The Journal of School Nursing2022, Vol. 38(6) 533–546© The Author(s) 2020Article reuse guidelines:sagepub.com/journals-permissionsDOI: 10.1177/1059840520965497journals.sagepub.com/home/jsn
Abstract
Adolescents often practice unhealthy behaviors to lose weight or keep from gaining weight. Centers for Disease Control and Prevention has conducted biennial Youth Risk Behavior Survey (YRBS) of various health risk behaviors since 1991 using U.S. representative samples of high school students and is therefore best for us to identify risk/preventive factors associated with unhealthy weight control behaviors (UWCB). We quantitatively assessed the association between various health risk behaviors with UWCB by gender using YRBS data. Due to the absence of UWCB items since 2015, we analyzed the latest (2013) data using binary multiple logistic regression. Among the 13,583 participants, 22.7% of girls and 10.1% of boys engaged in UWCB. Among girls and boys separately, the common significant factors included suicidal behaviors, alcohol drinking, misused prescription drug, feeling depressed, skipping breakfast, and attending physical education class. School nurses are suggested to have knowledge about the aforementioned risk factors and provide assessment, consultation, and education to help reduce UWCB.
Keywords
unhealthy weight control behavior, induced vomiting, fasting, laxatives, adolescent, health risk behavior, body image discrepancy, school nurse
Unhealthy weight control behaviors (UWCB) such as fasting, using diet pills/powders/liquids without medical advice, intentional vomiting, or taking laxatives can lead to eating disorders, anorexia nervosa, and bulimia nervosa (Daee et al., 2002; Gonsalves et al., 2014). Findings from studies revealed that UWCB was associated with other health-compromising behaviors including suicidal behavior (Johnson et al., 2016; Manzo et al., 2015), tobacco use (Sim et al., 2017; Vidot et al., 2016), alcohol use (Patte & Leatherdale, 2016; Thorlton et al., 2014; Vidot et al., 2016), drug use (Clayton et al., 2016; Jeffers & Benotsch, 2014; Jeffers et al., 2013; Striley et al., 2017; Vidot et al., 2016), and risky sexual behaviors (Eisenberg et al., 2005). