Introduction
Adolescent alcohol use is an identified public health concern. Scotland’s 15-year-olds rank fifth of 41 countries in Europe for having been drunk at least twice (Inchley et al.
2016). Further, it has been estimated that 15 individuals per day aged 17 or under are admitted to Scottish hospitals intoxicated (Christie
2008; NHS Quality Improvement Scotland
2008); this equates to approximately 1707 hospital admissions per 100,000 of the population aged 13–17, annually. These patterns are of concern given the wide array of harms associated with alcohol use among adolescents.
Because initiation into alcohol use often occurs in adolescence, this life stage has been established as a crucial period to reduce drinking (Kuntsche et al.
2005). Consequently, it is important to understand the risk and protective factors associated with alcohol use in order to develop targeted public health policies (Bryden et al.
2013). Evidence suggests adolescent alcohol use varies across neighbourhoods (Fagan et al.
2015; Jackson et al.
2016). However, which specific neighbourhood characteristics underlie this variation is not fully understood (Fagan et al.
2015).
Many features of the neighbourhood have been theorised to be associated with adolescent alcohol use (Fagan et al.
2015). Studies examining neighbourhood socio-economic factors have found mixed results (Bryden et al.
2013; Jackson et al.
2014), thus implying that more research is required to examine neighbourhood social factors. Neighbourhood social conditions, such as cohesion and collective efficacy, have drawn more recent attention and are often posited to underlie the relationship between neighbourhood economic conditions and alcohol use (Fagan et al.
2013; Jackson et al.
2014). Theories of the social environment and substance use suggest that the positive bonds in society deter adolescents from substance use (Wray-Lake et al.
2012),while neighbourhoods with greater disorder may encourage alcohol use as a way of coping with environmental stress (Hill and Angel
2005). However, reviews of neighbourhood social factors and drinking behaviour among adolescents indicate varied findings (Bryden et al.
2013; Jackson et al.
2014). This may, in part, reflect equivocal measurements of the social environment (Martin et al.
2017a) and/or different drinking outcomes included in these studies.
Research examining neighbourhood characteristics and adolescent drinking typically focuses on urban environments (Bryden et al.
2013). However, adolescents’ urban/rural status has been found to associate with their alcohol use and has been theorised to contribute to geographic variation in drinking behaviours (Slutske et al.
2016). Contemporary research has shown that adolescents residing in rural areas tend to drink alcohol at higher rates than those in urban areas (Dixon and Chartier
2016; Donath et al.
2011). The mechanisms behind this are not well understood but may be due to physical and/or cultural differences that exist between these communities (Donath et al.
2012).
There has also been much interest in the associations between commercial alcohol availability and adolescent alcohol use. Bryden et al. (
2012) report that the evidence is inconclusive regarding these relationships. Increased availability may make alcohol purchasing easier through greater physical access and reduced prices, due to market competition (Shortt et al.
2018; Treno et al.
2013). However, as it is often illegal to sell alcohol to someone under a certain age, 18 in Scotland, the presence of outlets does not necessarily mean alcohol is easily available. More likely, a higher density of alcohol outlets may influence adolescent alcohol use via neighbourhood social norms and the normalisation of alcohol consumption (Kuntsche et al.
2008; Shortt et al.
2018). Maimon and Browning (
2012) found that those residing in areas with higher alcohol outlet density and lower collective efficacy had higher predicted probability of alcohol use. It is important to consider alcohol availability as an important covariate in order to avoid biased conclusions about the influence of the social characteristics of the neighbourhood on alcohol use (Mohnen et al.
2011). This is particularly relevant given that more alcohol outlets tend to be present in areas of both higher deprivation and lower social capital (Shortt et al.
2015; Theall et al.
2009).
Results from neighbourhood studies that only assess neighbourhood variation may be misleading if variation from other contexts, such as school, are ignored (De Clercq et al.
2014; Dunn et al.
2015). Studies that examined adolescent smoking, using cross-classified multilevel models to account for the influence of non-nested contexts (where individuals are nested in schools and neighbourhoods, but schools are not necessarily nested within neighbourhoods or vice versa), found that neighbourhood effects are overestimated when ignoring school-level variation (De Clercq et al.
