This research article examined the relationship between frequency and intensity of physical activity and health behaviors in adolescents. Researchers analyzed survey data from over 800 high school students regarding their physical activity levels and health behaviors over the past 30 days. They found that adolescents who engaged in high levels of vigorous physical activity were less likely to use marijuana or engage in heavy marijuana use, consumed more healthy carbohydrates and fats, used stress management techniques more frequently, and reported better quality of sleep compared to those with low vigorous physical activity. Few differences were seen based on frequency of moderate physical activity. The findings suggest frequent vigorous physical activity in adolescents may reduce risky behaviors and promote healthy behaviors. More research is needed to better understand these relationships.

1. R E S E A R C H A R T I C L E
Relationship Between Frequency and
Intensity of Physical Activity and Health
Behaviors of Adolescents
TONY T. DELISLE, MSa
CHUDLEY E. WERCH, PhDb
ALVIN H. WONG, MS, CHESc
HUI BIAN, PhDd
ROBERT WEILER, PhD, MPHe
ABSTRACT
BACKGROUND: While studies have determined the importance
of physical activity in
advancing health outcomes, relatively few have explored the
relationship between
exercise and various health behaviors of adolescents. The
purpose of this study is to
examine the relationship between frequency and intensity of
physical activity and both
health risk and health promoting behaviors of adolescents.
METHODS:
Data were collected from 822 students attending a large, diverse
suburban high school

2. in northeast Florida using a self-administered survey.
Multivariate analysis of variance
(MANOVA) and analysis of variance (ANOVA) tests examined
differences on mean
health behavior measures on 3 exercise frequency levels (low,
medium, and high) and
2 intensity levels (vigorous physical activity [VPA] and
moderate physical activity [MPA]).
RESULTS: Results showed adolescents engaged in high levels
of VPA used marijuana
less frequently (p = .05) and reported heavy use of marijuana
less frequently (p = .03);
consumed greater numbers of healthy carbohydrates (p < .001)
and healthy fats in their
diets (p < .001); used stress management techniques more
frequently (p < .001); and
reported a higher quality of sleep (p = .01) than those engaged
in low levels of VPA.
Fewer differences were found on frequency of MPA and health
behaviors of adolescents.
CONCLUSIONS: These findings suggest that adolescents who
frequently participate
in VPA may be less likely to engage in drug use, and more
likely to participate in a
number of health promoting behaviors. Longitudinal and
experimental studies are
needed to determine what role frequent VPA may play in the
onset and maintenance of
health enhancing and protecting behaviors among adolescent
populations.
Keywords: adolescent health; physical fitness; health behaviors.
Citation: Delisle TT, Werch CE, Wong AH, Bian H, Weiler R.

3. Relationship between
frequency and intensity of physical activity and health
behaviors of adolescents. J Sch
Health. 2010; 80: 134-140.
Received August 13, 2008
Accepted July 9, 2009
aGraduate Assistant/Doctoral Student, ([email protected]),
Department of Health Education and Behavior, College of
Health and Human Performance, University of Florida,
Florida Gymnasium Room 5, Gainesville, FL 32611.
bProfessor and Director, ([email protected]), Addictive &
Health Behaviors Research Institute, University of Florida,
7800 Belfort Parkway, Suite 270, Jacksonville, FL 32256.
cResearch Assistant, ([email protected]), Addictive & Health
Behaviors Research Institute, University of Florida, 7800
Belfort Parkway, Suite 270, Jacksonville, FL 32256.
dCoordinator, ([email protected]), Data Management and
Analysis, Addictive & Health Behaviors Research Institute,
University of Florida, 7800 Belfort Parkway, Suite 270,
Jacksonville, FL 32256.
eProfessor, ([email protected]), Department of Health Education
and Behavior, College of Health and Human Performance,
University of Florida, Florida Gymnasium Room 5,
Gainesville, FL 32611.
Address correspondence to: Tony T. Delisle, Graduate
Assistant/Doctoral Student, ([email protected]), University of
Florida, College of Health and Human Performance,
Department of Health Education and Behavior, Florida
Gymnasium Room 5, Gainesville, FL 32611.
134 • Journal of School Health • March 2010, Vol. 80, No. 3 • ©
2010, American School Health Association

4. Physical activity is well documented as a protectivefactor
against many chronic diseases, such as
coronary heart disease, hypertension, type II diabetes
mellitus, colon cancer, obesity, osteoporosis, and
depression.1,2 It is widely believed that the combined
influence of physical activity with other health
promoting behaviors further reduces the likelihood
of developing these chronic diseases.3 Lack of
regular physical activity, smoking, and poor diet
are the leading preventable causes of death and
chronic disease in the United States.4 However,
the relationship between physical activity and other
health behaviors is not yet fully understood.5-7
These health behaviors are often established during
adolescence, share common determinants, are related
to similar health behavioral patterns in adulthood,
and are most beneficial to health outcomes when
practiced throughout the life span of individuals.8-13
Therefore, understanding the relationships among
multiple health behaviors is critical, especially in
adolescent populations.14
Investigators have recently expressed the need
for further research regarding the feasibility and
effectiveness of interventions promoting multiple
behavioral health changes during adolescence.7,15 An
extensive understanding about the relationship of
physical activity and other health behaviors among
adolescents might provide invaluable information for
the development of such interventions.16 According to
previous research, physical activity may be associated
with the promotion of other health enhancing

5. behaviors.17,18 However, there is also seemingly
contradictory evidence suggesting that being physically
active or involved with sports is associated with
health risk behaviors in adolescent populations.5,19,20
Most studies examining the relationship between
physical activity and other health behaviors have been
limited to comparing physical activity to either one
or a relatively small set of behaviors.6,8,13,17 Such
limitations in previous research reflect the need for
studies that examine the relationship of physical
activity across a broad range of both health risk and
health promoting behaviors.
It has been demonstrated that the physiological
benefits of physical activity are directly linked to
the frequency, intensity, and duration of the physical
activity performed.2,14,21 Few studies, however, have
examined the relationship between the intensity of
physical activity (eg, moderate or vigorous), as well as
the frequency (number of times a week engaging in
physical activity), on health.5 Varying levels of physical
exertion may help to explain the contradictory findings
about the relationship between physical activity and
other health habits.
This study examined the relationship between
the frequency and intensity of physical activity and
health behaviors of adolescents. Specifically, this
study investigated associations among low-, medium-,
and high-frequency levels of both vigorous and
moderate intensity physical activities and health risk
behaviors including alcohol, cigarette, and marijuana
use, and health promoting behaviors including
nutrition, sleep, and stress management of high school

6. aged adolescents. We hypothesized that adolescents
participating in increasing frequency of both vigorous
and moderate physical activities would be less likely
to engage in health risk behaviors, and more likely to
engage in health promoting behaviors.
METHODS
Subjects
Data were collected from a sample of 822 11th-
and 12th-grade students attending an ethnically and
socioeconomically diverse suburban school in north-
east Florida during fall 2005 and 2006. Participants
were recruited in classroom settings using formal pre-
sentations describing the study’s aims, procedures,
benefits, and risks. The mean age of participants was
17 years old (SD = 0.81). Females were slightly more
represented (56%). Most students were White (45%),
followed by African-American (26%), and Hispanic
youth (10%). The participant sample was similar to the
overall student population in terms of racial and ethnic
proportions; however, the participants slightly over-
represented the general female population (56% vs
48%). Less than a third (29%) of participants engaged
in 0-1 times of moderate physical activity (MPA) dur-
ing the past 7 days, compared to 37% of those who
engaged in MPA 2-4 times a week, and 33% for 5 or
more time a week. Approximately one third (33%)
of participants reported 0-1 times of vigorous physi-
cal activity (VPA) during the past 7 days, with 40%
reporting 2-4 times a week, and 27% reporting 5 or
more days a week. With regard to health risk behav-
iors, 34% of the participants reported using alcohol,
15% reported using marijuana, and 13% reporting
using cigarettes during the past 30 days. Meanwhile,

7. for health promoting behaviors, less than one third of
participants (30%) consumed 4 or more servings of
fruits and vegetables on average each day during the
same 30-day period (Table 1).
Procedures
This study analyzed baseline data collected from
2 prevention intervention trials. Data were collected
using identical procedures during each of the 2 trials.
Trained research staff followed standardized research
protocols and implemented the self-administered
survey to small groups of students within the
participating school.
Instrumentation
The Personal Development and Health Survey is
an aggregate of previously validated health behavior
Journal of School Health • March 2010, Vol. 80, No. 3 • ©
2010, American School Health Association • 135
Table 1. Demographic Characteristics of Participating
Students (N = 822)
Characteristics n (%)
Gender
Male 366 (44.5)
Female 456 (55.5)
Ethnicity
White 375 (45.4)
Black/African-American 216 (26.3)

