbia

N=100

Definition: adolescents with mild ID IQ 50-69 ICD-10 attending special schools

M=15.6 (SD 1.7)

M=15.6 (SD 1.8)

Range 13–20

63% Male

None

63% lifetime alcohol prevalence rate

14% past month alcohol prevalence rate


5

Notes: 1 PCT: Primary Care Trust. 2 AUDIT: Alcohol Use Disorders Identification Test. 3 SAD-Q: Severity of Alcohol Dependence Questionnaire. 4 Based on Munn et al. (2014)

Table 2. Included studies: prevalence of tobacco use.

Study

Country

Study Population

(Sample size & Description)

Age (years)

Gender

Comparison Condition

Findings

Study dates

Quality rating3


UK



Not reported

Not reported


52% current smokers vs. 40% without ID (single parent with ID)

52% current smokers vs. 20% without ID (2 parents with ID)

Statistical analysis of differences between groups not presented

2008-2012

6

Emerson & Hatton (2008)

UK

N=2898

Definition: 46% mild/mod (if answered most of Qs themselves), 47% severe (remainder), 7% profound (CSCI2 definition)

Not reported

Not reported

None

19% smoke cigarettes

Higher rate among people with mild/moderate LD (30%) than severe LD (11%) and profound and multiple LD (4%)

2003/04

5

Fortuna et al. (2016)

US, Italy & Israel

N=255 with Autism Spectrum Disorder

50% had ID (IQ<70)

Definition: confirmed upon manual chart abstraction

M=34

75% Male

General population

5.2% vs. 31.9% current smokers (18-29yrs: p<0.001)

3% vs. 27.5% current smokers (30-39yrs: p<0.001)

2.8% vs.24.5% current smokers (>40yrs: p<0.001)

Definition: tobacco/ nicotine use in last 5 days


5

Gress & Boss (1996)

US

N=371 in special education (severely behaviourally handicapped (SBH), specific learning disabled (SLD) and developmentally handicapped (DH) and “regular students”)

Definition: in receipt of special education


Not reported


30.5% (SLD) & 26.9% (DH) & 31.5% (SBH) vs. 28.3% (High School students: no sig differences between groups) tobacco use last 30 days


3

Haider et al. (2013)

Australia

N=897 (adults with ID: proxy respondents

Definition: previously sought assistance (26% mild; 47% mod; 22% severe; 5% profound ID)

M=38

55.5% Male

N=34,168 (general population)

5.7% current smokers vs. 19.1% general population (significant difference)

2009

6

Haveman et al. (2011)

14 European countries

N=1,253 (adults with ID)

Definition: mild 22.7%; moderate 28.2%; severe 20.7%; profound 11.8%; NK 16.6%

M=41

Range 19-90

51% Male

general population of 27 European countries

6%=daily smoker vs. 28.3% in general population

2005-2008

8

Havercamp et al. (2004)

US

N=946

Definition: developmental disability (91% ID - 39% mild; 27% mod; 15% severe; 11% profound)

47.5% 18-34

43% 35-54

9% => 55

56% Male

N=4358 no disabilities

17.8% (CI 14.9, 20.7) smoked cigarettes vs. 24.8% (CI 22.8, 26.9 no disabilities = not stat sig difference

2000-2002

8

Hemmingson et al. (2008)

Sweden

Total N=49,321

Definition: 1969 Swedish conscription survey: N of low IQ (bottom percentile) group not reported (IQ<74 to 89)

born 1949 to 1951

100% Male

N of high IQ group (111 to >126) not reported

Prevalence of smoking higher in low IQ (<74 to 89) vs. high IQ (111 to >126) group at all levels of years of education – largest difference for 12 years of education (9 is compulsory) = 62.9% low IQ group vs. 49.1% high IQ group

1969 & 1981-2002

4

Hymowitz et al. (1997)

US

N=136

Definition: adults with comorbid diagnoses of mental retardation and mental illness: 6% borderline; 47% mild; 28% moderate; 19% severe

M=35

Range 18-69

57% Male

None

18% current cigarette smokers

Mild retardation 30%

Borderline retardation 37%

Severe & moderate <10%

1994

3

McDermott et al. (1997)

US

N=366

Definition: living in the community with ID: borderline 1%; mild 30%; moderate 19%; severe 31%; profound 19%

M=40 (SD 11)

Range 19-64

38% Male

N=427 (Medicaid) and N=746 (privately-insured) without ID

3.3% chronic smoker rate vs. 13.1% (Medicaid) and 8.8% (Insured) in 2 comparison groups (both p<0.05)


5


US

N=122 (mild/moderate ID)

