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Multiple Risk Behavior and Injury
An International Analysis of Young People
William Pickett, PhD;
Holger Schmid, PhD;
William F. Boyce, PhD;
Kelly Simpson, BSc;
Peter C. Scheidt, MD, MPH;
Joanna Mazur, PhD;
Michal Molcho, MA;
Matthew A. King, BA;
Emmanuelle Godeau, MD;
Mary Overpeck, DrPH;
Anna Aszmann, MD;
Monika Szabo, MS;
Yossi Harel, PhD
Arch Pediatr Adolesc Med. 2002;156:786-793.
ABSTRACT
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Background Multiple risk behavior plays an important role in the social etiology
of youth injury, yet the consistency of this observation has not been examined
multinationally.
Objective To examine reports from young people in 12 countries, by country, age
group, sex, and injury type, to quantify the strength and consistency of this
association.
Setting World Health Organization collaborative cross-national survey of health
behavior in school-aged children.
Participants A multinational representative sample of 49 461 students aged 11,
13, and 15 years.
Main Exposure Measures Additive score consisting of counts of self-reported health risk behaviors:
smoking, drinking, nonuse of seat belts, bullying, excess time with friends,
alienation at school and from parents, truancy, and an unusually poor diet.
Main Outcome Measure Self-report of a medically treated injury.
Results Strong gradients in risk for injury were observed according to the numbers
of risk behaviors reported. Overall, youth reporting the largest number ( 5
health risk behaviors) experienced injury rates that were 2.46 times higher
(95% confidence interval, 2.27-2.67) than those reporting no risk behaviors
(adjusted odds ratios for 0 to 5 reported behaviors: 1.00, 1.22, 1.48,
1.73, 1.98, and 2.46, respectively; P<.001 for
trend). Similar gradients in risk for injury were observed among youth in
all 12 countries and within all demographic subgroups. Risk gradients were
especially pronounced for nonsports, fighting-related, and severe injuries.
Conclusions Gradients in risk for youth injury increased in association with numbers
of risk behaviors reported in every country examined. This cross-cultural
finding indicates that the issue of multiple risk behavior, as assessed via
an additive score, merits attention as an etiological construct. This concept
may be useful in future injury control research and prevention efforts conducted
among populations of young people.
INTRODUCTION
INJURY IS the leading cause of death in young people.1
Nonfatal injuries occur at least 1000 times more often than fatal injuries,2 and their impact, in terms of disability and the costs
of treatment, rehabilitation, and lost productivity, is substantial.3 The etiology of youth injury involves a complex interplay
between behavioral and environmental factors. Patterns of injury vary according
to demographic factors, including age, sex, residence, and socioeconomic status,2 all of which are difficult to modify. Consequently,
behavioral explanations of the etiology of injury are of interest and may
offer hope for prevention strategies.
Risk-taking behavior can be viewed as a vehicle by which adolescents
begin to make the transition to adulthood. Biologically based theories attribute
risk-taking behavior to genetic predispositions and hormonal and psychosocial
changes mediated through pubertal timing.4-5
Psychological theories suggest that sensation seeking, reflecting a need for
varied, novel, and complex experiences, encourages an active willingness to
take physical and social risks.4, 6-7
These perceptions and behaviors do not usually occur in isolation,8 and are often associated with peer group activities.4, 9
Relationships between adolescent injuries and individual risk behaviors,
such as drinking,10-11 drug use,12-13 and different types of sexual behavior,
have been examined.14-15 Some
research has examined the association between smoking and injury-related fatalities16 and between aggressive sporting behavior and injuries.17-18 Engaging in one form of risk behavior
may indicate an increased likelihood to engage in others.19-21
Increases in adolescent risk-taking behavior have been reported in international
trend analyses.22-23 These increases,
together with the association between different types of risk behaviors, have
been referred to as "risk behavior epidemics,"24
"risk syndromes," or "multiple risk activities."25
Various approaches to the assessment of risk-taking behaviors in youth
have been proposed, and additive risk scores are one such approach. Notable
proponents of additive scores include Jessor,26
who used a social-psychological framework (Problem Behavior Theory) to model
proneness to problem behaviors that were consolidated into an additive scale.