2014; Dunn et al.
2015).
This paper aims to address the following questions:
1.
To what extent does adolescent alcohol use vary by neighbourhood?
2.
Are there associations between neighbourhood characteristics and adolescent alcohol use?
Results
Participant characteristics
Table
1 outlines the characteristics of the sample. The majority of adolescents had drunk alcohol (83%), while almost half of the respondents (45%) had been drunk twice or more. Twenty-seven per cent of the respondents were weekly drinkers.
Table 1
Descriptive statistics of the study sample from the Scottish Health Behaviour in School-aged Children survey, 2010 (n = 1558)
Demographics and family characteristics
| | | | |
Age | 1554 | 15.55 (0.33) | 13.25 | 16.67 |
Male | 1558 | 772 (50%) | | |
White | 1558 | 1515 (97%) | | |
Family affluence
| 1558 | | | |
Low | | 496 (32%) | | |
Medium | | 479 (31%) | | |
High | | 583 (37%) | | |
Family structure
| 1530 | | | |
Both parents | | 1080 (71%) | | |
Single parent | | 274 (18%) | | |
Stepfamily/other | | 176 (11%) | | |
Individual neighbourhood perceptions
| | | | |
Perceived neighbourhood disordera | 1516 | 4.92 (1.53) | 3 | 9 |
Perceived social cohesiona | 1522 | 11.98 (2.59) | 3 | 15 |
Residential characteristics
| | | | |
Neighbourhood deprivation | 1558 | | | |
1 (most deprived) | | 343 (22%) | | |
2 | | 358 (23%) | | |
3 | | 461 (30%) | | |
4 (least deprived) | | 396 (25%) | | |
Urban/rurality | 1554 | | | |
Large urban | | 263 (17%) | | |
Other urban | | 267 (17%) | | |
Accessible small town | | 193 (12%) | | |
Accessible rural | | 241 (15%) | | |
Remote small town | | 198 (13%) | | |
Remote rural | | 392 (25%) | | |
Off-trade alcohol outlets (800 m) | 1557 | 1.59 (1.87) | 0 | 14.25 |
On-trade alcohol outlets (800 m) | 1557 | 2.91 (4.17) | 0 | 38.31 |
Neighbourhood-level disorderb | 1488 | − 0.01 (0.14) | − 0.27 | 0.37 |
Neighbourhood-level social cohesionc | 1506 | 0.04 (0.25) | − 0.61 | 0.64 |
Alcohol use
| | | | |
Have ever drunk | 1550 | 1281 (83%) | | |
Drink weekly | 1553 | 414 (27%) | | |
Drunk twice or more | 1545 | 689 (45%) | | |
Empty models
For ever drank, weekly drinking, and drunkenness, neighbourhood accounts for 9.7%, 5.7%, and 3.6% of the variation, respectively, when ignoring school-level variation. This was reduced to 7.6%, 5.0%, and 1.0%, respectively, when accounting for school-level variation. For having ever drank and weekly drinking, the DIC was lowest in the cross-classified model compared to the two-level models, suggesting best fit when including both levels. For drunkenness, the DIC was only slightly lower in the cross-classified model, compared to the school-only model (see Supplementary Material).
Multivariable models
Full results of Models 1–8 for the three drinking outcomes can be found in the Supplementary Material. Models 6–7 are presented in Tables
2 and
3.
