The Role of Physical Activity and Sedentary Behavior in Substance Use and Risky Sex Behaviors in Hispanic Adolescents

Abstract

The purpose of our study was to investigate the potential relationships in Hispanic adolescents (n = 575) between substance use and/or risky sexual behaviors and (a) physical activity (PA) and (b) sedentary time and (c) the moderating effect of gender. PA levels and sedentary behaviors were assessed using the PA Questionnaire for Adolescents, while risky behaviors were assessed using items similar to those used in the national epidemiological study, Monitoring the Future. We found significant, positive associations between PA and smoking, drug use, and risky sex measures. Similar positive associations existed between sedentary time and risky behaviors. However, after stratifying by gender, most of the relationships remained significant only for males. Our study is among the first to examine these relationships in Hispanic adolescents. Given the emphasis on increasing PA and decreasing sedentary behavior in adolescents, more efforts should be dedicated to understanding the effect of these lifestyle habits on risky behaviors.

Keywords

Hispanic/Latino/Latina health/nutrition/obesity sexual behavior pregnancy tobacco use/smoking sports substance use/alcohol and drug use

Introduction

The greatest impact on adolescent morbidity and mortality are risky behaviors, such as substance use and high-risk sexual behaviors (Institute of Medicine and National Research Council, 2009). Moreover, compared with non-Hispanic Whites, Hispanic youth report disproportionately higher risk behaviors, such as smoking cigarettes (43.2% vs. 42.9%), having ever had sexual intercourse (49.2% vs. 43.7%), drinking alcohol (37.5% vs. 36.3%), and using cocaine (9.5% vs. 4.8%; Centers for Disease Control and Prevention [CDC], 2013).

While risky behaviors in adolescents have remained high over time, healthy lifestyle behaviors, such as physical activity (PA), have declined due to economic growth, technological advancements, and social changes (Brownson, Boehmer, & Luke, 2005). The National Institutes of Health (2015) defines PA as “any body movement that works your muscles and requires more energy than resting” and includes anything from walking to playing (jumping rope, skipping) to sports participation. However, many times these terms are used interchangeably, thus creating a need to recognize the different ways in which PA (typically classified as non-sports participation) and sports participation are utilized in the literature, and how they often refer to different domains of youth activity levels.

Although several studies have examined the relationships between PA, and/or sports participation, and substance use and/or sexual risk behaviors, they have presented conflicting results depending on the type of activity and the variable being measured (Aaron et al., 1995; Escobedo, Marcus, Holtzman, & Giovino, 1993; Kulig, Brener, & McManus, 2003; Mays, Depadilla, Thompson, Kushner, & Windle, 2010; Pate, Heath, Dowda, & Trost, 1996; Pate, Trost, Levin, & Dowda, 2000; Rainey, McKeown, Sargent, & Valois, 1996; Tao et al., 2007). A recent systematic review found that greater sports participation was associated with increased alcohol use but was less clear about the relationship with illicit drug use (Kwan, Bobko, Faulkner, Donnelly, & Cairney, 2014). Some studies of high school students have suggested that sports and PA participation are associated with less smoking and marijuana use (Pate et al., 2000; Rainey et al., 1996), while others did not find a significant relationship (Aaron et al., 1995; Mahoney & Vest, 2012) in children/adolescents aged 12 to 18 years. In addition, in nationally representative studies of high school students, both PA and sports participation have been reported to have a significant negative association with sexual activity (Kulig et al., 2003; Pate et al., 1996). Moreover, some studies have examined the differences between sports participation and PA on risky behaviors (Kulig et al., 2003; Rainey et al., 1996; Terry-McElrath & O’Malley, 2011); however, the majority of studies conducted in adolescents have focused primarily on sports participation and substance use and sexual behaviors in adolescents, presenting limited data on the influence of other domains of PA on behavioral outcomes. Due to these equivocal findings, more research is necessary to better understand the relationship between different types of PA and risky behaviors in adolescents.

In addition to type of PA, gender may also play a significant role in influencing associations between activity levels and risky behaviors. It has been reported that boys engage in higher rates of risky behaviors (CDC, 2013). In addition, participation in PA may enhance their levels of risky sexual behaviors. It has been demonstrated that male athletes in seventh to ninth grades are significantly more likely than their non-athletic peers to initiate alcohol use (Aaron et al., 1995). These studies have also found inverse relationships between PA and the initiation of cigarette smoking, alcohol use initiation, and sexual risk for girls (Aaron et al., 1995; Miller, Barnes, Melnick, Sabo, & Farrell, 2002).

