Journal of Pediatric Psychology, Vol. 27, No. 7, 2002, pp. 575-583
© 2002 Society of Pediatric Psychology
The Influence of Socioeconomic Status and Ethnicity on Adolescents' Exposure to Stressful Life Events
University of Pittsburgh
All correspondence should be sent to Karen A. Matthews, Department of Psychiatry, University of Pittsburgh, 3811 O'Hara St., Pittsburgh, Pennsylvania 15213. E-mail: karenmat{at}pop.pitt.edu.
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Abstract |
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Objective: To test the relations between resource-based and prestige-based measures of socioeconomic status (SES), ethnicity, and life events that varied in valence, dependency on adolescent behavior, and duration.
Method: Six measures of SES were administered to the parents of 148 black and white adolescents, who completed a measure of five mutually exclusive categories of life events.
Results: As predicted, our results suggest that having few assets and being black were independently related to life events exposure. Correlations between socioeconomic indices were not so high as to suggest redundancy, and different SES indicators were of importance in predicting exposure to different types of life events.
Key words: socioeconomic status; ethnicity; adolescent behavior; life events.
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Introduction |
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Socioeconomic status (SES) is a composite measure of one's resources and prestige within a community (Krieger, Williams, & Moss, 1997
). Resources include both material goods
(e.g., owning a home) and assets (e.g., savings), whereas prestige refers to
one's status within a social hierarchy and is typically determined by the
classification of education and profession according to the esteem placed on
each by society. In nearly every disease category, adults of lower SES
experience higher rates of morbidity and mortality than adults of higher SES
(see Adler et al., 1994;
Anderson & Armstead, 1995;
Haan, Kaplan, & Syme,
1989; Marmot, Kogevinas, &
Elston, 1987, for reviews). Similar findings have been documented
in samples of children and adolescents when relations between family SES and
health are examined (see Chen, Matthews,
& Boyce, 2002, for a review).
Many mechanisms have been posited to explain the relation between lower SES
and poorer health in youths, including poorer health care, inadequate
nutrition, and unsafe living conditions. Such mechanisms would be of use in
explaining threshold effects of lower SES on health, but relations between SES
and health have been demonstrated to be linear across the entire spectrum of
SES (Chen et al., 2002;
Kitagawa & Hauser, 1973;
Marmot, Shipley, & Rose,
1984).
The purpose of this study is to explore one potential mechanism between
lower SES and poorer health in adolescence: exposure to stressful life events.
Available data suggest that adolescents exposed to greater amounts of
stressful life events report a greater incidence of physical illness,
including number of physicians' visits, diagnosed illnesses, current physical
problems (Gad & Johnson,
1980), headache proneness
(Newcomb, Huba, & Bentler,
1981), and overall symptoms of physical illness
(Baldwin, Harris, & Chambliss,
1997). Some data suggest that uncontrollable stressful life events
are particularly related to poor health, such as fatigue, coughing, and
headaches (Newcomb, Huba, & Bentler,
1986).
A first step in examining stressful life events as a potential mediator
between SES and health is to demonstrate that exposure to life events differs
meaningfully across the SES spectrum. Indices of lower SES relate to greater
numbers of stressful life events in youths ages 6 to 9
(Gillum, Prineas, Gomez-Marin, Chang, &
Finn, 1984), 5 to 14 (Chandler,
Million, & Shermis, 1985), 12 to 14
(Gad & Johnson, 1980) and
in ninth through eleventh grade adolescents
(Gore, Aseltine, & Colton,
1992). Krieger, Williams, and Moss
(1997) note that the
combination of SES indices into one index can be problematic for research
because it may obscure each component's distinct, and possibly different,
contribution to outcomes. Of the studies listed above, only two tested for
relations between different indices of SES and life events exposure. Gillum et
al. found that parents' education and employment status, prestige-based
measures of SES, and income, a resource-based measure of SES, were separately
related to reports of fewer life events. Gore et al. observed a stronger
inverse relation between adolescent-reported perceived standard of living
(resource-based) and life events than between parents' education
(prestige-based) and life events. None of the studies examined potential
relations between type of occupation or assets and life events exposure. One
goal of this study was to examine how multiple indices of resource- and
prestige-based definitions of SES are related to life events exposure.
