routine activities and alcohol use: constraints on outlet utilization

0 145-6008/95/1901-0044$03.00/0 ALCOHOLISM: CLINICAL AND EXPERIMENTAL RESEARCH

Vol. 19, No. 1 February 1995

Routine Activities and Alcohol Use: Constraints on Outlet Utilization

Paul J. Gruenewald, Andrew J. Treno, Thomas M. Nephew, and William R. Ponicki

Studies of consumers’ use of alcohol beverage outlets have provided a basis for understanding drinking behaviors in different drinking environments. These studies have shown that drinking environments are related to both demographic and drinking pattern measures. Absent from these studies has been a theoretical basis on which to make predictions regarding drinking patterns and choices of drinking environments under the various social, economic, and environmental constraints typically confronting alcohol consumers. This study presents one such theoretical approach.

The approach assumes that, in the context of individual preferences for alcohol, drinking choices are constrained by consumers’ economic and time-energy budgets for consumption. All other things being equal, it is suggested that greater budgets for consumption will be related to greater alcohol use, quality of beverages purchased, amenity values of purchase locations, or all three. Be- cause on-premise drinking entails greater economic costs, greater drinking levels will be related to lower utilization of on-premise establishments.

The predictions of this approach were tested using data obtained from telephone surveys of consumers conducted in 1990 and 1991. The results showed that controlling for income, variables related to greater time-energy budgets for consumption (i.e., marital status and household composition) were related to greater consumption levels and greater utilization of on-premise establishments. Control- ling for demographic measures, greater income was related to greater utilization of restaurants and increased beverage quality. Controlling for all other measures, frequencies of consumption were inversely related to consumption at on-premise establishments, reflecting the expected moderation in costs for heavier consumers on a limited alcohol budget.

Key Words: Alcohol Use, Outlets, Choice, Optimization, Routine Activities.

ENEVER AN individual drinks alcohol, he or she

Drinking choices may be contingent on events unrelated to consumption (e.g., drinking after one arrives at a restaurant), may be constrained by available options (e.g., bars that only serve beer), and may be contingent on one’s desires to consume alcohol (e.g., drinking at home to conserve costs). In fact, the number of contingent choices involved in drinking are likely innumerable. Thus, results of the empirical study of drinking choices are also likely to be

w chooses where, what, and how much to consume.

complex, depending as they will on individual drinking preferences, available drinking options, and variations in routine life activities. The theoretical problem in understanding human choice behavior in drinking contexts is how to formulate a mechanism that explains such drinking choices.

The empirical literature on consumers’ use of alcohol outlets has begun to reveal some of the correlates of consumers’ choices of locations to drink. Using general population survey data from a study of Canadian consumers, Single and Wortley’ found consumers’ uses of drinking locations to be associated with gender, age, education, income, and marital status. For example, alcohol consumption at bars was greatest among young, low income, unmarried males; consumption at restaurants was greatest among older, more highly educated females with higher incomes. Analyzing the results of a national survey in New Zealand, Casswell et a1.2 showed that the number of self-reported alcohol related problems varied as a function of choices of drinking environments (hotels, taverns, and clubs) and typical quantities consumed. Analyzing data from a household survey in Western Australia, Stockwell et al.3 showed that violent incidents (e.g., arguments or fights) were most likely to occur among young, male, heavy drinkers who drank on licensed premises.

Clearly, drinking patterns, locations, and problems co- vary. The operative question, however, is what behavioral mechanism explains these relationships? Taking on the somewhat smaller issue of the structure of relationships between drinking patterns and drinking locations, and leav- ing aside issues regarding the etiology of drinking problems, this study explores the relationships between economic factors, demographic variables, drinking patterns, and routine activities regarding the purchase and consumption of alcohol. For purposes of this study, routine activities of consumers, represented in their choices of drinking locations, reflect choices to take on the greater or lesser costs entailed by drinking in different places.

From the Prevention Research Center, Berkeley, California. Received for publication May 12, 1994; accepted July 28, 1994 This work was pe$ormed at the Prevention Research Center, Pacific

Institute for Research and Evaluation, under grants from the National Insti- tute on Alcohol Abuse and Alcoholism (ROI-AAO8395 and ROI-AA08395- 02SIA2 to P.J.G.).

Reprint requests: Paul J. Gruenewald, Ph.D., Prevention Research Center, 2150 Shattuck Avenue, Suite 900, Berkeley, CA 94704.

Copyright 0 I995 by The Research Socieg on Alcoholism.