8. Hispanic 85 (10.3)
Age
15 years old 5 (6)
16 years old 206 (25.1)
17 years old 361 (43.9)
18 years old 229 (27.9)
19 years old 21 (2.6)
Moderate physical activity
Low (0-1 times/week) 239 (29.1)
Medium (2-4 times/week) 303 (36.9)
High (5 or more times/week) 273 (33.0)
Vigorous physical activity
Low (0-1 times/week) 271 (33.0)
Medium (2-4 times/week) 326 (39.6)
High (5 or more times/week) 220 (26.7)
Past 30 day substance use
Alcohol (34.0)
Marijuana (15.0)
Cigarettes (13.0)
Consumption of 4 or more servings of fruits and vegetables
in past 30 days
(30.0)
surveys. We used this survey to collect data on
multiple health behaviors including physical activity
level (2 items); alcohol, cigarette, and marijuana
consumption (4 items each); dietary habits (3 items);
stress management (1 item); and sleeping patterns
(1 item). These measures were adapted from previous
research and were pilot tested on a sample of high

9. school students to ensure psychometrically sound and
highly readable items for the target population.
Physical Activity. We used an adaptation of the
Godin Leisure Time Exercise Questionnaire (LTEQ) to
assess MPA and VPA.22 Previous research has vali-
dated the LTEQ in adolescent populations, and has
demonstrated sound reliability and concurrent valid-
ity across multiple populations.23 The LTEQ measure
asked: ‘‘Considering a typical 7-day period (1 week),
how many times on the average do you do the fol-
lowing kinds of exercise for more than 15 minutes?’’
Two items defining MPA and VPA followed this ques-
tion. MPA was defined as nonexhausting exercises
such as fast walking, baseball, tennis, slow bicy-
cling, volleyball, badminton, and easy swimming. VPA
was defined as activities that cause the participant’s
heart to beat rapidly, such as running, jogging, foot-
ball, soccer, basketball, rollerblading, skateboarding,
vigorous swimming, and fast bicycling. Participants
were then grouped into low, medium, and high MPA
or VPA classifications based on the frequency of times
they reported corresponding physical activities in a
typical 7-day period. Participants reporting 0-1 times
of MPA/VPA in the past 7 days were grouped into low
categories; those reporting 2-4 times of MPA/VPA were
grouped into medium categories; and those reporting
5 or more times of MPA/VPA were grouped into high
categories.
Health Risk and Promoting Behaviors. Health risk
behavior measures included length of use, and past
30-day frequency, quantity, and heavy use of alco-
hol, cigarette, and marijuana consumption. Measure-
ment scales were identical for assessing length of

10. use (1 = do not use, 2 = 30 days or less, 3 = more
than 30 days but less than 6 months, 4 = more than
6 months but less than 1 year, 5 = more than 1 year)
and past 30-day frequency of use (1 = 0 days, 2 =
1-2 days, 3 = 3-5 days, 4 = 6-9 days, 5 = 10-19 days,
6 = 20-29 days, 7 = all 30 days) for alcohol, cigarettes,
and marijuana. Quantity of use and heavy use was
specifically tailored for the alcohol, cigarette, and mar-
ijuana measures. Quantity of past 30-day use included
average number of alcoholic drinks typically consumed
(1 = 0 drinks, 2 = 1 drink, 3 = 2 drinks, 4 = 3 drinks,
5 = 4 drinks, 6 = 5 drinks, 7 = 6 drinks, 8 = 7 drinks,
9 = 8 drinks, 10 = 9 drinks, 11 = 10 drinks, 12 = 11
drinks), average number of cigarettes smoked (1 = 0
cigarettes, 2 = less than 1 cigarette, 3 = 1-5 cigarettes,
4 = 6-10 cigarettes, 5 = 11-15 cigarettes, 6 = 16-24
cigarettes, 7 = more than 24 cigarettes), and average
number of times using marijuana in the past month
(1 = 0 times, 2 = 1-2 times, 3 = 3-5 times, 4 = 6-9
times, 5 = 10-19 times, 6 = 20-29 times, 7 = 30-39
times, 8 = 40 or more times). Past 30-day heavy use
(1 = 0 days, 2 = 1-2 days, 3 = 3-5 days, 4 = 6-9 days,
5 = 10-19 days, 6 = 20-29 days, 7 = all 30 days) of
alcohol consumption (defined as 5 or more drinks for
males, and 4 or more drinks for females in a row), of
cigarettes (defined as number of days smoking a pack of
cigarettes in 1 day), and marijuana (defined as number
of days participants were ‘‘very high/really stoned’’)
of participants were collected. Items assessing length
of substance use, and past 30-day frequency, quantity,
and heavy substance use were adopted from previ-
ous prevention research.24-27 Cronbach’s alpha for
the alcohol consumption scale was .79; for cigarette-
smoking behavior measures, .91; and for marijuana
use measures, .94.

11. Health promoting behaviors measures included
nutrition, use of stress management techniques, and
sleep. Three nutrition items (α = .78) examined past
30-day servings of fruits and vegetables, number of
times of eating foods with healthy carbohydrates,
and number of times of eating foods with healthy
fats (1 = 0 servings, 2 = 1 serving, 3 = 2 servings,
4 = 3 servings, 5 = 4 servings, 6 = 5 servings, 7 = 6
136 • Journal of School Health • March 2010, Vol. 80, No. 3 • ©
2010, American School Health Association
servings, 8 = 7 servings, 9 = 8 servings, 10 = 9, or
more servings). Stress management behaviors were
assessed with 5 sub-items that measured the frequency
of using a variety of stress management techniques
(eg, prayer, deep breathing, meditation). The sleep
measure included 1 item that measured the aver-
age quantity of sleeping for participants (1 = 9 or
more hours, 2 = 8 hours, 3 = 7 hours, 4 = 6 hours,
5 = 5 hours, or less).
Data Analysis
All analyses were performed using SPSS version
15.0 (SPSS Inc., Chicago, IL). χ 2 analyses tested
demographic differences in physical activities. Mul-
tivariate analysis of variance (MANOVA) and analysis
of variance (ANOVA) tests were conducted to assess
differences on mean health behavior scores across 3
categories (low, medium, and high) of frequency of
MPA and VPA. Tukey post hoc analyses were per-
formed when statistical significance (p ≤ .05) was
obtained to identify significant pairwise differences.

12. RESULTS
Table 2 shows that an overall MANOVA indicated
significant differences on VPA level for marijuana
(F = 2.13; p = .03). Univariate and post hoc pairwise
analysis showed that a high level of VPA was signif-
icantly associated with less frequent marijuana use
(F = 2.99; p = .05) and less heavy marijuana use
(F = 3.60; p = .03), compared to a low level of VPA.
An overall MANOVA was also significant for nutrition
(F = 3.63; p < .001), with univariate tests demonstrat-
ing that a high level of VPA was significantly associated
with greater consumption of healthy carbohydrates
(F = 5.63; p < .001), and healthy fats (F = 10.68;
p < .001), compared to a low level of VPA. In addition,
ANOVA and pairwise tests showed that a high level
of VPA was significantly associated with more use of
stress management techniques (F = 12.01; p < .001),
and a greater quality of sleeping (F = 4.83; p = .01),
compared to a low level of VPA. A similar pattern was
found for frequency and quantity of cigarette smoking,
with less cigarette use for those youth engaged at high
levels of VPA compared to those at low levels of VPA,
although the overall MANOVA was not significant.
Table 3 shows a significant overall MANOVA for
nutrition behaviors across MPA levels (F = 2.12;
p = .05), with univariate and post hoc pairwise analy-
sis revealing that a high level of MPA was significantly
associated with increased consumption of healthy
fats (F = 6.42; p < .001), compared to a low level of
MPA, and a similar pattern approaching significance
for eating good carbohydrates (p = .06). In addition,
stress management techniques differed across MPA

13. (F = 13.45; p < .001), with those engaged in high lev-
els of MPA using more stress management compared
to those engaged in low levels of MPA. No differences
Table 2. Means and Standard Deviations of Health Behaviors by
Level of Vigorous Physical Activity
Low∗ (0-1 times/week) Medium∗ (2-4 times/week) High∗ (≥5
times/week)
n = 271 n = 326 n = 220
Measures M SD M SD M SD F df p
Alcohola F = .95; df = 8, 1614; p = .47
Length 2.61 1.85 2.36 1.78 2.32 1.74 2.12 2, 814 .12
Frequency 1.73 1.11 1.63 1.16 1.58 1.08 1.07 2, 813 .34
Quantity 2.65 2.96 2.44 2.86 2.51 2.87 .43 2, 812 .65
Heavy use 1.34 .86 1.33 .87 1.33 .90 .06 2, 813 .94
Cigarettesa F = 1.35; df = 8, 1598; p = .21
Length 1.49 1.20 1.45 1.16 1.26 .93 2.72 2, 814 .07
Frequency 1.65 1.70 1.56 1.56 1.30 1.14 3.59 2, 812 .03
Quantity 1.34 .85 1.31 .86 1.16 .56 3.49 2, 813 .03
Heavy use 1.10 .50 1.15 .70 1.06 .46 1.72 2, 805 .18
Marijuanaa F = 2.13; df = 8, 1604; p = .03
Length 1.68 1.42 1.63 1.38 1.53 1.29 .77 2, 814 .46
Frequency 1.51 1.35 1.42 1.15 1.25 .89 2.99 2, 810 .05
Quantity 1.52 1.45 1.40 1.16 1.30 1.03 2.10 2, 813 .12
Heavy use 1.47 1.33 1.32 .98 1.22 .77 3.60 2, 810 .03
Nutritionb F = 3.63; df = 6, 1622; p = .001
Fruits/vegetables 4.54 2.40 4.73 2.53 5.01 2.48 2.23 2, 814 .11
Good carbohydrate 5.09 2.68 5.46 2.68 5.91 2.70 5.63 2, 813
.00
Good fats 4.11 2.56 4.58 2.59 5.21 2.75 10.68 2, 814 .00