A related issue in examining the association between SES and life events
exposure is whether lower SES places an individual at greater risk for
specific types of life events. It is possible that lower SES is most often
associated with greater occurrence of income-related events (e.g., losing
one's job, experiencing financial difficulty). If so, associations between SES
and life events exposure may represent commonality in measurement, as opposed
to relations of etiologic significance. Few studies have separated events that
are likely to be income-related from those that are not (for an exception, see
Gillum et al., 1984, who found
that SES was related to life events not related to income). SES may also be
related to important features of events, such as degree of negativity and
controllability, dimensions that may be particularly important to health.
Youths of lower SES may be exposed to a greater number of negative life events
because their families and communities do not have sufficient resources to
anticipate negative events, prevent their occurrence, or engage in behaviors
that will ameliorate their effects. For the same reason, youths of lower SES
may also be exposed to a greater number of uncontrollable life events (events
independent of youths' behavior). Of the studies reviewed above, only Gad and
Johnson (1980) divided events
into those that were negative or positive. Gillum et al. divided items on the
basis of desirability and controllability a priori, whereas Gore et al.
(1992) assessed the extent to
which participants were bothered by the occurrence of each event. Neither
Gillum et al. nor Gore et al. presented this information in their analyses,
however.
Black Americans in the United States are more likely to be of lower SES
than are white Americans (Montgomery &
Carter-Pokras, 1993; U.S.
Census Bureau, 1999), a circumstance that may place them at
greater risk for exposure to stressful life events. Ethnicity may also have an
independent influence over the stressfulness of one's social environment
beyond that of SES. For example, ethnic discrimination may occur regardless of
one's level of education, occupation, and income
(Gotham, 1998;
Klonoff & Landrine, 1999;
Turner & Turner, 1975;
Wilson, Tienda, & Wu,
1995).
Only two known studies jointly examined SES and ethnicity in relation to
life events exposure in childhood and adolescence: Gad and Johnson
(1980) and Gillum et al.
(1984). (Prelow and Guarnaccia
[1997] measured SES but did not find that SES and ethnicity independently
predicted exposure to specific categories of life events or total life
events.) Both studies found that lower SES and ethnic minority status were
related to greater numbers of life events. The ethnicity difference in Gillum
et al.'s study was not altered when SES (assessed by mother's education and
family income) was controlled, suggesting that SES and ethnicity explain
independent variance in life events exposure. However, the ethnicity
difference in Gad and Johnson's study did not remain significant when SES
(assessed by parental education and occupation) was controlled. The
differences between the two studies' results may be due to differences in SES
measurement or in the types of life events most prevalent in their
populations.
In light of the proposed cumulative effects that lower SES and ethnic minority status may have on adolescents' exposure to stressful life events, this study tests the hypothesis that SES and ethnicity have independent, additive effects on adolescents' exposure to stressful life events. In addition, specific indices of SES are expected to be related to particular types of life events. Specifically, because lack of resources may increase the likelihood that negative, uncontrollable events become ongoing or recurring problems, we hypothesized that resource-based indices of SES would be associated with negative, uncontrollable life events. Events considered more within the control of youths may be influenced in part through parents' modeling of behaviors. SES indices such as years of education and prestige of occupation may be conceptualized as parents' modeling of academic and career related achievements. Thus, we hypothesized that prestige-based indices of SES will be associated with negative, controllable events, including academic employment problems. These relations are expected to persist even when income-related life events are removed from analyses and when the effects of ethnicity are controlled. In addition, we hypothesized that ethnicity will be associated with negative, uncontrollable events independent of SES because of the extra burden discrimination places on minorities in our society.
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Method |
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Participants
The 148 adolescents in this study were participants in a larger longitudinal study addressing the behavioral antecedents of cardiovascular disease; they were initially recruited from school districts in the Pittsburgh metropolitan area of Allegheny County. School districts included sizable populations of black and white students and were generally representative of lower to upper middle SES families. Adolescents were 49% female, and 44% were of black ethnicity. Ethnicity was ascertained by asking parents the ethnic group or race of their participating child. Only 13 participants refused to participate in this protocol. Initial eligibility criteria included (1) no history of cardiovascular disease or a condition that required medication that could affect the cardiovascular system (e.g., high blood pressure, asthma, oral contraception); (2) no history of drug or alcohol abuse, mental illness, or professional psychiatric counseling within the past year; (3) less than 80% above ideal weight according to Metropolitan height and weight tables; and (4) no smoking within 12 hours prior to participating in the study. Black and white adolescents were matched for years of parental education, and parents did not have advanced professional degrees. At the time of the life events assessment, 123 adolescents' families had a father or father figure. Of these 123 families, 28 had living arrangements in which the adolescent lived with the mother primarily and the father lived outside of the home. The sample of black families was comprised of significantly more single mothers than the sample of white families (29% vs. 7%, p < .001). In those families with fathers, a greater percentage of fathers lived outside of the home (e.g., through divorce, separation) in black families than in white families (41% vs. 13%, p < .001). School administrations and the University of Pittsburgh Internal Review Board approved of recruitment and study procedures prior to contact with potential participants and their parents. Informed consent and assent were obtained from parents and adolescents prior to study procedures.