44

THE MODEL

The theoretical approach taken herein adopts the economic assumption that consumers seek to maximize their satisfaction from consumption of alcohol subject to the constraints of limited monetary and time-energy resources (a behavioral ecological appr~ach).~,’ Unlike typical de-

Alcohol Clin Exp Res, Vol19, No 1, 1995: pp 44-53

ROUTINE ACTIVITIES AND ALCOHOL USE

Ethnic Group

Budgetary Income

45

Fig. 1. Conceptual formulation of rela-

and consumption, utilization, and expenditure

Utilization Measures

1 Bars tionships between demographic variables

Restaurants

mand analyses, however, this approach allows for the fact that alcoholic beverages are not simple goods, but rather a combination of desired attributes-complex goods. The satisfaction that a consumer derives from alcohol depends not only on its ethanol content, but also on the quality of the beverage6 and the amenity values of places where it is c~nsumed.~ Thus, drinking patterns are determined through a process by which consumers optimize their utility from these attributes within the constraints of monetary and time-energy budgets. From this microsocioeconomic approach, it may be inferred that individual consumer decisions are shaped by the same process. However, these individual decisions are not subject of the current model.

The monetary costs of alcoholic beverages vary with brand quality and locations of consumption (on- or off- premise). As Treno et al.* observed from a survey of alcohol retailers in California, across beverage types, brands, and premise types, costs/unit pure ethanol differed by as much as a factor of 60. Consumers may use the range of prices available to them, within other constraints, to pro- vide themselves with affordable forms of alcohol. Monetary costs can be reduced by consuming less ethanol, drinking lower quality beverages, and purchasing them at lower cost locations (off-premise). Beyond monetary factors, consumers are also constrained by the time and energy involved in obtaining and drinking alcohol. Those facing tighter constraints on their time (e.g., married people and those with children) have less time to spend on drinking and face greater obstacles to drinking at bars or restaurants than they do for consuming off-premise.

As asserted by the model (Fig. l), controlling for normative forces, budgetary constraints (e.g., household income)

and limitations of time-energy budgets for use (e.g., reflected in marital status and household composition) will predictably shape drinking patterns, both in terms of amounts consumed and patterns of premise utilization. Which relationships predominate, of course, will depend on the degree to which consumers have saturated their tastes for alcohol, as well as the availability of broad ranges of beverage qualities and drinking contexts with differing amenity values. Given that ethanol is widely available and can be obtained at extremely low prices in California,* it appears likely that the market for alcohol per se is nearly saturated in this state (i.e., further reductions in cost or growth in availability are unlikely to lead to substantial increase in volumes of ethanol consumed). Thus, the primary option open to consumers with greater expendable budgets for alcohol may be to raise the quality of beverages purchased or increase their use of drinking environments with higher amenity values.

Based on the empirical work of Treno et al.,* it is clear that the amenity values of on-premise establishments ex- ceed those of other places of consumption. This is reflected in the increased costs of alcoholic beverages when they are prepared by someone else (e.g., at a bar) and are accompanied by other desired goods (e.g., food at a restaurant). It is also clear that beverages differ substantially in terms of quality. Given an efficient market, prices of different goods within commodities should reflect their relative quality as perceived by consumers.6 Because the cost of an ethanol ounce of Paul Masson Chablis ($4.06 on-premise) is mark- edly greater than the cost of Inglenook Chablis ($2.12 on-premise),8 the former has greater quality, in this sense, than the latter. The relative qualities of alcoholic beverages

46 GRUENEWALD ET AL.

are reflected in on-premise prices, because these prices include the costs of preparation normally carried by consumers when beverages are purchased for off-premise consumption.

As Deaton6 points out, the opportunity for substitution between goods within commodities (and as Godfrey7 points out between points of purchase with different amenity values) implies considerable flexibility in the choices consumers make. Thus, the basic hypothesis to be tested herein is whether consumers take these options as they are available. Based on the proposed model, the hypotheses to be tested are that greater budgets for alcohol consumption will be directly related to: (1) greater levels of consumption, (2) greater utilization of on-premise establishments, (3) greater quality of beverages purchased, and, therefore, (4) greater total expenditures for alcohol. Greater budgets for consumption will be represented in direct economic terms (e.g., household income net of household composition) and in terms of time-energy budgets for consuming activities.’ It is expected that, controlling for household income, greater burdens on time-energy budgets for drinking (e.g., as occur with the presence of children in a household) will be reflected in reductions in consumption, utilization of on- premise establishments, and total expenditures. Finally, it is expected that (5 ) , controlling for all other measures, greater levels of consumption will be inversely related to utilization of on-premise establishments and the quality of beverages purchased, reflecting the need of heavier consumers to conserve their budgets for alcohol.

METHODS

A general population survey of California alcohol consumers was conducted in three waves: October 1990, March 1991, and October 1991. The first two waves examined in the current study included 1,038 and 957 individuals 21 years of age or older who consumed alcoholic beverages in the previous 12 months. Stratified by geographic area, households were telephoned on a random digit dial basis. Household composition was enumerated and, within households, the interviewee was selected on the basis of nearest birth date to the date of call. The completion rate for the survey was 63.4%. Consumers within two cities were oversampled for purposes unrelated to the current study. Using demographic data from the current surveys and 1990 Census data, all analyses were weighted to correct for the number of phone lines/household, geographic stratifica- tion, and differential response rates related to age, race, and gender.

