Discussion on Neighborhood disorder, psychological distress, and heavy drinking

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Conduct 2 article critiques (1 research credit per article) of 2 different empirical papers on a topic of your choice (2 pages per article critique). You have until Tuesday, November 24th at 11:59pm to complete your article critiques. Use Georgia Tech’s online library to find the articles and use the following link as a guide to what is an acceptable journal for a published article for this assignment: https://www.scimagojr.com/journalrank.php?area=3200. This assignment should be written in APA style (https://owl.purdue.edu/owl/research_and_citation/apa_style/apa_formatting_and_style_guide/general_format.html):The main points of the paper should include answers to the following questions:Child Development in the Context of Adversity (ARTICLE 1)Neighborhood disorder, psychological distress, and heavy drinking (ARTICLE 2)

Social Science & Medicine 61 (2005) 965–975
Neighborhood disorder, psychological distress,
and heavy drinking
Terrence D. Hill, Ronald J. Angel
Department of Sociology, University of Texas, 1 University Station A1700, Austin, TX 78712, USA
Available online 19 February 2005
Abstract
Studies show that residents of disadvantaged neighborhoods drink more heavily than residents of more affluent
neighborhoods. However, explanations for this association are not well developed. Using data collected from a sample
of low-income women with children from Boston, Chicago, and San Antonio, we explore the possibility that
perceptions of neighborhood disorder encourage heavy drinking. Drawing on Conger’s (Q. J. Stud. Alcohol 17 (1956)
296) tension reduction hypothesis, we propose that the stress of living in a neighborhood characterized by problems
with drugs, crime, teen pregnancy, unemployment, idle youth, abandoned houses, and unresponsive police can be
psychologically distressing and lead some people to consume alcohol as a means of palliative escape, to regulate feelings
of anxiety and depression. In support of the tension reduction hypothesis, we find that the positive association between
neighborhood disorder and heavy drinking is largely mediated by anxiety and depression.
r 2005 Elsevier Ltd. All rights reserved.
Keywords: Neighborhood disorder; Alcohol consumption; Anxiety; Depression; USA
Introduction
If neighborhoods shape the drinking practices of
residents, how do they? In this paper, we explore the
possibility that perceptions of neighborhood disorder
encourage heavy drinking. Drawing on Conger’s (1956)
tension reduction hypothesis, we argue that the stress of
living in a neighborhood characterized by problems with
drugs, crime, teen pregnancy, unemployment, idle
youth, abandoned houses, and unresponsive police can
be psychologically distressing and lead some people to
consume alcohol as a means of palliative escape, to
regulate feelings of anxiety and depression.
Studies show that residents of disadvantaged neighborhoods drink more heavily than residents of more
affluent neighborhoods (Crum, Lillie-Blanton, & Anthony, 1996; Andrulis, 1997; Ennett, Flewelling, Lindrooth, & Norton, 1997; Fitzpatrick & LaGory, 2000;
LaVeist & Wallace, 2000); however, explanations for
this association are not well developed. Some scholars
argue that bars, liquor stores, and other retail alcohol
outlets are more prevalent in disadvantaged neighborhoods (Crum et al., 1996; Jones-Webb, Hsiao, Hannan,
& Caetano, 1997a; Alaniz, 1998; Gorman, Speer,
Gruenwald, & Labouvie, 2001; LaVeist & Wallace,
2000). Others contend that alcohol is heavily marketed
in poor and minority neighborhoods with billboards,
signs, and other forms of advertising (Lee & Callcott,
1994; Andrulis, 1997; Alaniz, 1998; Wallace, 1999;
Harwood et al., 2003). Although research shows that
alcohol availability and marketing are related to
ARTICLE IN PRESS
www.elsevier.com/locate/socscimed
0277-9536/$ – see front matter r 2005 Elsevier Ltd. All rights reserved.
doi:10.1016/j.socscimed.2004.12.027
Corresponding author. Fax: +1 512 471 1748.
E-mail addresses: tdh@mail.la.utexas.edu (T.D. Hill),
rangel@mail.la.utexas.edu (R.J. Angel).
patterns of heavy drinking in disadvantaged neighborhoods (Rabow & Watts, 1982; Cassisi, Delehant,
Tsoutsouris, & Levin, 1998; Wallace, 1999; George
et al., 2001), it is unlikely that these factors alone shape
the drinking practices of residents.
There is some evidence to suggest that various aspects
of the cultural environment may also promote heavy
drinking. That is, disadvantaged neighborhoods may
provide a normative context in which heavy drinking is
not sanctioned as strongly as within other neighborhoods (Crum et al., 1996; Krivo & Peterson, 1996;
Ennett et al., 1997; LaVeist & Wallace, 2000). Police
protection is often inadequate in disadvantaged neighborhoods, and, as a result, the consequences associated
with deviant behavior (e.g., public intoxication) may be
less severe than in other more affluent neighborhoods.
For whatever the reason, signs of alcohol consumption
are common in disadvantaged neighborhoods. For
example, Sampson and Raudenbush (1999) find that
public intoxication and empty or broken alcoholic
beverage containers are quite common in these neighborhoods. Taken together, neighborhood characteristics
such as these may signify to residents that mechanisms
of social control are weak or have ceased to function
(Sampson & Raudenbush, 1999; Gorman et al., 2001).
Building on prior research, we propose yet another
mechanism by which disadvantaged neighborhoods may
promote heavy drinking. In this paper, we argue that the
stress of living in a disadvantaged neighborhood
increases psychological distress, which in turn leads to
heavy drinking. Our presentation consists of four
sections. First, we develop the conceptual model upon
which subsequent analyses are based. Second, we
introduce the data source, measures, and statistical
procedures. Third, we use data collected from a sample
of low-income women with children from Boston,
Chicago, and San Antonio to test whether the relationship between perceived neighborhood disorder and
heavy drinking is mediated by psychological distress.
Finally, we conclude with a discussion of our findings
and the possible health implications for women and their
children.
Theoretical background
The tension reduction hypothesis
Although people consume alcohol for a variety of
reasons, research shows that people often use alcohol to
regulate unpleasant emotions (Abbey, Smith, & Scott,
1993; Holahan, Moos, Holahan, Cronkite, & Randall,
2001). Conger’s (1956) tension reduction hypothesis
proposes that (a) alcohol reduces stress-induced tension
or psychological distress, and (b) people consume
alcohol for its tension-reducing properties. Whether
alcohol actually reduces tension has yet to be established
in the literature (see Sayette, 1999). The key idea behind
the tension reduction hypothesis is that people often
consume alcohol in response to stressful conditions and
to relieve the symptoms of psychological distress,
including anxiety, depression, and other forms of
distress.
The tension reduction hypothesis has received modest
empirical support. For example, studies show that
anxiety (Pearlin & Radabaugh, 1976) and depression
(Peirce, Frone, Russell, & Cooper, 1994; Russell,
Cooper, Frone, & Peirce, 1999) may mediate the
relationship between financial stress and alcohol consumption. There is some evidence that the tension
reduction hypothesis may hold for illicit substances as
well. For example, Boardman, Finch, Ellison, Williams,
and Jackson (2001) find that psychological distress
partially mediates the association between neighborhood disadvantage and drug use. Drawing on the
tension reduction hypothesis, we argue that the stress
of living in a dangerous, threatening, or otherwise
noxious neighborhood environment can be psychologically distressing and, as a result, promote heavy
drinking.
Neighborhood disorder and stress
Neighborhoods with high levels of disorder present
residents with observable signs that social control is
weak (Ross, 2000; Ross & Mirowsky, 2001; Skogan,
1986, 1990; Skogan & Maxfield, 1981; Taylor & Hale,
1986). In these neighborhoods, residents often report
problems with crime, vandalism, graffiti, people hanging
out on the streets, public intoxication, run-down and
abandoned buildings, drug use, danger, trouble with
neighbors, and other incivilities associated with the
breakdown of social control (Geis & Ross, 1998;
LaGrange, Ferraro, & Supancic, 1992; Lewis & Maxfield, 1980; Lewis & Salem, 1986; Ross & Mirowsky,
1999; Skogan, 1986, 1990). These are some of the signs
of neighborhood disorder. They convey to residents that
social order has broken down and signify a potential for
threat and danger. In this paper, we argue that living
with this potential can be stressful and, in time,
psychologically distressing.