Measures
Life Events Questionnaire—Adolescent (LEQA). The LEQA was
developed to explore the relation between stressful life experiences and
adolescent adjustment (Garmezy &
Tellegen, 1984; Masten et al.,
1988; Masten, Neemann, &
Andenas, 1994). We judged 10 items independently to be related to
income (e.g., the family had funds cut off by some government agency during
the past year; the family financial situation was difficult during the past
year). Because the inclusion of income-related life events in this study may
have led to overestimation of any relation between life events and SES, we
removed income-related items from the scale. Five mutually exclusive subscales
consisting of 41 events are thus analyzed in this study: (1) independent of
adolescent behavior, negative, discrete onset: 15 items (e.g., During this
past year, one of my parents died); (2) independent, negative, chronic: 6
items (e.g., There were many arguments between adults living in the house
during this past year); (3) independent, ambiguous, discrete onset: 9 items
(e.g., I have a new brother or sister who was born during this past year); (4)
nonindependent of adolescent behavior, negative: 6 items (e.g., I failed a
grade or was "held back" during this past year); (5)
nonindependent, positive: 5 items (e.g., I had at least one outstanding
personal achievement this past year).
One-year test-retest correlations for the original LEQA version were
moderately high and statistically significant. For the negative, ambiguous,
and total life events categories, correlations ranged from .53 to .64
(Garmezy & Tellegen, 1984).
Correlations between an interview rating of stress and the negative and
ambiguous life events categories ranged from .45 to .49. Seven years later,
correlations between adolescents and their mothers' reports of life events
ranged from .38 to .67 (all ps < .001). Negative events were
significantly related to poorer adjustment, and positive events were related
to better adjustment. In the study sample, ambiguous events were related to
adjustment much in the same way as negative events.
Although reported family income was not associated with income-related life events in this study, black adolescents (M = 1.17) reported significantly more income-related life events than white adolescents (M = .64, p < .01). In addition, both mothers' (r = .17, p < .05) and fathers' (r = .23, p < .05) years of education were associated with greater report of income-related life events by adolescents.
Socioeconomic Measures. Six socioeconomic measures are analyzed in
this study: family income, assets, mother's years of education and occupation,
and, if applicable, father's years of education and occupation. Family income
and assets were obtained from parents as part of an interview developed to
assess the family financial status of study participants. When interview items
(except for income) were included in a Principle Component Analysis with
Varimax rotation, four items comprised the first component (eigenvalue = 2.15,
= .55), which we have labeled assets. The items are as follows: owning
a car (yes/no), owning as opposed to renting one's home (yes/no), having a
greater number of bedrooms in one's residence (1-8, ranging from a studio
apartment to a 4+ bedroom house), and having a greater number of debts over
$1,000 (0-4). Debts included automobile loans, student loans, other loans, and
credit card debt; these represent the accumulation of tangible goods through a
favorable credit history. The assets score for each participant was obtained
by standardizing the above items, adding them together, and dividing by 4
(range of -1.8 to 1.2). Annual family income ranged between $2,000 and
$107,000. Mothers' years of education and occupation were obtained from
parents, as were fathers' years of education and occupation, if applicable.
Fathers' socioeconomic variables were obtained if the father lived in the home
or contributed to the family income. Occupations were rated on a scale of 1-9
(increasing numbers indicate more prestigious occupations), as outlined in
Hollingshead's Four Factor Index of Social Status
(1975). Years of education
ranged between 9 and 18 for both mothers and fathers. Mothers' Hollingshead
occupational scores ranged between 1 and 9, while fathers' scores ranged
between 1 and 8. The ranges of SES indices confirm that a wide segment of the
socioeconomic spectrum is represented in the sample.
