Outlets, drinking and driving: a multilevel analysis of availability.

Gruenewald, Paul J.; Johnson, Fred W.; Treno, Andrew J.

doi:10.15288/jsa.2002.63.460

Cited by 146 publications

(126 citation statements)

References 23 publications

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“…In addition, two measures of riding with a drinking driver, and driving while drinking alcohol, were adopted from prior epidemiologic studies [21,22] (Alpha=.68).…”

Section: Methodsmentioning

confidence: 99%

Brief Multiple Behavior Interventions in a College Student Health Care Clinic

Werch

Bian

Moore

et al. 2007

Journal of Adolescent Health

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Purpose-This study examined the effects of brief image-based interventions, including a multiple behavior health contract, a one-on-one tailored consultation, and a combined consultation plus contract intervention, for impacting multiple health behaviors of students in a university health clinic.Methods-A total of 155 college students attending a major Southern university were recruited to participate in a study evaluating a health promotion program titled Project Fitness during the fall 2005 and spring 2006. Participants were randomly assigned to one of three treatments as they presented at the clinic: 1) a multiple behavior health contract, 2) a one-on-one tailored consultation, or 3) a combined consultation plus contract intervention. Baseline and one-month post-intervention data were collected using computer-assisted questionnaires in a quiet office within the student health clinic.Results-Omnibus repeated measures MANOVAs were significant for drinking driving behaviors, F(2,136)=4.43, p=.01, exercise behaviors, F(5,140)=6.12, p=.00), nutrition habits, F(3,143)=5.37, p=.00, sleep habits, F(2,144)=5.03, p=.01, and health quality of life, F(5,140)=3.09, p=.01, with improvements on each behavior across time. Group by time interaction effects showed an increase in the use of techniques to manage stress, F(2,144)=5.48, p=.01, and the number of health behavior goals set in the last 30 days, F(2,143)=5.35, p=.01, but only among adolescents receiving the consultation, or consultation plus contract. Effect sizes were consistently larger across health behaviors, and medium in size, when both consult and contract were employed together.Conclusions-Brief interventions using a positive goal image of fitness, and addressing a number of health habits using a contract and consultation strategy alone, or in combination, have the potential to influence positive changes in multiple health behaviors of college students attending a university primary health care clinic.

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“…In addition, two measures of riding with a drinking driver, and driving while drinking alcohol, were adopted from prior epidemiologic studies [21,22] (Alpha=.68).…”

Section: Methodsmentioning

confidence: 99%

Brief Multiple Behavior Interventions in a College Student Health Care Clinic

Werch

Bian

Moore

et al. 2007

Journal of Adolescent Health

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“…For example, social ecological theory 12 suggests that the high concentration of liquor stores increases the physical availability of alcohol, and the heavy promotion of alcohol makes heavy drinking more socially acceptable and encourages consumption in disadvantaged neighborhoods. Studies have found that alcohol outlet density is associated with increased alcohol consumption and drinking problems or consequences, [13][14][15] and other studies have shown that alcohol advertising is associated with more positive attitudes regarding drinking, drinking initiation at younger ages, brand preference, and alcohol consumption. [16][17][18][19][20] Several studies have investigated the effects of neighborhood disadvantage on substance use, but findings have been mixed.…”

Section: Introductionmentioning

confidence: 97%

Neighborhood Disadvantage, High Alcohol Content Beverage Consumption, Drinking Norms, and Drinking Consequences: A Mediation Analysis

Jones‐Webb

Karriker‐Jaffe

2013

J Urban Health

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Alcohol use can cause significant harm. We examined the relationships between neighborhood disadvantage, consumption of high-alcohol-content beverages (HACB), drinking norms, and self-reported drinking consequences using data from the 2000 and 2005 National Alcohol Surveys (N09,971 current drinkers) and the 2000 Decennial Census. We hypothesized that (1) individuals living in disadvantaged neighborhoods would report more negative drinking consequences than individuals living in more affluent neighborhoods, and (2) this relationship would be mediated by HACB consumption and pro-drunkenness drinking norms. Neighborhood disadvantage was based on a composite measure of socioeconomic indicators from the 2000 Decennial Census (five-item composite, alpha00.89). We measured high alcohol content beverage consumption in terms of whether respondents engaged in frequent or heavy consumption of malt liquor, fortified wine, or distilled spirits/liquor. The outcome was a dichotomous indicator of two or more of 15 past-year social, legal, work, and health consequences. Simultaneous, multivariate path modeling tested direct and indirect effects of neighborhood disadvantage, HACB consumption, and prodrunkenness norms on consequences. Individuals living in disadvantaged neighborhoods reported significantly more negative drinking consequences than individuals living in more affluent neighborhoods. Consumption of high-alcoholcontent beverages and pro-drunkenness norms did not mediate this relationship. However, heavy distilled spirits/liquor use was a significant mediator of other neighborhood characteristics (i.e., percent African American). Living in an African American neighborhood was related to increased spirits/liquor consumption and, in turn, reporting more negative drinking consequences. Greater scrutiny of advertising and tax policies related to distilled spirits/liquor is needed to prevent future drinking problems, especially in minority neighborhoods.