Neighborhood disorder and psychological distress
It is easy to see how neighborhoods characterized by
problems with drugs, crime, teen pregnancy, unemployment, idle youth, abandoned houses, and unresponsive
police can be stressful. Still to be conceptualized are
the mechanisms through which neighborhood disorder
may shape the drinking practices of residents. In this
paper, we hypothesize that the relationship between
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966 T.D. Hill, R.J. Angel / Social Science & Medicine 61 (2005) 965–975
neighborhood disorder and heavy drinking is mediated
by psychological distress.
It is evident that living in a neighborhood where the
streets are dirty and dangerous, buildings are run-down,
abandoned and vandalized, and young people are
hanging out can be psychologically distressing. Indeed,
studies consistently show that daily exposure to disadvantage, disorder, and decay in one’s neighborhood is
psychologically distressing (Aneshensel & Sucoff, 1996;
Ross, 2000; Ross, Reynolds, & Geis, 2000; Schulz et al.,
2000; Boardman et al., 2001; Steptoe & Feldman, 2001;
Christie-Mizell, Steelman, & Stewart, 2003; Latkin &
Curry, 2003).
Mirowsky and Ross (2003a) describe a two-stage
process by which neighborhood disorder can be
psychologically distressing. They argue that neighborhood disorder is likely to create frequent or chronic
activation of the fight-or-flight response, which is the
body’s initial neuroendocrine response to threat or
danger. In the short term, frequent activation of the
fight-or-flight response is conducive to feelings of fear
and anxiety. In the long term, the perceived inability to
escape threat or danger and feelings of fear and anxiety
may take its toll in depression—feeling run-down,
lethargic, and hopeless about the future. In accordance
with this two-stage process, we hypothesize that (1) the
observed relationship between neighborhood disorder
and heavy drinking is mediated by anxiety, and (2) the
association between anxiety and heavy drinking is
mediated by depression. See Fig. 1 for an illustration
of our conceptual model.
Sample
We test our hypotheses using a sample of disadvantaged women from the Welfare, Children, and Families
(WCF) project (see http://www.jhu.edu/welfare/). The
WCF project is a household-based, stratified random
sample of approximately 2400 low-income families from
Boston, Chicago, and San Antonio. The data were
collected in 1999 with a follow-up in 2001, when about
87% of the sample was re-interviewed. The WCF first
sampled census blocks (or neighborhoods) with at least
20% of residents below the Federal Poverty line based
on the 1990 census. Within these neighborhoods,
households under 200% of the poverty line were
sampled, with an over-sample of households below
100% of the poverty line. Because one of the goals of the
WCF project is to assess the impact of welfare policy
and work on children, households were screened for the
presence of children. Households with preschool children (aged 0–4) and young adolescents (aged 10–14)
were sampled (see Chase-Lansdale et al. 2003). The
children’s caregivers, all women, were interviewed
face-to-face.
Respondents live in Boston (37%), Chicago (32%),
and San Antonio (31%). The sample is Black (43%),
Mexican origin (24%), other Hispanic (22%), and White
(9%). On average respondents are 33 years of age, with
11 years of formal education. The majority of respondents are not married (86%) and unemployed (59%).
See Appendix A for bivariate correlations and baseline
descriptive statistics.
Measures
Heavy drinking is the dependent variable. It captures
the most fundamentally problematic aspect of drinking
behavior—getting drunk. Instead of asking respondents
to recall various frequencies or quantities, our measure
of heavy drinking requires respondents to recollect
discrete occasions during which they had gotten drunk.
Respondents were asked, ‘‘In the past twelve months,
how often have you gotten drunk?’’ Response categories
were coded never (0), once or twice (1), several times (2),
and often (3). Using the 1985 National Survey on Drug
Abuse, Robbins (1989) employed a similar measure of
heavy drinking and found strong positive associations
with psychological distress, social, and behavioral
problems.
Perceived neighborhood disorder is the focal exogenous
variable. Neighborhood disorder refers to conditions
ARTICLE IN PRESS
+
+ + +
+
Neighborhood
Disorder
Fearful
Anxiety
Depression Heavy
Drinking
Fig. 1. Conceptual model of a process by which neighborhood disorder affects heavy drinking.
T.D. Hill, R.J. Angel / Social Science & Medicine 61 (2005) 965–975 967
and activities that signify the breakdown of social order.
Neighborhood disorder is measured as a summed
response to ten items. Respondents were asked to rate
their neighborhood environment in terms of assaults
and muggings, drug dealing in the open, gangs, unsafe
streets during the day, burglaries and thefts, teenage
pregnancy, abandoned houses, police not being available, unsupervised children, and high unemployment.
Response categories for these items were coded not a
problem (0), somewhat of a problem (1), and a big
problem (2).
Fearful anxiety and depression are the mediating
variables. Both are composite measures obtained from
the Brief Symptom Inventory (BSI) developed by
Derogatis (2000). Fearful anxiety is measured as the
mean response to five items. Respondents were asked to
indicate how much, during the past 7 days, they were
distressed or bothered by feeling tense or keyed up,
suddenly feeling scared for no reason, feeling so restless
they could not sit still, spells of terror or panic, and
feeling fearful. Depression is measured as the mean
response to six items. Respondents were asked to
indicate how much, during the past 7 days, they were
distressed or bothered by feeling no interest in things,
feeling lonely, feeling blue, feelings of worthlessness,
feeling hopeless about the future, and thoughts of
ending their life. Response categories for both sets of
measures were coded not at all (0), a little bit (1),
moderately (2), quite a bit (3), and extremely (4).
Numerous background factors have been identified as
significant correlates of risky drinking practices. While
heavy drinkers are often younger (Catalano, Dooley,
Wilson, & Hough, 1993; Midanik & Clark, 1994; JonesWebb, 1998), unemployed (Sampson & Laub, 1990;
Catalano et al., 1993), and financially disadvantaged
(Pearlin & Radabaugh, 1976; Pierce et al., 1994; JonesWebb et al., 1997a, b), they are less likely to be black
(Jones-Webb, 1998; Wallace, 1999), married (Horwitz &
Raskin-White, 1991; Stack & Wasserman, 1993), highly
educated (Cooper, Russell, & Frone, 1990; Mirowsky &
Ross, 2003b), or religiously involved (Beeghley, Bock, &
Cochran, 1990; Gorsuch, 1995; Stark & Bainbridge,
1998). In accordance with previous research, subsequent
multivariate analyses control for age, race, education,
marital status, church attendance, work status, and
economic hardship.
We divide background factors into socioeconomic
and sociodemographic control variables. Socioeconomic
control variables include education (in years), employment status (1 ¼ worked for pay in past week), and
economic hardship. Economic hardship is measured as
the mean response to thirteen items, and each of these
items has been standardized to account for metric
differences (see Appendix B). Sociodemographic control
variables include age (in years), race/ethnicity (White,
Mexican, and other Hispanic compared with Black),
marital status (1 ¼ married and living with spouse),
church attendance (0 ¼ never to 4 ¼ more than once per
week), and city (Boston and San Antonio compared
with Chicago).
Analytic strategy
Main analyses: drinking at baseline and change in
drinking
In our main analysis, we use ordinary least-squares
regression (OLS) to model the prediction of
heavy drinking at baseline (time 1) in three steps.1
Model 1 tests whether neighborhood disorder affects
heavy drinking over and above relevant background
factors. Models 2 and 3 add potential mediators.
Model 2 includes fearful anxiety, and model 3 introduces
depression.
Although we hypothesize that fearful anxiety and
depression mediate the impact of neighborhood disorder
on heavy drinking, alcohol consumption and psychological distress are reciprocally related. To ensure that our
hypothesized pathways are not simply a reflection of
reciprocal influence, we also model the change in heavy
drinking over time. Adjusting for heavy drinking at
Time 1, we predict the change in heavy drinking (Heavy
DrinkingT2Heavy DrinkingT1) with neighborhood
disorder at Time 1, the change in neighborhood
disorder, anxiety at Time 1, the change in anxiety,
depression at Time 1, the change in depression, and the
background factors.
Supplemental analyses: change in depression and attrition
analysis
To formally test whether anxiety leads to depression
in a longitudinal sense, we model the change in
depression over time. Adjusting for depression at Time
1, we predict the change in depression (DepressionT2DepressionT1) with fearful anxiety at Time 1,
the change in anxiety, neighborhood disorder at Time 1,
the change in neighborhood disorder, and the background factors.
Because the dependent variables for the change
models incorporate measures from Time 1 and 2, we
estimated a logistic regression model predicting sample
attrition (see Appendix C). The dependent variable in
this case is dummy-coded such that respondents who
completed questionnaires at both points in time were
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1
Because the dependent variable is ordinal with four
categories, the models presented in Table 1 were also estimated
with ordered logistic regression. Because both the ordered
logistic and OLS models support identical substantive conclusions, the more conventional OLS models are reported here.
968 T.D. Hill, R.J. Angel / Social Science & Medicine 61 (2005) 965–975
given a value of zero, and those who completed the Time
1 questionnaire only were given a value of one. Overall,
attrition is seemingly random and is only predictable
from San Antonio residence at the 0.10 level. Since we
adjust for San Antonio residence, attrition is unlikely to
bias regression coefficients (Winship & Radbill, 1994).
As an added precaution, we compare results from the
change analysis to the results from the Time 1 crosssectional analysis, which includes all respondents
(Mirowsky & Reynolds, 2000).
Results
Neighborhood disorder, psychological distress, and heavy
drinking
Model 1 of Table 1 shows that neighborhood disorder
is positively associated with heavy drinking, net of
socioeconomic variables indicative of disadvantage and
hardship. Women who live in neighborhoods they
characterize as having a lot of problems with drugs,
crime, teen pregnancy, unemployment, idle youth,
abandoned houses, and unresponsive police drink more
heavily or get drunk more often than those who report
more order in their neighborhoods.
The remaining models show a sequence of mediators
that explain the association between neighborhood
disorder and heavy drinking. With the addition of
fearful anxiety in model 2, the association between
disorder and heavy drinking is reduced by 50%
(.006–.003)/.006). Neighborhood disorder is no longer
significant at conventional levels with the introduction
of fearful anxiety. Fearful anxiety is positively associated with heavy drinking.
Depression is added in model 3. Depression is
positively associated with heavy drinking and further
explains the association between fearful anxiety and
heavy drinking. With the introduction of depression, the
coefficient for anxiety is reduced by 62% and becomes
insignificant. Compared with residents who report little
disorder in their neighborhoods, residents of neighborhoods with high levels of disorder drink more heavily or
get drunk more often, and fearful anxiety explains about
half of this association. In turn, respondents who report
high levels of fearful anxiety also drink more heavily
than others, and depression explains about two-thirds of
this relationship.
Table 2 shows the effects of neighborhood disorder,
fearful anxiety, and depression on the change in heavy
drinking, with adjustment for heavy drinking at Time 1.
The results of this analysis are similar to those shown in
Table 1. People who report high levels of neighborhood
disorder and people who report increasing levels of
disorder over time drink more heavily or get drunk more
often by Time 2, even with adjustment for heavy
drinking at baseline. It does not appear to be the case
that the associations between fearful anxiety, depression,
and heavy drinking are actually reflections of the effect
of drinking on distress. People who have high levels of
fearful anxiety and depression at baseline, and people
whose psychological distress worsens over time, drink
more heavily by Time 2.
These analyses also support a causal sequence in
which fearful anxiety and depression mediates the
influence of neighborhood disorder on heavy drinking.
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Table 1
Heavy drinking regressed on individual level socioeconomic,
sociodemographic characteristics, and neighborhood disorder
(Model 1), fearful anxiety (Model 2), and depression (Model 3).
WCF (1999)
Model 1 Model 2 Model 3
Neighborhood
disorder
0.006* 0.003 0.003
(0.002) (0.002) (0.002)
Fearful anxiety — 0.138*** 0.052
(0.023) (0.034)
Depression — — 0.225***
(0.030)
Education 0.003 0.002 0.003
(0.006) (0.006) (0.006)
Employment status
(1 ¼ employed)
0.028 0.034 0.035
(0.027) (0.026) (0.026)
Economic hardship 0.074** 0.033 0.008
(0.024) (0.025) (0.024)
Age 0.009*** 0.009*** 0.008***
(0.001) (0.001) (0.001)
Whitea 0.112* 0.095 0.103*
(0.050) (0.049) (0.049)
Mexicana 0.014 0.028 0.027
(0.037) (0.037) (0.037)
Other Hispanica 0.124** 0.136*** 0.136***
(0.037) (0.036) (0.036)
Marital status 0.125** 0.120** 0.107**
(1 ¼ married) (0.039) (0.038) (0.038)
Church attendance 0.082*** 0.079*** 0.078***
(0.011) (0.011) (0.011)
Bostonb 0.013 0.004 0.003
(0.034) (0.034) (0.034)
San Antoniob 0.128** 0.116** 0.110**
(0.035) (0.034) (0.034)
Intercept 0.715 0.559 0.443
Nested F — 35.353*** 5.481***
R2 0.089 0.103 0.124
Notes: N ¼ 2286. Shown are metric coefficients with standard
errors in parentheses. All variables are measured at Time 1.
*po0.05, **po0.01, ***po0.001 (two-tailed t-tests).
aCompared with Black.
b
Compared with Chicago.
T.D. Hill, R.J. Angel / Social Science & Medicine 61 (2005) 965–975 969
With the addition of anxiety and change in anxiety in
model 2, the association between disorder and the
change in heavy drinking is reduced by 14%. The
association between the change in disorder and the
change in heavy drinking remains the same. Although
the effect of neighborhood disorder is slightly reduced
with the addition of the anxiety measures, both disorder
measures continue to be significantly related to the
change in heavy drinking across models. With the
introduction of the depression measures in model 3,
the anxiety measures become insignificant.
Table 3 shows the effects of anxiety and the change in
anxiety on the change in depression, with adjustment for
depression at baseline. People who report high levels of
fearful anxiety and people whose anxiety increases over
time, report more depression by Time 2. Overall, the
hypothesized sequence of mediators receives support in
the change analysis. This is not to say that anxiety,
depression, and heavy drinking are not reciprocally
related. Research has shown that they are. Our results
simply provide evidence that is consistent with the
sequence of mediators postulated by our model.
Neighborhood disorder, economic hardship, and heavy
drinking
Of the three socioeconomic variables included in our
analyses, only economic hardship is consistently correlated with heavy drinking. According to model 1 of
Table 1, people who report high levels of economic
hardship drink more heavily than those who experience
less hardship. With the addition of fearful anxiety in
model 2, the association between economic hardship and
heavy drinking is reduced by 55% and is no longer
significant at conventional levels. The introduction of
depression in model 3 further attenuates the association
between economic hardship and heavy drinking—by a
total of 89% from model 1. Model 1 of Table 2 indicates
ARTICLE IN PRESS
Table 2
Change in heavy drinking regressed on individual level socioeconomic, sociodemographic characteristics, and neighborhood
disorder (Model 1), fearful anxiety (Model 2), and depression
(Model 3). WCF (1999, 2001)
Model 1 Model 2 Model 3
Neighborhood
disorderT1
0.007**
(0.003)
0.006*
(0.003)
0.006*
(0.003)
Neighborhood
disorderT2T1
0.006*
(0.003)
0.006*
(0.003)
0.006*
(0.003)
Fearful anxietyT1 — 0.106*** 0.024
(0.025) (0.041)
Fearful anxietyT2T1 — 0.134*** 0.040
(0.026) (0.038)
DepressionT1 — — 0.092*
(0.038)
DepressionT2T1 — — 0.112**
(0.033)
Heavy drinkingT1 0.558*** 0.565*** 0.570***
(0.021) (0.021) (0.021)
Education 0.004 0.003 0.003
(0.006) (0.006) (0.006)
Employment status 0.045 0.056* 0.057*
(1 ¼ employed) (0.026) (0.026) (0.026)
Economic hardshipT1 0.040
(0.027)
0.010
(0.028)
0.001
(0.028)
Economic
hardshipT2T1
0.080**
(0.025)
0.055*
(0.025)
0.044
(0.025)
Age 0.005*** 0.005*** 0.004**
(0.001) (0.001) (0.001)
Whitea 0.124** 0.113* 0.111*
(0.048) (0.048) (0.048)
Mexicana 0.088* 0.091* 0.096**
(0.036) (0.036) (0.036)
Other Hispanica 0.074* 0.079* 0.083*
(0.035) (0.035) (0.035)
Marital status
(1 ¼ married)
0.022
(0.037)
0.020
(0.037)
0.011
(0.037)
Church attendance 0.045*** 0.043*** 0.041***
(0.011) (0.011) (0.011)
Bostonb 0.013 0.020 0.021
(0.033) (0.033) (0.033)
San Antoniob 0.067* 0.066* 0.065
(0.034) (0.034) (0.033)
Intercept 0.313 0.190 0.153
Nested F — 15.585*** 5.882**
R2 0.280 0.291 0.295
Notes: N ¼ 2004. Shown are metric coefficients with standard
errors in parentheses.
po0:05; po0:01; po0:001 (two-tailed t-tests).
aCompared with Black.
b
Compared with Chicago.