Families in which fathers and mothers held more prestigious occupations earned greater yearly incomes (rs = .38 and .51, ps < .001, respectively) and possessed a greater number of assets (rs = .33 and .44, ps < .001, respectively) than families in which the fathers or mothers held a less prestigious occupation. Although the black and white adolescents in this study were matched for years of parental education, the families of black adolescents reported lower family incomes, fewer assets, and less prestigious occupations in comparison to the families of white adolescents.
Procedure
The LEQA was administered to participants during a laboratory visit.
Adolescents were asked to rate whether or not each life event had occurred
during the past year. All socioeconomic measures were obtained from a parent
or legal guardian over the telephone or while they waited for their children
to complete the laboratory visit.
Data Analyses
Descriptive statistics included calculation of the mean, standard
deviation, and intercorrelations among life events categories and
socioeconomic indices, as well as presentation of participants' range of
reported life events. As a preliminary step to hypothesis testing,
correlations between life events categories and both socioeconomic indices and
ethnicity were examined. Multiple regression was used to test the overarching
hypothesis that SES and ethnicity have independent, additive effects on
adolescents' exposure to stressful life events. Multiple regression estimates
the partial effect of X1, on Y, statistically adjusting for
X2's correlation with X1 and Y. Similarly, the partial
effect of X2 on Y is estimated, statistically adjusting for
X1. The regression equation takes the form of Y =
ß0 + ß1X1 +
ß2X2. B1 and B2 are partial effects derived from a
series of regression equations. B1 is derived by regressing Y on
X2 and X1 on X2 in separate equations. The
residuals from the first equation are regressed on the residuals from the
second equation, yielding in partial effect B1. B2 is
derived in similar fashion, exchanging X1 and X2 in the
regression equations. Each significant correlation between a life events
category and either ethnicity or a socioeconomic index was tested through
multiple regression to determine whether the partial effect of ethnicity or
SES was significant. Potential interactions between ethnicity and the SES
index were also examined (Y = ß0 +
ß1X1 + ß2X2 +
ß3X1X2). SES variables were centered for
analyses.
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Results |
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Descriptive Statistics
The upper left portion of Table I presents the mean and standard deviation for each of the five mutually exclusive life events categories and for adolescents' total life events scores within the total sample. The mean number of total life events experienced was 7 out of a possible 41. Adolescents were exposed to an average of three negative life events, three positive life events, and one ambiguous life event over the course of 1 year. Some of the adolescents in the sample experienced as many as 20 life events during the past year; others experienced as few as one life event. Three life events categories (independent, negative, discrete; independent, negative, chronic; nonindependent, negative) were log transformed in subsequent analysis to eliminate positive skew. Exposure to negative and ambiguous life events tended to cluster (rs between .20 and .31, ps < .05), regardless of whether the events were discrete or chronic in occurrence or whether they were independent or nonindependent of the adolescent's behavior. The one exception to this pattern occurred between independent, ambiguous, discrete life events and independent, negative, chronic life events (r = .10, ns). Exposure to positive life events was unrelated to negative and ambiguous life events exposure. Gender and age group did not significantly distinguish between adolescents' report of life events.
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The bottom left portion of Table I presents the mean and standard deviation of each SES index within the total sample. The absolute values of skewness and kurtosis indicators were less than 1.0 and 1.5, respectively, supporting a nearly normal distribution for each index (not shown in table). Table II presents intercorrelations among the SES indices. The majority of these intercorrelations were significant; however, they are not so high as to suggest redundancy. The strongest intercorrelation occurred between family income and assets. With two exceptions, the patterns of intercorrelations were similar across black and white participants (not shown in table). The correlations between mothers' years of education and both income (r = .62 vs. r = .23; Fisher's z = 2.79, p < .01) and assets (r = .43 vs. r = -.02; Fisher's z = 2.82, p < .01) were larger for black participants than for white participants.
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Correlations Between Life Events, SES, and Ethnicity
Table III presents
correlations of separate SES indices and ethnicity with life events exposure.