As a measure of alcohol consumption, respondents estimated the number of days in the past 28 they had consumed one or more, two or more, three or more, six or more, and nine or more drinks. Similar annual drinking questions were asked of those individuals who had not consumed any alcohol in the past 28 days, but had consumed in the past year. Frequencies of consumption were measured by self-reports of the number of occasions individuals consumed one or more drinks in the past 28 days (or 1 year standardized to a 28-day basis). The remaining self-reports of drinking to two, three, six, or nine or more drinks were modeled using a log-logistic function.” For consumers who continued to drink to these levels on at least one occasion, this model of continued drinking afforded interpolated estimates of numbers of occasions on which four, five, seven, and eight or more drinks were consumed, and extrapolated estimates of the numbers of times 10,11,12, and so on, drinks were consumed (see ref. 10 for a full development of the model). These estimates were then used to calculate average expected drinks/occasion for each consumer. Total

monthly consumption was estimated as the product of frequency and average drinks/occasion.

Respondents also reported the beverage and brand they typically consumed, the typical location of purchase, the volume in which the beverage brand was typically purchased, and its cost. These responses were used to calculate typical beverage purchase prices in units pure ethanol at the reported on- or off-premise location. For wine and spirits, ethanol contents are displayed on the label. A search of liquor and grocery stores was performed to obtain brand-specific content conversions. Beer ethanol contents were obtained from data available from the Connecticut Agri- cultural Experiment Station.” For brands of unknown ethanol content, the most recent available industry average was used.12 Of the 1,038 respondents in the first wave, 908 (87%) gave both a price and a volume for a typically purchased beverage; of these, 328 (36%) named a brand that could be assigned a known rather than an industry-average ethanol content. The figures for wave 2 were 859 (90%) known unit price figures, of which 442 (51%) used exact ethanol contents. Respondents were also asked the number of days on which they consumed a drink at home, in a bar, in a restaurant, and elsewhere in the past 4 weeks. These responses were used to estimate the relative frequency of utilization of bars and restaurants. These questions were asked only of consumers who had consumed alcohol in the past 28 days.

A final series of questions asked for each respondent’s age, gender, ethnic group membership, household income, completed education, marital status, and the number of adults and minor children within the household. Race was coded Hispanic, White, or other. Education was coded as “less than completed high school,” “completed high school,” or “college graduate.” Annual household income was coded into ranges of $20,000 or less, $20,001-$40,000, $40,001-$50,000, >$50,000, or “re- fused.” Marital status was defined as “married or living with someone,” “never married,” or “divorced, separated, or widowed.” The age, gender, ethnic group, and education variables were taken as surrogates for normative background characteristics. As noted in the introduction, income was assumed to reflect monetary budgets for consumption, and the marital status and household composition variables were assumed to reflect time- energy constraints on drinking. Although crudely related to more precise measures (e.g., disposable income and more direct measures of routine time-energy allocations), within the context of variables collected on the survey, these measures were taken to reflect constraints indirectly on both monetary and time-energy budgets for alcohol use.

Estimating Beverage Quality and Total Expenditures

In lieu of having complete information on all beverage purchases by consumers, estimates of beverage quality and total expenditures relied on self-reports of typical costs of the beverage most often consumed at the most typical location of purchase. Given this information, costs/unit pure ethanol on-premise were used to index beverage quality. When consumers reported an off-premise rather than an on-premise cost for purchased beverages, the off-premise cost was extrapolated to an on-premise cost using information on contemporaneous price differentials from Treno et a].’ Estimates of total expenditures for alcohol were based on reported purchase prices for the typical beverage weighted by estimates of total 28-day consumption and relative utilization rates of on- and off-premise establishments.

Analysis Procedures

The analysis procedures used in the study followed the conceptual outline presented in Fig. 1. First, the consumption, utilization, and expenditure measures were regressed over demographics, evaluating the general relationships indicated by the straight arrows on the left side of the figure. Subsequent to these analyses, an evaluation of residual relationships was conducted to ascertain correlations among the consumption, utilization, and expenditure measures net of these demographic effects, indicated by the curved arrows on the right side of the figure. Each of these procedures will be discussed in turn.

ROUTINE ACTIVITIES AND ALCOHOL USE 47

One of the most often empirically observed, and analytically neglected, aspects of the distribution of alcohol consumption measures is their nonnormal character. Distributions of these measures are characteristically highly skewed and truncated (at 0 drinks in the general population and at some small number among consumers). Although logarithmic and power transformations may reduce the extreme skewness of these distributions, they cannot correct for truncation. Thus, the results of typical ordinary least-squares analyses of these measures, which assume complete Gaussian distributions, are biased. To remediate this problem, nonlinear TOBIT regression models were used to analyze these o ~ t c o m e s . ~ ~ , ~ ~ These models assume that the observed distribution is truncated normal and correct for the biases that would otherwise arise through neglect of this feature of the dependent measure. Thus, appropriately transformed measures of total consumption, drinking frequency, and average drinks/ occasion were regressed over all exogenous measures, with truncation points referring to limits of measurement across respondents (one drinW28 or 365 days for the measures of frequency and total consumption, one drink for the measure of drinks/occasion).

