Published by Oxford University Press on behalf of the International Epidemiological Association
© The Author 2005; all rights reserved. Advance Access publication 28 February 2005
International Journal of Epidemiology 2005;34:772–780
doi:10.1093/ije/dyi026
Neighbourhood deprivation and alcohol
consumption: does the availability of
alcohol play a role?
Craig Evan Pollack,1 Catherine Cubbin,2 David Ahn2 and Marilyn Winkleby2*
Accepted
20 December 2004
Background Previous studies suggest that the physical availability of alcohol may mediate the
association between neighbourhood-level material deprivation and alcohol
consumption. This study tests the relationships between neighbourhood-level
deprivation, alcohol availability, and individual-level alcohol consumption using
a multilevel analysis.
Methods
Data are from cross-sectional surveys conducted between 1979 and 1990 as part of
the Stanford Heart Disease Prevention Program (SHDPP). Women and men
(n = 8197) living in four northern/central California cities and 82 neighbourhoods
were linked to neighbourhood deprivation variables derived from the US census
(e.g. unemployment, crowded housing) and to measures of alcohol availability
(density of outlets in the respondent’s neighbourhood, nearest distance to an outlet
from the respondent’s home, and number of outlets within a half mile radius of the
respondent’s home). Separate analyses were conducted for on- and off-sale outlets.
Results
The most deprived neighbourhoods had substantially higher levels of alcohol
outlet density than the least deprived neighbourhoods (45.5% vs 14.8%,
respectively). However, multilevel analyses showed that the least deprived
neighbourhoods were associated with the heaviest alcohol consumption, even
after adjusting for individual-level sociodemographic characteristics (OR 1.30,
CI 1.08–1.56). Alcohol availability was not associated with heavy drinking and thus
did not mediate the relationship between neighbourhood deprivation and heavy
alcohol consumption.
Conclusions Although alcohol availability is concentrated in the most deprived
neighbourhoods, women and men in least deprived neighbourhoods are most
likely to be heavy drinkers. This mismatch between supply and demand may
cause people in the most deprived neighbourhoods to disproportionately suffer
the negative health consequences of living near alcohol outlets.
Keywords
Alcohol drinking, outlets, socioeconomic status, neighbourhood, deprivation,
multilevel
Heavy alcohol consumption is linked to multiple health
problems, including motor vehicle crash injuries, domestic
violence, and chronic diseases such as cancer and liver
cirrhosis.1 Because the environments in which people live
1 Division of General Internal Medicine, San Francisco General Hospital,
University of California, San Francisco, CA, USA.
2 Stanford Prevention Research Center, Stanford University School of
Medicine, Stanford, CA, USA.
* Corresponding author. Stanford Prevention Research Center, Stanford
University School of Medicine, 211 Quarry Road, Room N229, Stanford,
CA 94305–5705, USA. E-mail: [email protected]
shape many health behaviours,2–4 there has been increased
attention as to how neighbourhood environments may
influence alcohol consumption and how environmental
changes may decrease the burden of alcohol-related health
problems.1
Although studies have shown that higher individual-level
socioeconomic status/position (SES) is associated with increased
rates of drinking, studies investigating the relationship between
neighbourhood-level deprivation and alcohol consumption
have found varying results.2 Karvonen and Rimpela5 found
that teenage boys but not girls from neighbourhoods with high
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NEIGHBOURHOOD DEPRIVATION AND ALCOHOL CONSUMPTION
rates of unemployment had increased risk of alcohol
consumption. Other studies have found little evidence of
neighbourhood variation in alcohol consumption before and
after controlling for individual-level indicators of SES.6,7
Although Scribner et al.8 found significant variation in rates of
alcohol consumption between neighbourhoods, this variation
did not depend upon the level of neighbourhood deprivation.
Alcohol availability, measured by access to stores and
restaurants that sell alcohol, may shed light on these
inconclusive findings by helping to explain the potential link
between neighbourhood deprivation and alcohol consumption.
Previous research has examined multiple dimensions of this
argument. First, a neighbourhood’s level of deprivation has
been associated with the number of alcohol outlets, with more
outlets located in deprived neighbourhoods.9,10 Second, alcohol
availability is likely to be associated with increased alcohol
consumption.8,11,12 Third, the density of alcohol outlets may
affect alcohol-related outcomes rather than consumption per se.