Table 2
Having ever drunk regressed on neighbourhood and individual measures from the Scottish Health Behaviour in School-aged Children survey, 2010 (95% credible intervals) (n = 1457; intermediate data zones n = 190; schools n = 152)
Sex (male) | 1.01 (0.74, 1.34) | 0.971 | 1.02 (0.75, 1.35) | 0.959 |
Age | 2.04 (1.30, 2.92) |
0.001
| 1.83 (1.37, 2.49) | < 0.001 |
Family structure (reference: both parents) | | | | |
Single parent | 1.37 (0.89, 2.04) | 0.173 | 1.31 (0.84,1.96) | 0.256 |
Stepfamily/other | 2.05 (1.16, 3.49) |
0.016
| 2.00 (1.13, 3.40) |
0.021
|
Family affluence (reference: low) | | | | |
Medium | 1.50 (1.00, 2.15) |
0.048
| 1.50 (1.00, 2.18) | 0.051 |
High | 1.51 (1.02, 2.15) |
0.036
| 1.51 (1.02, 2.16) |
0.041
|
Ethnicity (white) | 3.06 (1.31, 5.95) |
0.007
| 2.74 (1.17, 5.43) |
0.018
|
On-trade licence density | 0.97 (0.92, 1.03) | 0.307 | 0.97(0.93, 1.03) | 0.322 |
Off-trade licence density | 1.02 (0.90, 1.16) | 0.742 | 1.01 (0.88, 1.15) | 0.873 |
Urban/rurality (reference: large cities) | | | | |
Other urban | 1.47 (0.85, 2.40) | 0.181 | 1.48 (0.84, 2.44) | 0.188 |
Accessible small towns | 2.02 (1.03, 3.58) |
0.038
| 2.02 (1.04, 3.62) |
0.042
|
Accessible rural | 2.46 (1.29, 4.28) |
0.005
| 2.50 (1.31, 4.40) |
0.005
|
Remote small towns | 3.70 (1.80, 6.94) | < 0.001 | 3.83 (1.83, 7.21) | < 0.001 |
Remote rural | 3.64 (1.91, 6.37) | < 0.001 | 3.61 (1.87, 6.43) | < 0.001 |
Neighbourhood deprivation (reference: 1 most deprived) | | | | |
2 | 1.21 (0.70, 1.95) | 0.557 | 1.26 (0.73, 2.04) | 0.450 |
3 | 0.94 (0.54, 1.52) | 0.728 | 1.01 (0.58, 1.63) | 0.910 |
4 (least deprived) | 1.01 (0.57, 1.66) | 0.907 | 1.05 (0.59, 1.74) | 0.964 |
Neighbourhood social cohesion | 0.33 (0.12, 0.75) |
0.011
| 0.33 (0.10, 0.80) |
0.017
|
Neighbourhood disorder | 1.25 (0.22, 4.10) | 0.941 | 0.45 (0.06, 1.62) | 0.169 |
Perceived social cohesion | – | | 0.99 (0.93, 1.06) | 0.806 |
Perceived disorder | – | | 1.24 (1.10, 1.40) |
0.001
|
Neighbourhood variance | 0.30 (0.03, 0.66) | | 0.31 (0.04, 0.68) | |
DIC | 1302.86 | | 1291.59 | |
Table 3
Weekly drinking and drunkenness regressed on neighbourhood and individual measures from the Scottish Health Behaviour in School-aged Children survey, 2010, among those who have drank (95% credible intervals) (intermediate data zones n = 190; schools n = 152)
Sex (male) | 1.43 (1.10, 1.84) |
0.007
| 1.44 (1.10, 1.86) |
0.008
| 0.98 (0.77, 1.24) | 0.835 | 0.99 (0.77, 1.25) | 0.879 |
Age | 1.38 (0.80, 2.39) | 0.339 | 1.10 (0.75, 1.66) | 0.704 | 1.25 (0.87, 1.75) | 0.266 | 1.18 (0.79, 1.58) |
0.346
|
Family structure (reference: both parents) | | | | | | | | |
Single parent | 1.52 (1.06, 2.10) |
0.021
| 1.47 (1.02, 2.04) |
0.038
| 1.38 (0.98, 1.89) | 0.070 | 1.36 (0.96, 1.87) | 0.082 |
Stepfamily/other | 1.16 (0.76, 1.68) | 0.537 | 1.13 (0.74, 1.65) | 0.619 | 2.04 (1.36, 2.97) |
0.001
| 2.02 (1.36, 2.97) |
0.001
|
Family affluence (reference: low) | | | | | | | | |
Medium | 1.21 (0.85, 1.67) | 0.305 | 1.25 (0.87, 1.73) | 0.236 | 0.93 (0.67, 1.26) | 0.606 | 0.94 (0.68, 1.26) | 0.625 |