Consistent with predictions, resource-based measures of SES (i.e., greater
income and assets) were significantly related to reports of fewer negative,
ambiguous, and total life events, including negative life events that were
uncontrollable (independent of adolescent behavior). Also consistent with
predictions, fathers' education and occupation, prestige-based measures of
SES, were related to reports of fewer negative, nonindependent life events
(e.g., doing poorly on an exam, suspension from school, trying to get a job
and failing).
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Both mothers' and fathers' occupations were related to reports of fewer independent, discrete life events (negative or ambiguous). After controlling for family income and assets, the relations between parents' occupational score and both independent, negative, discrete life events (partial r = -.14, ns for fathers; pr = -.05, ns for mothers) and independent, ambiguous, discrete life events (pr = -.19, p < .05 for fathers; pr = .08, ns for mothers) weakened considerably. In contrast, the relation between fathers' occupational score and nonindependent, negative life events remained highly significant after controlling for family income and assets (pr = -.26, p < .01).
As predicted, black adolescents reported significantly more independent, discrete life events (negative or ambiguous), nonindependent, negative life events, and total life events in comparison to white adolescents.
Multiple Regression of Life Events on SES and Ethnicity
To test whether SES and ethnicity were independently related to life events
exposure, separate multiple regressions were performed for each life events
category and SES index. The superscripts of
Table III indicate whether SES
and ethnicity remained significant predictors of life events exposure
statistically independent of each other. Consistent with prediction, ethnicity
was a significant predictor of independent, discrete life events (negative or
ambiguous) and total life events, independent of every SES index
(prs> .20, p < .05). Ethnicity was also a significant
predictor of nonindependent, negative life events, independent of mothers' and
fathers' education and mothers' occupation (prs> .19, p
< .05). In each case, black adolescents reported a greater number of life
events than did white adolescents. Of the six SES indices separately entered
into regressions, assets and fathers' education and occupation predicted life
events exposure independent of ethnicity. Greater assets predicted fewer
discrete (pr = -.19, p < .05) and chronic (pr =
-.21, p < .05) independent, negative life events and fewer total
life events (pr = -.21, p < .05). Within the subset of
participants with fathers, greater years of fathers' education (pr =
-.22, p < .05) and greater prestige of fathers' occupation
(pr = -.24, p < .01) predicted fewer nonindependent,
negative life events. Greater prestige of fathers' occupation also predicted
fewer total life events (pr = -.18, p < .05).
We did not predict significant interactions between SES and ethnicity in relation to life events exposure. However, fathers' SES and ethnicity interacted to influence nonindependent, positive life events; independent, negative, chronic life events; and total life events (prs < -.18, ps < .05). Greater years of fathers' education (r = -.41, p < .01) and occupational prestige (r = -.38, p < .01) were related to fewer nonindependent, positive life events and total life events, respectively, within black adolescents only. Greater years of fathers' education (r = .23, p < .05) were related to greater independent, negative, chronic life events within white adolescents only.
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Discussion |
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This study tested whether fewer SES resources and ethnic minority status are independently associated with negative, uncontrollable life events in adolescence, while lower SES prestige is associated with negative, controllable life events. As predicted, the resource-based SES indicator assets was related to less exposure to negative, uncontrollable (independent of adolescent behavior) life events, both discrete and chronic, even after the removal of income-related life events and controlling for ethnicity. A family's assets appear to predict more than traditional indices of SES such as income, education, and occupation. Family assets may represent parents' ability to channel their own educational and career-related achievements into goods that protect their children from adverse, uncontrollable life events (e.g., obtaining better health care to prevent illness, replacing a stolen object).
As predicted, the prestige-based SES indicators of fathers' years of education and prestige of occupation were related to fewer negative life events that may have been influenced by adolescent behavior (e.g., doing poorly on an exam, suspension from school, trying to get a job and failing). The career-related achievements of fathers may set a positive example for adolescents to achieve in school and within the larger community (e.g., doing well in school, obtaining employment), developmental tasks that may contribute to successful adjustment later in life. It is also possible that adolescents of lower SES have less belief in their ability to prevent negative events.
Black adolescents reported significantly more independent, discrete life events, both negative and ambiguous, and nonindependent, negative life events in comparison with white adolescents. When SES was included as a predictor of life events exposure along with ethnicity, only the relation between ethnicity and nonindependent, negative life events became nonsignificant. This finding has two important implications. First, a family's SES rather than ethnicity appears to influence the occurrence of negative life events that are within the control of adolescents. Second, black adolescents may be exposed to more negative situations and situations that require greater amounts of change in comparison to white adolescents. Although ambiguous life events could not be classified as positive or negative, they shared a common feature in requiring significant adaptation to change (e.g., the birth of a new sibling, changing schools, a parent's hours at work changing such that he or she is away from home more often).