For example, past studies have shown that higher density of
alcohol outlets is associated with increased rates of youth
drinking and driving,13 assault violence,14 and motor vehicle
crashes15 at the city level after controlling for indicators of city
deprivation. It has also been shown that higher density of
alcohol outlets is associated with rates of injury16 and driving
after drinking11 at the neighbourhood level, and with
homicide17 and rates of traffic injury12 after controlling for
aspects of neighbourhood deprivation. Finally, one intervention
study suggests that decreasing access to alcohol outlets has
decreased injuries resulting from night-time motor vehicle
crashes and emergency room visits for assaults.18 We know of
only one previous study that has specifically examined the
relationship between neighbourhood deprivation, alcohol
availability, and individual alcohol consumption, and this
research demonstrated a potential mediating effect of alcohol
availability on the relationship between neighbourhood
deprivation and alcohol consumption.19
The present study examines whether neighbourhood-level
deprivation is associated with alcohol consumption after taking
into account individual-level sociodemographic characteristics,
including a composite indicator of SES. Furthermore, it tests
whether alcohol availability, measured in three different ways
(density of alcohol outlets, closest distance to respondent’s
home, number of outlets within a 0.5 mile buffer zone),
mediates this relationship. Individual survey data on drinking
and individual geocoded addresses were linked to
neighbourhood deprivation data from the US census and to
measures of alcohol availability to examine these questions.
Methods
Data
The analysis was based on three data sources: cross-sectional
survey data from the Stanford Heart Disease Prevention
Program (SHDPP) 1979–1990 was linked to census-defined
neighbourhood variables, and to alcohol availability records
from the California Department of Alcoholic Beverage Control.
The SHDPP was a long-term field trial designed to test whether
a comprehensive programme of community organization and
health education produced favourable changes in cardiovascular disease (CVD) risk.20 The SHDPP drew participants from
773
two treatment cities (Monterey, Salinas) and two control cities
(Modesto, San Luis Obispo) in northern/central California,
ranging in population size from 35 000 to 145 000 residents in
1980. To assess change in risk factors, five separate crosssectional surveys of randomly selected households were
conducted. All persons aged 12–74 years were eligible to
participate and were invited to attend survey centres located in
each city. The study is known for its comprehensive and careful
assessment of individual risk factors and refined sampling
methodology. Detailed descriptions of the study design and
methodology have been published previously.21
Since few significant changes in risk factors and no significant
changes in morbidity and mortality resulted from the
intervention in treatment compared with control cities, the data
for this analysis were pooled across cities.22,23 The sample for this
analysis included one woman and/or man per household aged
25–74 years, interviewed during one of the five cross-sectional
surveys (n = 8419). The lower age cut-off point of 25 years was
chosen to ensure that most individuals had completed their
education. The sample was stable in terms of mobility: nearly
80% had lived in their community for 5 years or longer.
A number of factors were considered in defining the
neighbourhood boundaries in the four cities. In order to be able
to characterize neighbourhoods using census data, we chose
a priori to rely upon census-defined boundaries, i.e. tracts
and/or block groups, both of which have been used as proxies
for geographically based neighbourhoods in previous
research.24–26 Since our study was conducted only in four
cities, we also had the opportunity to verify the census-defined
boundaries with archival neighbourhood maps. A further
consideration was determining whether census-defined
boundaries in the 1980 census were identical to those in the
1990 census. Accordingly, site visits were made to each city to
meet with key contacts in the city planning departments to
obtain neighbourhood maps and solicit advice on how each city
defined its neighbourhoods at the time of the SHDPP. For the
large majority of neighbourhoods, the boundaries corresponded
well with single census tracts or block groups. When there was
a difference (n = 12), we used a combination of tracts or block
groups to better represent neighbourhood boundaries. As a
result, a total of 82 neighbourhoods across the four cities were
defined. The same neighbourhood boundaries were used for all
the survey years and covered a median of 0.8 square miles
(range 0.2–116.7). At the 1980 census, these neighbourhoods
each contained a median of 363 people (range 16–1308). By the
1990 census, the population had increased in each
neighbourhood to a median of 4251 (range 525–12153).