Table 3
Change in depression regressed on fearful anxiety. WCF (1999,
2001)
Model 1
Fearful anxietyT1 0.620***
(0.024)
Fearful anxietyT2T1 0.836***
(0.018)
DepressionT1 0.692***
(0.020)
Intercept 0.305
R2 0.656
Notes: N ¼ 2004. Shown are metric coefficients with standard errors in parentheses. Model includes controls for
neighborhood disorder and all background factors. po0:05:
po0:01; po0:001 (two-tailed t-tests).
970 T.D. Hill, R.J. Angel / Social Science & Medicine 61 (2005) 965–975
that people whose economic hardship increases over
time drink more heavily by Time 2. With the addition of
fearful anxiety in model 2, the association between the
change in economic hardship and the change in heavy
drinking is reduced by 31%. The introduction of
depression in model 3 further reduces this association
by a total of 45% from model 1.
Taken together, these results reveal a pattern of
mediation that is similar to the one described in the
disorder model. While anxiety appears to explain a
greater portion of the direct effect of economic hardship
and disorder, depression seems to explain more of the
main effect of economic hardship than disorder. These
similarities lend further support for our model and
suggest that the sequence of mediators postulated by our
model may extend to other chronic stressors such as
economic hardship.
Background factors and heavy drinking
Overall, the background correlates of heavy drinking
are the same among disadvantaged women in disadvantaged neighborhoods as they are for all Americans.
What differs for these women is their inordinate
exposure to disorder and hardship, not the impact of
these problems on drinking. Notably, age, marriage
(baseline only), and church attendance are inversely
associated with heavy drinking. Education is one
exception to this general conclusion. In representative
samples, education is inversely related with problem
drinking.
Discussion and conclusion
Previous research has shown that residents of
disadvantaged neighborhoods are disproportionately
exposed to a number of potential risk factors for heavy
drinking. Although alcohol availability and marketing
in disadvantaged neighborhoods are clearly related to
the drinking practices of residents, research has focused
almost entirely on the hazards of opportunity and
exposure. To further understand the relationship between neighborhood context and the drinking practices
of residents, we explored the possibility that perceptions
of neighborhood disorder encourage heavy drinking.
Drawing on Conger’s (1956) tension reduction hypothesis, we argued that the stress of living in a neighborhood characterized by problems with drugs, crime, teen
pregnancy, unemployment, idle youth, abandoned
houses, and unresponsive police could be psychologically distressing and that people consume alcohol as a
means of palliative escape, to regulate feelings of anxiety
and depression. In support of the tension reduction
hypothesis, we find that neighborhood disorder is
positively associated with heavy drinking and that this
association is largely mediated by anxiety and depression. More specifically, we find evidence of a two-stage
process (see Mirowsky & Ross, 2003a) by which the
observed relationship between neighborhood disorder
and heavy drinking is mediated by anxiety, and the
association between anxiety and heavy drinking is
mediated by depression.
Heavy drinking under stressful conditions is understandable. However, drinking to cope with psychological distress is likely make things worse, not better.
Indeed, studies show that heavy drinking may undermine the health and well-being of women and their
children (see Thadani, 2002). For women, heavy
drinking can damage the nervous system, including the
brain (Oscar-Berman, Shagrin, Evert, & Epstein, 1997),
alter endocrine operations and diminish immune function (Emanuele & Emanuele, 1997; Kovacs & Messingham, 2002), elevate blood pressure and increase the risk
of hypertension, stroke, and heart disease (Russell et al.,
1999; Mukamal & Rimm, 2001), impede bone growth
and bone tissue replacement, resulting in decreased bone
density and increased risk of fracture (Sampson, 1998).
Heavy drinking may also interfere with normal sleep
patterns (Oscar-Berman et al., 1997; Roehrs & Roth,
2001) and increase psychological distress (Mirowsky &
Ross, 2003a; Petrakis, Gonzalez, Rosenheck, & Krystal,
2002).
For children, maternal alcohol use during pregnancy
may contribute to a range of negative health outcomes,
including hyperactivity and attention problems, learning
and memory deficits, and problems with physical, social,
and emotional development (Goodlett, 2001; Maier,
2001; Jacobson & Jacobson, 2002). Once the child is
born, alcohol abuse on the part of the mother can also
lead to child abuse, including physical abuse, sexual
abuse, neglect, and emotional or psychological abuse
(Widom & Hiller-Sturmhofel, 2001).
Needless to say, research on the health implications of
heavy drinking suggests a number of interesting
prospects for future research. Although studies show
that neighborhood disorder is associated with poor
health, explanations for this association are undeveloped
at this time. Based on the results of the present study, we
recommend that future research consider whether risky
drinking practices help to explain how perceptions of
neighborhood problems might adversely affect health,
both mental and physical.
Our research has several limitations that should be
addressed. While the WCF is a valuable data source for
examining the effects of neighborhood disorder, it does
have certain restrictions. One limitation is our measurement of heavy drinking. Our measurement is based on a
single item. Studies often combine multiple measures of
drinking behavior, which tends to increase reliability.
Although our measure heavy drinking is less reliable
than would be ideal, the associations presented in this
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T.D. Hill, R.J. Angel / Social Science & Medicine 61 (2005) 965–975 971
ARTICLE IN PRESS
Appendix A. Bivariate correlations and descriptive statistics
A B C D E F G H I J K L M N O P Q
A. Heav y drinking — — — — — — — — — — — — — — — — —
B. Neighborhood disorder 0.09** — — — — — — — — — — — — — — — —
C. Fearful anxiety 0.15** 0.17** — — — — — — — — — — — — — — —
D. Depression 0.23** 0.18** 0.77** — — — — — — — — — — — — — —
E. Education 0.04* 0.01 0.03 0.01 — — — — — — — — — — — —
F. Employed 0.01 0.06** 0.06** 0.05* 0.12** — — — — — — — — — — — —
G. Economic hardship 0.07** 0.15** 0.30** 0.32** 0.04* 0.04 — — — — — — — — — — —
H. Age 0.17** 0.09** 0.03 0.06** 0.16** 0.01 0.10** — — — — — — — — — —
I. White 0.05* 0.01 0.06** 0.02 0.01 0.04 0.03 0.12** — — — — — — — —
J. Black 0.05* 0.07** 0.07** 0.04* 0.25** 0.07** 0.02 0.01 — — — — — — — — —
K. Mexican 0.03 0.00 0.03 0.02 0.25** 0.06** 0.02 0.07** — — — — — — — — —
L. Other Hispanic 0.11** 0.08** 0.02 0.02 0.05** 0.00 0.02 0.02 — — — — — — — — —
M. Married 0.10** 0.11** 0.06** 0.09** 0.06** 0.00 0.09** 0.02 0.01 0.13** 0.13** 0.01 — — — — —
N. Church attendance 0.20** 0.11** 0.07** 0.08** 0.01 0.04* 0.02 0.19** 0.12** 0.00 0.03 0.04 0.13** — — — —
O. Boston 0.07** 0.12** 0.00 0.00 0.08** 0.01 0.04 0.06** 0.16** 0.10** 0.43** 0.41** 0.03 0.05* — — —
P. Chicago 0.03 0.16** 0.04 0.05* 0.06** 0.02 0.02 0.02 0.00 0.12** 0.03 0.15** 0.01 0.00 — — —
Q. San Antonio 0.10** 0.04* 0.03 0.04* 0.02 0.00 0.02 0.09** 0.09** 0.01 0.43** 0.29** 0.02 0.05* — — —
Min–Max 0–3 0–20 1–5 1–4.6 0–14 0–1 0.90–3.3 15–74 0–1 0–1 0–1 0–1 0–1 0–4 0–1 0–1 0–1
Mean or proportion 0.39 8.46 1.38 1.52 10.51 0.41 0.00 32.78 0.09 0.43 0.24 0.22 0.14 1.58 0.37 0.32 0.31
Standard deviation 0.65 5.53 0.59 0.68 2.38 — 0.56 9.98 — — — — — 1.19 — — —
Alpha reliability — 0.88 0.81 0.84 — — 0.83 — — — — — — — — — —
*po0.05, **po0.01(two-tailed t-tests).
972 T.D. Hill, R.J. Angel / Social Science & Medicine 61 (2005) 965–975
paper are likely to reflect conservative estimates.
Another limitation is that the sample is entirely
composed of women. While it is true that women are
especially vulnerable to psychological distress, it is also
the case that men tend to drink more heavily. It is
unclear whether the model developed in this paper
would find support in a sample of men.