It is unsurprising that, with decreased levels of PA, sedentary behaviors have increased (Brownson et al., 2005). Sedentary behavior is defined as engaging in activities at a low energy expenditure and can include activities such as lying down, playing on the computer, and watching television (Pate, O’Neill, & Lobelo, 2008). Children and adolescents in the United States have reported to be sedentary an average of 6 to 8 hours a day (Tremblay et al., 2011). Sedentary adolescents are more likely to engage in other high-risk health behaviors than adolescents who participate in a variety of exercise and physical activities (Nelson & Gordon-Larsen, 2006).

In examining literature on PA, sedentary time, and risky behaviors, a majority of the studies have been conducted in populations in which Hispanic adolescents make up less than 10% of the study sample (Aaron et al., 1995; Mays et al., 2010) or in which Hispanics are not identified in the study sample (Escobedo et al., 1993). This raises the question of the generalizability of these results with Hispanic youth. Since Hispanic adolescents have been found to be at a higher risk of substance abuse and risky sexual behaviors than non-Hispanic White adolescents, it is especially essential to understand the influence of their lifestyle behaviors, particularly PA, on the engagement in risky behaviors. Therefore, the aims of this study were to investigate the (a) relationships between PA and substance use and/or risky sexual behavior in Hispanic adolescents, (b) relationships between sedentary time and substance use and/or risky sexual behavior in Hispanic adolescents, and (c) moderating effect of gender on the association between PA and substance use/sexual practices.

Methods

Participants in this study were part of a larger study examining the effectiveness of Familias Unidas, a family-based intervention that has been shown to reduce substance use and sex risk behaviors in Hispanic adolescents (Prado et al., 2012). The methods for this study were approved by the University of Miami’s Institutional Review Board and the Miami-Dade County Public School’s Research and Ethics Committee.

Recruitment and Study Participants

A total of 746 participants were enrolled in the larger, parent trial. Participants were recruited from 18 public middle schools in Miami-Dade County. Criteria for inclusion in the parent study required adolescents to (a) identify as Latino/Hispanic, (b) be enrolled in eighth grade at baseline, (c) live with an adult primary caregiver who was willing to participate, (d) live within the areas of the participating middle schools, and (e) plan to live in South Florida for the duration of the study. Participants were asked if they were sick in the past week or if they did anything to prevent them from doing normal physical activities. Those that indicated “yes” were excluded from the sample so that it was reduced to 575. No significant differences were found in the baseline demographics and risky behavior variables between the overall and the reduced samples.

Measures

The constructs used in this study included indicators of PA and risky behaviors. Data were collected by self-report surveys administered to youth at the beginning of the study through an audio computer-assisted self-administered interview that presented text on-screen while a pre-recorded voice reads the text to the respondent.

Physical activity

PA levels and sedentary behaviors were assessed using the PA Questionnaire for Adolescents (PAQ-A) that has been previously validated in adolescent populations (Kowalski, Crocker, & Donen, 2004). The PAQ-A is a self-report questionnaire designed for adolescents to elicit recall of their PA in the past 7 days. Survey items were divided into two main categories: (a) PA and (b) sedentary behavior. Overall, PA refers to all activity that was conducted throughout the day, organized or unorganized, both in- and out-of-school. Activities in other PA domains, such as household and transportation, are not included as a part of the PAQ-A. PA scores were based on 24 items. These questions probed how often adolescents engaged in a specific PA (e.g., aerobics, basketball, martial arts, gymnastics, and dance) in the past 7 days. Responses from these questions ranged from 1 (none), 2 (1-2 times per week), 3 (3-4 times per week), and 4 (5-6 times per week). The mean of these questions were then calculated to compute an overall PA score. Participants who indicated that they participated in a particular type of PA were then asked if this activity was organized or unorganized. Organized PA was defined as a coached sport or structured lesson, whereas unorganized PA would include specific PA that was not systematized. Responses were used to calculate a mean score for both organized and unorganized PA, respectively.

Sedentary time

Sedentary time was obtained from a series of questions that asked about time spent watching television, playing videogames, instant messaging or browsing the Internet, and talking on the phone. Participants were asked how many hours a day they participated in sedentary behaviors. Responses were categorized as 1 (less than 1 hour/day or nothing at all), 2 (at least 1 hour/day, but less than 2 hours/day), 3 (at least 2 hours/day, but less than 3 hours/day), 4 (at least 3 hours/day, but less than 4 hours/day), 5 (4 hours/day or more).