Others27 have criticized the use of additive
scales and, instead, have created behavioral constructs that are multidimensional.
Still others28 have cautioned that predictive
factors are specific to individual behaviors and that the health consequences
of risk behaviors are best modeled individually. For youth injury, it is,
therefore, unknown how behavioral risk factors should be optimally measured
and considered in etiological models. If an additive scale is used, it is
also not understood whether the numbers of risk behaviors engaged in are more
important than the nature of the individual risks themselves.
Consistent with the theoretical approach of Jessor,26
a recent analysis of young Canadians29 showed
that the likelihood of youth injury increased in accordance with the number
of risk behaviors reported. This supported the use of an additive risk model,
but whether this is a universal phenomenon is unclear. The present analysis
built on Jessor's theories and this Canadian study by examining associations
between risk behaviors and youth injury in 12 countries. Health Behavior in School-aged Children (HBSC), a World Health Organization
cross-national study,30 provided the opportunity
to explore these associations.
Focused objectives of this international analysis were to examine (1)
the strengths and consistencies of associations between individual health
risk behaviors and the occurrence of injury between countries and (2) whether
risks for youth injury increased in accordance with the number of risk behaviors
identified in an additive scale. This was done to provide data that might
affirm or refute the importance of the multiple risk concept for studies of
youth injury. It also explored whether use of the additive risk score was
helpful when applied to a large international sample of young people and an
etiological study of youth injury.
PARTICIPANTS AND METHODS
The 1998 HBSC is a study of nationally representative samples of adolescents
in 29 countries. In each country, a cluster sample design was used, with the
school class being the basic cluster. Schools and classes within schools were
selected to be representative by age level and regional geography. Three age
groups of young people were sampled. Age group levels were "designed to represent
the onset of adolescence—age 11; the challenge of physical and emotional
changes—age 13; and the middle years when very important life and career
decisions are beginning to be made—age 15."30(p9)
Recommended sample sizes for each country were 1536 students per age group.
Sample sizes ensured a 95% confidence interval of ±3% for prevalence
estimates, with a design effect of no more than 1.44 in any country.30 All national samples, with the exception of Israel,
were selected to be self-weighting.
Full descriptions of the questionnaire items assessed during 1998 and
their development appear elsewhere.30-31
The overall goal of the HBSC study is to "gain insights into and to increase
our understanding of health behaviors, lifestyles and context in young people."30(p1) This occurs in part by identifying characteristics
of youth that influence their health and well-being. Major categories of variables
addressed in the survey include the following: demographics, general health
and well-being, family and peer relationships, school environments, exercise
and leisure-time activities, diet, substance use, and sexual behavior.30
INJURY
Reports describing medically treated injuries were collected in 12 of
the 29 countries only: Belgium (Flemish sample), Canada, England, Estonia,
Hungary, Israel, Lithuania, Poland, Republic of Ireland, Sweden, Switzerland,
and the United States. Injury questions were derived from the 1988 child health
supplement to the US National Health Interview Survey32
and a previous version of the HBSC.33 Injured
youth were defined as those providing a response of 1 or more times to the
question: "During the past 12 months, how many times were you injured and
had to be treated by a doctor or nurse?" Students then described their single
most serious injury, if any. Supplementary questions asked about the nature
of the injury (medical sequelae), injury type (eg, sports or fighting related),
treatment(s) administered, and number of days lost from school or other normal
activities. Using a modified approach to the classification of severity,34 severe injuries were operationally defined as those
leading to 1 or more of the following: (1) 1 or more days missed from school
or usual activities, (2) hospitalization overnight, (3) the use of casts or
stitches, and/or (4) a surgical operation (these descriptors were only collected
in 8 of the 12 countries).