Although a fair amount of research suggests that
residents of disadvantaged neighborhoods drink more
heavily than residents of other neighborhoods, explanations for this association are not well established.
Despite the limitations of the data, our results provide
insight into the complex nature of this relationship. In
this paper, we find that the stress of living in a
neighborhood characterized by problems with drugs,
crime, pregnant teens, unemployment, young people
hanging out, abandoned houses, and unresponsive
police can be psychologically distressing and that people
consume alcohol as a means of palliative escape, to
regulate feelings of anxiety and depression.
Acknowledgments
We thank Catherine Ross for valuable comments on
previous drafts.
Appendix B. Measurement ofeconomic hardship
How often does your household have to borrow money
to pay bills? Responses are coded never (0) to all the
time (4).
How often does your household have put off buying
something you need because you don’t have money?
Responses are coded never (0) to all the time (4).
How often can your household afford to do things just
for fun like going to the movies or eating out? Responses
are coded all the time (0) to never (4).
During the past 12 months, how much difficulty did
your household have paying the bills? Responses are
coded no difficulty at all (0) to a great deal of difficulty
(4).
Does your household have enough money to afford the
kind of housing, food, and clothing you feel you should
have? Responses are coded definitely yes (0) to and
definitely no (3).
Think about the end of each month over the past 12
months, how much money did your family end up with?
Responses are coded more than enough money left over
(0) to not enough to make ends meet (3).
At any time in the past 12 months, did you or other
adults in your household cut the size of your meals or
skip meals because there wasn’t enough money for food?
Responses are coded yes (1) and no (0).
At any time in the past 12 months, did you or other
adults in your household not eat for a whole day
because there wasn’t enough money for food? Responses
are coded yes (1) and no (0).
At any time in the past 12 months, were you ever hungry
but didn’t eat because you couldn’t afford enough food?
Responses are coded yes (1) and no (0).
In the past 12 months, did you lose weight because there
wasn’t enough food? Responses are coded yes (1) and no
(0).
At any time in the past 12 months, did you cut the size of
any of [child’s] meals because there wasn’t enough
money for food? Responses are coded yes (1) and no (0).
At any time in the past 12 months, did [child] skip a meal
because there wasn’t enough money for food? Responses
are coded yes (1) and no (0).
At any time in the past 12 months, was [child] hungry,
but you just couldn’t afford more food? Responses are
coded yes (1) and no (0).
Appendix C. Logistic regression analysis predicting
sample attrition
Variable Odds Ratios
Heavy drinking 1.146
Neighborhood disorder 0.994
Fearful anxiety 0.907
Depression 0.975
Education 0.967
Employment Status (1 ¼ employed) 1.037
Economic Hardship 0.921
Age 0.996
Whitea 1.236
Mexicana 1.048
Other Hispanica 1.118
Marital status (1 ¼ married) 0.981
Church Attendance 0.955
Bostonb 0.848
San Antoniob 0.738+
Model w2 11.352
+
po.10.
aCompared with Black.
b
Compared with Chicago.
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Child Development in the Context of Adversity
Experiential Canalization of Brain and Behavior
Clancy Blair and C. Cybele Raver
New York University
The authors examine the effects of poverty-related adversity on child development, drawing upon psychobiological
principles of experiential canalization and the biological
embedding of experience. They integrate findings from
research on stress physiology, neurocognitive function,
and self-regulation to consider adaptive processes in response to adversity as an aspect of children’s development.
Recent research on early caregiving is paired with research in prevention science to provide a reorientation of
thinking about the ways in which psychosocial and economic adversity are related to continuity in human development.
Keywords: stress, self-regulation, preventive intervention,
poverty, development
Pand early childhood, perhaps throughout the life span, are to a considerable extent characterized by erceptual and cognitive development in infancy
the shaping and constraining of abilities by experience, by
gain through loss. A widely cited illustrative example of
such environmentally induced specificity in development is
a decline in the ability to discriminate phonetic contrasts in
infancy. Between approximately 6 and 10 months of age,
infants lose the ability to discriminate phonemes in nonnative languages while maintaining and strengthening the
ability to discriminate phonemes in the native language
(Kuhl, Williams, Lacerda, Stevens, & Lindblom, 1992;
Werker & Tees, 1986). With such a trade-off or narrowing
of development in infancy, however, come gains in perceptual ability that enable the coordination of multiple
sensory attributes (Pons, Lewkowicz, Soto-Faraco, & Sebastia ´n-Galle ´s, 2009). The tuning of perceptual networks to
attend primarily to regularly occurring contrasts precedes
the development of the ability to integrate across perceptual
networks, facilitating the emergence of more elaborate and
complex types of perceptual experience (Lewkowicz &
Ghazanfar, 2009).
The progressive selection and shaping of abilities has
also been proposed as a chief characteristic of life span
development (Baltes, Staudinger, & Lindenberger, 1999).
In life span theory, development in later adulthood has
been described as a process of selective optimization with
compensation, in which ability within a given domain is
maintained by a narrowing of the focus and scope of
activities within that domain in order to compensate for a
gradual decline in ability. Although only one of several
competing theories concerning development in middle and
later adulthood, the theory of selective optimization with
compensation embodies the idea that the shaping of behavior by biology and experience represents a general developmental process involving trade-offs. As development
takes away with one hand, it gives with the other.
The idea that development is shaped by biology and
experience coactively to promote specific abilities over
others is known as experiential canalization (Gottlieb,
1991, 1997). Experiential canalization describes a general
developmental process through which biology and typically occurring experience combine, often in ways that go
largely unnoticed, to influence behavior. A foundational
demonstration of the process of the experiential canalization of development is provided by Gilbert Gottlieb’s research on the development of the recognition of the maternal call in mallard and wood duck hatchlings.
Recognition of the maternal call, in which the hatchling
orients to the vocalizations of its own species and not to
those of another, appears to be a classic example of instinctual behavior, meaning that it is hardwired and innate.
Gottlieb demonstrated, however, that the wiring that underlies this behavior is malleable and that this seemingly
instinctual behavior is driven as much by experience as by
genes. A central idea in the canalization model is that
experience induces functional activity from the behavioral
level to the cellular level to shape development to maximize functioning within a specific expected environment.
As such, the environment in combination with genetic
background directs the process of development; this combination functions as the source of information in a developmental system. In other words, directions for developThis article was published Online First March 5, 2012.
Clancy Blair and C. Cybele Raver, Department of Applied Psychology, Steinhardt School of Culture, Education, and Human Development,
New York University.
Clancy Blair acknowledges support from Eunice Kennedy Shriver
National Institute of Child Health and Human Development Grants R01
HD51502 and P01 HD39667 (with co-funding from the National Institute
on Drug Abuse) and from Institute of Education Sciences Grant
R305A100058. C. Cybele Raver acknowledges support from Eunice Kennedy Shriver National Institute of Child Health and Human Development
Grant R01 HD046160.
Correspondence concerning this article should be addressed to
Clancy Blair, Department of Applied Psychology, Steinhardt School of
Culture, Education, and Human Development, New York University,
Kimball Hall, 8th Floor, 246 Greene Street, New York NY 10003. E-mail:
clancy.blair@nyu.edu
May–June 2012 ● American Psychologist 309
© 2012 American Psychological Association 0003-066X/12/$12.00
Vol. 67, No. 4, 309–318 DOI: 10.1037/a0027493
This document is copyrighted by the American Psychological Association or one of its allied publishers.
This article is intended solely for the personal use of the individual user and is not to be disseminated broadly.
ment are not simply encoded in DNA or present in the
environment in a predetermined sense (Oyama, 2000);
rather, genetic information and environmental information
coactively and probabilistically determine behavioral and
psychological development.
Without reference to experiential canalization, little in
development makes sense. That is, without taking into
account functional relations across levels of analysis, explanations for processes of development become overly
determined, and the individual contributions of either biology or experience, of nature or nurture, are overemphasized
(Lickliter & Honeycutt, 2003). Accordingly, experiential
canalization, or the selective optimization of behavior in
response to experience, is a central aspect of what is known
as the developmental psychobiological model. This model
offers a framework for understanding the implications of
developmental trade-offs, of opportunities taken or foreclosed, that are inherent in distinct developmental pathways. Such a perspective on development provides for
greater complexity and specificity as well as for greater
probability of change or reversibility than is implied by an
additive or simple interactive model of biological and environmental inputs leading to child outcomes.