Definition: “mental retardation”; mean IQ: 64

M=27

49% Male

None

23% past month tobacco use


8

McGuire et al. (2007)

Ireland

N=157 (main carers of adults with ID)

Definition: diagnostic data from the National Intellectual Disability Database (NIDD): 14% mild IQ 50-69; 64% mod IQ 35-49; 13% Severe IQ 20-34; 9% profound IQ <20

M=37 (SD 12)

53.5% Male

General population health survey

Prevalence of smoking=2.6% vs. 24% general population survey

Definition: proxy reports from carers


7

Pezzoni & Kouimtsidis (2015)

UK

N=40

Definition: mild ID with a psych diagnosis +/or behaviour problems: community ID team providing secondary care services

Mean not reported

Range 22-60

75% Male

None

35% current smokers

2009-2010

8

Rimmer et al. (1995)

US

N=329

Definition: diagnosis of mild to severe mental retardation IQ up to 75

Mean not reported

Range 17-70

56.5% Male

None

<10% current smokers

Definition: proxy completion


4


UK

N=500

Definition: people with ID in residential settings (35%-47% autism) no details re IQ

M=40; 45.5; 47.5 (3 groups)

59%; 60%; 62% Male (3 groups)

General population**

Between 2% and 12% any smoking (3 groups = 2%; 8%; 12%) vs. 30% (male); 27% (female) gen pop


8


UK

N=520

Definition: self-reported long-term intellectual impairments coexisting with low self-reported educational attainment

Mean not reported

Range 16–49

Not reported

No ID in same sample

55.7% current smoker vs. 26.2% (no ID) p<0.001

Wave 1 2009-2011; wave 2 not reported published in 2014

8

Swerts et al. (2017)

Belgium

N=123

Definition: American Association on Intellectual and Developmental Disabilities (AAIDD) mild (90%) to moderate (10%) ID (IQ<70) receiving support from independent living services

M=45 (SD 12)

Range 22-77

49% Male

Some comparisons with current non users

48% current (past month) tobacco use

77% lifetime prevalence of tobacco use


8

Taylor et al. (2004)

UK

N=435

Definition: adults with learning disabilities attending 4 social services day centres in a large urban area: mild 27%; mod 36%; severe 33%; profound 4%

M=37 (SD 12)

53% Male

None

6.2% current smokers (overall)

Mild 9.3%; mod 8.4%; severe 2.1%; profound 0%

1998

4

Tracy & Hosken (1997)

Australia

N=36

Definition: people with ID living independently

Mean not reported

69% <35

50% Male

general Victorian adult population

36% current smoking prevalence (39% men, 33% women) vs. 26% in general population


6

Westermeyer et al. (1988)

US

N=40

Definition: mild ID “mentally retarded” IQ 50-70 with substance abuse (DSM-III)

M=32 (SD 7)

Range 19-48

67.5% Male

N=40 matched controls with mild ID but without substance use

82.5% lifetime prevalence of tobacco use vs. 35% ID but no substance use


5

Whitaker & Hughes (2003)

UK

N=581

Definition: people with LD attending special education facilities: borderline to severe

Not reported

Not reported

1.89% overall smoking prevalence rate


6

Žunić-Pavlović et al. (2013)

Serbia

N=100

Definition: adolescents with mild ID IQ 50-69 ICD-10 attending special schools

M=15.6 (SD 1.7)

M=15.6 (SD 1.8)

Range 13–20

63% Male

None

49% lifetime smoking prevalence rate

34% past month smoking prevalence rate


5

Notes: 1 PCT: Primary Care Trust. 2 CSCI: Commission for Social Care Inspection (2006). 3 Based on Munn et al. (2014). * World Health Organization Regional Office for Europe (2010). ** Department of Health (1998). *** Substance Use and Misuse in Intellectual Disability—Questionnaire.

Table 3. Included studies: prevalence of illicit drug use.

Study

Country

Study Population (Sample size & Description)

Age (years)

Gender

Comparison Condition

Findings

Study dates

Quality rating2

Chaplin et al. (2011)

UK

N=115

Definition: people with ID referred to specialist mental health services: ICD-10

M=40 (SD 13)

64% Male

None

3% current recreational cannabis use

1% current recreational cocaine use

1% other (includes heroin, solvents, ecstasy) recreational use

3% current heavy cannabis use

2% current heavy cocaine use

1% other (includes heroin, solvents, ecstasy) heavy use

Definition: DSM-IV recreational/occasional & heavy/continuous


7

Didden et al. (2009)