14. Sleepa 3.72 1.06 3.55 1.05 3.44 .99 4.83 2, 812 .01
Stress managementb 1.92 .58 2.14 .66 2.25 .70 12.01 2, 562 .00
∗ Low, medium, and high groups are characterized by
frequency of exercise per week.
a Higher mean score = higher risk.
b Higher mean score = lower risk.
Journal of School Health • March 2010, Vol. 80, No. 3 • ©
2010, American School Health Association • 137
Table 3. Means and Standard Deviations of Health Behaviors by
Level of Moderate Physical Activity
Low∗ (0-1 times/week) Medium∗ (2-4 times/week) High∗ (≥5
times/week)
n = 239 n = 303 n = 273
Measures M SD M SD M SD F df p
Alcohola F = .53; df = 8, 1610; p = .83
Length 2.58 1.81 2.35 1.79 2.39 1.80 1.19 2, 812 .30
Frequency 1.75 1.16 1.60 1.09 1.62 1.13 1.22 2, 811 .30
Quantity 2.69 2.94 2.48 2.90 2.45 2.85 .52 2, 810 .60
Heavy use 1.36 .88 1.31 .84 1.33 .90 .24 2, 811 .79
Cigarettesa F = 1.12; df = 8, 1594; p = .34
Length 1.48 1.22 1.40 1.09 1.36 1.07 .82 2, 812 .44
Frequency 1.63 1.70 1.46 1.43 1.47 1.42 1.13 2, 810 .32
Quantity 1.36 .96 1.25 .73 1.23 .68 1.99 2, 811 .14
Heavy use 1.18 .78 1.08 .50 1.07 .44 2.71 2, 803 .07
Marijuanaa F = 1.09; df = 8, 1600; p = .36

15. Length 1.67 1.42 1.58 1.35 1.62 1.36 .33 2, 812 .72
Frequency 1.51 1.40 1.34 1.03 1.38 1.07 1.61 2, 808 .20
Quantity 1.54 1.52 1.36 1.09 1.37 1.10 1.84 2, 808 .16
Heavy use 1.48 1.36 1.28 .91 1.30 .92 2.77 2, 810 .06
Nutritionb F = 2.12; df = 6, 1618; p = .05
Fruits/vegetables 4.47 2.50 4.78 2.42 4.91 2.51 2.07 2, 812 .13
Good carbohydrate 5.15 2.67 5.45 2.74 5.71 2.66 2.82 2, 811
.06
Good fats 4.13 2.59 4.61 2.60 4.96 2.69 6.42 2, 812 .00
Sleepa 3.63 1.10 3.55 .98 3.56 1.06 .41 2, 810 .67
Stress managementb 1.90 .62 2.14 .63 2.24 .68 13.45 2, 561 .00
∗ Low, medium, and high groups are characterized by frequency
of exercise per week.
a Higher mean score = higher risk.
b Higher mean score = lower risk.
were found across MPA on alcohol, cigarette or mari-
juana use, and quality of sleep.
DISCUSSION
This study examined the relationships of physical
activity levels with health risk and health promoting
behaviors among adolescents. Our findings supported
the hypothesis that adolescents participating in
increased levels of physical activity would be less
likely to engage in health risk behaviors and more
likely to engage in health promoting behaviors. The
main findings demonstrate that adolescents engaged
in high levels of VPA were using less marijuana, had
a healthier dietary intake, greater stress management
skills, and better quantity of sleep than those engaged
in low or no VPA. Although overall MANOVA analysis

16. for the cigarette use scale was nonsignificant for VPA,
significant differences were found with the high VPA
group demonstrating lower frequency of cigarette
smoking and quantity of cigarette smoking than the
low VPA grouping.
Less supportive of our hypothesis was the finding
that participation in high levels of MPA was not as
consistently associated with other health behaviors
when compared to participation in high levels of
VPA. Increased healthy fat food consumption and
improved stress management were the only health
behaviors found to be statistically significant among
adolescents engaged in high levels of MPA. This
suggests VPA is a better predictor of other health habits
in adolescence than MPA. Further research should
examine why these differences may exist, as this
finding has potential implications for increasing our
understanding and possibly affecting multiple behavior
patterns of youth.27
Our results indicate VPA may be an important
factor to consider for interventions that simultane-
ously address multiple health behaviors, especially in
similarly diverse adolescent populations in the south-
eastern United States. Additional studies of adolescents
involving more geographically diverse populations
will improve the generalizability of the relation-
ship between VPA and other health behaviors in
adolescents.
The associations between high levels of VPA and
smoking, dietary behaviors, and stress management
are particularly important considering these are lead-
ing factors for longevity, chronic disease prevalence,

17. and quality of life.1,3 Additionally, the finding that
adolescents participating in high levels of VPA smoked
marijuana less frequently and heavily is signifi-
cant considering marijuana is the most commonly
used illicit drug, and is equal to rates of cigarette
smoking among adolescents.28,29 Longitudinal stud-
ies are needed to examine the temporal relationships
138 • Journal of School Health • March 2010, Vol. 80, No. 3 • ©
2010, American School Health Association
and causal associations among levels and types of
physical activity and other critical health behaviors of
adolescents.
It is possible that the relationship between increased
physical activity and healthy psychological well-being
may serve as a protective factor against health
risk behaviors and contribute to health promoting
behaviors.30-32 Moreover, those who engage in high
levels of physical activity may be exposed to positive
social influences that promote healthy behaviors.33,34
Social images that characterize individuals who are
engaged in large amounts of physical activity may
also help to explain this relationship. For example,
social images attributed to individuals participating in
high levels of VPA reflect an individual engaged in
other positive health behaviors, such as good nutrition
and the avoidance of smoking behaviors.15,35 In addi-
tion, motivational factors associated with participating
in high levels of physical activity, may inherently
attract individuals who are already predisposed toward
avoiding unhealthy behaviors and engaging in healthy

18. behaviors.36
Our findings suggest the importance of promoting
VPA among adolescents, especially considering rates of
VPA among this population are very low.9,37 National
prevalence studies estimate that between 34% and 7%
of adolescent populations meet the Centers for Disease
Control and Prevention’s (CDC’s) guidelines for regu-
lar vigorous physical activity.14,16,29 Our study supports
these findings with less than 27% of our sample
meeting the CDC standards for engaging in VPA. Con-
sidering the impact VPA has on physical health and its
potential influence on other health risk and promoting
behaviors, along with the low rates of VPA within this
population, the promotion of regular VPA in adoles-
cents should continue as a major public health priority.
Limitations
Results of this study should be interpreted in lieu
of several limitations. First, our findings are based
on a sample of 11th- and 12th-grade students from
a single suburban high school. Additional studies
of adolescents involving probability samples drawn
from urban, rural, suburban, and more geographically
diverse populations would improve generalizability.
A second limitation of this study was the exclusive use
of self-reported data, without corroboration from other
sources. The use of costly biochemical or mechanical
verification of self-reports remains a challenge for
those engaged in multiple behavior research. A third
limitation was the use of cross-sectional data,
which precludes establishing a temporal and causal
relationship among varying levels of physical activity
and health behaviors. A final limitation was the lack
of more precise measures of identifying participation

19. in specific physical activities (ie, swimming, cycling,
tennis, skateboarding), and the lack of inclusion of
measures of sport participation. Recent research has
indicated that certain types of physical activities and
sports are associated with both positive and negative
health behaviors of young people.38
Conclusions
In conclusion, the results from this study sug-
gest that high-frequency levels of VPA are associated
with a number of health risk and health promoting
behaviors in adolescents. Future research is needed to
examine whether the statistically significant associa-
tions found in the high VPA groupings are practically
significant for improving other health behaviors in
adolescence. Our findings underscore the critical need
for incorporating more robust experimental method-
ologies, such as physiological health measures and
longitudinal research designs, into examining the prac-
tical importance between VPA and various adolescent
health risks and promoting behaviors. Such studies
will help to inform the potential public health impact
of school-based interventions targeting multiple health
behaviors in adolescents.
IMPLICATIONS FOR SCHOOLS
Innovative school health promotion and educa-
tion efforts incorporating VPA with multiple health
behavioral change strategies may help to improve the
magnitude of mean difference seen in our significant
findings. A theme of physical activity is congruent
with recent studies advocating for the promotion of
healthy youth development to enhance a wide range