Poverty, Parenting, and the
Psychobiology of Self-Regulation
In this article we apply the developmental psychobiological model of experiential canalization to research on
children’s development in the context of poverty-related
adversity in an effort to break new ground for interpreting
recent research findings and for designing future research
and preventive and therapeutic interventions. Consideration of psychobiological processes may be particularly
important for understanding the ways in which variation in
typical experience associated with socioeconomic status
(SES) affects child development. It is well established that
the material and psychosocial contexts of poverty adversely
affect multiple aspects of development in children (Bradley
& Corwin, 2002; Duncan & Brooks-Gunn, 2000; Noble,
McCandliss, & Farah, 2007). Poverty affects where and
how family members live, limiting housing options to those
that are often characterized by higher levels of crowding,
violence, and lack of safety (Evans, 2004; Kohen, Leventhal, Dahinten, & McIntosh, 2008). Economic hardship
exacerbates conflict between adults, with children in poor
households facing a higher probability of disrupted social
relationships with key adults in their lives (Watson &
McLanahan, 2011). As parents struggle with a range of
stressors, the probability of parents’ depressive symptoms,
emotional distress, and expressions of anger and aggression
in the household also rises, with cascading effects on
children’s psychological development (Ackerman &
Brown, 2010; Foster & Brooks-Gunn, 2009; Molnar, Buka,
Brennan, Holton, & Earls, 2003). Children in conditions of
economic hardship face a wide array of dangers (e.g.,
higher probability of exposure to environmental teratogens
such as lead, higher levels of noise and crowding, and
lower levels of household and neighborhood safety) and
simultaneously lower access to supportive environments,
such as high-quality child care (Brooks-Gunn & Duncan,
1997).
The material and psychosocial hardships of poverty
are very real, and their effects on development are often
severe. As such, these effects, generally speaking, have
tended to be characterized within a deficit model in which
children are seen as lacking specific inputs, whether environmental or genetic or both, that are needed to avoid
compromised development. For example, a gradient between the amount of input, such as maternal language, and
output, such as vocabulary development in children, is well
established and has been shown to covary with income
(Hart & Risley, 1985). Consideration of the context of
poverty only from a deficit-oriented, input–output perspective on child development, however, is of less theoretical
and empirical value than one might hope. An important
feature of the experiential canalization model is that it
indicates the relevance of focusing not only on the absence
of particular types of stimulation but also on the presence
of alternative types of stimulation that actively shape development to meet a specific set of contingencies. Although
cognition and behavior in children from low-income homes
are often clearly differentiated from those of their middleincome counterparts, there is little to suggest that the mechanisms underlying the observed differences, whether defined in terms of environmental factors or in terms of
genetic similarity, are best explained in an additive, input–
output fashion. The principle of experiential canalization
indicates the need to focus on the ways in which variables
across levels of analysis, from the genetic to the social,
combine to shape development in favor of one trajectory
over another and to promote continuity for good and for ill.
Clancy Blair
310 May–June 2012 ● American Psychologist
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Experiential Canalization of
Development in Low- Versus
High-Resource Environments
Recent advances in neuroscience and neuropsychology illustrate the developmental psychobiological model and experiential canalization of self-regulation development in
children. In the model shown in Figure 1, characteristics of
the environment influence parents’ psychological functioning and in turn the quality of caregiving they provide.
Quality of caregiving is then in turn hypothesized to act as
a key mediator of the linkage between children’s exposure
to poverty-related hazard and subsequent physiological,
neurobiological, and cognitive development. In this process, the development of stress physiology is a central
component of the model, one in which stress hormone
levels act as a primary canalizer or mechanism through
which cognitive and social-emotional development in early
childhood is shaped by experience—most specifically, the
development of neural systems important for self-regulation, defined here as the primarily volitional regulation of
attention, emotion, and executive functions for the purposes of goal-directed actions (Blair & Ursache, 2011).
The basis for the experiential canalization model of
self-regulation development is found in a number of animal
models that examined the effects of early experience on
development. This research (primarily with rats) has demonstrated that chronic stress in the prenatal and/or very
early neonatal periods has multiple negative sequelae.
These studies demonstrate that early stress alters gene
expression and induces structural changes as well as
changes in connectivity in brain areas that underlie stress
response physiology (Karssen et al., 2007; Liston et al.,
2006; Patel, Katz, Karssen, & Lyons, 2008; Radley, Arias,
& Sawchenko, 2006). In turn, alteration of stress response
physiology influences activity in neural systems that underlie self-regulation abilities, including executive functions (Cerqueira, Mailliet, Almeida, Jay, & Sousa, 2007;
Holmes & Wellman, 2009), or what can be considered
tendencies to a more reflective or more reactive response to
experience. This is because stress hormones are modulators
of neural activity in the brain (Arnsten, 2000; Yuen et al.,
2009) and at moderate levels of increase lead to long-term
synaptic potentiation in corticolimbic circuitry associated with
prefrontal cortex (PFC), the seat of executive function abilities. At very high or very low levels of neuroendocrine increase, however, synaptic activity in PFC circuitry is decreased, and activity in brain systems associated with more
reactive forms of learning and behavior is increased (Ramos
& Arnsten, 2007; Segal, Richter-Levin, & Maggio, 2010).
Given the relations among the constructs in Figure 1,
it appears that one way in which early experience may
shape or program the development of the organism is by
altering neural connectivity and sensitivity to neuroendocrine levels in pathways that underlie tendencies to more
reactive as opposed to more reflective responses to experience. With an increasingly established relation between
stress hormone levels and self-regulation, a central research
C. Cybele
Raver
Figure 1
Model of the Experiential Canalization of Self-Regulation Development
May–June 2012 ● American Psychologist 311
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question concerns the extent to which effects of environmental quality on the neural substrate that supports selfregulation are mediated by and can be remediated through
early experience, particularly early caregiving. The idea
that caregiving acts as a key mediator of the effect of
poverty on child development has been shown in a number
of studies (McLoyd, 1998). Research on early experience
in animal models indicates the psychobiological shaping of
behavior and cognition through early caregiving effects on
stress physiology. In one widely cited example, Meaney
and collaborators (Meaney & Szyf, 2005) have shown that
variation in naturally occurring maternal behavior in the rat
during the offspring’s first eight postnatal days is associated with the expression of a gene that codes for the density
of neural receptors for glucocorticoids in the hippocampus.
This effect is a highly meaningful one in that glucocorticoid receptor density is central to the regulation of neuroendocrine levels, which, as noted above, are highly relevant to the activity in brain areas associated with more
volitional and proactive responses to stimulation (Robbins
& Arnsten, 2009) and with complex learning and memory
(Liu, Diorio, Day, Francis, & Meaney, 2000).
Although there are many interesting aspects of the
developmental process linking early caregiving experience
to later behavior in the animal models described above, one
of the most important from the standpoint of developmental
psychobiology is that variation in the maternal behaviors in
the rat that initiate the cascade from the behavioral to the
genetic level and back again is in part driven by the quality
of the environment in which development is occurring. The
idea here is that environmental quality leads to particular
types of caregiving behaviors that initiate a physiological
cascade leading to patterns of development that are appropriate or beneficial for that environment (Cameron et al.,
2005; Meaney, 2001, 2010). Such coactions among genes,
behavior, and environments provide new insight into processes of development. These and other studies provide
growing evidence to support the idea that early caregiving
and stress physiology serve as primary conduits or sources
of information in a developmental system. As such, early
caregiving can be understood to shape the development of
child behavior in ways that are appropriate for the context
in which development is occurring.
Adaptation and Change in Development
The notion of developmental trade-offs in the experiential
canalization approach is consistent with a rationale for
future research that might profitably investigate the idea
that adversity in the context of poverty shapes neural development and perhaps also molecular genetic processes
and leads to adaptations in behavior and mental states that
are relevant to that environment. Adaptive shaping of behavior in low-resource environments, however, should not
be taken to imply the development of necessarily optimal
or desirable states of functioning. On the contrary, adaptation to low-resource environments involves short-term
“benefits” as well as long-term “costs” to the organism,
both psychologically as well as physically, that are due to
increased stress on organ systems resulting from alterations
to stress and immune system functioning. Recent epidemiological findings suggest that low SES is consistently related to poorer health in later life (Jackson et al., 2004;
Miller et al., 2009). One mechanistic interpretation of these
findings is that alterations to stress and immune system
functioning in children in low-SES homes represent an
adaptive trade-off. For example, low-SES background has
been associated with up-regulation of genes associated with
adrenergic function and down-regulation of genes associated with the regulation of the hypothalamic–pituitary–
adrenal (HPA) axis (Miller et al., 2009). Increased adrenergic and glucocorticoid responses to stimulation would
enable a more reactive and faster response to threats, both
physical and psychosocial, and as such would confer an
advantage in unsafe environments. Such a trade-off, however, would come with short- and long-term costs to health
and well-being that would preferentially shape physical and
psychological development along particular trajectories
while limiting the likelihood of development along others.