Before analysis, each of the three consumption measures were log- transformed and Box plots used to evaluate their relative frequency distributions. Because Box plots are designed to reflect the asymmetries of observed distributions, they were appropriate to the detection of outliers in the transformed data. This analysis revealed outlying observations for the measures of drinkdoccasion (0.5% of all cases) and total consumption (0.2%). These observations were Winsorized to the adjacent whisker from each plot (1.5 times the left or right interquartile range). That is, the values of the observed outliers were changed to the nearest nonoutlying value of the endogenous measure. This procedure retained these values in analysis, but reduced their influence on the outcome of the TOBIT models.

In each TOBIT regression, it was assumed that the endogenous measures were likely to be heteroskedastic across age and gender cohorts,” and the model specification included adjustments for these effects (with disturbance terms defined as functions of age and gender). Cragg specification tests were used to ascertain the appropriateness of the TOBIT specification to the analyses of these data relative to a more general truncated regression m0de1.l~ Whereas the TOBIT model assumes iso- morphism in both truncation and level effects, truncated regression models do not. For example, in the TOBIT specification, the effects of age on total consumption would be assumed to decrease the likelihood of the occurrence of an observation above the truncation point and to decrease the level of consumption when observed. On the other hand, truncated regression models would allow the relationships of age to the likelihood of truncation and observed levels of consumption to vary independently. In every case, the C r a g specification test was significant (p < 0,001). How- ever, effects observed in the truncated regression models were not substantively different from those obtained using TOBIT specifications. For this reason, the simpler TOBIT regression models are reported herein.

Measures of the relative utilization of bars and restaurants were bimo- dally distributed with modes at 0 and 1, representing double truncation points for these measures (lower and upper). Respondents’ individual truncation points were empirically established at the limits of measurement for each case (a function of total available observations), conditional truncated normal distributions were obtained using logit transformations of these measures, and double-truncated TOBIT models used for their analysis. Again, it was assumed that disturbance terms were heteroskedastic with respect to age and gender. Although C r a g specification tests proved significant for both these endogenous measures, effects from the truncated regressions were not substantively different from those obtained using TOBIT specifications. Again, the simpler TOBIT regression models are reported herein.

Because the natural logarithm of the endogenous measures of beverage quality and total expenditures were conditionally normally distributed, ordinary least-squares regression models were used for their analysis. After transformation, there were a number of outliers from each measure (Box plots, 0.3% of all cases for total expenditure and 3% for quality).

Outlying observations were Winsorized to the location of the adjacent whisker from the plots. Again, it was assumed that these effects would be heteroskedastic with respect to age and gender cohorts. Given the require- ment that these two models use complete data, and the restriction of the utilization measures to individuals who reported drinking in the past 28 days, the risk of selectivity bias was substantial. That is, results of analysis models from this subsample of more frequent users of bars and restaurants could be characteristically different from less frequent users of these venues for drinking. Tests of selectivity bias,” however, proved not significant.

Subsequent to these analyses, a nonparametric analysis of the correlations among observed residuals was conducted (based on mean expectations from the ordinary least squares and conditional mean expectations from the TOBIT models). Given the many tied scores obtained among the residuals (arising largely from truncated observations in the utilization measures) and the varied distributions underlying the original regression models (truncated and nontruncated Gaussians), Kendall’s Tau-b was used to test the significance of the relationships between residuals from the consumption patterns, utilization patterns, and total expenditure and quality regressions.

Each analysis was performed using the first wave of data available from the study (1990) and replicated using data from the second wave (1991). Given that some 56 tests were performed in each wave of analysis, findings obtained in wave 1 (p < 0.05) that are not replicated in wave 2 should be considered only marginally significant and possibly due to type I errors in analysis.16

RESULTS

The average age of the respondents to the survey was 40.2 years (SD = 14.86). 54.9% of the respondents were female and 45.1% male. Most respondents (57.9%) were married or living with someone, with somewhat fewer never married (23.3%) or divorced, widowed, or separated (18.8%). The typical respondent had completed high school (56.7%), with many having graduated from college (36.9%) and fewest having less than a high school education (6.5%). The majority of respondents were White (73.4%), with a small minority of Hispanics (9.4%), and a wide diversity of other ethnic groups represented in the sample (17.2%). Household incomes ranged broadly, with 12.3% of respondents reporting earning $20,000 or less, 29.5% earning $20,001-$40,000, 15.3% earning $40,001- $50,000, 19.8% earning $50,001 or more, and 23.1% refus- ing to report. Number of other adultshousehold averaged 1.09 (SD = 0.87) and number of youthhousehold averaged 0.77 (SD = 1.08).

Table 1 presents the results of the wave one TOBIT model regressions of the consumption pattern measures. Each independent variable was tested using either an as- ymptotic t statistic ( t ; for the interval variables age, number of adults and children, and the single degree-of-freedom dummy variable representing gender) or a likelihood ratio test (G2; for the categorical variables marital status, education, ethnic group, and income). All categorical variables were effects-coded, reflecting the categories noted in “Methods.” The test of the income effect excludes refusals. Asterisks affixed to t h e p values of significant (p < 0.05) wave 1 effects indicate those replicated using the second wave of data (p < 0.05).


