Original Research
Gender and Ethnic Differences in Health-Promoting Behaviors of Rural Adolescents
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 jsn.sagepub.com
Lynn Rew, EdD, RN, AHN-BC, FAAN1, Kristopher L. Arheart, EdD2, Sharon D. Horner, PhD, RN, FAAN1, Sanna Thompson, PHD, MSW3, and Karen E. Johnson, PhD, RN1
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 physical 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 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 management (Groft, Hagen, Miller, Cooper, & Brown, 2005), physical 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 committed 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.
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 behaviors among Hispanic, non-Hispanic Black (NHB), and nonHispanic White (NHW) adolescents residing in three rural communities and (2) do health-promoting behaviors change
Purpose
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]
This article is a report of findings from a large longitudinal study of health-risk and health-promoting behaviors among
1
The University of Texas at Austin School of Nursing, Austin, TX, USA Department of Epidemiology and Public Health, The University of Miami, Miami, FL, USA 3 The University of Texas at Austin School of Social Work, Austin, TX, USA 2
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as adolescents matriculate through Grades 9–12? Our hypotheses were as follows 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 contribute 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 associated 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 contributes 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 contrast, 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 everyday 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 (Gottfredson & Hussong, 2011; Leeman, Hoff, Krishnan-Sarin, Patock-Peckham, & Potenza, 2014; Taliaferro, Muehlenkamp, Borowsky, McMorris, & Kugler, 2012; Thompson, Dewa, & Phare, 2012 ), we have much less evidence of those factors related to health-promoting behaviors. Previous studies 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 mentioned previously, describe a nationally representative sample 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 adolescents 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 developmental 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 predominantly 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 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 services, with this percentage being higher in rural counties where people of color are the majority (Probst, Moor, Glover, & Samuels, 2004). These disparities create a socialenvironmental 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
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a secondary analysis of rural adolescents ages 12 through 17 from the cross-sectional 2005 California Health Interview 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 adolescents 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 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 sample 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 collection point when they were in Grade 12 (68% retention over 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 consisted 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 investigator 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 support, were not included in the present analysis because they are conceptually different from health-promoting behaviors. 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, parents 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 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 survey 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 exhibit the fewest health-promoting behaviors, we used separate 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
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Table 1. Demographic Characteristics in Sample of Rural Adolescents in Grade 9 Through Grade 12. Grade Cohort Grade A B C D Grade A B C D Grade A B C D Grade A B C D
9
10
11
12
n
Age, M + SE
Female (%)
Hisp (%)
NHB (%)
NHW (%)
Both Parents (%)
Subsidized Lunch (%)
BSa (%)
814 205 177 254 176 825 119 294 218 194 818 213 210 214 181 707 170 211 193 133
14.7 + 0.02 15.0 + 0.05 14.9 + 0.03 14.5 + 0.03 14.4 + 0.04 15.5 + 0.02 16.2 + 0.04 15.5 + 0.03 15.3 + 0.03 15.2 + 0.04 16.3 + 0.02 16.7 + 0.04 16.3 + 0.04 16.1 + 0.04 16.1 + 0.04 17.2 + 0.02 17.5 + 0.0 17.1 + 0.03 17.0 + 0.04 17.0 + 0.04
56 58 58 56 54 57 68 55 54 55 58 62 61 55 55 61 67 67 59 53
47 47 44 48 48 48 50 47 46 49 45 43 40 47 51 48 47 43 49 53
13 13 9 15 16 13 12 11 16 14 14 15 13 15 20 12 14 10 14 12
40 40 47 37 36 39 38 12 38 37 41 42 47 38 19 40 39 47 37 35
59 54 66 56 63 60 58 62 56 64 60 55 61 59 66 62 58 62 61 69
57 59 59 52 58 57 59 57 55 58 59 62 62 54 59 60 61 64 55 61
15 13 13 17 16 16 14 14 19 16 15 13 12 17 18 14 13 11 18 14
34 38 36 35 28 32 37 32 33 29 31 32 30 30 31 32 35 30 33 29
31 32 29 31 31 31 30 32 31 30 33 36 33 34 28 32 32 33 31 30
12 7 11 12 15 12 6 12 12 16 12 7 13 13 15 12 7 14 12 19
8 10 11 5 10 9 13 10 5 9 9 12 12 6 8 10 13 12 6 8
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 Grade 9 Range by cohort Grade 10 Range by cohort Grade 11 Range by cohort Grade 12 Range by cohort
n 814 176–254 825 119–294 818 181–214 707 133–211
Nutrition
Physical Activity
Safety
Stress Management
M + SE (a)
M + SE (a)
M + SE (a)
M + SE (a)
25.1 + 24.1 + 25.0 + 24.3 + 25.1 + 24.9 + 24.8 + 23.4 +
0.3 (0.89) 0.6 - 25.9 + 0.7 0.3 (0.89) 0.8–25.3 + 0.6 0.3 (0.90) 0.6–25.1 + 0.6 0.3 (0.91) 0.7–25.7 + 0.8
15.6 15.4 15.2 14.2 14.5 14.0 13.6 12.6
+ 0.2 (0.89) + 0.4–16.2 + + 0.2 (0.90) + 0.6–15.8 + + 0.2 (0.90) + 0.5–15.1 + + 0.2 (0.89) + 0.5–14.3 +
0.5 0.4 0.5 0.6
36.7 + 36.2 + 36.0 + 35.2 + 36.3 + 35.5 + 35.9 + 34.9 +
0.2 (0.76) 0.4–37.1 + 0.2 (0.80) 0.7–36.3 + 0.2 (0.79) 0.4–36.7 + 0.2 (0.77) 0.5–36.7 +
14.3 + 0.2 (0.65) 0.4 14.0 + 0.2–14.5 + 0.4 14.3 + 0.2 (0.66) 0.4 14.0 + 0.3–14.5 + 0.3 14.3 + 0.2 (0.62) 0.4 14.1 + 0.3–14.9 + 0.3 14.2 + 0.2 (0.68) 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.
