Neil Donnelly, Patricia Menéndez & Nicole Mahoney NSW Bureau of Crime Statistics and Research February, 2015

Background Evidence of relationship between total liquor licence concentrations & some harms (e.g. assaults, motor vehicle accidents) Local areas with a higher no. of liquor outlets have more of these problems (Gruenewald et al., 2006; Chikritzhs et al., 2007) However some variability about the most important licensed premises type for these harms (e.g. hotels/on- premises or packaged liquor)

Current outlet density study Investigate the relationship between liquor licence concentrations and assault rates in New South Wales LGAs cross-sectional design using 2011 data

Research questions Is there an association between liquor licence concentrations in LGAs in NSW and: 1. DV related assault rates? 2. Non-DV related assault rates? after controlling for important covariates

Are concentrations of particular licence types associated with higher assault rates? a)Hotel licences b)Packaged liquor licences c)On-Premises licences d)Club licences

Is there a linear or a non-linear relationship between liquor licence concentration and assault? Does this differ by liquor licence type? Spatial autocorrelation between LGAs and assault rates measured & taken account of

Data sources Recorded crime DV and non-DV assault incidents in 2011 (COPS data) DV & non-DV assault rates (per 1,ooo pop in LGAs) Liquor licensing Licence types operating in 2011 (OLGR, NSW) Hotel rates (per 1,ooo pop in LGAs) Packaged liquor rates On-Premises rates Club rates

Other LGA data LGA population size (ERP) LGA population density % males aged yrs % Indigenous (ATSI) Socio-economic disadvantage (SEIFA IRSD) location category (ARIA) % born in non-English speaking country

LGAs included 147 of 152 LGAs used in final analyses (97% of LGAs)  Exclusions City of Sydney Snowy River Broken Hill Urana Conargo One LGA excluded during final analyses diagnostics as an outlier (n=146; 96% of LGAs) Warren

Analyses Log transformation of each assault rate Linear regression (OLS) Moran’s I - spatial autocorrelation present? Simultaneous Autoregression (SAR) Lambda (λ) – spatial autocorrelation taken account of? SAR weighted Diagnostics – model selection

RESULTS

Descriptive statistics for assault rates in LGAs (n=147) MeanMedian 25 th percentile 75 th percentile DV related assault rate (per 1,000 population) Non-DV related assault rate (per 1,000 population)

SAR weighted regression of DV assault rates (log) SAR weighted model (n=146) EstimateSEp value Constant <.001 * Hotels linear =.023 * Hotels non-linear squared =.096 Hotels non-linear cubed <.001 * Packaged linear <.001 * Packaged non-linear squared <.001 * Packaged non-linear cubed <.001 * On-Premises linear <.001 * Clubs linear =.020 * Population density # =.320 Indigenous (%) <.001 * Males years (%) =.023 * Socio-economic disadvantage <.001 * Born NES country (%) =.848 City =.817 Outer regional/remote =.075 λ (lambda) =.237 LR test = 0.60, p =.439

DV assault rate – Elasticity effects Log-Linear On-Premises 10% increase from mean concentration level produced a 2.2% increase in DV assault rate (log) Clubs 10% increase from mean concentration level produced a 1.3% increase in DV assault rate (log)

SAR regression of non-DV assault rates (log) SAR model (n = 146) EstimateSEp value Constant <.001 * Hotels linear =.270 Hotels non-linear squared =.045 * Hotels non-linear cubed =.001 * Packaged linear <.001 * Packaged non-linear squared =.062 Packaged non-linear cubed =.001 * On-Premises linear <.001 * Clubs linear =.021 * Clubs non-linear squared =.013 * Population density # =.057 Indigenous (%) <.001 * Males years (%) <.001 * Socio-economic disadvantage <.001 * Born NES country (%) =.001 * λ (lambda) =.109 LR test = 0.90, p =.342 # Population density estimate is

Non-DV assault rate – Elasticity effect Log-Linear On-Premises 10% increase from mean concentration level produced a 3.0% increase in non-DV assault rate (log)

Summary Different concentration effects found by licence type and assault type adjusted for important covariates & spatial autocorrelation Hotels, very strong non-linear predictor of DV & non-DV assault rates Packaged liquor also a non-linear predictor but not as strong as hotels On-Premises, strong linear predictor of both assault rates Clubs strong linear predictor of DV assault rates non-linear predictor of non-DV assault but smaller effect size

Limitations Hotel licences can also supply packaged alcohol Does not apply to LGAs with a very high transient population Lack of alcohol sales data Cross-sectional study, not longitudinal

General conclusions Consistent with other cross-sectional outlet density studies strong relationship between high concentrations of licensed premises and assault rates Non-linear effects for hotels of particular policy importance Longitudinal studies also very important to assess effects of changes in the concentration of licence types