Table 1. Consumption Pattern Measures (TOBIT Regressions)

Total Frequency Drinksloccasion Independent

variables b t D G' P b t P G2 P b t P G2 P

Constant

Gender Marital status

Age

Education

Ethnic group

lncomet

No. of adults No. of children

Heteroskedasticity Age Gender

1fU

2.696 -0.11 -1.153 -0.020

0.112 -0.095

0.012 0.012 0.180 0.1 11 0.126

-0.184 0.122 0.010

-0.168

0.005 0.018

1.471

- -2.122 -9.006 -0.220

1.066 -0.672

0.134 0.093 1.919 0.764 I .I 54

- 1.433 0.893 0.146

-2.908

2.334 0.326

12.292

- 0.034

<0.001* - - - - - - - - - -

0.884 0.004'

0.009- 0.372

<0.001'

993 (96%)

1.358 0.001

-1.003 1.066 0.587 0.025

0.218 0.554 0.758 -0.396

0.109 5.572 0.062 -0.064

0.100 3.324 0.505 -0.075

0.079 -0.069

0.121 0.01 8

-0.162

- 0.123

0.268 2.029

1.168

1.034

0.702

0.843 0.249

-7.845

-2.814

-0.498

-0.497

-0.502

-2.766

0.013 6.136 <0.001' -0.039 -0.689 0.245

1.167 11.800 <0.001'

993 (96%)

1.400 -0.016 -0.382

4.404 0.111 -0.071 -0.028

6.062 0.048 0.166

1.046 0.593 0.072 0.086

1.360 0.851 0.152 0.048

-0.093 0.052 0.013

-0.037

-0.049

- -7.816 -7.619 -1.947 -0.607

2.542

1.272 2.181 2.515 1.132

0.918 0.441

-0.914

- 1.634

-2.036

- <0.001* <0.001' - 5.374 0.062

- 8.260 0.016'

- 13.676 0.001

- 6.914 0.141

-

-

-

- - -

0.659 0.042

0.003 1.371 0.085 -0.044 -0.686 0.246

0.647 10.642 <0.001'

993 (96%)

* Indicates wave 2 replication. t Test of income effect absent of missing values, nonresponses, and refusals.

As shown in Table 1, age was significantly related to lower average drinks/occasion; females consumed significantly less frequently, less per occasion, and less in total than males; and lower educational levels were related to greater average drinkdoccasion. Additional effects, significant at wave 1, were obtained for age related to total consumption (inversely), education related to frequencies of consumption (directly), and ethnic group related to average drinks/occasion (Hispanics and Whites drinking more per occasion than others.) None of these additional effects replicated at wave 2. Net of these measures, the measures of marital status, income, and number of adults/ household were unrelated to any measure of consumption in either wave. However, increases in the number of children/household were significantly related to declines in frequencies of consumption and total consumption in both waves 1 and 2, and to drinks/occasion in wave 1 alone. Observed heteroskedasticity was significantly and positively related to age for the measures of drinking frequency and total consumption in both waves.

Table 2 presents the results of TOBIT regressions for the on-premise utilization measures. Younger individuals used bars significantly more frequently than older individuals. Gender and education appeared unrelated to bar and restaurant use across both waves. However, the directions of significant (p < 0.05) effects relating gender and education to restaurant use in wave 1 were repeated in wave 2. These effects suggested that females, and more educated individuals, were more likely to purchase alcohol at restaurants. Controlling for these measures, marital status was significantly related to bar use in both waves (unmarried individuals using bars more frequently than married individuals),

and income was significantly related to restaurant use in both waves (greater income related to greater restaurant use). Number of childrenhousehold was significantly inversely related to bar use in both waves, but unrelated to restaurant use. Observed heteroskedasticity was significantly related to gender for the measure of restaurant use (greater among females) and significantly related to age for the measure of bar use (lesser among older individuals) in both waves.

Table 3 presents the results of ordinary least squares regressions for the total expenditure and quality measures. Greater age was significantly related to lesser total expenditures for alcohol, and females expended less for alcohol yet purchased higher quality beverages than males. Con- trolling for these measures, greater number of children in the household was related to lesser total expenditures for alcohol, and greater income was related to the purchase of higher quality beverages. A marginal effect for marital status on total expenditure (indicating that unmarried individuals expended more on alcohol) was found only in wave 1. The observed degree of heteroskedasticity was significantly related to gender for the measures of total expenditure and quality in both waves.