MULTIPLE RISK BEHAVIOR SCORE
A list of health risk behaviors common to adolescents, as suggested
by the literature, was compiled from the available questions in the HBSC.
The following close-ended items were used (responses in parentheses were interpreted
as the presence of the risk factor): smoking,10, 35
"How often do you smoke tobacco at present?" (currently smoking from once
a week to daily); drinking,10-11,15-16,36-38
"Have you ever had so much alcohol that you were really drunk?" (1 time);
seat belts,39-40 "How often do
you use a seat belt when you sit in a car?" (never, rarely, or sometimes);
bullying,41 "How often have you taken part
in bullying other students in school this term?" (more than once or twice);
excess time with friends,31 "How many evenings
per week do you usually spend out with your friends?" (5-7 evenings); alienation
at home,31 "How easy is it for you to talk
to your father/mother about things that really bother you?" (difficult or
very difficult for all parents in the home); alienation at school,31 "I feel I belong at this school." (disagree or strongly
disagree); truancy,42 "How many days did you
skip classes or school this term?" (2 days); and an unusually poor diet,37 "How often do you eat or drink cola/sweets/potato
chips or crisps?" (at least once a day for all 3).
Some of the preceding factors were selected as risk behaviors that could
directly lead to injury. Others were selected as more generic indicators of
a risk-taking lifestyle. Although there were several additional risk behaviors
that optimally could have been included in the score (illicit drug use, nonuse
of bicycle helmets, and unprotected sex), these were not assessed by most
participating HBSC study countries. The 9 available risks were combined into
an unweighted multiple risk behavior frequency score. Because of their low
relative frequency, scores from 5 to 9 were collapsed subsequently into a
single category, leaving 6 levels (0 to 5 behaviors).
COVARIATES
Factors selected as potential confounders were age (in years), sex,
socioeconomic status (5 categorical responses to the following: "How well-off
do you think your family is?"), country of origin, and, because sports injuries
are common among youth, hours of sports activity or exercise per week outside
of normal school hours (0 to >7). This list was based on previous analyses29 and exploratory analyses for colinearity within the
international HBSC data set.
STATISTICAL ANALYSES
Analyses were initially conducted within individual countries for comparative
purposes. Correlation analyses were used to examine the strengths of associations
between individual risk factors contained in the multiple risk behavior score.
Internal consistency analyses were performed by country, using Kuder-Richardson
formula 20 (range, 0-1.0; with a score of >0.6 viewed, conservatively, as
acceptable) and computer software (Statistical Product and Service Solutions;
SPSS Inc, Chicago, Ill). This was done to explore the reliability of the multiple
risk behavior score and the individual high-risk behaviors used to construct
the score.
The etiological analysis was conducted in 2 stages. First, unconditional
logistic regression (the conventional form for unmatched data analyses) was
used to examine each high-risk behavior (individually) as a potential risk
factor for injury. Second, the same analytical technique was used to examine
the strength of associations between the additive risk score and the occurrence
of youth injury. For the individual risk behavior and additive score analyses,
crude and adjusted odds ratios (ORs) and associated 95% confidence intervals
were calculated for each level of exposure compared with baseline (the referent
level: multiple risk behavior score of 0).
Because consistent findings were obtained from the 12 countries, a combined
logistic regression analysis was then performed using the overall sample.
This involved calculation of adjusted ORs for each level of the multiple risk
behavior score relative to baseline, controlling for the 5 covariates identified
a priori, including country of origin. Stratified analyses were then performed
to examine the consistency of the risk estimates by sex and age group. Restricted
analyses were conducted to examine variations in risks for severe, nonsevere,
sports, nonsports, and fighting-related injury.