20. of health behaviors in adolescent populations.39,40
School health professionals and policy makers should
examine the feasibility of utilizing VPA interventions
within school-based curriculums (such as physical and
health education courses), and in extracurricular activ-
ities (ie, athletics and other after school programming)
to improve multiple health behaviors in adolescents.
School health officials and policy makers will then
have the opportunity to evaluate and compare the
efficacy and effectiveness of previous health promotion
efforts with those incorporating VPA toward improving
multiple health behaviors in adolescence. Addition-
ally, this type of approach toward school-based health
promotion may be more cost effective and ready for
widespread dissemination and adoption than more tra-
ditional approaches to school health.7,15 Furthermore,
exploring the efficacy of these interventions will help
to fill a void in the scientific knowledge of school-
based health promotion and multiple health behavior
intervention research.
Human Subjects Approval Statement
The protocols for conducting the intervention
trials, including parent consent and youth assent
procedures, were approved by the University of
Florida’s institutional research review board.
Journal of School Health • March 2010, Vol. 80, No. 3 • ©
2010, American School Health Association • 139
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140 • Journal of School Health • March 2010, Vol. 80, No. 3 • ©
2010, American School Health Association
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27. Community Health Advocacy Project – Part 3
NUR/544 Version 6
1
Assignment Grading Criteria
Community Health Advocacy Project– Part 3
Week 6
Using the theory or model that you selected in Week Four,
develop an intervention thataddresses one of the levels of
prevention for your aggregate.
Describe the intervention plan and how it may be actualized.
Include the following:
· Formulate one outcome goal and various objectives (as
appropriate) and explain why these are appropriate
· Explain the intervention plan (including the steps and
resources needed)
· Identify organizations within the community that may be able
to assist with the intervention and explain why they are
appropriate to partner with.
· Explain how you plan to evaluate the intervention. Include
methods and why they are appropriate
Develop a presentation using one of the following formats:
· Microsoft® PowerPoint® Presentation including 15–20 slides
with detailed speaker’s notes
· Oral presentation including appropriate visual aid (for
example, a handout or brochure)— with separate referenced
speaker notes

28. · Prezi® Presentation—with separate referenced speaker notes
· Go animate (animation)— with separate referenced speaker
notes
· Another format approved by your facilitator.
Format your presentation consistent with APA guidelines.
Include a minimum of 8 scholarly references.
Submit the assignment as directed by the instructor.
Present your intervention plan to the class.
Note. Points are awarded based on the quality of the content
submitted and the degree to which assignment expectations are
met.
Content
20 points possible
Points possible
Points earned
Uses the model or theory of health promotion from part 2 of the
project to formulate one outcome goal and appropriate
objectives and explain why these are appropriate for the chosen
aggregate’s health need
5
Explains the intervention plan including the steps and resources
needed
5
Identifies organizations within the community that may be able
to assist with the intervention and explains why they are
appropriate to partner with
5

29. Explains how you plan to evaluate the intervention and includes
methods and why they are appropriate
5
Organization
2 points possible
Presentation is well-organized, clear, and effectively structured
0.5
Time is well used and not rushed
0.5
Introduction explains the purpose of the presentation and
previews major points
0.5
Conclusion is logical, flows from the presentation, and reviews
the major points
0.5
Format
3 points possible
Points possible
Points earned
Visual aids are appropriately professional, easy to read, and
contribute to effectiveness of presentation
3
Follows rules of grammar, punctuation, and spelling
Consistent with APA formatting guidelines for formatting of
references and citation of outside works

30. Presenter(s) content knowledge/confidence are evident, involve
audience, and solicit feedback
Cites the required number of sources
Total
25
Copyright © 2015 by University of Phoenix. All rights reserved.
Original Research
Gender and Ethnic Differences in
Health-Promoting Behaviors of
Rural Adolescents
Lynn Rew, EdD, RN, AHN-BC, FAAN
1
, Kristopher L. Arheart, EdD
2
,
Sharon D. Horner, PhD, RN, FAAN
1
, Sanna Thompson, PHD, MSW
3
,

31. and Karen E. Johnson, PhD, RN
1
Abstract
Although much is known about health-risk behaviors of
adolescents, less is known about their health-promoting
behaviors.
The purpose of this analysis was to compare health-promoting
behaviors in adolescents in Grades 9–12 by gender and
ethnicity and explore how these behaviors changed over time.
Data were collected from 878 rural adolescents (47.5%
Hispanic; mean age at baseline 14.7 years). Males from all
ethnic groups scored significantly higher than all females on
phys-
ical activity; non-Hispanic Black males and females scored
significantly higher than other ethnic groups on safety
behaviors.
Hispanic and non-Hispanic White females scored higher than
males in these ethnic groups on stress management. Nutrition,
physical activity, and safety behaviors decreased significantly
for most participants from Grade 9 to 12 whereas stress
management remained relatively stable. Findings are similar to
those from nationally representative samples that analyzed
cross-sectional data and have implications for school nursing
interventions to improve health-promoting behaviors in rural
adolescents.
Keywords
health/wellness, high school, cultural issues, exercise, nutrition
Despite an expanding literature about the factors that relate
to and predict adolescent health-risk behaviors, less is

32. reported in the literature about health-promoting behaviors
in adolescents—particularly among those living in rural areas.
Health-promoting behaviors emphasize lifestyle choices that
improve physical health and well-being (Steinberg, 2014).
Health-promoting behaviors such as safety, stress manage-
ment (Groft, Hagen, Miller, Cooper, & Brown, 2005), physi-
cal activity (Kalak et al., 2012), and adequate nutrition
(Williams & Mummery, 2012) contribute to positive rather
than adverse health outcomes. Research that focuses on the
presence of health-promoting behaviors, as opposed to the
risk-focused perspective, is essential to understand how to
help young people make the successful transition from child
to adult. As part of an interdisciplinary education team com-
mitted to student success, school nurses are in ideal settings to
collaborate with others (e.g., health education teachers, food
service staff, and school health advisory councils) to deliver
interventions that enhance adolescent health.
Purpose

33. This article is a report of findings from a large longitudinal
study of health-risk and health-promoting behaviors among
rural adolescents as they progressed through high school (in
Grades 9–12). The specific aims of this analysis, which was
a component of the larger study, were to (1) compare the
health-promoting behaviors of adolescents by gender and
ethnicity and (2) explore how health-promoting behaviors
of these adolescents changed during the high school years.
Findings about health-risk behaviors have been published
previously (Horner, Rew, & Brown, 2012).
We sought to answer two research questions: (1) what are
the gender and ethnic differences in health-promoting beha-
viors among Hispanic, non-Hispanic Black (NHB), and non-
Hispanic White (NHW) adolescents residing in three rural
communities and (2) do health-promoting behaviors change
1
The University of Texas at Austin School of Nursing, Austin,
TX, USA
2 Department of Epidemiology and Public Health, The

34. University of Miami,
Miami, FL, USA
3
The University of Texas at Austin School of Social Work,
Austin, TX, USA
Corresponding Author:
Lynn Rew, EdD, RN, AHN-BC, FAAN, The University of Texas
at Austin,
School of Nursing, 1710 Red River, Austin, TX 78701, USA.
Email: [email protected]
The Journal of School Nursing
2015, Vol. 31(3) 219-232
ª The Author(s) 2014
Reprints and permission:
sagepub.com/journalsPermissions.nav
DOI: 10.1177/1059840514541855
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as adolescents matriculate through Grades 9–12? Our
hypotheses were as follows

35. Hypothesis 1: Of all groups examined (gender, grade,
and race/ethnicity), racial and ethnic minority males will
exhibit the fewest health-promoting behaviors.
Hypothesis 2: Adolescents’ health-promoting behaviors
will decrease each year from Grade 9 through Grade 12.
Background
Adolescent Health Behavior
During childhood, patterns of behavior are initiated that con-
tribute to the individual’s health and well-being throughout
the life span. Health behaviors are reflected in a continuum
from those that promote and enhance optimum development
and well-being (i.e., health-promoting behaviors) to those
that threaten development and well-being (i.e., health-risk
behaviors). Engaging in health-promoting behaviors, such
as eating nutritional snacks, engaging in physical activity,
and managing stress effectively, has been shown to protect
adolescents from adverse health outcomes (Iannotti & Wang,
2013; Peterhans, Worth, & Woll, 2013) and has been asso-