Substance use and sexual risk behaviors

The items that assessed substance use were similar to those used in the national epidemiological study, Monitoring the Future, which evaluated the national prevalence of alcohol and other drugs use (Johnston, O’Malley, Bachman, & Schulenberg, 2013). Substance use outcomes included history of alcohol use, smoking, and drug use. Sexual behavior was established using items that assessed lifetime sexual behavior, safe sex practices, and number of sexual partners. Lifetime sexual behavior was measured by the response to the survey item that asked, “Have you ever had vaginal, anal, or oral sex?” Having multiple partners was categorized by dichotomizing the response to the number of sexual partners as ≤1 and >1. Any sexual activity, vaginal, anal, or oral, was included. Early sex was established as sexual activity by age 15 years based on the definition used in existing literature (Dickson, Paul, Herbison, & Silva, 1998). Unprotected sex was measured by the response to the survey item that asked, “Have you ever had vaginal or anal sex without using a condom?”

Statistical Analysis

The first step in the analysis plan examined the relationship between PA variables, including overall PA, organized PA, unorganized PA, and sedentary time, and each risky behavior outcomes through the use of separate logistic regression models. We then estimated the same models with an interaction term to evaluate whether the relationships between the different types of PA and sedentary behavior with each of the risk behavior outcomes varied by gender. Because participants were recruited from 18 middle schools (24 cohorts), the non-independence of observations within schools would cause underestimations of the standard error of estimates. Thus, clustering effects at the school was accounted for using complex survey design in order to obtain accurate standard error estimates. More specifically, we used Mplus type = complex and specified cluster = school in the analysis.

Results

Descriptive analyses of demographics, PA variables, and risky behaviors are summarized for the overall sample and stratified by gender in Table 1. Forty-five percent of participants were female (n= 260). The mean age of the adolescents was 13.8 years (SD = 0.64) and slightly more than half (55%; n = 318) reported being U.S.-born. Participants were primarily low-income families, with 63% of household incomes <US$30,000 annually. Females reported significantly lower levels of PA and sexual risk behaviors.

Table 1.

Descriptive Analyses of Demographics.

	All	Males	Females
Demographics
Sample size	575	315 (55%)	260 (45%)*
Age	13.81 (0.64)	13.88 (0.72)	13.72 (0.52)**
Household income <US$30,000/year	362 (63%)	210 (67%)	152 (58%)*
U.S. born	318 (55%)	166 (53%)	152 (58%)
PA
Leisure time PA	1.53 (0.49)	1.59 (0.53)	1.45 (0.41)***
Organized PA	1.31 (0.46)	1.34 (0.51)	1.27 (0.39)*
Unorganized PA	1.32 (0.44)	1.37 (0.49)	1.25 (0.36)**
Sedentary time	2.67 (0.96)	2.65 (0.92)	2.70 (1.00)
Risky behavior
Lifetime alcohol use	76 (13%)	44 (14%)	32 (12%)
Lifetime smoking	33 (6%)	20 (6%)	13 (5%)
Lifetime drug use	28 (5%)	14 (4%)	14 (5%)
Lifetime sex	36 (6%)	26 (8%)	10 (4%)*
Unprotected sex (Lifetime)	23 (4%)	18 (6%)	5 (2%)*
Number of sexual partners (Lifetime)	23 (4%)	18 (6%)	5 (2%)*

Note. Data are displayed as mean (SD) for continuous variables and n (%) for categorical variables. PA = physical activity.

Significant gender differences indicated by *p < .05. **p < .01. ***p < .001.

PA, Substance Use, and Sexual Risk Behaviors

Our primary analysis (Table 2) indicated a significant positive relationship between overall PA and smoking (odds ration [OR] = 2.34, 95% confidence interval [95% CI] = [1.54, 3.57]), drug use (OR = 2.45, 95% CI = [1.38, 4.35]), lifetime sexual behavior (OR = 2.39, 95% CI = [1.58, 3.61]), unprotected sex (OR = 2.80, 95% CI = [1.88, 4.16]), and multiple partners (OR = 2.66, 95% CI = [1.76, 4.02]), suggesting that greater levels of PA are associated with increased risky behaviors. This relationship was also significant for both organized and unorganized PA in most of the substance use and sexual risk behaviors categories, except for organized PA and unprotected sex. The analyses also showed significant positive relationships between sedentary time and alcohol use (OR = 1.69, 95% CI = [1.35, 2.12]), smoking (OR = 1.51, 95% CI = [1.10, 2.06]), drug use (OR = 1.52, 95% CI = [1.06, 2.18]), lifetime sexual behavior (OR = 1.86, 95% CI = [1.38, 2.50]), and multiple partners (OR = 1.67, 95% CI = [1.18, 2.36]), suggesting that greater time spend on sedentary behaviors is associated with risky behaviors.