The experiential canalization approach offers a
sharper lens through which to reexamine models of poverty
and child development. Although research on the canalization of development through caregiving and stress physiology is in an early stage, a growing number of studies
provide a neurobiological basis for well-documented associations between poverty and child physical and psychological health and development. For example, a longitudinal study with pre- and early adolescent children has
demonstrated that a cumulative risk index composed of
psychosocial and physical characteristics of the home environment differentiated high- from low-SES homes and
was positively and linearly associated with an index of
stress physiology biomarkers in children that included cardiovascular function, body mass index, and overnight levels of catecholamines and cortisol. Furthermore, the risk
index was associated with reduced delay of gratification,
increased learned helplessness, greater psychological distress, and reduced working memory in children, indicating
links among poverty, stress physiology, and self-regulation
(Evans, 2003; Evans & English, 2002; Evans & Schamberg, 2009).
A second longitudinal study beginning at birth that we
have been conducting with a large group of collaborators
has followed a sample of 1,292 children from predominantly low-income and nonurban communities. This study,
known as the Family Life Project, has demonstrated that
poverty is associated with elevated cortisol in infancy and
early childhood and that this association is mediated
through characteristics of the household (Blair, Raver, et
al., 2011; Hibel, Granger, Blair, Cox, & the Family Life
Project Investigators, 2011). Furthermore, this study has
shown that, as outlined above, parenting sensitivity mediates the relation between poverty and stress physiology
(Blair et al., 2008; Mills-Koonce et al., 2011) and that, in
combination, parenting sensitivity and elevated cortisol
mediate the association between poverty and low levels of
executive function abilities in children (Blair, Granger, et
al., 2011).
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Studies of young children in conditions of more extreme forms of compromised caregiving involving neglect
and maltreatment in infancy and early childhood also provide evidence of experiential canalization in the context of
adversity. Children who have experienced exceptionally
harsh treatment from caregivers demonstrate alterations to
HPA axis function including hyperactivity followed by
later hyporeactivity (Gunnar, Fisher, & the Early Experience, Stress, and Prevention Network, 2006). An important
aspect of this model is that it can be extended to include
exposure to aggression from peers as well as adults. In a
sample of monozygotic twins discordant for the experience
of bullying, the bullied members of the twin pairs showed
blunted, or hyporesponsive, cortisol secretion in response
to a lab stressor compared with their nonbullied but genetically identical counterparts (Ouellet-Morin et al., 2011). In
contrast, the nonbullied twins showed an expected increase
in cortisol secretion in response to the moderately stressful
lab task. These findings highlight the neurophysiological
and behavioral trade-offs that accompany the process of
experiential canalization in the face of environmental
adversity. In discussing their findings, the investigators
squarely considered these trade-offs and addressed the
question of whether the blunted, hyporesponsive HPA
axis profile demonstrated by the bullied children’s response to psychosocial stress was “adaptive or detrimental” (Ouellet-Morin et al., 2011, p. 580).
Here development may be giving with one hand—
conferring developmental advantage through blunting of
the HPA axis to protect the brain from iatrogenic effects of
prolonged cortisol elevations—while taking away with the
other—the blunting of the cortisol response leading to
longer term health costs. This set of trade-offs is manifested at the behavioral level as well in that chronic exposure to others’ anger and aggression tunes children’s attention and responsiveness in favor of heightened vigilance to
emotionally negative stimuli (Cicchetti & Rogosch, 2009;
Pollak, Messner, Kistler, & Cohn, 2009; Pollak, Vardi,
Putzer Bechner, & Curtin, 2005). Such heightened vigilance may be beneficial in the short run, keeping children
alert and ready to respond when facing potentially threatening situations or interactions at home or at school. That
same level of behavioral vigilance may translate to a level
of wariness or reticence with unfamiliar teachers and peers
that carries longer term social costs. These findings provide
support for the idea that chronic exposure to adversity, such
as can occur more frequently in the context of poverty,
actively shapes physiological and behavioral development
in ways that are adaptive for that context.
Implications of Experiential Canalization for
Reversibility, Reoptimization, and
Intervention
As noted above, physiological, cognitive, and behavioral
adaptations to the context of adversity and compromised
caregiving can result in objectively worse chances of positive life course outcomes. Applied to children in poverty,
such a psychobiological process in development might
understandably be associated with short-term “beneficial”
adaptations but potentially harmful long-term sequelae. In
the context of maltreatment specifically, or in low-resource,
unpredictable caregiving environments more generally, altered HPA axis responsivity, biased attributional style, and
hypervigilance to environmental cues allow for more rapid
learning and response to conditions of threat (Champagne
et al., 2008; Pollak, 2008). These processes, however, also
increase the chances of negative interpersonal interactions
and high levels of difficulty in social contexts such as
school (Cicchetti & Rogosch, 2009).
Attention to potential exchanges or trade-offs that
make given behaviors rewarded and rewarding versus
problematic provides insight into ways that poverty-related
adversity may profoundly shape children’s development.
Attention to these trade-offs, however, also underscores
ways in which neurocognitive and behavioral profiles of
self-regulation can be altered. A central implication of the
experiential canalization approach is that the shaping of
development by experience offers an opportunity for repair
and reversal. Just as the system is open to shaping and
selective optimization in the face of high levels of disadvantage, so too might the system be reoptimized to meet
changing environmental demands and conditions. A sanguine implication of models of experiential canalization,
however, is that there are few if any opportunities for an
“easy fix”: In setting aside input–output models of development, seemingly straightforward solutions for altering
children’s self-regulation and executive function will have
a lower probability of success than will interventions that
take canalizing processes across multiple levels into account.
Repair Through Mediating Mechanisms of
Caregiving
In the developmental psychobiological framework, experiential and biological influences on development are highly
intertwined. For this reason, supporting adults to maintain
high levels of responsiveness, consistency, and warmth can
be expected to lead to more flexible regulation of stress
physiology with cascading influences on child self-regulation. A considerable body of research in prevention science
demonstrates that parenting intervention can be successful
in altering the quality of caregiving that adults provide to
young children while those adults navigate a large number
of stressful poverty-related hazards. Recent parent training
programs have shown significant success in helping adults
to acquire new caregiving goals and schema, alter their use
of negative forms of discipline, and engage in more sensitive and responsive and less coercive and inept forms of
caregiving, with short-term reductions in young children’s
behavioral dysregulation (Brotman, Gouley, Klein, Castellanos, & Pine, 2003; Dishion et al., 2008; Dozier et al.,
2009; Izard, Sann, Spelke, & Streri, 2009; Landry, Smith,
Swank, & Guttentag, 2008; Mendelsohn et al., 2005; Webster-Stratton, 1998).
For example, implementation of multiple years of the
SAFEChildren intervention supporting parenting practices
among low-income families facing high levels of violence
led to significant increases in parents’ use of more stable,
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consistent forms of caregiving and limit setting, with concomitant improvements in children’s regulation of attention, impulsivity, and behavior (Tolan, Gorman-Smith,
Henry, & Schoeny, 2009). Effect sizes of these interventions range from small impacts with “dilute” forms of
intervention (see Dishion et al., 2008) to larger effect sizes
for more intensive intervention efforts (e.g., d .5 for
improvement in responsive caregiving and child attention
deployment; Landry et al., 2008). An essential point from
the perspective of the experiential canalization of development is that these models of parent skills training often
engage parents through attention to parents’ own regulatory
profiles of affect, behavior, and cognition in conditions of
high environmental stress (Dishion et al., 2008; Izard et al.,
2009; Fisher & Stoolmiller, 2008). Equally important is
that careful experimental designs in “real-world” contexts
have dramatically increased our ability to make clear causal
inferences regarding the role of caregiving provided by
adults as a critical mediating mechanism in canalization
models of human development.
Studies of parenting training also provide some evidence of effects on aspects of child self-regulation, including attention and emotion regulation (Landry, Smith, &
Swank, 2006). As well, evaluations of outcomes for children experiencing extreme caregiving disruption that results in foster care placement provide initial support for a
process by which changes in caregiving behavior are associated with changes in stress physiology that should be
conducive to executive function abilities and more reflective self-regulation of behavior. Children of foster care
parents receiving training in emotionally supportive and
contingent behavior demonstrated a more typical pattern of
diurnal cortisol change (higher morning levels and a consistent decline through the day) as well as lower overall
cortisol levels (Dozier, Peloso, Lewis, Laurenceau, &
Levine, 2008; Fisher, Stoolmiller, Gunnar, & Burraston,
2007). Similarly, preschool children at risk for conduct
disorder in families receiving an intervention to promote
responsive parenting demonstrated an appropriate increase
in cortisol in anticipation of a moderate social challenge
relative to children in a randomly assigned control group
(Brotman et al., 2007).