36. ciated with better health outcomes in later adulthood than
engaging in health-risk behaviors during adolescence (Dorn,
Beal, Kalkwarf, Pabst, Noll, & Susman, 2013; Olshansky
et al., 2005). Engaging in health-promoting behaviors contri-
butes to development of a healthy lifestyle (Kelder et al.,
2003). For example, running for 30 min daily was shown to
improve sleep quality and psychological functioning in
healthy adolescents (Kalak et al., 2012).
Previous studies have shown gender and age differences
in health-promoting behaviors. For example, Williams and
Mummery (2012) found that compared with males, females
were more likely to exhibit healthy eating patterns. In con-
trast, cross-sectional findings from the 2011 Youth Risk
Behavior Survey (YRBS) suggest males were more likely
than females to exhibit various health-promoting behaviors,
including eating three or more daily servings of fruit, three
or more servings of vegetables, three or more servings of
milk, and participating in 60 min of physical activity every-

37. day for a week prior to completing the survey (Centers for
Disease Control and Prevention [CDC], 2012, p. 29). Similar
to Williams and Mummery’s findings (2012), ninth graders
reported a higher prevalence than 12th graders of these same
nutritional and physical activity behaviors (CDC, 2012).
Although we have ample evidence of risk and protective
factors related to health-risk behaviors in adolescents (Gott-
fredson & Hussong, 2011; Leeman, Hoff, Krishnan-Sarin,
Patock-Peckham, & Potenza, 2014; Taliaferro, Muehlen-
kamp, Borowsky, McMorris, & Kugler, 2012; Thompson,
Dewa, & Phare, 2012 ), we have much less evidence of those
factors related to health-promoting behaviors. Previous stud-
ies of health-promoting behaviors in adolescents have been
primarily cross-sectional and involved small samples that
were mostly White (Mahon, Yarcheski, Yarcheski, & Hanks,
2007; Yarcheski, Mahon, & Yarcheski, 1997). The biannual
reports from the YRBS, such as the CDC (2012) report men-
tioned previously, describe a nationally representative sample

38. of adolescents, but they too are cross-sectional. Moreover,
these studies focus on trends in the population as opposed
to changes over time within a particular population such as
those living in rural areas.
In this study, we began with a public health approach
grounded in the premise that ‘‘health is a product of lifestyle
shaped heavily by social and physical environments’’
(Crosby, Kegler, & DiClemente, 2009, p. 4). Basic social
and physical attributes such as ethnicity, sex, socioeconomic
status (SES), parent’s level of education, and marital status
have a profound effect on learned behaviors, including those
that are health related. Identifying these attributes and their
effects on health-promoting behaviors may influence the
development of interventions that can be tailored to adoles-
cents with diverse personal and cultural characteristics.
Similarly, identifying if and when these health-promoting
behaviors change over time may influence the development
and testing of interventions targeted at specific developmen-

39. tal stages of adolescence when adult lifestyles are being
shaped. These interventions are needed to ensure a healthy
generation of adults.
Importantly, the health behavior of adolescents living in
rural communities is studied less often than those of youth
in urban or suburban environments—particularly those
from racial/ethnic minority backgrounds (Curtis, Waters,
& Brindis, 2011). For example, a survey of health status
and clinic use among ninth graders in rural Mississippi
yielded a response rate of only 27.6% for a mostly White
school and a 2.6% response rate for a school that was pre-
dominantly African American (Bradford & O’Sullivan,
2007). Compared to urban and suburban areas, rural areas
rank low in most population health indicators including
health behaviors and maternal and child health (Hartley,
2004). As an example of this, Nanney, Davey, and Kubik
(2013) evaluated policies and practices of secondary
schools in 28 states and found that schools in smaller towns
and rural areas did not have as many healthy eating policies

40. and practices as schools in urban/suburban areas.
Well over half of rural counties (65%) experience
shortages in health care providers and access to health ser-
vices, with this percentage being higher in rural counties
where people of color are the majority (Probst, Moor,
Glover, & Samuels, 2004). These disparities create a social-
environmental context for adolescent health and development
that is distinctly different from that of suburban or urban
contexts. Geographic isolation and lack of community
resources such as confidential health care services may
present barriers to rural adolescents having the supports
they need to engage in health-promoting behaviors (Curtis
et al., 2011). Curtis, Waters, and Brindis (2011) conducted
220 The Journal of School Nursing 31(3)
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a secondary analysis of rural adolescents ages 12 through
17 from the cross-sectional 2005 California Health Inter-

41. view Survey and found disparate levels of sexual activity,
substance use, depressive symptoms, and risk factors for
obesity (i.e., poor diet and low levels of physical activity).
Although nationally representative samples of adolescents
include those from rural areas, we found no published
longitudinal studies of how behaviors in rural areas may
be different from or the same as behaviors in urban and
suburban youth. This longitudinal analysis examining
health-promoting behaviors among rural adolescents can
extend Curtis et al.’s cross-sectional findings and help to
fill gaps in the literature regarding rural adolescent health.
Method
Design and Setting
A cohort-sequential longitudinal design was used to explore
changes in the development of health behaviors in adoles-
cents residing in rural communities in central Texas. Four
cohorts of students were initially recruited over a period of
2 years by sending letters to parents of children who were

42. then in Grade 4 through Grade 6 (Rew, Horner, & Brown,
2011). These participants were followed through Grade 8,
and subsequently recruited again for a second longitudinal
study when they were in Grade 9 (Rew, Arheart, Thompson,
& Johnson, 2013). Sixty-seven percent of the original sam-
ple were retained for this study.
Protection of Human Participants
The study was reviewed annually by the institutional review
board at the first author’s university. Both written parental
consent and adolescent assent were collected each year of
the study for all participants. When adolescents reached
18 years of age, they provided their own consent.
Sample
The sample for this analysis was drawn from a total of 1,294
adolescents who were recruited for a longitudinal study
when they entered high school in Grade 9 and consisted of
878 adolescents who were retained at the final data collec-
tion point when they were in Grade 12 (68% retention over

43. 4 years). This retention rate reflects an average loss of
approximately 14% of the sample each succeeding year of
the study. Participants were an average of 14.7 years old
in Grade 9 and 17.18 years old in Grade 12. The sample con-
sisted of four Cohorts (i.e., A, B, C, and D) that reflect the
grade the participant was in at the beginning of the previous
longitudinal study to which this was a 4-year follow-up. For
example, Cohort A would have been in Grade 6 during the
first year of the previous study, Cohort B would have been
in Grade 5, and so on.
Measures
Two measures were used for this analysis: a demographic
form and the Adolescent Lifestyle Questionnaire (ALQ). The
demographic form was developed by the principal investiga-
tor of the study and consisted of age, sex, race, and ethnicity.
Health-promoting behaviors were measured using four
subscales from the ALQ: nutrition, physical activity, safety,
and stress management (Gillis, 1997). Three other subscales
of the ALQ, identity awareness, health awareness, and social

44. support, were not included in the present analysis because
they are conceptually different from health-promoting beha-
viors. The ALQ consists of 43 six-point Likert-type items
(6 ¼ always and 1 ¼ never); high scores mean greater
engagement in health-promoting behaviors; we used only
the 23 items that comprised the four subscales used in this
analysis. Examples of items are ‘‘I usually make informed
choices about sexual relationships’’ (safety); ‘‘I participate
in a regular program of sports/exercise at school’’: (physical
activity); ‘‘I read labels on packaged foods I eat’’ (nutrition);
and ‘‘I usually use helpful strategies to help me deal with
stress’’ (stress management; Gillis, 1997, pp. 38–39).
Procedures
Following approval from the institutional review board, par-
ents signed informed consent forms and adolescents under
age 18 signed informed assent forms annually; adolescents
18 years of age and older signed their own consents. In the
first 2 years of the study, data were gathered through home

45. visits using computer-assisted self-interviewing (CASI) or
via a secure website that the adolescent could access from
home. In the final 2 years, data were gathered by mailed sur-
vey owing to increased difficulty in making appointments
for home visits. Scheduling difficulties arose, as adolescents
became older and involved in more after-school and evening
activities.
Data Analysis
Descriptive statistics (mean + standard error or percentage)
were used to describe the demographic data by year and
cohort within year. Descriptive statistics (M + SD) and
Cronbach’s a reliability coefficient were computed for each
health-promoting behavior for each year and cohort within
year. To address Research Question 1—what are the gender
and ethnic differences in health-promoting behaviors among
Hispanic, non-Hispanic Black, and non-Hispanic White
adolescents residing in three rural communities—and
Hypothesis 1—of all groups examined (gender, grade, and
race/ethnicity), racial and ethnic minority males will exhi-
bit the fewest health-promoting behaviors, we used sepa-

46. rate general linear mixed models for each year and
health-promoting behavior. The fixed effects of interest
included in the models were gender, race/ethnicity, and the
interaction of gender and race/ethnicity. Fixed covariates
for age, two-parent household (yes/no), subsidized school
Rew et al. 221
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lunch (yes/no), and mother’s highest education were included
to control for their possible confounding effects. A random
effect was included for cohort. Planned comparisons were
made for gender differences within each race/ethnic category
and between race/ethnic categories for each gender.
To address Research Question 2—do health-promoting
behaviors change as adolescents matriculate through Grade
9 through Grade 12 and Hypothesis 2—adolescents’ health-
promoting behaviors will decrease each year from Grade 9