Addresses of alcohol outlets were obtained from the California
Department of Alcoholic Beverage Control. Only licences listed
as active at the time of each survey year were included. The
licences were divided into on-sale outlets that allow for alcohol
consumption on the premises (e.g. bars and restaurants) and offsale outlets that allow alcohol to be purchased for consumption
off the premises (e.g. convenience and liquor stores). A total of
921 outlets were located in the 82 neighbourhoods between
1979 and 1990. Of these, 56 outlets (6%) could not be
successfully geocoded and were thus excluded, resulting in a
total of 865 on- and off-sale alcohol outlets.
SHDPP respondents were linked to neighbourhoods and
alcohol outlets based on geocoding their addresses. Following
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INTERNATIONAL JOURNAL OF EPIDEMIOLOGY
the methodology of Krieger et al.,27 we tested the accuracy of
the geocodes in two ways. Using the government geocoding
website as the ‘gold standard’ (http://www.ffiec.gov/geocode/
default.htm), we found that 95–98% (depending on the survey
year) of a random sample of 173 participant records geocoded
to the same 1990 census tract geocode as the geocoding service
that we used. Similarly, 94% of a random sample of 34 alcohol
outlets were geocoded to the same location as the geocoding
service. In addition, we conducted a site visit in two of the cities
with maps from the Bureau of the Census to determine the ‘real
world’ accuracy of the geocodes using a convenience sample of
21 records. We found that 20 out of the 21 geocodes were
located in the correct geographic area according to the Census
maps. We excluded participants who reported an address that
was not within one of the cities (n = 84 or 1.0%) and
participants whose addresses could not be geocoded (n 138 or
1.6%), resulting in a final analytical sample size of 8197. There
was an average of 21 and a median of 17 participants per
neighbourhood (range 1–107).
Dependent variable
The dependent variable was heavy alcohol consumption based
on the total number of drinks consumed per week. SHDPP
respondents were interviewed by nurses at the survey centres
in each city and were asked separate questions about their
consumption of beer or ale, wine, hard alcohol, and afterdinner liquors. The total number of drinks per week was then
classified as heavy alcohol consumption (7 drinks per week
for females and 14 drinks per week for males) based on the
increased risk of mortality associated with this level of
drinking.1
Independent variables at the individual level
The independent variables at the individual level were gender,
age, race/ethnicity, marital status, and a composite measure of
SES. The SES composite measure was calculated as the mean
of two categorical variables, each with four levels: annual
household income as a percentage of the federal poverty level
(0–200%, 201–400%, 401–600%, and 600%) and
educational attainment (12, 12, 13–15, and 16 years of
completed schooling). The Spearman correlation between
income and education was 0.33. City and survey time were
included as control variables.
Neighbourhood-level Townsend Material
Deprivation Index
The Townsend Material Deprivation Index28 was used as
the measure of neighbourhood deprivation for the
82 neighbourhoods and was composed of four census variables
(proportion of crowded occupied housing units, unemployed
persons in the civilian labour force, tenant occupied housing
units, and occupied housing units without a vehicle available).
For the first survey (1979–1980), the Townsend Index was
calculated from 1980 census data. For the last survey
(1989–1990), the Index was calculated from 1990 census data.
For surveys two through four, the Townsend Index was
calculated through a linear interpolation of the four census
variables using the values from the 1980 and 1990 censuses.
Crowded housing and unemployment were first log
transformed. Next each of the four variables were standardized
separately by city and survey as a relative measure, (i.e. high
deprivation in Monterey at survey 1 was considered to be
qualitatively different than high deprivation in Modesto at
survey 5), and then summed with equal weights. Higher
numbers indicate higher levels of deprivation (mean 0, range
8.4 to 7.9). Because neighbourhood effects are thought to be
non-linear, where significant effects are hypothesized to occur
beyond a threshold,29 the Townsend Index was categorized into
three groups; below 1 SD from the mean (least deprived), above
1 SD from the mean (most deprived), and within 1 SD of the
mean (moderately deprived). This categorization allowed us to
assess both protective and harmful effects of living in the most
and least deprived neighbourhoods in relation to respondents
living in the moderately deprived neighbourhoods.