High | 1.23 (0.88, 1.68) | 0.241 | 1.26 (0.89, 1.72) | 0.209 | 1.28 (0.93, 1.72) | 0.132 | 1.28 (0.93, 1.71) | 0.135 |
Ethnicity (white) | 0.71 (0.28, 1.50) | 0.713 | 0.66 (0.25, 1.42) | 0.246 | 0.68 (0.26, 1.47) | 0.282 | 0.66 (0.25, 1.41) | 0.241 |
On-trade licence density | 1.00 (0.96, 1.05) | 0.938 | 1.00 (0.96, 1.05) | 0.866 | 1.03 (0.99, 1.08) | 0.180 | 1.03 (0.99, 1.08) | 0.174 |
Off-trade licence density | 1.01 (0.90, 1.13) | 0.934 | 0.99 (0.88, 1.11) | 0.876 | 1.00 (0.90, 1.11) | 0.947 | 0.99 (0.89, 1.10) | 0.850 |
Urban/rurality (reference: large cities) | | | | | | | | |
Other urban | 1.23 (0.73, 1.96) | 0.490 | 1.25 (0.72, 2.01) | 0.476 | 1.09 (0.69, 1.66) | 0.771 | 1.09 (0.69, 1.66) | 0.779 |
Accessible small towns | 2.04 (1.13, 3.42) |
0.017
| 2.08 (1.14, 3.54) |
0.016
| 2.24 (1.31, 3.61) |
0.003
| 2.24 (1.31, 3.58) |
0.003
|
Accessible rural | 1.23 (0.68, 2.06) | 0.557 | 1.28 (0.70, 2.19) | 0.474 | 1.34 (0.81, 2.11) | 0.280 | 1.35 (0.81, 2.13) | 0.277 |
Remote small towns | 1.26 (0.69, 2.13) | 0.501 | 1.32 (0.72, 2.25) | 0.418 | 1.41 (0.83, 2.24) | 0.221 | 1.42 (0.84, 2.26) | 0.208 |
Remote rural | 1.41 (0.78, 2.35) | 0.277 | 1.39 (0.77, 2.34) | 0.302 | 2.04 (1.23, 3.19) |
0.005
| 2.01 (1.21, 3.15) |
0.006
|
Neighbourhood deprivation (reference: 1 most deprived) | | | | | | | | |
2 | 0.89 (0.59,1.31) | 0.518 | 0.91 (0.60, 1.35) | 0.593 | 0.73 (0.49, 1.06) | 0.096 | 0.75 (0.49, 1.07) | 0.115 |
3 | 0.76 (0.49, 1.14) | 0.173 | 0.80 (0.51, 1.21) | 0.271 | 0.73 (0.49, 1.06) | 0.099 | 0.74 (0.48, 1.09) | 0.126 |
4 (least deprived) | 0.63 (0.39, 0.97) |
0.034
| 0.64 (0.40, 1.00) |
0.048
| 0.70 (0.48, 1.04) | 0.072 | 0.70 (0.45, 1.04) | 0.080 |
Neighbourhood social cohesion | 1.07 (0.48, 2.10) | 0.989 | 1.38 (0.56, 2.88) | 0.579 | 0.88 (0.42, 1.62) | 0.580 | 0.88 (0.39, 1.69) | 0.590 |
Neighbourhood disorder | 2.31 (0.58, 6.44) | 0.291 | 1.23 (0.25, 3.74) | 0.965 | 3.50 (1.00, 9.10) | 0.051 | 2.36 (0.60, 6.54) | 0.272 |
Perceived social cohesion | – | | 0.95 (0.89, 1.01) | 0.082 | | | 1.00 (0.94, 1.06) | 0.958 |
Perceived disorder | – | | 1.14 (1.03, 1.27) |
0.011
| | | 1.09 (0.99, 1.19) | 0.090 |
Neighbourhood variance | 0.12 (0.00, 0.40) | | 0.17 (0.00, 0.46) | | 0.06 (0.00, 0.22) | | 0.05 (0.00, 0.22) | |
DIC | 1513.15 | | 1499.86 | | 1631.51 | | 1631.68 | |
Urban/rurality showed a clear gradient in alcohol use (Table
2—Model 7); those in remote and rural regions had higher odds of having ever drunk than those in large cities, while those in smaller urban areas were not significantly different in terms of ever drinking (
p > 0.05). A significant association was present for neighbourhood social cohesion on having ever drunk alcohol (odds ratio = 0.33,
p = 0.017), in fully adjusted models. Including this measure also improved model fit compared to the null model (DIC = 1301.69 vs. 1304.15) (see Supplementary Material). In fully adjusted models (Model 7), no significant associations were found for AODs or neighbourhood disorder with having ever drank (
p > 0.05); however, individual perceived disorder was associated with having ever drank, (odds ratio = 1.24,
p = 0.001).