Table 2.

Association Between Leisure Time PA, Sedentary Behavior, and Adolescent Substance Use and Risky Sex Behaviors.

	Leisure time PA	Organized PA	Unorganized PA	Sedentary time
All
Alcohol use	1.33 [0.83, 2.15]	1.12 [0.59, 2.13]	1.44 [0.95, 2.20]	1.69 [1.35, 2.12]
Smoking	2.34 [1.54, 3.57] *	2.21 [1.41, 3.46] *	2.56 [1.56, 4.10] *	1.51 [1.10, 2.06]
Drug use	2.45 [1.38, 4.35] *	2.32 [1.38, 3.89]	2.96 [1.67, 5.28] *	1.52 [1.06, 2.18]
Sexual behavior	2.39 [1.58, 3.61]	2.04 [1.44, 2.90]	2.15 [1.37, 3.38]	1.86 [1.38, 2.50]
Unprotected sex	2.80 [1.88, 4.16] *	1.92 [0.96, 3.82]*	2.55 [1.19, 5.46]	1.16 [0.49, 2.72]
Multiple partners	2.66 [1.76, 4.02] *	2.08 [1.50, 2.88] *	2.49 [1.42, 4.36]	1.67 [1.18, 2.36]
Males
Alcohol use	1.67 [0.94, 2.95]	1.55 [0.79, 3.05]	1.56 [0.98, 2.48]	1.37 [1.06, 1.78]
Smoking	3.60 [1.20, 6.58]	3.26 [1.72, 6.15]	3.57 [1.98, 6.44]	1.55 [0.99, 2.44]
Drug use	4.75 [2.32, 9.71]	4.06 [2.32, 7.12]	5.41 [2.36, 12.43]	1.61 [0.91, 2.83]
Sexual behavior	2.81 [1.81, 4.53]	2.40 [1.47, 3.94]	2.40 [1.53, 3.77]	2.15 [1.44, 3.18]
Unprotected sex	3.22 [2.12, 4.92]	2.33 [1.15, 4.75]	2.49 [1.15, 5.42]	2.02 [0.63, 6.47]
Multiple partners	3.09 [2.12, 4.51]	2.46 [1.61, 3.75]	2.65 [1.54, 4.56]	1.90 [1.29, 2.80]
Females
Alcohol use	0.62 [0.12, 2.31]	0.19 [0.02, 1.68]	1.12 [0.41, 3.04]	2.91 [1.40, 3.49]
Smoking	0.19 [0.05, 0.77]	0.10 [0.001, 2.62]	0.43 [0.12, 1.71]	1.47 [0.63, 3.45]
Drug use	0.23 [0.05, 1.07]	0.16 [0.01, 4.57]	0.40 [0.07, 2.40]	1.44 [0.91, 2.28]
Sexual behavior	0.56 [0.07, 4.78]	0.43 [0.01, 13.00]	0.55 [0.04, 7.35]	1.53 [0.78, 3.00]
Unprotected sex	0.19 [0.01, 2.53]	0.001 [0.0001, 0.47]^a	1.01 [0.25, 4.16]	1.00 [0.35, 2.85]
Multiple partners	0.21 [0.02, 2.65]	0.001 [0.0001, 0.14]^a	1.06 [0.25, 4.51]	1.35 [0.56, 3.25]

Note. Odds ratio [95% confidence interval]. PA = physical activity.

Limited number of cases responded “yes” to these risk outcomes.

Interaction between predictor and gender was statistically significant at p < .05.

Bolded values indicate significant relationship between predictor and outcome.

We found that gender was a significant moderator of the relationship between PA and substance use and sexual risk behaviors. After stratifying by gender, significant relationships in males were observed between overall PA and smoking (OR = 3.60, 95% CI = [1.20, 6.58]), drug use (OR = 4.75, 95% CI = [2.32, 9.71]), sexual behavior (OR = 2.81, 95% CI = [1.81, 4.53]), unprotected sex (OR = 3.22, 95% CI = [2.12, 4.92]), and multiple partners (OR = 3.09, 95% CI = [2.12, 4.51]), suggesting that these relationships are only true for males. Similar relationships were seen with organized and unorganized PA in males. We found that sedentary time was also a risk factor in males for alcohol use (OR = 1.37, 95% CI = [1.06, 1.78]), sexual behavior (OR = 2.15, 95% CI = [1.44, 3.18]), and multiple partners (OR = 1.90, 95% CI = [1.29, 2.80]).