The empirical relationships between the distributions of residuals obtained from the 12 regression models are plot- ted in Fig. 2. A lowess regression is fit to each of the plots outlining the observed relationships between the measures of outlet utilization, expenditure patterns, and the consumption measures. Although Fig. 2 presents the patterns of relationships for all observations, Fig. 3 presents patterns of relationships for all but the lower truncated

ROUTINE ACTIVITIES AND ALCOHOL USE

Table 2. Premise Utilization Patterns (TOBIT Regressions)

49

Restaurant use Bar use Independent

variables b t P G2 P b t P G Z P

Constant


Age

Education

Ethnic group

Incomet



l/u

n I%)

-2.261 -0.007 0.433

-0.01 7 -0.032 -0.100 -0.135 -0.018 0.161

-0.520 -0.120

0.210

-0.030 -0.049

0.287

0.004 0.215

1.289

- -0.889 2.520

-0.191 -0.273 -0.441 -1.081 -0.105 1.516

-2.372 - 1.028 1.679 2.345

-0.387 -0.832

1.494 10.196

10.196

- 0.374 0.01 2 - - - - - - - - - - 0.699 0.405

0.067 <0.001'

813 178%)

0.172

8.572

3.876

15.082

<0.001*

- 1.341 -0.032 -0.174

0.918 -0.277 0.271

0.014 0.047 0.004

0.144 0.01 7 0.092

0.005' 0.120

-0.024 -0.037 0.001

0.028

-0.248

-0.015 -0.116

3.043

- -4.671 -0.875 -2.998

0.283

0.881

2.342

0.038 0.102

0.797 0.294

-0.177 -0.298 0.017

-3.404

-7.186 -1.917

9.394

10.606 0.005'

0.288 0.866

1.744 0.418

0.624 0.960

<0.001'

\ I

* Indicates wave 2 replication. t Test of income effect absent of missing values, nonresponses, and refusals.

Table 3. Expenditure Patterns (Ordinary Least Squares Regressions)

Total expenditure Quality Independent

variables b t P G' P b t P G2 P

Constant


Education

Age

Ethnic group

Incornet



3.957 -0.015 -0.569 -0.120 0.266 0.009 0.016 0.056 0.051 0.112

-0.140 -0.057 0.144

-0.039 -0.181

0.003 -0.307

- -3.387 -5.405 - 1.535 2.670

0.177 0.466 0.607

0.058

0.831 - 1.567 -0.479 1.277

-0.606 -3.350

0.764 -2.781

681 (66%)

- <0.001' <0.001' - - - - - - - - - - 0.272

<0.001*

0.223 0.003'

I 238 -0.001 0.115

7.362 0.025 0.008 0.035

0.052

0.014 4.464 0.216 0.004

0.128 0.938 -0.085

1.288 0.525 -0.046

-0.024 -0.076 0.079

-0.031 -0.01 1

-0.001 0.258

- -0.186 3.661 0.318 1.161

- 1.967 1.994

-1.279 0.573 0.089

-0.898 -2.145 2.405

- 1.583 -0.655

-0.324 2.380

- 0.426

<0.001" - 1.940 0.379

- 4.416 0.110

- 1.673 0.433

- 9.221 0.026"

- -

-

-

- 0.056 0.256

0.746 o.ooa*

658 (63%)

Indicates wave 2 replication. t Supplementary 3 degrees-of-freedom test of income effect absent of missing values, nonresponses, and refusals.

observations for the utilization measures (utilization rates of <3% over 28 days for restaurant and bar use).

The most striking feature of the relationships between the utilization and consumption pattern measures revealed in Fig. 2 is the bifurcated nature of the plots. In each of these plots, two clouds of points can be seen: a group of points at the lower extreme of the y-axis representing those cases in which little to no utilization of restaurants or bars took place regardless of level of consumption, and a group

of points descending from the upper left to the lower right-hand corners of the plots representing those cases in which some utilization took place. Clearly, whereas the relationships between the utilization and consumption measures seem positive when all cases are included (Fig. 2), considering only that subset of cases in which individuals showed some measurable rate of utilization (Fig. 3) the relationships then seem negative. As further shown in Fig. 2, the relationships between total expenditure and the con-


Table 4. Residual Analysis (Kendall's Tau-b)

RESTUSE

BARUSE

TOTEXP

QUALITY

TCTAL FREC DPO

Fig. 2. Scatterplot matrix representing residual intercorrelations of restaurant use (RESTUSE), bar use (BARUSE), total expenditure (TOTEXP), and quality (QUALIPI) measures with total consumption (TOTAL), frequency (FREQ), and average drinks per occasion (DPO). All observations.

I

1 1 TOTAL FREO

. . . . ' . _. . . . . . .

BARUSE ... . . . . . . . . . . . , .. . . . . . .I. .

DPO

. :.: . _: :. ' .-'!; ::.>'.:. .I ...< .: . . . .

. . . . . '. . ....... :\ . . .

...... :.?.. ......

... . . . . . . . I .

Fig. 3. Scatterplot matrix representing residual intercorrelations of restaurant use (RESTUSE) and bar use (BARUSE) measures with total consumption (TOTAL), frequency (FREQ), and average drinks per occasion (DPO). Non-lower truncated observations only.

sumption measures were strongly positive, whereas the relationships between the measure of quality and the consumption measures were slightly negative.