Membership in an ethnic minority group may confer greater risk for life
events exposure through a variety of mechanisms. For example, 6 of the 15 life
events included in the independent, negative, discrete category assess illness
or death of family members. Black families may be at greater risk for these
types of life events due to lifestyle differences or health problems. Obesity,
hypertension, and diabetes are more prevalent within blacks than whites
(Dustan, 1990;
Harris, 1990;
Williamson, Kahn, & Byers,
1991). Other life events may occur more frequently within black
communities due to environmental differences. Black communities are exposed to
higher rates of crime and discriminative practices than white communities
(Gotham, 1998;
Klonoff & Landrine, 1999;
Richters & Martinez, 1993;
Turner & Turner, 1975;
Wilson et al., 1995). An
additional mechanism involves SES differences between black and white
families. Although black and white adolescents in this study were similar in
years of parental education by study design, the families of black adolescents
reported lower family incomes, fewer assets, and less prestigious occupations
than the families of white adolescents. Thus, the families of black
adolescents had fewer resources with which to plan for and prevent negative
life events.
Limitations of this study include the underassessment of positive life events in comparison to negative life events. In consequence, we could not test with confidence the hypothesis that higher SES is associated with more positive events. Indeed, the pattern we obtained was the opposite among black adolescents whose fathers had greater years of education. An additional limitation concerns the exclusion criteria for this study: no history of drug or alcohol abuse, mental illness, or psychiatric counseling within the past year. These exclusion criteria may have led to an underestimation of adolescents' exposure to negative life events. Recruitment of participants from the Pittsburgh metropolitan area may allow for generalization of adolescents' life events exposure to the city and surrounding communities, but it may underestimate the life events to which adolescents from highly impoverished or inner-city communities are exposed. A third limitation concerns the choice to assess the breadth of adolescents' life events exposure, rather than the frequency to which they might have been exposed to few or many life events. Life events exposure may have been underestimated in adolescents who were very often exposed to a few types of life events. Finally, although ethnicity and SES were related to life events statistically independent from one another, each of these concepts is in fact a marker of a more general set of environmental exposures not measured in this study. Ultimately, ethnicity and SES cannot be completely disentangled from one another. Findings of this study will need to be verified by future research, as a large number of statistical tests were conducted ancillary to the main hypotheses.
Advantages of this study include an adolescent population of diverse age
and roughly equal number in gender and black and white ethnicity. An
additional advantage is the a priori categorization of life events based on
constructs relevant to families of low SES and ethnic minority status,
including negativity of events and controllability. Consistent with
recommendations by Krieger et al.
(1997), these findings also
demonstrate the utility of considering separate indices of SES in research.
Assets may prove to be a particularly important concept in SES-related
research, as they are measured with ease and involve less intrusive
questioning than asking for family income.
The purpose of this study was to undertake the first step in evaluating why
SES is linked to poor health outcomes in adolescence. We suggest that
stressful life events may be a major mechanism in this regard and have
presented evidence that resource-and prestige-based indices of family SES are
associated with adolescents' risk for uncontrollable and controllable negative
life events, respectively. In addition, we have presented evidence that
ethnicity is associated with risk for uncontrollable life events when
statistically controlling for SES. Interventions to reduce youths' exposure to
stressful life events may need to target interactions that occur within and
between ethnic communities (e.g., increasing community resources, decreasing
discrimination), as well as SES disadvantages (e.g., increasing educational
and occupational opportunities). Other research has clearly shown that
stressful life events among children and adolescents are associated with
elevated risk for physical health problems
(Baldwin et al., 1997;
Gad & Johnson, 1980;
Newcomb et al., 1981,
1986). The next step is to
evaluate mediational pathways in populations where multiple indices of SES,
stressful life events, and health outcomes are all available.
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Acknowledgments |
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This research was supported by NIH grants HL25767 and MH 19953. We thank the staff members of the Child Health Study and Edith Chen, PhD, for reviewing an earlier draft of this article.
Received August 10, 2000; revision received August 1, 2001; accepted August 27, 2001
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