For females, overall PA was associated with a significant reduction in risk against smoking (OR = 0.19, 95% CI = [0.05, 0.77]), while organized PA was associated with a significant reduction in risk for engaging in unprotected sex (OR = 0.001, 95% CI = [0.0001, 0.47]) and having had multiple partners (OR = 0.001, 95% CI = [0.0001, 0.14]), suggesting that PA can protect females against some risky behaviors. No such associations were identified between unorganized PA and risky behaviors in females. The only significant risk factor that we identified for females with sedentary time was with alcohol use (OR = 2.91, 95% CI = [1.40, 3.49]), indicating that an increase in sedentary behavior is associated with greater alcohol use in girls.

Discussion

The primary goal of this study was to explore the relationship between PA and substance use and sexual risk behaviors in Hispanic adolescents. The results of this study identified significant associations between PA and a number of risky behaviors, including smoking, drug use, early sex, unprotected sex, and multiple partners. After stratifying by gender, we found that the majority of these relationships remained statistically significant only in males. We found similar associations between sedentary behavior and these risky behaviors.

Adolescents who reported higher levels of PA were more likely to engage in substance use and sexual risk behaviors, a finding that was consistent across participation in both organized and unorganized activities. Although some existing evidence has shown that certain risky behaviors in different races and ethnicities, such as smoking and drug use, decrease with increased sports participation (Crosnoe, 2002; Escobedo et al., 1993; Ewing, 1998; Mays et al., 2010; Pate et al., 1996), results have been largely inconsistent. In addition, while sports participation has been related to binge drinking in Chinese adolescents (Tao et al., 2007) and faster acceleration of alcohol use and alcohol-related problem behavior in a nationally representative sample of middle and high school students (Kwan et al., 2014; Mays et al., 2010), we found no significant relationships between levels of PA and alcohol use in our Hispanic adolescent sample. These differences may be attributed to the comparison between our entirely Hispanic sample and other studies that consisted of more nationally representative samples. One study found that strenuous exercise is associated with increased odds of sexual risk in boys across race/ethnicity and that Hispanic boys exceeded White boys in sexual risk (Miller et al., 2002). In addition, differences in our findings may be potentially attributed to the younger age group of our participants (12-14 years) compared with the participants in other studies, which ranged from 12 to 18 years of age.

Consistent with our results, existing literature has shown that the relationship between sports participation and risky behaviors varies depending on gender (Kwan et al., 2014). Greater participation in sports has been associated with lower substance use regardless of gender (Eitle, Turner, & Eitle, 2003; Kujala, Kaprio, & Rose, 2007; Pate et al., 1996; Terry-McElrath & O’Malley, 2011), while others agree with our findings that greater activity levels are associated with increased substance use in males, but not females (Crosnoe, 2002; Ewing, 1998). In addition, while previous research has shown that sports participation is associated with decreased smoking in both males and females across different racial/ethnic backgrounds (Diehl et al., 2012; Escobedo et al., 1993; Lisha & Sussman, 2010; Martens, Dams-O’Connor, & Beck, 2006; Mays et al., 2010), we found this to be true only in females. In fact, we found that males who reported greater PA were at an increased risk of smoking. Finally, our findings regarding PA and risky sexual behavior are consistent with previous studies that suggest that higher levels of PA are associated with increased sexual risk in males, but were protective against risky sexual behaviors in females (Miller et al., 2002). These gender differences may be explained by the fact that adolescents who participate in sports, particularly in school, are bonded to that institution, but by different mechanisms (Crosnoe, 2002). For male athletes, who are traditionally at the top of the social hierarchy, the bond is centered on status and many of their actions may be prompted by activities that can propel their status, including smoking and sex. However, girls are typically bonded by the motivation of long-term goals, making their involvement of risky behaviors less likely. These results may therefore suggest that promoting PA may be a mechanism by which to prevent risky sex in females, but emphasize a need for a targeted intervention for male athletes.