Table 4 presents the Kendall Tau4 correlation coeffi- cients associated with each of the plots presented in Figs. 2 and 3. These nonparametric tests document the statistical

Consumption measures

Drinks/ Total Freauencv occasion

~

All Observations Utilization measures

Restaurant use -0.020 -0.015 -0.020 Bar use 0.102' 0.056* 0.153'

Total expenditure 0.576' 0.489' 0.357* Expenditure patterns

Quality -0.070* -0.083' 0.016

Removing Lower Truncated Cases Utilization measures

Restaurant use -0.312' -0.311' -0.1177 Bar use -0.281* -0.281' -0.059

* p < 0.05, waves 1 and 2. tp < 0.05, wave 1.

replicability of the relationships depicted in the figures. As the plots and the correlations show, for all observations (Fig. 2, top of Table 4), the correlations of bar use to the consumption measures were positive and significant across both waves. The correlations of restaurant use to the consumption measures were negative and not significant. The correlations of total expenditures to the consumption measures were positive and significant across both waves. Fi- nally, the correlations of quality to the measures of total consumption and frequency were negative and significant across both waves, whereas the correlation of quality with drinks/occasion was not significant.

The plots and correlations for the subset of non-lower truncated observations (Fig. 3, bottom of Table 4) show that, when cases are excluded in which less than a 3% utilization rate was observed, obtained correlations were negative and significant between the utilization measures and measures of frequency and total consumption. Consid- ering only those cases for which a measurable rate of utilization was obtained, substantive negative correlations were observed between the utilization of on-premise establishments and measures of frequency and total consumption.

DISCUSSION

The model of drinking behavior presented herein assumes that, net of their individual preferences for alcohol, consumers prefer to purchase high-quality alcohol in environments with the greatest amenity value. It is assumed that beverage quality is represented by the on-premise costs/ethanol ounce of alcoholic beverages and that amenity value is greatest at on-premise establishments. It is further assumed that these preferences are constrained only by consumers' economic and time-energy budgets for consumption. The results of this study generally verified the predictions from the model. That is, directions of effect and all replicated significant statistical tests supported model expectations. However, the observed effects were more specific than originally suspected.


The model suggested that consumption would be greater among individuals with greater budgets for consumption. Controlling for the normative effects represented by age, gender, and education, however, the measure of budgetary constraint (i.e., household income net of household composition) was not significantly related to any measure of drinking. This supports the suggestion that increased economic budgets for alcohol may not be realized in increased consumption, if the demand for ethanol per se is saturated. On the other hand, one measure of time-energy budget constraints (number of children) was significantly related to lower frequencies of consumption. Thus, the greater time and energy investments required for child rearing reduced available time and energy for the consumption of alcohol.

The conceptual separation of economic from time-energy budgets made herein asserts that household income, net of household composition, reflects disposable income available for alcohol use. It also assumes that net of household income and number of adultsihousehold, numbers of children reflect time-energy investments in child care. It is possible, however, that greater numbers of children also reflect greater economic demands on households for the provision of such care. Although it was not possible to ascertain directly this possibility in the current study, it is of some note that numbers of adults/household was not significantly related to any measure of consumption patterns or, indeed, any other outcome. If economic budgets were of singular importance to the maintenance of dependents on a single household income, regardless of age, one would expect that similar effects would appear for both numbers of adults and children.

The model also suggested that greater budgets for alcohol would be related to greater utilization of on-premise establishments. As expected, net of all other measures, greater levels of income were related to greater utilization of on-premise establishments for drinking. The focus of this effect, however, was in the use of restaurants. On-the- other-hand, greater time-energy budgets for drinking were associated with greater consumption at bars. Unmarried individuals, and those from households without children, were most likely to consume alcohol in these places.

The differentiation of effects between restaurants and bars reflects the primary distinction between drinking in these two environments. Although one goes to restaurants to eat, drinking at bars is an activity in and of itself. Al- though available income acts as a constraint on the consumption of alcohol with food (food costs adding substantially to the costs of drinking), this constraint does not operate in terms of drinking at bars (where added costs consist only of the preparation of drinks themselves). Time- energy constraints, on-the-other-hand, dominate in the use of bars where drinking is not accompanied by any other essential life activity (e.g., eating). Thus, drinking at bars is limited by the time and energy needed to pursue this activity in and of itself.

The suggestion that greater budgets for alcohol con-

sumption would be related to greater quality of beverages purchased was supported by the analyses presented herein. Net of all other measures, household income was significantly related to beverage quality. Time-energy budget measures were not. Thus, choice of beverage quality is not time-energy budget-limited. Reasonably enough, although the affordability of higher quality beverages is reflected in economic budget constraints, the time and energy it takes to consume alcoholic beverages remain constant regardless of beverage quality.

The expectation that, due largely to increases in outlay for higher quality beverages at on-premise establishments, greater budgets for alcohol consumption would be reflected in greater total expenditures for alcohol was only partially supported. Surprisingly, although total expenditures for alcohol were related to age and gender (older individuals spending less and males spending more), and to one measure reflecting limits on time-energy budgets (greater number of children related to lower total expenditures), there was no significant relationship with household income.