Alcohol availability
To our knowledge, no standard exists for the measurement of
availability of alcohol outlets; therefore, we tested three
different measures (density of alcohol outlets, closest distance to
respondent’s home, and number of outlets within a 0.5 mile
buffer zone), with all outlets combined, and then separately for
on-site vs off-site outlets. The density of alcohol outlets is a
neighbourhood-level variable that represents the sum of
alcohol outlets in a particular neighbourhood divided by the
neighbourhood’s square mileage. This variable was then
dichotomized into high and low outlet densities with cut-off
points specific for both survey year and city. High outlet density
neighbourhoods were defined as being in the highest 25% of
neighbourhoods within a particular city during a given survey
year. The same method was used to define neighbourhoods as
having a high density of on-sale and off-sale alcohol outlets.
The other measures of alcohol outlets were calculated at the
individual-level using geographic information system software
(ArcView version 3.3, ESRI). For multilevel analyses these
variables were used in both a dichotomized and continuous
form. One measure was the closest straight-line distance
between a respondent’s home and an alcohol outlet. Living near
an alcohol outlet was defined as the 25% of respondents in a
given city for a specific survey year who lived closest to an
outlet. The other measure was the number of alcohol outlets
within a circular 0.5 mile buffer zone around the respondent’s
home. This distance represents a 10–15 min walk which, for
most people, is considered a maximum walking distance.30 The
25% of respondents who had the highest number of alcohol
outlets in their buffer zone (based on city and survey year) were
classified as living in a high concentration buffer zone. Similar
methods were used to determine the closest distance to on-sale
and off-sale alcohol outlets and the number of on-sale and offsale outlets in one’s buffer zone.
Analysis
To examine the extent to which alcohol consumption varied by
individual-level and neighbourhood-level factors, crosstabulations with chi-square statistics were initially employed
using SPSS, version 11.0. A series of multilevel logistic regression
models with random intercepts were then examined using the
SAS GLIMMIX macro (SAS Institute, Cary, NC). City, survey year,
and the Townsend Deprivation Index were first entered into a
model (model 1); then gender, age, race/ethnicity, and marital
NEIGHBOURHOOD DEPRIVATION AND ALCOHOL CONSUMPTION
status were added (model 2); next the composite SES measure
was added (model 3). The next set of models tested the potential
mediating effect of alcohol availability with each of the measures
added one at a time (model 4, with density of alcohol outlets
shown). A final set of models tested the independent effect of
alcohol outlets with only city and survey year included (data not
shown). We also tested for random slopes for the composite SES
measure and a cross-level interaction between the composite SES
measure and the Townsend Deprivation Index.
775
neighbourhoods also had a significantly higher density of off-sale
outlets; no significant differences were found for on-sale outlets.
Alcohol consumption, individual SES, and
neighbourhood deprivation
Figure 1 shows heavy alcohol consumption as grouped by both
individual SES and neighbourhood deprivation. In both the
lowest and the highest SES groupings, people were significantly
more likely to be heavy drinkers when they lived in the least
deprived areas.
Results
Multilevel analyses
The nested structure of the dataset showed 8197 individuals
living in 82 neighbourhoods in four different cities at five
different time points. Table 1 presents the distribution of alcohol
consumption per week for men and for women, and shows that
women were more likely to abstain from alcohol. Table 2
presents characteristics of the sample population, with the
percentage of respondents with high alcohol consumption. In
bivariate analyses, it can be seen that men, and people who
were white, non-Hispanic, previously or never married, in the
highest SES group, and living in the least deprived
neighbourhoods were significantly more likely to be heavy
alcohol consumers than their counterparts. The percentage of
heavy drinkers also varied by city and by survey year. The three
measures of alcohol availability were not significantly related to
high alcohol consumption; these measures were also not
significantly related to high consumption when stratified by
on-and off-site outlets (data not shown).
