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Identifying community factors associated with risky alcohol consumption and alcohol-related crime in regional NSW Courtney Breen, Anthony Shakeshaft, Richard.

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Presentation on theme: "Identifying community factors associated with risky alcohol consumption and alcohol-related crime in regional NSW Courtney Breen, Anthony Shakeshaft, Richard."— Presentation transcript:

1 Identifying community factors associated with risky alcohol consumption and alcohol-related crime in regional NSW Courtney Breen, Anthony Shakeshaft, Richard Mattick, Rob Sanson-Fisher, Cate D’Este

2 Alcohol consumption and harm Costs of alcohol substantial, second only to tobacco:  Collins & Lapsley, 2008  Laslett et al, 2010 Alcohol research in regional Australia (Miller et al. 2010):  Limited  Harms appear disproportionately high Aims:  Do regional communities differ from each other?  Do community characteristics predict rates of consumption and harm?

3 Alcohol Action in Rural Communities - AARC RCT to reduce alcohol-related harm at the community level Selection criteria:  Population approximately 5,000 – 15,000  At least 100km from a regional / metro centre  At least 100km between experimental and control towns 10 matched pairs in NSW:  Population size  Age and gender distribution  Proportion indigenous One randomly allocated to experimental condition

4 Alcohol Action in Rural Communities (AARC) Grafton Inverell Kempsey Gunnedah Sydney Parkes Forbes Griffith Leeton Tumut Corowa

5 AARC Survey Baseline data Postal survey in 2005 Random sample residents from the electoral roll (aged 18-62) Cochrane methods to optimise response rate, 39% (comparable to NDSHS) Data weighted to reflect gender and age distribution of each town (N=2977)

6 AARC survey sample, N=2977 Mean (SD) Age40 (12) n%(95%CI) Male – 52 Indigenous With post school qualification – 49 Unemployed Married/de facto – 71 Household income >=700 per week

7 Self- reported alcohol consumption and harm Drinking at risky levels for harm in the long term  Males – 29 or more standard drinks per week  Females – 15 or more standard drinks per week Drinking at risky levels for harm in short term  Males – more than 6 standard drinks on any one occasion  Females – more than 4 standard drinks on any one occasion Identified as harmful or hazardous on the The Alcohol Use Disorders Identification Test (AUDIT)  Score >=8

8 Alcohol consumption and harm

9 Are there differences in alcohol consumption between communities? What accounts for the differences? Mixed models (multi-level models)  Control for clustering within communities (inds in communities more similar)  Allows analysis of both individual and community factors

10 Individual factors Age Gender Ethnicity Country of birth Marital status Income Education Employment Health score Community factors Proportion young males (ABS census) Proportion indigenous (ABS census) Socio-Economic Indexes For Areas (SEIFA) Accessibility/Remoteness Index of Australia (ARIA) Rate licensed premises / pop - hotels and clubs - retailers and wholesalers - other licensed premises Rate GPs / pop Rate police / pop

11 Findings: individual and community correlates RISK OF HARM IN THE LONG TERM HIGHER FOR: Individual - male, unmarried, those with worse subjective health. Communities with - more GPs, fewer police RISK OF HARM IN THE SHORT TERM HIGHER FOR: Individual - younger, unmarried, non-indigenous, Australian born, higher incomes Communities with - more hotels and clubs AUDIT Individual - younger, male, unmarried, Australian born, higher incomes

12 Alcohol related crime – routinely collected data Incidents reported to /detected by police (BOCSAR) – Proxy of alcohol related crime Ratio = alcohol related crimes at alcohol-related times same crimes at non alcohol-related times Assaults, malicious damage, street offences

13 Alcohol-related crime,

14 Alcohol-related crime and community factors There are differences between communities in alcohol-related crime Community factors associated with higher risk of crime: - Greater socioeconomic advantage - More GP’s / population (loading on income, hopefully!) - More pubs/clubs / population

15 Limitations Sample size – 20 communities limited, but enough individual data Cross sectional survey / correlations - does not necessarily mean causality Response rate of 39%, but samples weighted Other community characteristics could be considered? Limited to medium size regional communities, but other analyses show differences between Sydney LGAs (Shakeshaft et al, 2010).

16 Conclusions Regional communities differ in their rates of alcohol consumption and crime Individual and community factors are associated with alcohol consumption and crime Target those communities at highest risk of specific types of risky consumption and crime, rather than similar interventions across all communities


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