All data management was performed using computer software (Excel 97;
Microsoft, Redmond, Wash). The statistical analyses were conducted using computer
software (Statistical Product and Service Solutions).
RESULTS
A total of 50 691 youth in the 12 countries responded to the injury
questions, and 49 461 completed records were considered in the final
analysis. There were variations between countries in the types and numbers
of health risk behaviors reported and the prevalence of medically treated
and severe injuries (Table 1).
Strong variations were observed between countries for the following behaviors:
excess drinking, nonuse of seat belts, bullying, excess time spent with friends,
an unhealthy diet, and truancy. There was considerably less variation between
countries in the numbers of health risk behaviors reported by youth.
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Table 1. Frequency Distribution of Respondents Reporting the Presence
of Selected Health Risk Behaviors and Injuries
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The internal reliability of the additive scale varied between countries
(Kuder-Richardson formula 20 range, 0.50 [Estonia] 0.63 [Sweden]). The inspection
of the corrected item-total correlation for the different risk behaviors showed
rather modest correlations ( <0.50).
Adjusted ORs that describe risks for injury associated with individual
risk behaviors were all larger than unity (OR>1.0) (Table 2). Risk estimates that were consistently higher were associated
with smoking, drinking, and bullying; yet, even these ORs were modest. Within
each country, risks for injury increased in accordance with the multiple risk
behavior score (Table 3). Because
all crude ORs calculated were within the bounds of the associated adjusted
confidence intervals, only adjusted ORs are presented in Table 2 and Table 3.
These results suggest the presence of fairly strong associations between the
additive risk score and the occurrence of injury.
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Table 2. Logistic Regression Analysis Examining Associations Between
Individual Health Risk Behaviors and Youth Injury*
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Table 3. Adjusted Logistic Regression Analysis for Health Behaviors
and Youth Injury*
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A graphical summary of the combined analysis of data from the 12 countries
(Figure 1) shows the overall gradient
in risk for injury associated with the numbers of risk behaviors reported
(P<.001 for trend). The risk gradients were also
observed among male and female subjects and within each of the 3 age groups.
A stronger risk gradient was observed for severe vs nonsevere injuries, nonsports
vs sports injuries, and injuries attributable to fighting (Figure 2).
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Figure 1. Associations between numbers of
health risk behaviors and youth injury: combined 12-country analyses. A, Overall.
B, By sex. C, By age. The ORs are simultaneously adjusted for age, sex, socioeconomic
status, physical activity, and country. OR indicates odds ratio; CI, confidence
interval.
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Figure 2. Associations between numbers of
health risk behaviors and youth injury: analyses restricted to specific injury
types. A, By injury severity. Data not available for 4 countries. B, By sports
involvement. Data not available for 2 countries. C, Fighting-related injuries.
Data not available for 3 countries. The ORs are simultaneously adjusted for
age, sex, socioeconomic status, physical activity, and country. OR indicates
odds ratio; CI, confidence interval.
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COMMENT
This international analysis of young people found that the risk for
reported injuries increased in direct association with increasing frequency
of reported risk behaviors. These gradients were observed in the combined
multinational analysis; within young people from every country that collected
these data (12 of 12 countries); in the restricted analyses of severe, nonsevere,
sports, nonsports, and fighting-related injuries; and within all demographic
strata defined by age and sex. The gradients were observed with and without
adjustment for potential confounders, including indicators of socioeconomic
status. Consistency across countries with different cultures suggests that
this is a robust finding for affirming the relationship between risk-taking
behavior and injuries.
There are several reasons why youth engage in risk behaviors. One reason
is that risk-taking behavior represents a means by which independence can
be asserted.4 The extent of this independence
seeking is influenced by individual personality and cultural norms that imperil
or protect the growing child.38, 43
Personal behavior is influenced by peers, parents, the school, and the neighborhood
in which adolescents reside.44 Normative behavior
may be related to protective concepts of social capital, including social
networks, civic responsibility, perceptions of resources, and local identity.45 The ability to predict health outcomes, such as injury
from risk behavior alone, is tempered by these protective factors.46
Risk behavior may also be of social benefit to the growing adolescent.