47. through Grade 12, we used a general linear mixed model for
each health-promoting behavior to perform a linear growth
curve analysis. The model included random terms for the
intercepts and slopes (trajectories) for each gender-race/
ethnicity combination. A random term was included for per-
son nested within cohort. Statistical Analysis Software (SAS)
9.3 (SAS Institute, Inc., 2013) was used for all analyses. Sta-
tistical tests resulting in a probability level less than .05 were
considered to be statistically significant.
Results
Demographic data by year and cohort within year are sum-
marized in Table 1. Table 2 is a summary of the means,
standard errors, and Cronbach’s a for each of the four
health-promoting behaviors (nutrition, physical activity,
safety, and stress management) measured for each year and
Table 1. Demographic Characteristics in Sample of Rural
Adolescents in Grade 9 Through Grade 12.
Grade
Cohort n

48. Age,
M + SE
Female
(%)
Hisp
(%)
NHB
(%)
NHW
(%)
Both Parents
(%)
Subsidized
Lunch (%)
<HS
a
(%)
HS
a
(%)
Some
College
a

49. (%)
BS
a
(%)
>BS
a
(%)
Grade 9 814 14.7 + 0.02 56 47 13 40 59 57 15 34 31 12 8
A 205 15.0 + 0.05 58 47 13 40 54 59 13 38 32 7 10
B 177 14.9 + 0.03 58 44 9 47 66 59 13 36 29 11 11
C 254 14.5 + 0.03 56 48 15 37 56 52 17 35 31 12 5
D 176 14.4 + 0.04 54 48 16 36 63 58 16 28 31 15 10
Grade 10 825 15.5 + 0.02 57 48 13 39 60 57 16 32 31 12 9
A 119 16.2 + 0.04 68 50 12 38 58 59 14 37 30 6 13
B 294 15.5 + 0.03 55 47 11 12 62 57 14 32 32 12 10
C 218 15.3 + 0.03 54 46 16 38 56 55 19 33 31 12 5
D 194 15.2 + 0.04 55 49 14 37 64 58 16 29 30 16 9
Grade 11 818 16.3 + 0.02 58 45 14 41 60 59 15 31 33 12 9
A 213 16.7 + 0.04 62 43 15 42 55 62 13 32 36 7 12
B 210 16.3 + 0.04 61 40 13 47 61 62 12 30 33 13 12
C 214 16.1 + 0.04 55 47 15 38 59 54 17 30 34 13 6
D 181 16.1 + 0.04 55 51 20 19 66 59 18 31 28 15 8
Grade 12 707 17.2 + 0.02 61 48 12 40 62 60 14 32 32 12 10
A 170 17.5 + 0.0 67 47 14 39 58 61 13 35 32 7 13
B 211 17.1 + 0.03 67 43 10 47 62 64 11 30 33 14 12
C 193 17.0 + 0.04 59 49 14 37 61 55 18 33 31 12 6
D 133 17.0 + 0.04 53 53 12 35 69 61 14 29 30 19 8

50. Note. M ¼ mean; SE ¼ standard error; Hisp ¼ Hispanic; NHB ¼
non-Hispanic Black; NHW ¼ non-Hispanic White; HS ¼ high
school; BS ¼ bachelor’s degree.
a
Mother’s highest level of eduction.
Table 2. Overall Means, Standard Errors, and Cronbach’s a
Coefficients for Health-Promoting Behaviors in Adolescents.
Grade n
Nutrition Physical Activity Safety Stress Management
M + SE (a) M + SE (a) M + SE (a) M + SE (a)
Grade 9 814 25.1 + 0.3 (0.89) 15.6 + 0.2 (0.89) 36.7 + 0.2
(0.76) 14.3 + 0.2 (0.65)
Range by cohort 176–254 24.1 + 0.6 - 25.9 + 0.7 15.4 + 0.4–
16.2 + 0.5 36.2 + 0.4–37.1 + 0.4 14.0 + 0.2–14.5 + 0.4
Grade 10 825 25.0 + 0.3 (0.89) 15.2 + 0.2 (0.90) 36.0 + 0.2
(0.80) 14.3 + 0.2 (0.66)
Range by cohort 119–294 24.3 + 0.8–25.3 + 0.6 14.2 + 0.6–15.8
+ 0.4 35.2 + 0.7–36.3 + 0.4 14.0 + 0.3–14.5 + 0.3
Grade 11 818 25.1 + 0.3 (0.90) 14.5 + 0.2 (0.90) 36.3 + 0.2
(0.79) 14.3 + 0.2 (0.62)
Range by cohort 181–214 24.9 + 0.6–25.1 + 0.6 14.0 + 0.5–15.1
+ 0.5 35.5 + 0.4–36.7 + 0.4 14.1 + 0.3–14.9 + 0.3
Grade 12 707 24.8 + 0.3 (0.91) 13.6 + 0.2 (0.89) 35.9 + 0.2
(0.77) 14.2 + 0.2 (0.68)
Range by cohort 133–211 23.4 + 0.7–25.7 + 0.8 12.6 + 0.5–14.3
+ 0.6 34.9 + 0.5–36.7 + 0.4 14.1 + 0.4–14.5 + 0.4
Note. Nutrition: 8 items, score range (8–48); Physical Activity:
4 items, score range (4–24); Safety: 7 items, score range (7–42);
Nutrition: 8 items, score range
(8–48). M ¼ mean; SE ¼ standard error.

51. 222 The Journal of School Nursing 31(3)
at LOYOLA MARYMOUNT UNIV on October 8,
2015jsn.sagepub.comDownloaded from
http://jsn.sagepub.com/
T
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(M
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)

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d
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ar
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lly
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if
ic
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t.
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¼
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p
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o
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¼
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s
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94. e
d
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95. ck
;
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h
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96. rr
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97. e
lo
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s
d
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gr
e
e
.
223
at LOYOLA MARYMOUNT UNIV on October 8,
2015jsn.sagepub.comDownloaded from
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T
a
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4
.
P
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98. A
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it
y
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r
b
y
R
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th
n
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y

99. an
d
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d
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r
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it
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va
ri
at
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s.
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e
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100. C
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va
ri
at
e
s
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al
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e
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al
e
ve
rs
u
s
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101. H
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is
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ra
d
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th
n
ic
it
y
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102. E
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126. 3
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128. 9
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133. ch
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ra
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136. fi
x
e
d
ra
ce
/e
th
n
ic
it
y
an
d
ge
n
d
e
r
e
ff
e
ct
s
ad
ju

137. st
e
d
fo
r
fi
x
e
d
T
ab
le
5
.B
o
ld
e
d
va
lu
e
s
ar
e
st

138. at
is
ti
ca
lly
si
gn
if
ic
an
t.
H
is
p
¼
H
is
p
an
ic
;M
o
m
e
d

139. ¼
m
o
th
e
r’
s
h
ig
h
e
st
le
ve
lo
f
e
d
u
ca
ti
o
n
;M
¼
m
e
an

140. ;
N
H
B
¼
n
o
n
-H
is
p
an
ic
B
la
ck
;
N
H
W
¼
n
o
n
-H
is
p

141. an
ic
W
h
it
e
;
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142. h
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224

143. at LOYOLA MARYMOUNT UNIV on October 8,
2015jsn.sagepub.comDownloaded from
http://jsn.sagepub.com/
T
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181. e
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182. d
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183. o
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184. ic
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185. ig
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186. o
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187. S
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188. lle
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225
at LOYOLA MARYMOUNT UNIV on October 8,
2015jsn.sagepub.comDownloaded from
http://jsn.sagepub.com/
T
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189. b
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192. M
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216. .0
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217. e
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219. .4
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221. +
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223. W
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225. 1
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226. —
>
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n
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ll
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227. ix
e
d
m
o
d
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lf
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r
fi
x
e
d
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ce
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n
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228. d
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r
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ff
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s
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229. ct
s
an
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a
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d
o
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co
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rt
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ld
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d
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e
s

230. ar
e
st
at
is
ti
ca
lly
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gn
if
ic
an
t.
H
is
p
¼
H
is
p
an
ic
;M

231. o
m
e
d
¼
m
o
th
e
r’
s
h
ig
h
e
st
le
ve
l
o
f
e
d
u
ca
ti
o
n

232. ;
M
¼
m
e
an
;
N
H
B
¼
n
o
n
-H
is
p
an
ic
B
la
ck
;
N
H
W
¼

233. n
o
n
-H
is
p
an
ic
W
h
it
e
;
S
E
¼
st
an
d
ar
d
e
rr
o
r;
H
S
¼

234. h
ig
h
sc
h
o
o
l;
C
¼
co
lle
ge
;
B
S
¼
b
ac
h
e
lo
r’
s
d
e

235. gr
e
e
.
226
at LOYOLA MARYMOUNT UNIV on October 8,
2015jsn.sagepub.comDownloaded from
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cohort within each year. Results to answer the first research
question and test the first hypothesis are presented in
Tables 3–6. Results to answer the second research question
and test the second hypothesis are in Table 7. The number
of participants in each table varies because those who did
not provide complete data on a particular variable were not
included in that analysis.
Demographic Attributes
In addition to age, sex, and ethnicity, Table 1 also shows the
percentage of participants who lived with both parents, the
percentage who received subsidized lunch (low SES), and