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’ healthpromoting behaviors will decrease each year from Grade 9 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 person nested within cohort. Statistical Analysis Software (SAS) 9.3 (SAS Institute, Inc., 2013) was used for all analyses. Statistical 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 summarized 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
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Hisp NHB NHW
Hisp NHB NHW
Hisp NHB NHW
Hisp NHB NHW
9
10
11
12
Female (M + SE) 25.30 + 0.62 24.68 + 1.19 26.55 + 0.67
25.22 + 0.62 24.54 + 1.15 27.57 + 0.67
25.29 + 0.61 23.85 + 1.10 26.83 + 0.64
25.51 + 0.74 22.88 + 1.29 27.41 + 0.78
Male (M + SE)
25.20 + 0.73 25.05 + 1.23 24.20 + 0.75
25.07 + 0.71 24.23 + 1.29 23.30 + 0.75
24.95 + 0.73 23.84 + 1.24 23.17 + 0.73
23.86 + 0.88 21.92 + 1.50 23.87 + 0.90 .081 .605 .001
.705 .993
Gender and Ethnic Differences in Health-Promoting Behaviors of Rural Adolescents
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 jsn.sagepub.com
Lynn Rew, EdD, RN, AHN-BC, FAAN1, Kristopher L. Arheart, EdD2, Sharon D. Horner, PhD, RN, FAAN1, Sanna Thompson, PHD, MSW3, and Karen E. Johnson, PhD, RN1
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 physical 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 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 management (Groft, Hagen, Miller, Cooper, & Brown, 2005), physical 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 committed 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.
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 behaviors among Hispanic, non-Hispanic Black (NHB), and nonHispanic White (NHW) adolescents residing in three rural communities and (2) do health-promoting behaviors change
Purpose
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]
This article is a report of findings from a large longitudinal study of health-risk and health-promoting behaviors among
1
The University of Texas at Austin School of Nursing, Austin, TX, USA Department of Epidemiology and Public Health, The University of Miami, Miami, FL, USA 3 The University of Texas at Austin School of Social Work, Austin, TX, USA 2
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as adolescents matriculate through Grades 9–12? Our hypotheses were as follows 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 contribute 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 associated 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 contributes 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 contrast, 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 everyday 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 (Gottfredson & Hussong, 2011; Leeman, Hoff, Krishnan-Sarin, Patock-Peckham, & Potenza, 2014; Taliaferro, Muehlenkamp, Borowsky, McMorris, & Kugler, 2012; Thompson, Dewa, & Phare, 2012 ), we have much less evidence of those factors related to health-promoting behaviors. Previous studies 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 mentioned previously, describe a nationally representative sample 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 adolescents 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 developmental 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 predominantly 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 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 services, with this percentage being higher in rural counties where people of color are the majority (Probst, Moor, Glover, & Samuels, 2004). These disparities create a socialenvironmental 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