In the multilevel analyses, model 1 showed that the odds of
heavy alcohol consumption was significantly higher for people
living in the least deprived neighbourhoods (OR 1.33)
compared with those living in the moderately deprived
neighbourhoods (Table 4). In model 2, which included
demographic variables, the odds associated with living in the
least deprived neighbourhood remained significant. Model 3
added individual-level SES. With the exception of Salinas, each
variable that was significant in models 1 and 2 remained
significant in model 3. In addition, people with the highest
individual SES were significantly more likely to be heavy
drinkers than people with the lowest SES. In each model, the
survey year was significant, indicating that heavy alcohol
consumption varied over time even after accounting for
compositional factors. In the next set of models, each measure
of alcohol availability was added to the previous model in order
to test for potential mediating effects of neighbourhood
deprivation on alcohol consumption. Only the model for outlet
density is displayed because no measures related to alcohol
availability (including both the dichotomized and continuous
variables) reached statistical significance. In model 4, none of
the alcohol availability measures appeared to have a mediating
effect on the deprivation index. Similarly, none of the measures
of alcohol availability reached significance in a model
containing only city and survey year (data not shown).
Checking for random slopes of the individual-level composite
SES measure did not find significant results (not shown),
indicating that the effect of individual-SES did not vary across
neighbourhoods. In addition, there was no significant crosslevel interaction between the composite SES measure and the
Townsend Deprivation Index (not shown), indicating that the
effect of individual SES did not vary across neighbourhood
deprivation.
Density of alcohol outlets over time
The neighbourhoods showed an increasing density of alcohol
outlets over time. In the 1979–80 survey, the number of outlets
per square mile ranged between 0 and 7.9 (with 81.7% of the
neighbourhoods having 0 outlets). By the final survey in
1989–90, the range was between 0 and 87.2 outlets per square
mile, with only 4.9% of the neighbourhoods having no outlets.
The other measures of alcohol outlets did not follow a clear
trend over time. The distance to the nearest alcohol outlet
ranged from an average of 0.66 miles in survey 1, to 0.43 miles
in survey 2. Similarly, the average number of alcohol outlets in
an individual’s buffer zone was lowest in survey 1 (1.5 outlets)
and highest in survey 2 (3.6 outlets).
Alcohol outlets and neighbourhood deprivation
Table 3 shows the distribution of alcohol outlets by the
Townsend Deprivation Index. The most deprived
neighbourhoods had the highest density of alcohol outlets, the
highest percentage of individuals living near outlets, and
the highest percentage with a high number of outlets in
their buffer zone (P values 0.03). The most deprived
Table 1 Distribution of alcohol consumption by gender, Stanford
Heart Disease Prevention Program (SHDPP), 1979–1990, ages 25–74,
n = 8197
Number of alcoholic drinks in the past week
0
1–6
7–13
14–20
21+
Women (%)
46.5
36.1
10.7
4.0
2.7
Men (%)
31.1
31.4
17.1
9.8
10.7
Conclusion
The first question asked by this study was whether
neighbourhood deprivation was related to alcohol consumption. Although the most deprived neighbourhoods had the
highest density of alcohol outlets, living in the most deprived