Among those who had ever drank, those residing in the least deprived areas had reduced odds of weekly drinking compared to those in the most deprived areas (odds ratio = 0.64,
p = 0.048), in fully adjusted models (Table
3—Model 7). Additionally, those in accessible small towns had higher odds of weekly drinking than those in large urban areas (odds ratio = 2.08,
p = 0.016). No significant associations were found for AODs, neighbourhood disorder, or neighbourhood social cohesion (
p > 0.05). Individual perceived disorder was associated with weekly drinking (odds ratio = 1.14,
p = 0.011).
Turning now to drunkenness, among those who had ever drank, those in accessible small towns (odds ratio = 2.24,
p = 0.003) and remote rural areas (odds ratio = 2.01,
p = 0.006) had higher odds of drunkenness than those in large urban areas (Table
3—Model 7), in the fully adjusted models. Those residing in areas of lower deprivation had significantly reduced odds of drunkenness; however, this relationship became non-significant when accounting for neighbourhood disorder (see Supplementary Material). Neighbourhood-level disorder was associated with increased odds of drunkenness (see Supplementary Material); however, this relationship was no longer significant when accounting for neighbourhood social cohesion and individual neighbourhood perceptions (Models 6–7).
For all outcomes, the associations in Model 7 were still observed after accounting for school-level variation (see Supplementary Material). Sensitivity analysis using different distance bands to measure AODs did not influence main findings from the models.
Because the data are spatially distributed, a global Moran’s I was calculated on the IDZ residuals from Model 8 to detect whether spatial autocorrelation was present, which would violate the assumption of independence of error-terms. The Moran’s I statistic was not significant (
p > 0.05) (see Supplementary Material), indicating no spatial clustering in the model residuals (Anselin and Griffith
1988).
Discussion
This study used multilevel analysis to examine associations of neighbourhood characteristics with adolescent drinking behaviours. The results are strengthened by the inclusion of the school-level; thus, testing whether the findings are, in fact, overestimated due to the omission of the school-level variance. Results show that having ever consumed alcohol and weekly alcohol use varied by neighbourhood and are in line with a study of US adolescents that found significant variance of alcohol misuse at the neighbourhood level but not the school level (Ennett et al.
2008). However, school explained a greater amount of variance in drunkenness. This may be due to binge drinking being more influenced by shared peer culture experienced at school (Kuntsche and Jordan
2006).
The more remote and rural the area an adolescent resided in, the higher the odds of having ever drank. Other studies in Scotland have found an urban/rural difference (using a dichotomous measure) in whether adolescents had ever drunk alcohol (The Scottish Government
2016). Our current research found that among drinkers, those living in accessible small towns had higher odds of weekly drinking and drunkenness and those in remote rural areas had higher odds of drunkenness. This supports the principle that more detailed classifications of urban/rural are necessary, as suggested by Dixon and Chartier (
2016). Additionally, the results reflect previous research on adolescent illicit substance and tobacco use, which maintain that adolescent substance use in Scotland is not concentrated in urban areas (Forsyth and Barnard
1999; Levin et al.