236. the highest grade level of the participants’ mothers.
Annual Means of Health-Promoting Behaviors
Table 2 shows the means and standard errors for each type of
health-promoting behavior measured in each of the 4 years
of the study and the ranges for each of the four cohorts. See
our previous report on that study for a fuller description of
the cohorts (Rew et al., 2011). Table 2 also shows the relia-
bility coefficients (a) for each of the health-promoting
behavior subscales. These ranges for cohorts were .88–.91
for nutrition, .88–.92 for physical activity, .73–.86 for safety,
and .59–.71 for stress management.
Differences in Nutrition-Related Behaviors
There were no statistically significant gender differences in
nutrition-related health-promoting behaviors for Hispanic and
NHB participants in any of the four grades; however, NHW
females engaged in significantly more healthy eating beha-
viors such as avoiding foods high in fat and salt than NHW
males in each of the four grades. Although NHW females

237. exhibited a higher frequency of these nutrition-related beha-
viors than Hispanic and NHB females in all four grades, the
differences were statistically significantly greater than Hispa-
nics in Grade 10 only and greater than NHB females in
Grades 10, 11, and 12.
Differences in Physical Activity Behaviors
There were statistically significant sex differences in physi-
cal activity behaviors such as participating in sports or exer-
cising regularly for all ethnic groups in each of the four
Table 7. Trajectories of Health Behaviors Over Time by
Race/Ethnicity and Gender.
Intercept Trajectory (Slope)
Race/Ethnicity–Gender b + SE p b + SE p
Nutrition
Hispanic males 25.04 + 0.98 <.001 �0.31 + 0.17 .066
Non-Hispanic Black males 24.18 + 1.18 <.001 �0.57 + 0.28
.046
Non-Hispanic White males 23.67 + 1.09 <.001 �0.09 + 0.19
.627
Hispanic females 25.16 + 0.95 <.001 �0.06 + 0.13 .631
Non-Hispanic Black females 23.93 + 1.10 <.001 �0.55 + 0.29
.055
Non-Hispanic White females 27.49 + 1.05 <.001 0.26 + 0.13
.048

238. Physical activity
Hispanic males 15.08 + 0.74 <.001 �0.37 + 0.12 .002
Non-Hispanic Black males 17.01 + 0.89 <.001 �0.40 + 0.18
.033
Non-Hispanic White males 14.44 + 0.82 <.001 �0.39 + 0.12
.002
Hispanic females 12.34 + 0.72 <.001 �0.33 + 0.10 .001
Non-Hispanic Black females 12.35 + 0.83 <.001 �0.24 + 0.19
.203
Non-Hispanic White females 12.55 + 0.80 <.001 �0.74 + 0.11
<.001
Safety
Hispanic males 34.66 + 0.72 <.001 �0.17 + 0.14 .206
Non-Hispanic Black males 37.27 + 0.88 <.001 0.20 + 0.26 .430
Non-Hispanic White males 35.07 + 0.80 <.001 �0.35 + 0.12
.003
Hispanic females 36.31 + 0.70 <.001 �0.06 + 0.10 .512
Non-Hispanic Black females 37.19 + 0.81 <.001 �0.39 + 0.18
.029
Non-Hispanic White females 36.36 + 0.77 <.001 �0.21 + 0.10
.027
Stress management
Hispanic males 13.04 + 0.51 <.001 �0.06 + 0.10 .538
Non-Hispanic Black males 14.48 + 0.62 <.001 0.18 + 0.19 .352
Non-Hispanic White males 12.02 + 0.57 <.001 �0.08 + 0.10
.431
Hispanic females 14.22 + 0.50 <.001 0.01 + 0.07 .912
Non-Hispanic Black females 14.15 + 0.58 <.001 �0.06 + 0.14
.696
Non-Hispanic White females 14.12 + 0.55 <.001 �0.01 + 0.08
.870
Note. General linear mixed model for fixed race/ethnicity–

239. gender and year nested within race/ethnicity–gender effects
adjusted for fixed covariates for
subsidized lunches, two-parent households, and mother’s
education. Random effects were intercept, trajectory, and child
nested within cohort. SE ¼ standard
error.
Rew et al. 227
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grades (i.e., Grades 9–12). Males in all racial/ethnic groups
reported significantly more of these physical activity beha-
viors than their respective racial/ethnic females in each of
the four grades with the exception of NHW in Grade 9
(p ¼ .065). NHB males reported statistically significantly
more of these physical activity behaviors than Hispanic
males in Grade 9 and more than NHW in Grades 9 and 11.
The only statistically significant difference among females
by race/ethnicity was between Hispanic and NHW females
in Grade 9: NHW females reported engaging in significantly
more of these physical activity behaviors than Hispanic

240. females. Although not statistically significant, NHW females
engaged in more of these physical activity behaviors than eth-
nic minority females in Grades 9 and 10, but Hispanic females
engaged in these behaviors more than NHB or NHW in Grade
11 and NHB engaged in the greatest number of physical activ-
ity behaviors in Grade 12.
Differences in Safety Behaviors
Overall, NHBs reported the highest frequency of safety
health-promoting behaviors such as wearing a seatbelt or
refusing to ride with a driver who is drinking alcohol. At all
time points, Hispanic and NHW females reported higher
levels of these safety behaviors than Hispanic and NHW
males, respectively. Hispanic males scored lower than all
other males in all grades, but these differences were not
statistically significant. The NHB males engaged in signifi-
cantly more of these safety behaviors than Hispanic males
at all time points except Grade 10, and significantly more than
NHW males in Grade 11. There were no statistically signifi-

241. cant race/ethnicity differences in frequency of these safety
behaviors among females in any of the four grades.
Differences in Stress Management
There were statistically significant sex differences in stress
management health-promoting behaviors such as having
friends to talk to between Hispanic males and females and
between NHW males and females in each of the four grades.
Females engaged in significantly more of these stress man-
agement behaviors than males in each of the 4 years. There
were no statistically significant sex differences for NHB
participants.
The NHB males engaged in significantly more of these
stress management behaviors than NHW males in all grades;
they also engaged in statistically significantly more of these
behaviors than Hispanic males in Grades 11 and 12. There
were no statistically significant differences among females
in Grade 9 through Grade 12.
Hypothesis 1

242. The first hypothesis that racial and ethnic minority males
would exhibit fewer health-promoting behaviors than NHW
males and all females during high school (Grades 9–12) was
only partially supported. Nutrition behaviors of Hispanic
and NHB males were greater than those of NHW males in
all grades, except Grade 12 when NHW exhibited slightly
more of these behaviors than NHB and Hispanic males, but
these differences were not statistically significant. NHB
males exhibited the greatest frequency of physical activity
in all grades and, although not statistically significant, His-
panic males exhibited a greater frequency of physical activ-
ity than NHW males in all four grades. Similarly, NHB
males exhibited a greater frequency of safety behaviors and
stress management behaviors than NHW or Hispanic males
in all four grades.
Females consistently engaged in fewer physical activity
behaviors than males, which does not support the hypoth-
esis; however, NHW females engaged in more nutrition-

243. related behaviors than all ethnic minority males and females
across all four grades, which provides partial support for the
hypothesis.
Hypothesis 2
Hypothesis 2, that adolescents’ health-promoting behaviors
would decrease each year from Grade 9 through Grade 12,
was partially supported. Table 7 shows the growth curve or
trajectory for each health-promoting behavior over time.
All statistically significant trajectories are negative, which
means that the behaviors decreased over time. None of the
trajectories for stress management changed significantly
over time. The only statistically significant positive trajec-
tory was for non-Hispanic white females’ nutrition. This
change indicates that their eating behaviors were better
over time.
The trajectories for each health-promoting behavior
indicate particular changes by race and sex. For example,
the nutrition behaviors of Hispanic, NHB, and NHW males

244. all decreased over time. The change was statistically signif-
icant for the NHB males (p ¼ .046), but not for the Hispa-
nic males (p ¼ .066), nor for the NHW males (p ¼ .627).
Physical activity behaviors declined for all racial/ethnic
groups over time and all were statistically significant
except for the NHB females. Similarly, safety behaviors
declined for all racial/ethnic groups over time except for
NHB males whose frequency of engaging in safety beha-
viors increased over time, but the trajectory was not statis-
tically significant (p ¼ .430). Stress management behaviors
decreased over time in all groups except NHB males and
Hispanic females, but these changes were not statistically
significant. This means that participants continued to talk
with friends, family, teachers, and coaches about the stres-
sors in their lives with similar frequency in all four grades.
Discussion
The specific aims of this analysis were to compare the
health-promoting behaviors of adolescents by gender and
ethnicity, and explore how health-promoting behaviors of
these adolescents changed during the high school years.