neighbourhoods was not related to heavy drinking. Rather,
respondents who lived in the least deprived neighbourhoods
had the highest levels of heavy alcohol consumption, even after
controlling for a range of individual sociodemographic characteristics. The second question examined was whether alcohol
availability, as measured by alcohol outlets, mediated any
association between neighbourhood deprivation and heavy
alcohol consumption. Alcohol availability was not associated
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INTERNATIONAL JOURNAL OF EPIDEMIOLOGY
Table 2 Sample distributions and prevalences of high alcohol consumptiona, 1979–1990, ages 25–74, n = 8197
Percentage of Sample
(n = 8197)
Percentage with high alcohol
consumption (Overall = 15.7%)
Women
54.6
14.3
Men
45.4
18.2
25–34
30.8
14.9
35–44
23.3
16.3
45–54
16.9
17.1
55–64
16.8
16.6
65–74
12.1
16.7
P-value (two-tailed
2 test)
Sociodemographic characteristics
Gender
0.001
Age (years)
0.36
Race/ethnicity
White, non-Hispanic
83.1
17.3
Hispanic
10.8
10.5
6.1
9.1
Other race/ethnicity
0.001
Marital status
Married
68.5
14.2
Previously married
20.6
20.0
Never married
10.9
20.6
0.001
Composite SES
1 (lowest SES)
37.7
13.5
2 (low/middle SES)
20.1
16.0
3 (middle/high SES)
19.0
15.8
4 (highest SES)
23.2
20.5
0.001
Survey factors
City
Modesto
25.7
13.2
Monterey
26.8
20.7
Salinas
25.7
12.7
San Luis Obispo
21.8
17.6
1 (1979–80)
18.9
17.7
2 (1981–82)
19.0
19.4
3 (1983–84)
21.3
15.9
4 (1985–86)
20.3
16.7
5 (1989–90)
20.6
11.4
7.6
11.4
Moderately deprived
77.1
15.6
Least deprived
15.3
20.9
0.001
Survey/Time
0.001
Townsend neighbourhood deprivation
Most deprived
0.001
Alcohol availability indicators
Density of alcohol outlets
High
29.2
17.2
Low
70.8
15.6
Close
25.2
16.1
Far
74.8
16.1
0.07
Distance to nearest alcohol outlet
0.95
Alcohol outlets in 0.5 mile buffer zone
High
25.3
15.9
Low
74.7
16.1
a High alcohol consumption is defined as 14 drinks per week for men and 7 drinks per week for women.
0.80
NEIGHBOURHOOD DEPRIVATION AND ALCOHOL CONSUMPTION
777
Table 3 Distribution of alcohol outlets by Townsend neighbourhood deprivation, 1979–1990, ages 25–74, n = 8197.
Alcohol outlet indicators
Percentage of
neighbourhoods having a
high density of alcohol outlets
Townsend neighbourhood
deprivation
Percentage of respondents
living near an alcohol outlet
Percentage of respondents with a
high number of alcohol outlets in
their 0.5 mile buffer zone
All outlets
Most deprived
45.5
30.0
28.8
Moderately deprived
22.3
24.9
25.3
Least deprived
14.8
23.9
23.3
0.001
0.01
0.03
31.8
27.9
25.0
P-valuea
On-sale outlets
Most deprived
Moderately deprived
22.6
24.7
22.9
Least deprived
18.0
23.5
23.8
P-valuea
0.16
0.12
0.44
45.5
27.1
28.7
Off-sale outlets
Most deprived
Moderately deprived
19.8
25.0
28.3
Least deprived
11.5
23.9
25.4
0.001
0.33
0.10
P-valuea
a P-value based on two-tailed 2 test.
% High Alcohol Consumption
30
25
P=
0.002
0.214
0.423
Low
Low/Middle
Middle/High
0.022
20
15
10
5
0
Individual SES
Townsend
Deprivation Index
Most deprived
Moderately deprived
High
Least deprived
Figure 1 High alcohol consumption by individual-level SES and Townsend neighbourhood deprivation, 1979–1990, ages 25–74, n = 8197.
P-values based on two-tailed 2 test.
with heavy consumption and, thus, did not mediate the
relationship.
Why would living in the least deprived neighbourhoods be
associated with greater alcohol consumption? One plausible
explanation is that because heavy alcohol consumption is
associated with higher individual SES, neighbourhood
deprivation may be a proxy for unmeasured individual SES.