Experimentation is normal and reflects a willingness on the part of the adolescent
to move away from dependence on family to a peer orientation. Problem Behavior
Theory and Primary Socialization Theory47 postulate
that adolescent risk taking largely takes place within peer groups that provide
a means of social support. Further understanding is required about the positive
impacts of these social networks. The negative impacts of risk-taking lifestyles
include elevated long-term risks for cardiovascular disease, cancer, and other
debilitating illnesses. Our findings show that risk behaviors also have more
immediate consequences in terms of injury, irrespective of the country and
related cultural setting. Although associations were stronger for certain
types of injury, the general association between numbers of behaviors and
risk for injury was consistently positive.
Our analysis was unique in that we used a multiple risk behavior score
to predict a negative health outcome: injury. While the dimensions and structure
of adolescent risk-taking behavior still need to be identified, it may be
fruitful to include additional risk behaviors, rather than fewer, in such
indexes. Furthermore, behavioral risks may be grouped into categories, such
as (a) active risk seeking: consumption of alcohol
or tobacco or bullying; (b) passive safety and health
risk seeking: lack of seat belt use or adherence to a nutritious diet; and
(c) independence seeking and/or nonsupportive environments:
alienation from parents or school, truancy, or excess time spent with friends.
These groupings of risk behaviors need to be confirmed in other contexts using
formal statistical techniques (such as factor analyses). Associations between
the multiple risk index and other health outcomes, both positive and negative,
require similar confirmation.
Our findings provide indirect support for the targeting of multiple
forms of risk behavior simultaneously in health interventions. By themselves,
individual risk behaviors may be only modestly associated with poor health
outcomes because they may be mere markers for the development of a more involved
behavioral complex. Our results suggest that, rather than the individual risk
behaviors that are engaged in, what seems to be important is the total number
of different risk behaviors that are experienced. The latter may be more important
in the etiology of injury, especially if they eventually lead to overt risk-taking
behaviors, such as physical abuse or impaired driving. A failure to address
concurrent forms of risk behavior in interventions may lead to naive preventive
strategies.
Common forms of bias warrant consideration as explanations for the observed
associations. The population-based nature of the samples limited the extent
to which selection bias could account for the gradients. The multivariate
analysis simultaneously adjusted for the influence of some confounders, although
it was limited to those that were measured and the self-reported manner in
which they were assessed. It is possible that the results were enhanced because
of the simultaneous conscientious overreporting of risk behavior and injuries
by some adolescents, a form of recall bias. Yet, the associations were strong
and consistent multinationally, despite the fact that countries varied in
social and cultural factors that might influence reporting inaccuracies. A
further limitation is the focus on only 1 of possible multiple injuries reported
by youth in the previous 12 months. This is most likely to bias the ORs and
gradients toward unity,29 meaning that the
results presented are conservative.
The additive risk score used herein is admittedly at an early stage
of development. The score itself and our approach to analysis were developed
using conventional epidemiological methods and the rationale espoused by an
existing behavioral model.26 Formal factor
analyses were not used during its construction, and the measures of reliability
conducted suggest that there is room for improvement. Correlation between
types of behavior contained in the score also might not be sufficiently high
to fulfill criteria for reliability when compared with the psychometric theory
and associated standards. The associations identified using our score were,
however, consistent and robust. We would argue that the basic concept (if
not the scale) has considerable potential for etiological research.
CONCLUSIONS
The associations between risk behavior and injury are intriguing, although
it would be premature to suggest that they are causal. The observed associations
were strong and statistically significant, followed a gradational pattern
of risk, and were consistent with human theory that attests to their plausibility.