245. 228 The Journal of School Nursing 31(3)
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Overall, the findings from this rural sample are similar to
other recent cross-sectional findings in national samples of
adolescents. For all race/ethnic groups, females engaged in
more safety behaviors than males 3 of the 4 years (i.e.,
Grades 9, 10, and 12). NHB females engaged in fewer of
these safety behaviors than males only in Grade 11. These
disparate findings may be related to timing of learning to
drive and having one’s own car or access to a family vehicle.
It could be that parents are more protective of female chil-
dren and give male and female children different messages
about safety. This interpretation warrants further study.
As other studies have shown, we found that males
engaged in more sports and exercise activities than females
over all 4 years of the study. This finding supports those of

246. the 2011 YRBS (CDC, 2012) and the National Health and
Nutrition Examination Survey (NHANES; Liu, Sun, Beets,
& Probst, 2013). The finding that NHW females reported
significantly more of these physical activity behaviors than
Hispanic females in Grade 9 supports previous findings that
suggest NHW females participate in higher levels of physi-
cal activity, including sports teams, than racial/ethnic minor-
ity females (Biddle, Whitehead, O’Donovan, & Nevill,
2005; CDC, 2012; Liu et al., 2013). These disparities may
be related to barriers to participation in sports commonly
faced by racial/ethnic minority females. These barriers
include lower SES (Biddle et al., 2005; Glennie & Stearns,
2012), the higher prevalence of overweight/obesity among
racial/ethnic minority females (Kimm et al., 2002), lack of
resources in the home/yard or neighborhood (Graham, Wall,
Larson, & Neumark-Sztainer, 2014), and cultural differ-
ences in perceptions of various physical activities. In Grade
11 however, unexpectedly, NHW females reported signifi-

247. cantly lower levels of physical activity behaviors than NHB
females and nearly significantly lower levels in Grade 12. It
could be that these females are driving or riding in cars more
than walking or biking. By Grade 11, many students are being
advised to take on more service-learning projects and other
volunteer activities to improve their chances for admission
to the college or university of their choice. These other extra-
curricular activities can reduce the available time for enga-
ging in physical activity (Spring, Grimm, & Dietz, 2008).
Analysis of data from the National Longitudinal Study of
Adolescent Health (Add Health) showed that extracurricular
activities were related to friendships, particularly among ado-
lescents in high school, when it was more difficult to be part
of a sports team (Schaefer, Simpkins, Vest, & Price, 2011).
The finding that engaging in physical activity declined
for both males and females from Grade 9 to Grade 12 is sim-
ilar to the findings in the national YRBS study of 2011
(CDC, 2012). The national data showed a higher prevalence

248. of physical activity among adolescents in Grade 9 than in
Grades 10, 11, and 12. These similar findings underscore the
importance of developing activities that keep adolescents,
particularly females, physically active throughout high
school. Further study of how the rural contexts influence
physical activity levels is needed to understand how to trans-
late promising physical activity interventions successfully to
rural adolescents.
The significant gender differences in nutrition health-
promotion behaviors for NHW only, with females scoring
higher than males all 4 years, was a new and somewhat sur-
prising finding, given that males reported higher levels of
fruit, vegetable, and milk intake on the 2011 YRBS (CDC,
2012). These findings, however, are similar to those of
Williams and Mummery (2012) who found that Australian
adolescents’ reports of healthy nutrition behaviors were
greater in girls than in boys. These findings also support
those of a systematic review by Rasmussen et al. (2006),

249. who found that female gender was a consistent predictor of
higher fruit and vegetable intake among children and adoles-
cents. Although the ‘‘thin ideal’’ that dominates U.S. youth
culture may contribute to eating disorders among females, it
may also lead to the adoption of healthier practices such as
eating more fruits and vegetables than junk foods that are high
in salt and sugar.
Hispanic and NHW females scored significantly higher
than males in their respective ethnic groups on the measure
of stress management. This finding is similar to that of G. S.
Wilson, Pritchard, and Revalee (2005) who found that
females used more coping strategies than males when deal-
ing with stressful experiences. There were no significant
gender differences among NHB participants. This is an
interesting finding that suggests cultural differences in cop-
ing as well as sex differences in coping within cultures. This
finding also has implications for developing gender- and
ethnic-specific interventions to assist adolescents in learning

250. adaptive coping mechanisms or stress management strate-
gies that contribute to health.
Limitations
This study has several limitations. Data were drawn from a
single geographic area in central Texas and, therefore, do not
represent all high school-age rural adolescents in the United
States. All of the data analyzed in this study were self-report
thus open to self-report bias. Owing to the mobile nature of
the populations of these rural communities, the declining
participation rates are also a limitation. Strengths, however,
include the power of the sample size, large ethnic minority
participation, and the longitudinal design. Despite the long-
itudinal design, this analysis does not reflect individual dif-
ferences over time, but cohort changes only. Nevertheless,
this study yields some important new findings about
health-promoting behaviors with implications for nursing
in general and school nursing in particular.
Implications for School Nurses

251. School nurses act to prevent adolescents from engaging in
health-risk behaviors such as using alcohol and drugs, using
tobacco products, and having unprotected sex, but we should
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also strive to enhance the health-promoting behaviors of
adolescents. The role of the school nurse in rural settings
is particularly crucial for promoting health behaviors among
adolescents, given the disparate access to health services
experienced by rural communities (Hartley, 2004), and
school nurse-led programs for rural adolescents in other
countries have shown promise (Barnes, Walsh, Courtney,
& Dowd, 2004). The evidence presented here suggests that
adolescents decrease their health-promoting behaviors dur-
ing the same developmental period that the literature shows
their health-risk behaviors simultaneously increase. School

252. nurses can play a critical role in the development of health
policies and practices in their school districts. School nurse
participation on the School Wellness Committee is an
important venue for helping shape health-related school pol-
icies that can have long-term benefits for students (National
Association of School Nurses, 2014).
The National Association of School Nurses (2013) holds the
position that professional school nurses are leaders within the
school environment and can be instrumental in setting health
policies for the school in addition to developing and providing
informational and educational programs. School nurses, there-
fore, can have a strong influence on setting policies about avail-
able foods and beverages within the school. They can also
influence policies about physical activity. School nurses are
encouraged to lead interdisciplinary teams within schools and
school districts who will advocate for policies and practices
that promote, rather than risk, the health of adolescents. Such
teams might include other interested professionals such as

253. school counselors, athletic directors and coaches, social work-
ers, and science teachers. School nurses who work in states that
have State School Nurse Consultants should also partner with
these consultants to advocate and influence the development of
health policies (Broussard & Howat, 2011).
As these findings show, racial/ethnic differences among
girls underscore the need to help racial/ethnic minority girls
find more opportunities to engage in sports and dance. These
findings suggest particular activities that could be increased
in the areas of safety, physical activity, nutrition, and stress
management. For example, interventions to promote physi-
cal activity could be organized for hours immediately after
school (Atkin, Gorely, Biddle, Cavill, & Foster, 2011).
School nurses are already knowledgeable about the signs
of distress in adolescents and may be in positions of leader-
ship where they can refer those who show maladaptive cop-
ing responses to the school counselor or other community
resources (Fitzsimons & Krause-Parello, 2009). Moreover,

254. many school nurses have opportunities to reach out to the
broader community by making presentations to parent–
teacher organization meetings, organizing health fairs for
parent nights, or creating short community/parent newsletter
items that promote positive strategies for stress management
and other health-promoting behaviors. These strategies have
been used to decrease health-risk behaviors such as smoking
and could also be implemented to enhance health-promoting
behaviors (Hamilton, O’Connell, & Cross, 2004). Previous
research shows that early adolescents, in particular, are
enthusiastic about learning more about how to live a healthy
lifestyle (L. F. Wilson, 2007). The challenge is to embrace
this enthusiasm throughout adolescence.
Conclusion
There are significant gender and ethnic differences in health-
promoting behaviors that may underlie the future health out-
comes of rural adolescents. Findings of this study could
influence the development of school-based interventions for

255. adolescents. Health-promoting behaviors were found to
decrease over time, which suggests that school nurses, teach-
ers, and parents should pay greater attention to sending mes-
sages to adolescents throughout their high school years
about the health benefits of nutrition, physical activity,
safety, and stress management.
Authors’ Note
The content is solely the responsibility of the authors and does
not
necessarily represent the official views of the National
Institutes of
Health.
Declaration of Conflicting Interests
The author(s) declared no potential conflicts of interest with
respect
to the research, authorship, and/or publication of this article.
Funding
The author(s) disclosed receipt of the following financial
support
for the research, authorship and/or publication of this article:

256. This
work was supported by grants from the National institutes of
Health
(National Institute of Child Health and Human Development
[R01
HD39554] and National Institute of Nursing Research [R01
NR0009856] to the first author.
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