This explanation seems unlikely given the finding that even
respondents with the lowest individual SES were significantly
more likely to be heavy drinkers if they lived in the least
deprived areas (Figure 1). Instead, the social and cultural
climate in the least deprived neighbourhoods may make alcohol
consumption more acceptable.31 Such norms may be
influenced by the rates and types of advertising that occur
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INTERNATIONAL JOURNAL OF EPIDEMIOLOGY
Table 4 Odds ratios (OR) and 95% confidence intervals (CI) for high alcohol consumption, 1979–1990, ages 25–74, n = 8197
Model 1
OR
Model 2
CI
OR
Model 3
CI
OR
Model 4
CI
OR
CI
Sociodemographic characteristics
Gender
Women
1.00
Men
Age (per 10 years)
1.00
1.00
1.40
1.24–1.58
1.35
1.19–1.52
1.35
1.19–1.52
1.02
0.98–1.07
1.03
0.98–1.07
1.03
0.98–1.08
Race/ethnicity
White, non-Hispanic
1.00
Hispanic
0.71
0.56–0.91
0.77
1.00
0.60–0.99
0.77
1.00
0.60–0.99
Other race/ethnicity
0.50
0.37–0.69
0.51
0.37–0.70
0.51
0.37–0.70
Marital status
Married
1.00
1.00
1.00
Previously married
1.60
1.38–1.86
1.65
1.42–1.91
1.64
1.42–1.91
Never married
1.52
1.25–1.84
1.53
1.26–1.86
1.53
1.26–1.86
Composite SES
1 (low SES)
1.00
2 (low/middle SES)
1.11
0.93–1.33
1.00
1.11
0.93–1.33
3 (middle/high SES)
1.10
0.91–1.31
1.10
0.91–1.31
4 (high SES)
1.47
1.25–1.74
1.47
1.25–1.74
0.77
0.62–0.96
0.79
0.64–0.98
Survey factors
City
Modesto
0.70
0.57–0.87
0.74
0.60–0.92
Monterey
1.18
0.96–1.45
1.15
0.94–1.41
1.16
0.95–1.42
1.18
0.96–1.44
Salinas
0.71
0.57–0.88
0.79
0.63–0.99
0.80
0.65–1.00
0.82
0.66–1.03
San Luis Obispo
1.00
1.00
1.00
1.00
Survey/time
1 (1979–80)
1.67
1.32–2.10
1.68
1.33–2.11
1.75
1.39–2.20
1.75
1.39–2.21
2 (1981–82)
1.77
1.41–2.22
1.77
1.41–2.23
1.86
1.48–2.34
1.86
1.48–2.34
3 (1983–84)
1.44
1.15–1.81
1.46
1.16–1.84
1.48
1.18–1.85
1.48
1.18–1.86
4 (1985–86)
1.56
1.24–1.95
1.49
1.19–1.88
1.51
1.21–1.90
1.48
1.18–1.86
5 (1989–90)
1.00
1.00
1.00
1.00
Townsend neighbourhood deprivation
Most deprived
0.91
Moderately deprived
1.00
Least deprived
1.33
0.69–1.21
0.97
0.72–1.29
1.00
1.10–1.59
1.37
1.01
0.75–1.35
1.00
1.14–1.65
1.30
0.99
0.74–1.33
1.00
1.08–1.56
1.32
1.09–1.59
High
1.12
0.96–1.31
Low
1.00
Density of alcohol outlets
in different communities (depending, in part, on the sociodemographic profile of the community).32
Another explanation that did not find support in our study is
that neighbourhood deprivation is related to consumption
through alcohol availability. Our findings using our measures of
alcohol availability require a deeper examination of the ways in
which people access alcohol and the extent to which access has
an impact on behaviour. For example, the use of cars and public
transportation may extend the distances people are willing to
travel to purchase alcohol. This may be of greater importance in
small city urban environments and suburbs, like the ones in the
present study, where people may be more likely to drive than in
the centre of larger cities.33 This may be especially true when
people commute to work in another neighbourhood or city.
A better understanding of the division between time spent at
home, at work, and in other environments, as well as how people
move between these spaces, may better elucidate the relationship
between alcohol availability and consumption. Furthermore,
NEIGHBOURHOOD DEPRIVATION AND ALCOHOL CONSUMPTION
other factors may influence alcohol purchases including whether
off-sale outlets sell other goods (i.e. groceries), taxes on alcohol,
hours of store operation, and the concentration of outlets in
surrounding neighbourhoods.34 Unfortunately, these factors
were not available for analysis in the present study.