The results of our study suggest that higher levels of sedentary behavior may lead to increased smoking, alcohol and drug use, early sex, and multiple partners in our adolescent sample. This finding is consistent with previous literature suggesting that adolescents with sedentary lifestyles are more likely to smoke (Kujala et al., 2007; Pate et al., 1996; Sallis, Prochaska, & Taylor, 2000; Rodriguez & Audrain-McGovern, 2005), use alcohol (Miller et al., 2002), and illicit drugs (Korhonen, Kujala, Rose, & Kaprio, 2009; Nelson & Gordon-Larsen, 2006) when compared with their more active peers. After stratifying by gender, we found that the relationship between sedentary behavior and alcohol use remained significant in both males and females; however, the association between sedentary behavior and risky sexual behaviors was significant only in males. It is possible that sedentary time is significantly related to alcohol consumption across both boys and girls because drinking is viewed as a normative behavior typically associated with most sedentary, social gatherings (Crosnoe, 2002). The connection between sedentary and risky sexual behaviors, particularly in Hispanic males, may be a novel finding, as there is limited research on this topic. Such findings may be an important area of future exploration of this relationship, which may have important implications for the design of preventive interventions targeting sexual behaviors.

Several study strengths and limitations are worth noting. Our study is the first entirely Hispanic study to analyze the relationship between PA and adolescent substance use and sexual risk behaviors. Hispanics constitute the largest minority population in the United States (U.S. Census Bureau, 2012), necessitating more comprehensive research on their lifestyle choices. Previous studies focused on the association between sports participation and risky behaviors. Our study expands upon previous studies by including PA across domains, including both organized and unorganized. Also, we were able to examine the impact of sedentary activity on risky behaviors that has been overlooked in previous studies. However, our study is not without its limitations. First, this study used self-reported measures of PA, substance use, and sexual behavior. Adolescents may have under- or over-reported any of these behaviors. In addition, a limitation is how all studies use different categorizations of PA. Differences in our findings with previous work may be related to the way in which PA and sports participation are categorized across studies, suggesting the need for more precise measurement in the future. PA and sedentary time were measured over different time periods (PA was recorded as the frequency of activity in the last 7 days; sedentary time was recorded as the number of hours per day in the last week), which may limit comparability between these variables. Another limitation was the cross-sectional design which limits our ability to establish causality.

In summary, our findings indicate that there are associations between PA and sedentary behaviors and multiple substance use and sexual risk behaviors in our sample of Hispanic adolescents. Given the emphasis on increasing PA and decreasing sedentary behavior in adolescents, more attention should be dedicated to examining the impact of both of these activities independently on substance use and sexual risk behaviors. In addition, our study reaffirms previous findings that suggest that these associations are distinctly moderated by gender, where physically active males are at a greater risk of substance use and risky sexual behavior. Finally, should these findings be replicated in longitudinal designs, they can have important implications for the design of targeted drug abuse and sexual risk behavior preventive interventions.

Footnotes

Authors’ Note

The contents of this article are solely the responsibility of the authors and do 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: This study was supported by National Institute on Drug Abuse (NIDA) and National Institute on Alcohol Abuse and Alcoholism (NIAAA) funds (grants R01 DA025192 and 3R01 DA025192 S1) awarded to Guillermo Prado. The work done by Mark Stoutenberg was supported by Grant Number 1KL2TR000461, Miami Clinical and Translational Science Institute, from the National Center for Advancing Translational Sciences and the National Institute on Minority Health and Health Disparities.

Author Biographies

Cynthia Lebron is a doctoral student in Prevention Science at the University of Miami Miller School of Medicine Department of Public Health Sciences. She is interested in the socioeconomic correlates of physical activity and nutrition in children and adolescents.

Mark Stoutenberg is a research assistant professor in the Department of Public Health Sciences at the University of Miami. As an exercise physiologist, his research examines the influence of physical activity on physical and mental health, as well as chronic disease prevention, in diverse populations.

Mariel Janowsky is studying medicine and public health at the University of Miami Miller School of Medicine. She plans to pursue a combined residency in family medicine and psychiatry.

Lila Asfour is a doctoral student in Epidemiology at the University of Miami’s Department of Public Health Sciences. Her research interests include psycho-social aspects of disease progression, prevention science, and health disparities.

Shi Huang is a biostatistician III in the Department of Statistics at Vanderbilt University, Nashville, TN. His research interests are applying advanced statistical methods in prevention science and longitudinal clinical trials.

Guillermo Prado is miller professor of Public Health Sciences and the chief of the Division of Prevention Science and Community Health in the Department of Public Health Sciences at the University of Miami Miller School of Medicine. He is a prevention scientist with extensive experience in health disparities research, prevention intervention science, and Hispanic adolescent health.

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