The fact that the similar associations were found across countries and cultures
provides evidence in support of a common etiology to these injuries. Furthermore,
the strong and consistent nature of these associations suggests that the additive
risk score model of risk behavior, while admittedly at an early stage of development,
has promise. Based on these findings, we conclude that the issue of multiple
risk behavior, as assessed via an additive score, merits attention as an etiological
construct. The latter may be useful in future injury control research and
prevention efforts conducted among populations of young people.
| What This Study Adds
Increases in adolescent risk-taking behavior have been reported internationally.
The immediate health consequences associated with these behaviors are poorly
understood, although there is some suggestion that they lead to elevated risks
for injury. Whether this is a universal phenomenon is unclear.
The present study examined associations between adolescent risk-taking
behavior and risks for injury among 49 461 youth in 12 countries. Strong
gradients in injury risk were observed in association with the number of risk-taking
behaviors reported. This was true in all 12 countries and for all demographic
subgroups and injury types examined. Based on these findings, we conclude
that the issue of multiple risk behavior, as assessed via an additive score,
merits attention as an etiological construct.
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AUTHOR INFORMATION
Accepted for publication March 29, 2002.
This study was supported in part by the Canadian Population Health Initiative,
a program of the Canadian Institute for Health Information, Ottawa, Ontario.
(The Canadian Population Health Initiative supports research advancing knowledge
on the determinants of the health of the Canadian population and develops
policy options to improve population health and reduce health inequalities.
The Canadian Institute for Health Information is a national not-for-profit
organization responsible for developing and maintaining Canada's comprehensive
health information system.) Dr Pickett is a Career Scientist funded by the
Ontario Ministry of Health and Long-term Care.
The HBSC is a European Region of the World Health Organization collaborative
study. The international coordinator of the 1997-1998 study was Candace Currie,
University of Edinburgh, Edinburgh, Scotland; and the data bank manager was
Bente Wold, University of Bergen, Bergen, Norway. This publication on the
1997-1998 HBSC reports on data from the following countries (principal investigators
at that time are given in parentheses): Belgium (Flemish sample) (Lea Maes
and Els Van de Mieroop), Canada (Alan King and William F. Boyce), England
(Mary Hickman), Estonia (Mai Maser), Hungary (Anna Aszmann), Israel (Yossi
Harel), Lithuania (Apolinaras Zaborskis), Poland (Barbara Woynarowska), Republic
of Ireland (Saoirse Nic Gabhainn), Sweden (Ulla Markland), Switzerland (Beatrice
Janin Jacquat and Yves Francois), and United States (Peter C. Scheidt and
Mary Overpeck).
Corresponding author and reprints: William Pickett, PhD, Department
of Community Health and Epidemiology, Queen's University, c/o Emergency Medicine
Research, Angada 3, Kingston General Hospital, 76 Stuart St, Kingston, Ontario,
Canada K7L 2V7 (e-mail: PickettW{at}post.queensu.ca).
From the Department of Community Health and Epidemiology (Drs Pickett
and Boyce and Ms Simpson) and the Social Program Evaluation Group (Dr Boyce
and Mr King), Queen's University, and the Canadian Adolescents at Risk Research
Network (Drs Pickett and Boyce and Ms Simpson); Kingston, Ontario; the Swiss
Institute for the Prevention of Alcohol and Drug Problems, Lausanne, Switzerland
(Dr Schmid); the National Institute of Child Health and Human Development,
Bethesda, Md (Dr Scheidt); the National Research Institute of Mother and Child,
Warsaw, Poland (Dr Mazur); the Department of Sociology and Anthropology, Bar-Ilan
University, Ramat Gan, Israel (Ms Molcho and Dr Harel); the Service M dical
du Rectorat de Toulouse, Toulouse, France (Dr Godeau); the Maternal and Child
Health Bureau, Rockville, Md (Dr Overpeck); and the National Public Health
Centre, Budapest, Hungary (Dr Aszmann and Ms Szabo).
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