Netherlands

N=39

Definition: mild to borderline ID with behavioural/ emotional problems: SU group IQ Mean 70 (48-80); non SU group IQ Mean 68 (48-84)

M=30

Range 21–46

Not reported (comparable with non-user group)

None (N=21 matched non-substance abusers)

36% (14/39) drug abuse (e.g. cannabis) – no further details provided

Definition: having emotional/behavioural problems resulting from drug use

1995-2005

6


UK



Not reported

Not reported


15% current drug abuse vs. 7% without ID (single parent with ID)

9% current drug abuse vs. 1% without ID (2 parents with ID)

Definition: not reported

2008-2012

5

Gress & Boss (1996)

US

N=371

Definition: in receipt of special education: severely behaviourally handicapped (SBH), specific learning disabled (SLD), developmentally handicapped (DH)


Not reported


16.5% (SLD) & 13.8% (DH) & 17.8% (SBH) vs. 16.5% (High School students: no sig differences between groups) marijuana use last 30 days

4.3% (SLD) & 1.5% (DH) & 3.9% (SBH) vs. 3.2% (High School students: no sig differences between groups) cocaine use last 30 days

6.5% (SLD) & 2.5% (DH) & 6.3% (SBH) vs. 8.3% (High School students: no sig differences between groups) amphetamine use last 30 days


3


UK

N=1040 (adults with borderline ID)

Definition: DSM IV IQ range between 1 & 2 SDs below mean (70–84)

25% 16-24

35% 25-44

40% 45-74

52% Male

N=7410 adults without ID

Greater dependence on any drug = 5.3% for borderline ID group vs.3.1 (p<0.01)

Definition: past year dependence

2000

8


UK

N=170

Definition: prisoners with ID: IQ ≤ 65

38% 16-20

41% 21-29

15% 30-39

5% 40+

94% Male

N=2630 (prisoners with no ID)

No statistically significant differences between groups on lifetime drug use (85% vs. 83%, p=0.65)

Cannabis dependence + frequent use 51% in ID group vs. 42% (p=0.01)


8

Kishore et al. (2004)

India

N=60

Definition: ICD-10: mild 37%; moderate 43%; severe 20%

M=21 (SD 7)

Range 12-55

77% Male

None

1.7% substance use disorder

Definition: ICD-10


4

Larson et al. (2003)

US

Total sample = c. 108,000 (48,000 households) N of study group (people with intellectual/ developmental disabilities) not reported

Not reported

Not reported

Adults with functional limitations N not reported

2.2% of those with ID/DD had received drug/ alcohol abuse services vs. 0.9% of those with FLs only

Definition: last 12m service use (proxy for dependence)

1994/95

3

Männynsalo et al. (2009)

Finland

N=44

Definition: offenders with ID: mild ID IQ 51-75: 84%; moderate ID IQ 36-50: 14%, severe 2%)

M=35 (SD 13)

Range 17-69

82% Male

None

68% diagnosis of any substance abuse/dependence

Definition: DSM and ICD

1996-2006

7

McDermott et al. (1997)

US

N=366

Definition: primary diagnosis of ID living in the community: borderline 1%; mild 30%; moderate 19%; severe 31%; profound 19%

M=40 (SD 11)

38% Male

N=427 (Medicaid recipients) and N=746 (privately-insured individuals) without ID

0.5% substance abuse rate vs. 12.6% (Medicaid) and 6.8% (Insured) in 2 comparison groups (both p<0.05)

Definition: determined by the family physician


5


US

N=122

Definition: mild/moderate ID: mean IQ 64

M=27

49% Male

None

4% past month use of illicit drugs

Definition: any substance use


8

McGillivray & Moore (2001)

Australia

N=30

Definition: adolescent offenders with mild ID (not defined)

M=30

Range 20-46

90% Male

N=30 (matched non-offending adolescents with mild ID)

23.3% daily use of marijuana vs. 0% in non-offenders (p<0.05)

10% past-year use of cocaine, amphetamines, heroin vs. 0% (p<0.05)

Definition: 12m period prior to programme


4

McGillivray & Newton (2016)

Australia

N=33

Definition: prisoners with “established diagnosis if ID”: no further details

M=28

Range 19-47

91% Male

None

Past 12m use 9% (cocaine); 67% (cannabis); 40% (opioids); 52% (amphetamines)

Definition: 12m period prior to sentence


8

Plant et al. (2011)

UK

N=74

Definition: inpatient forensic service for ID ICD-10 – no further details

Median=29

Range 18‐57

73% Male


Between 7% and 28% harmful use/ dependence

28% cannabis

11% opiates

8% stimulants

7% cocaine

Definition: ICD-10


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