Evidence from the obstacles and successes encountered within parenting interventions also highlights the
extent to which canalizing processes are bidirectional and
reciprocal and the extent to which attention to this reciprocity, as a process of the active maintenance of patterns
of behavior, is needed to promote intervention efficacy.
Children’s behaviors and regulatory profiles that may have
been adaptive in the context of past environmental contingencies may also shape future environmental contingencies, eliciting continued styles of suboptimal care from
adults in ways that are sometimes difficult to disrupt in
intervention contexts that focus only on adult behavior
change. For example, in the preventive intervention for
children in foster care noted above, family members
needed interventionists’ support in order to avoid becoming
caught in an escalating cycle of rising negative arousal,
biased cognitive attributions, and behavioral responses of
dismissiveness, disengagement, and withdrawal (Dozier,
2005; Dozier et al., 2009). In light of this cycle of escalating dysregulation and withdrawal, Dozier and colleagues
(2009) designed their intervention to support foster parents’
ability to structure a set of environmental contingencies
that might canalize children’s more optimal trajectories of
regulation over time. In so doing, the interventionists considered that there are also significant trade-offs in shifting
into new patterns of emotional regulation and that caregivers need to be supported in making greater investments in
approaching rather than withdrawing during emotionally
negative bouts of interaction with their foster children. The
implication from such an approach is that caregivers would
need to concomitantly shift the expectations and responses
of others in additional environmental contexts, including,
for example, teachers in their children’s preschools, in
order for their children’s altered forms of self-regulation to
be sustained rather than transitory. In short, canalizing
models indicate that change in multiple, rather than single,
environmental contexts is necessary if newly canalized
trajectories of responding are to be supported over time.
While promising, the above findings provide limited
but suggestive evidence of canalizing processes in development and the potential malleability of development
through intervention and support. Within this framework, a
key question concerns whether intervening in cycles of
maladaptive caregiving and dysregulation in parent– child
interactions yields linked improvements both in child stress
physiology and self-regulation abilities. Although no intervention studies to date have fully tested such a model, the
findings described above strongly indicate the need for
direct empirical examinations of this model. As well, two
important points related to the foregoing concern prenatal
experience as well as the possibility that some children may
be more or less sensitive or susceptible to alterations to
experience. A substantial literature on the relation of prenatal experience to postnatal development indicates that
canalizing processes begin early and can have meaningful
implications for later self-regulation (Davis & Sandman,
2010; Markham, Toth, & Lickliter, 2006). Similarly, the
growing literature on differential susceptibility or biological sensitivity to context suggests that temperamental and
physiological differences among children are central to the
processes by which biology and experience coactively
shape development (Ellis, Boyce, Belsky, BakermansKranenburg, & van Ijzendoorn, 2011).
Alternative Pathways to Repair Through
Mediating Mechanisms: Classroom-Based
Intervention
Although findings emerging from the recent parenting interventions discussed above are promising, it is important
to underscore that behavioral change may be easier to
engineer among some parents than among others (e.g.,
among full-time working parents who are not able to attend
extensive trainings and workshops). Further, the estimated
size of the effect or impact of those interventions on child
outcomes is generally small and may not be sustained
unless the “dose” of intervention is high and continues
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across several developmental periods (see Landry et al.,
2008). A clear implication from both theoretical and policy
perspectives is that for many children, interventions targeting the quality of caregiving represent only partial rather
than full solutions to children’s self-regulatory difficulty.
One benefit of an experiential canalization approach is
that multiple ecological contexts can be viewed as positive
canalizers of self-regulation development. Those new, enriched environmental contexts can be viewed as mediators
of the impact of poverty-related hazard on long-term trajectories of development (Blair, 2002). For example, results from recent preschool intervention trials suggest that
exposure to cognitively stimulating and behaviorally wellmanaged classrooms benefits low-income children’s executive functioning (Bierman, Nix, Greenberg, Blair, &
Domitrovich, 2008; Diamond, Barnett, Thomas, & Munro
2007; Morris, Raver, Lloyd, & Millenky, 2009; Raver,
Jones, et al., 2011). An important qualification to these
findings is that it remains to be seen whether interventions
would benefit children to an even greater extent if both
home and preschool contexts were targeted. However,
these intervention trials offer compelling evidence that
out-of-home environments may serve as additional mediating influences for young children’s developmental trajectories. These findings also provide powerful empirical support for the claim that new experiences of environmental
enrichment can be structured to capitalize on those biobehavioral and neurocognitive processes, such as the development of executive functioning, that may be “late breaking” in developmental time.
This theoretically motivated recognition of stage salience
in considering experiential canalization might be profitably
applied to a next generation of interventions: How can neuroendocrine and neurocognitive reorganizations that coincide
with key developmental transitions in early childhood, middle
childhood, and early adolescence be targeted through intervention, and in what settings would such interventions have
maximal impact? We are only just beginning to understand
processes through which stress response physiology, corticolimbic neural circuitry, and self-regulation behavior may be
shaped in developmental periods extending past infancy.
Pressing questions regarding normative patterns of change in
stress physiology as well as specific biobehavioral mechanisms through which change occurs need to be tested within
experimental contexts offered by randomized controlled trials.
Experimental changes in the environmental conditions
of poverty itself offer an additional, powerful way to test
theoretical propositions laid out by the experiential canalization approach. Do such interventions lead to reductions
in psychological stress, or lower wear and tear on the part
of adults and children, and are hypothesized reductions in
allostatic load in low-income families associated with measurable changes in children’s neuroendocrine and neurocognitive functioning? Although evidence is sparse, a
quasi-experimental study from the Opportunidades poverty-alleviation program in Mexico suggests that among children at high risk (with caregivers experiencing high depressive symptoms at baseline), community-level efforts to
reduce poverty are associated with lower average cortisol
levels in children (Fernald & Gunnar, 2009). To our knowledge, studies of antipoverty programs (such as evaluations
of the benefits of the Earned Income Tax Credit and of
conditional cash transfers) have not yet included assessments of whether children’s self-regulatory trajectories are
affected. However, we view this potential line of inquiry as
promising, with the caveat that the induction and facilitation of new patterns of stress reactivity and behavior may
be limited unless we are committed to substantial and
sustained efforts to intervene across ecological settings and
across time.
Conclusion
The evidence reviewed in the foregoing sections helps us to
recognize that exposure to environmental adversity is a
primary shaper of development from the cellular to the
behavioral and social levels. Environmental exposure, as a
primary constituent of development, is like other contributors to development, malleable. Poverty presents a remediable rather than a static set of environmental conditions
that must be borne by families and children. The environmental conditions of poverty, however, work to maintain
continuity by constraining change across levels of analysis.
Conceiving of development as a process of continuity
through adaptation provides us with large, new empirical
territory in which to test models of experiential canalization
and the limits of developmental change. To do that, we can
deploy hybrid models of experimental design at the policy
level combined with careful measurement at the biobehavioral and neurocognitive levels to detect developmental
benefits across a broad array of pathways. Such hybrid
models of scientific inquiry also allow us to ask whether the
timing of intervention is central to limiting the ultimate
developmental cost of the hazard and maximizing the opportunity for remedy.
Throughout this article we have argued that development
is shaped by biology and experience coactively to promote
specific abilities over others, in processes of gain through loss
(Gottlieb, 1997). We have argued that advances in developmental science may be powerfully fueled by recognition of the
potential trade-offs posed by a given behavior and the environmental contingencies that make such a behavior rewarded
and rewarding versus problematic or costly to the individual.
We have also outlined new ways to conceptualize developmental continuity as a result of both socially and biobehaviorally mediated processes rather than as a result of faulty or
inadequate environmental input or genetic vulnerability. By
considering the processes linking early experience, stress
physiology, and gene expression as canalizing forces that
shape the development of brain and behavior, we offer a
model of development that is fundamentally plastic and remarkably complex and that veers markedly away from simple
input–output, deficit-compensation models. In so doing, we
hope to shed light on the new directions that the fields of
developmental science, prevention science, and public policy
may take in the years ahead.
May–June 2012 ● American Psychologist 315
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