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“…Gruenewald et al (2002), however, found that both driving after drinking and driving while intoxicated were related to venue preference (e.g., restaurants over bars) and that the strongest infl uence on both driving after drinking and driving while intoxicated was preferred drinking location, considered together with (i.e., interacted with) drinking patterns, particularly drinking frequency. All of these ecological studies have been cross-sectional, but a recent panel study done at the ZIP-code level (Treno et al, 2006) showed that greater alcohol-outlet densities were related to higher alcohol-related crash rates over a 6-year time frame just as in the crosssectional studies.…”

mentioning

confidence: 95%

Drinking, Driving, and Crashing: A Traffic-Flow Model of Alcohol-Related Motor Vehicle Accidents

Gruenewald¹,

Johnson²

2010

J. Stud. Alcohol Drugs

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ABSTRACT. Objective: This study examined the infl uence of onpremise alcohol-outlet densities and of drinking-driver densities on rates of alcohol-related motor vehicle crashes. A traffi c-fl ow model is developed to represent geographic relationships between residential locations of drinking drivers, alcohol outlets, and alcohol-related motor vehicle crashes. Method: Cross-sectional and time-series cross-sectional spatial analyses were performed using data collected from 144 geographic units over 4 years. Data were obtained from archival and survey sources in six communities. Archival data were obtained within community areas and measured activities of either the resident population or persons visiting these communities. These data included local and highway traffi c fl ow, locations of alcohol outlets, population density, network density of the local roadway system, and single-vehicle nighttime (SVN) crashes. Telephone-survey data obtained from residents of the communities were used to estimate the size of the resident drinking and driving population. Results: Cross-sectional analyses showed that effects relating on-premise densities to alcohol-related crashes were moderated by highway traffi c fl ow. Depending on levels of highway traffi c fl ow, 10% greater densities were related to 0% to 150% greater rates of SVN crashes. Time-series cross-sectional analyses showed that changes in the population pool of drinking drivers and on-premise densities interacted to increase SVN crash rates. Conclusions: A simple traffi c-fl ow model can assess the effects of on-premise alcohol-outlet densities and of drinking-driver densities as they vary across communities to produce alcohol-related crashes. Analyses based on these models can usefully guide policy decisions on the siting of on-premise alcohol outlets. STUDIES OF THE RELATIONSHIP between alcohol outlets and alcohol-related crashes have shown that greater numbers of alcohol outlets are related to higher motor vehicle crash rates across large geographic units such as provinces and cities (e.g., Rush et al., 1986;Watts and Rabow, 1983); within states over time (e.g., Escobedo and Ortiz, 2002;Holder and Blose, 1987); and within smaller geographic units, such as smaller cities within a dense urban region (e.g., Los Angeles; Scribner et al., 1994). Although studies have shown that at the neighborhood level outlet densities are related to crashes independently of local patterns of alcohol use (e.g., Van Oers and Garretsen, 1993), studies also have shown that greater travel distance between outlets is unrelated to greater crash (Gruenewald and Ponicki, 1995;Jewell and Brown, 1995) and arrest rates (Lapham et al., 1998). Finally, these studies have shown in addition that the geographic patterning of alcohol outlets and alcohol-related crash and arrest rates are related, with neighborhoods with greater outlet densities having more crashes and adjacent areas (even those with no alcohol outlets) also experiencing higher crash rates (Gruenewald et al., 1996;Lapham et al., 199...

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Outlets, drinking and driving: a multilevel analysis of availability.

Cited by 146 publications

References 23 publications

Brief Multiple Behavior Interventions in a College Student Health Care Clinic

Brief Multiple Behavior Interventions in a College Student Health Care Clinic

Neighborhood Disadvantage, High Alcohol Content Beverage Consumption, Drinking Norms, and Drinking Consequences: A Mediation Analysis

Drinking, Driving, and Crashing: A Traffic-Flow Model of Alcohol-Related Motor Vehicle Accidents

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