The clustering of alcohol outlets in more deprived
neighbourhoods warrants particular attention in light of the
lack of association between alcohol availability and heavy
drinking. Although residents of more deprived areas were less
likely to be heavy drinkers, studies have shown that alcoholrelated outcomes such as homicide, motor vehicle accidents,
and assault are often clustered near alcohol outlets and in
poorer communities. Thus, alcohol availability may not reveal
how social disparities impact health through access to goods and
services. Instead, alcohol availability may impact health by
creating more hazardous physical areas in more deprived
neighbourhoods. For example, a concentration of outlets may
create areas of decreased monitoring and relaxed social
restrictions where people congregate to drink. This may, in turn,
give rise to a greater number of accidents and/or criminal
offences and increased health risks.35
From both a health and social justice perspective, the high
level of alcohol outlet density, especially off-sale outlets, in the
more deprived neighbourhoods requires careful examination of
zoning practices, licensing procedures, and other system level
policies. Revisions of licensing procedures must focus not only
on ways of reducing the deleterious effects of heavy alcohol use
(binge drinking, public disorderliness, etc.) but also the
distribution of these effects across communities. Although
debates over hours of operation and proof-of-age requirements,
for example, are likely to be important,36 they fail to address
neighbourhood-level disparities that may continue to exist.
This study has a number of limitations. As it is cross-sectional
in design, no causal inference can be drawn about the
association between neighbourhood deprivation, alcohol
availability, and alcohol consumption. Data from this study are
from the 1980s and cannot be extrapolated to the current
environment. The five different time periods suggest that over
time the number and density of alcohol outlets increased, that
outlets tended to become more concentrated in more deprived
areas (analyses performed by each survey year, not shown), and
that the percentage of heavy alcohol drinkers decreased. This
finding is consistent with the decline of alcohol consumption in
the United States that has been documented by previous
studies.37 Although the cause of this decline in consumption
remains unclear, the concomitant decrease in consumption and
increase in outlets strengthens the null findings in this study.
Though restricted in its geographic scope of four cities in
northern California, the data facilitated comparison among the
cities and showed that rates of heavy drinking varied across
cities. This suggests that place effects, where they exist, are
likely to be specific for the locale and time period. Though the
majority of participants in this study lived in their ‘community’
for 5 years or more, this study did not specifically address length
of exposure because we cannot assume that participants’
definition of community is the same as their definition of
neighbourhood; future studies therefore need to include more
refined assessments of exposure to neighbourhoods. Another
limitation was the lack of more in-depth information about
alcohol consumption and availability, including an assessment
779
of binge drinking, places where alcohol was purchased, and
alcohol availability in surrounding neighbourhoods.
Two further methodological concerns warrant attention.
First, sampling was by household with more than one member
of each household included. To counter the potential
correlation between household members, ancillary analyses
were conducted in which one member of the household was
randomly selected for inclusion. The only appreciable difference
in results was that the town of Monterey became a significant
variable in all multilevel models (OR 1.28, CI 1.02–1.60 in
model 1). Second, this study relied upon geographically defined
census boundaries, which were verified with site visits,
interviews, and archival data. Nonetheless, census boundaries
may not accurately conform to neighbourhood boundaries as
defined by residents. Moreover, it has been argued that
neighbourhoods should be defined on the basis of patterns of
social interactions.
The strengths of this study include its use of comprehensive
and careful assessment of individual risk factors in face-to-face
interviews conducted by health professionals, its careful
construction of neighbourhood boundaries, accurate coding of
residences and alcohol outlets, and multiple measures of alcohol
availability.
In conclusion, we found that living in the least deprived
neighbourhoods was associated with heavier alcohol
consumption compared with living in the most deprived
neighbourhoods, and that this relationship was not mediated by
the availability of alcohol. In addition, we found a clustering of
alcohol outlets in the most deprived neighbourhoods. Careful
attention by researchers and policy makers is warranted to
better understand why alcohol availability is concentrated in
poorer neighbourhoods although residents in these areas are
less likely to be heavy drinkers. This seeming mismatch
between supply and demand may cause people living in the
most deprived neighbourhoods to disproportionately suffer the
negative health consequences of living near alcohol outlets.
Acknowledgements
The authors thank Naomi Kawakami for her technical assistance
in geographical information systems and Alana Koehler for her
technical assistance in preparing the tables and figures. This
work was co-funded by the National Institute of Environmental
Health Sciences and the National Heart, Lung, and Blood
Institute: Grant RO1 HL67731 to Dr. Winkleby.
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