2014). The associations related to urban/rurality remained unexplained after controlling for neighbourhood social conditions and AOD, indicating that there may be other reasons for these inequalities. It may be that in rural areas and accessible small towns, adolescent alcohol use may be normalised and used as a form of “cultural capital” (Kloep et al.
2001).
It is important to note that the sample was made up of 15-year-olds; therefore, findings of an urban/rural gradient in having ever drunk represent a more delayed initiation to drinking but do not necessarily translate to lifetime abstention throughout adulthood. Conversely, many studies have found that, among adults, those in urban areas have higher rates of alcohol use compared to those in rural areas (Dixon and Chartier
2016; Slutske et al.
2016). Comprehension of different drinking trajectories across the life course, in terms of urban/rurality, is needed to explain this pattern.
Those living in an area of low deprivation had lower odds of weekly drinking, but not having ever drunk, or drunkenness (in fully adjusted models). Based on these findings, a potential explanation for the mixed results found in previous studies of neighbourhood socio-economics and adolescent alcohol use could be due to differing alcohol outcomes. Our results are in accordance with other research that found a relationship with neighbourhood deprivation and regular drinking among adolescents in Scotland (Petrou and Kupek
2018). The current study strengthens that evidence in that it adjusts for other neighbourhood conditions and family factors and confirms that this relationship holds.
Neighbourhood social cohesion was negatively associated with having ever drunk by S4; however, among drinkers, there was no association with alcohol use drinking behaviours. This is counter to findings from an urban US study that found neighbourhood collective efficacy did not influence adolescent alcohol use (Fagan et al.
2015). This may be due to their measures of the social environment originating from adults rather than adolescents. Conversely, Jackson et al. (
2016) found collective efficacy, as measured by adolescents, was associated with adolescent drinking outcomes in an urban sample. Our findings support theories which argue that positive social connections discourage adolescent alcohol use; however, the association is limited to alcohol initiation. More research is needed to determine if creating more cohesive communities could reduce the likelihood of adolescents commencing alcohol use.
Unlike previous studies of Scottish adult populations (Shortt et al.
2018), we did not find an association between AOD and adolescent drinking outcomes. This may be because 15-year-olds are unlikely to purchase alcohol directly from retailers due to Scotland’s age restrictions and regulations (The Scottish Government
2016). It is noteworthy that the measure of on-trade outlets did not distinguish between establishment types. These may have differing impacts for adolescents as, unlike adults, they are restricted in terms of alcohol access in these venues. Some establishments would primarily be drinking establishments and may influence social norms in the neighbourhood, while other establishments may serve as a source of entertainment with alcohol consumption not being the primary activity. Moreover, the impact of AOD may only be observed over time after repeat exposure; longitudinal studies are needed to examine this possibility.
This study has several strengths, including having a boosted sample of non-urban youth, accounting for a variety of theoretically important neighbourhood conditions, and adjusting for school-level variation. Some limitations are worth consideration. First, this study is cross-sectional, so causation cannot be inferred. Additionally, IDZs were used to represent neighbourhoods. However, this is an administrative unit and may not correspond to the respondents’ understandings of their neighbourhood boundaries. Moreover, the neighbourhood-level social cohesion and disorder measures are derived from the same adolescents who reported their drinking behaviours; therefore, this study is at risk of same-source bias (Jackson et al.
2016). Further, we were unable to examine family structures that did not include a biological parent due to small numbers of students reporting these family compositions. Future studies designed to explicitly examine alcohol consumption among young people in alternative family situations are required. Finally, the focus of this study was on neighbourhood characteristics. Future studies may examine school characteristics. This is of particular interest for drunkenness given the greater proportion of variance accounted for by school compared to neighbourhood.
Despite these limitations, the results have important implications for public health strategies. Efforts that are targeted to rural areas, small towns, and neighbourhoods with low social cohesion are needed, given higher rates of adolescent alcohol use. Additionally, services and interventions should be directed at regions of high deprivation in Scotland, due to the higher rates of regular alcohol use. Future work is needed to develop and evaluate intervention and prevention approaches targeted to neighbourhoods at greatest risk.
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