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

2. 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)

3. 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

4. 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

5. 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

6. 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

7. 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

8. Other LGA data LGA population size (ERP) LGA population density % males aged 15-34 yrs % Indigenous (ATSI) Socio-economic disadvantage (SEIFA IRSD) location category (ARIA) % born in non-English speaking country

9. 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

10. 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

11. RESULTS

12. Descriptive statistics for assault rates in LGAs (n=147) MeanMedian 25 th percentile 75 th percentile DV related assault rate (per 1,000 population) 5.133.672.555.68 Non-DV related assault rate (per 1,000 population) 5.884.832.887.30

15. SAR weighted regression of DV assault rates (log) SAR weighted model (n=146) EstimateSEp value Constant 7.1071.328<.001 * Hotels linear -0.4000.175=.023 * Hotels non-linear squared -0.3240.194=.096 Hotels non-linear cubed 0.2360.053<.001 * Packaged linear -1.6470.255<.001 * Packaged non-linear squared -3.0430.709<.001 * Packaged non-linear cubed 10.9741.564<.001 * On-Premises linear 0.2290.049<.001 * Clubs linear 0.2910.125=.020 * Population density # 0.000 =.320 Indigenous (%) 0.0290.006<.001 * Males 15-34 years (%) 0.0550.024=.023 * Socio-economic disadvantage -0.0070.001<.001 * Born NES country (%) -0.0020.013=.848 City 0.0770.333=.817 Outer regional/remote 0.1670.094=.075 λ (lambda) =.237 LR test = 0.60, p =.439

20. 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)

21. SAR regression of non-DV assault rates (log) SAR model (n = 146) EstimateSEp value Constant 6.6380.681<.001 * Hotels linear -0.1190.108=.270 Hotels non-linear squared -0.2580.128=.045 * Hotels non-linear cubed 0.1460.044=.001 * Packaged linear -0.8520.237<.001 * Packaged non-linear squared -1.3300.713=.062 Packaged non-linear cubed 5.1771.569=.001 * On-Premises linear 0.3140.051<.001 * Clubs linear -0.4630.200=.021 * Clubs non-linear squared 0.4940.199=.013 * Population density # 0.000 =.057 Indigenous (%) 0.0290.005<.001 * Males 15-34 years (%) 0.0900.016<.001 * Socio-economic disadvantage -0.0060.001<.001 * Born NES country (%) -0.0140.004=.001 * λ (lambda) =.109 LR test = 0.90, p =.342 # Population density estimate is -0.0000586

25. 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)

27. 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

28. 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

29. 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