The final hypothesis tested from the model was that, all other things being equal (particularly household income and composition), greater consumption of alcohol would be related to increased expenditures, reduced utilization rates of on-premise establishments, and lower quality of beverages purchased. Clearly, from Fig. 2 and Table 4, greater consumption was accompanied by substantively greater levels of total expenditures. However, these greater levels of expenditure were not related to reductions in utilization rates and quality for all consumers. Thus, in comparing Figs. 2 and 3, it appeared that many consumers utilized bars and restaurants so infrequently that they simply were not subject to the effects of these constraints (at least not in areas observed in these analyses). On the other hand, among those who exhibited some use of bars and restaurants (Fig. 3), increases in the measures of consumption were all significantly related to reductions in both bar and restaurant use. Clearly, as this last analysis suggests, the sources of these divisions among the consuming population remain to be addressed.

Conclusions Data presented herein indicate that drinkers’ choices

regarding consumption patterns, on-premise utilization, and beverage quality are the result of complex social and economic factors. Economic constraints were found to ex- ert their greatest influence by affecting how much individuals pay for the alcohol they consume. Lower income individuals did not drink less, rather, they consumed lower quality goods and consumed them less in high-cost environments (e.g., restaurants). Thus, these consumers appeared willing to sacrifice quality and forgo amenity value, rather than decrease consumption. This supports an earlier speculation* that consumers could frustrate economically based interventions to decrease consumption (e.g., excise

GRUENEWALD ET AL. 52

tax increases) by altering the quality of the alcohol they consume or the locations in which they consume it. On a brighter note, it would appear that such interventions could bring about the desired result of reducing some alcohol- related problems (e.g., alcohol-related traffic crashes) by encouraging consumers to make substitutions that involve shifting consumption from higher risk on-premise locations to lower risk off-premise locations.

Although income effects appeared restricted to the expenditure-related measures, it was found that time-energy constraints on drinking behavior exerted considerable influence across the consumption, premise utilization, and expenditure measures. Notably, the presence of children in the household was related to lower levels of frequency and total consumption, reduced utilization of bars, and lower alcohol expenditures. Similarly, marital status, reflecting individuals’ investments in domestic activities, was related to the utilization of bars (greatest among single individuals). These findings suggest that those most likely to be involved in alcohol-related problems (e.g., drunken driv- ing) are likely to be those individuals with the greatest time and energy to invest in pursuing drinking as a specific routine life activity, unencumbered by economic constraints or domestic commitments.

In general, the reconceptualization of drinking patterns in terms of drinking choices serves to focus issues related to the primary epidemiology of alcohol use. Who uses alcohol and in which environments is an important question to ask regarding the implementation of preventive interventions. However, to the extent that the answers to such questions are subject to variations in environmental constraints (availability of outlets, relative costs of alcohol, and so on), flexible theoretical models, such as that proposed herein, are essential to the task. Thus, the most important empirical work suggested by this approach is the examination of drinking choices in widely different structural environments, environments in which prices for alcohol diverge in systematically different ways and in which availability is specifically constrained.

A complementary area of important work to be pursued is the empirical exploration and theoretical explanation of drinking choices made by different subpopulations of consumers. For example, distinctively different drinking choices appear to be made by drinking drivers (preferring beer) versus individuals diagnosable as alcoholic or alcohol- dependent (preferring spirit^).'^,^^ The current approach makes the straightforward suggestion that, because choice of beer minimizes costs at on-premise establishments whereas choice of spirits minimizes costs off-premise, drinking drivers will most likely be found consuming beer (thus maximizing amenity value and minimizing costs of on-premise consumption), whereas heavy drinkers will be found consuming spirits (thus maximizing consumption and minimizing total costs by purchasing spirits off-premise). Whether or not the approach can be extended to an explanation of these choices (and other more apparently anom-

alous ones, such as the preference of alcoholics for consumption of spirits at bars) remains for future research.

In addition, it seems that the approach presented herein remains somewhat theoretically limited. First, it is clear that not all the options open to consumers have been captured in the current model. For example, it is reason- able to expect that consumers could further manage their costs of drinking by consuming lower quality beverages in higher amenity value environments and higher quality beverages in lower amenity value environments (e.g., at home). Thus, remaining within the same basic theoretical frame- work, the model could be expanded to take into account trade-offs in quality and amenity value across beverage types (predicting mixtures of beverage utilization). Second, although it has been assumed that all the demographic, budgetary, and time-energy budget measures are exogenous to the measures of consumption, premise utilization, and expenditures, this is by no means a certain or even, perhaps, palatable assumption. A more appropriate model of choice under the constraints discussed herein would offer conditions under which consumers could simulta- neously optimize consumption, utilization, and expenditures in conjunction with economic and time-energy constraints. A more fuiy developed model would begin to answer how drinking choices are integrated into the every- day lives of individuals and suggest how those individual choices lead to the individual crises so evident from making the “wrong” choice.

ACKNOWLEDGMENTS

The authors appreciate the assistance of Patrick Mitchell and Alex Millar in the preparation of this manuscript, and the valuable aid of comments from three anonymous reviewers.

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