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a secondary analysis of rural adolescents ages 12 through 17 from the cross-sectional 2005 California Health Interview 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 adolescents 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 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 sample 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 collection point when they were in Grade 12 (68% retention over 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 consisted 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 investigator 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 support, were not included in the present analysis because they are conceptually different from health-promoting behaviors. 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, parents 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 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 survey 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 exhibit the fewest health-promoting behaviors, we used separate 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
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The Journal of School Nursing 31(3)
Table 1. Demographic Characteristics in Sample of Rural Adolescents in Grade 9 Through Grade 12. Grade Cohort Grade A B C D Grade A B C D Grade A B C D Grade A B C D
9
10
11
12
n
Age, M + SE
Female (%)
Hisp (%)
NHB (%)
NHW (%)
Both Parents (%)
Subsidized Lunch (%)
BSa (%)
814 205 177 254 176 825 119 294 218 194 818 213 210 214 181 707 170 211 193 133
14.7 + 0.02 15.0 + 0.05 14.9 + 0.03 14.5 + 0.03 14.4 + 0.04 15.5 + 0.02 16.2 + 0.04 15.5 + 0.03 15.3 + 0.03 15.2 + 0.04 16.3 + 0.02 16.7 + 0.04 16.3 + 0.04 16.1 + 0.04 16.1 + 0.04 17.2 + 0.02 17.5 + 0.0 17.1 + 0.03 17.0 + 0.04 17.0 + 0.04
56 58 58 56 54 57 68 55 54 55 58 62 61 55 55 61 67 67 59 53
47 47 44 48 48 48 50 47 46 49 45 43 40 47 51 48 47 43 49 53
13 13 9 15 16 13 12 11 16 14 14 15 13 15 20 12 14 10 14 12
40 40 47 37 36 39 38 12 38 37 41 42 47 38 19 40 39 47 37 35
59 54 66 56 63 60 58 62 56 64 60 55 61 59 66 62 58 62 61 69
57 59 59 52 58 57 59 57 55 58 59 62 62 54 59 60 61 64 55 61
15 13 13 17 16 16 14 14 19 16 15 13 12 17 18 14 13 11 18 14
34 38 36 35 28 32 37 32 33 29 31 32 30 30 31 32 35 30 33 29
31 32 29 31 31 31 30 32 31 30 33 36 33 34 28 32 32 33 31 30
12 7 11 12 15 12 6 12 12 16 12 7 13 13 15 12 7 14 12 19
8 10 11 5 10 9 13 10 5 9 9 12 12 6 8 10 13 12 6 8
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 Grade 9 Range by cohort Grade 10 Range by cohort Grade 11 Range by cohort Grade 12 Range by cohort
n 814 176–254 825 119–294 818 181–214 707 133–211
Nutrition
Physical Activity
Safety
Stress Management
M + SE (a)
M + SE (a)
M + SE (a)
M + SE (a)
25.1 + 24.1 + 25.0 + 24.3 + 25.1 + 24.9 + 24.8 + 23.4 +
0.3 (0.89) 0.6 - 25.9 + 0.7 0.3 (0.89) 0.8–25.3 + 0.6 0.3 (0.90) 0.6–25.1 + 0.6 0.3 (0.91) 0.7–25.7 + 0.8
15.6 15.4 15.2 14.2 14.5 14.0 13.6 12.6
+ 0.2 (0.89) + 0.4–16.2 + + 0.2 (0.90) + 0.6–15.8 + + 0.2 (0.90) + 0.5–15.1 + + 0.2 (0.89) + 0.5–14.3 +
0.5 0.4 0.5 0.6
36.7 + 36.2 + 36.0 + 35.2 + 36.3 + 35.5 + 35.9 + 34.9 +
0.2 (0.76) 0.4–37.1 + 0.2 (0.80) 0.7–36.3 + 0.2 (0.79) 0.4–36.7 + 0.2 (0.77) 0.5–36.7 +
14.3 + 0.2 (0.65) 0.4 14.0 + 0.2–14.5 + 0.4 14.3 + 0.2 (0.66) 0.4 14.0 + 0.3–14.5 + 0.3 14.3 + 0.2 (0.62) 0.4 14.1 + 0.3–14.9 + 0.3 14.2 + 0.2 (0.68) 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.
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’ healthpromoting behaviors will decrease each year from Grade 9 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 person nested within cohort. Statistical Analysis Software (SAS) 9.3 (SAS Institute, Inc., 2013) was used for all analyses. Statistical 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 summarized 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
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Hisp NHB NHW
Hisp NHB NHW
Hisp NHB NHW
Hisp NHB NHW
9
10
11
12
Female (M + SE) 25.30 + 0.62 24.68 + 1.19 26.55 + 0.67
25.22 + 0.62 24.54 + 1.15 27.57 + 0.67
25.29 + 0.61 23.85 + 1.10 26.83 + 0.64
25.51 + 0.74 22.88 + 1.29 27.41 + 0.78
Male (M + SE)
25.20 + 0.73 25.05 + 1.23 24.20 + 0.75
25.07 + 0.71 24.23 + 1.29 23.30 + 0.75
24.95 + 0.73 23.84 + 1.24 23.17 + 0.73
23.86 + 0.88 21.92 + 1.50 23.87 + 0.90 .081 .605 .001
.705 .993
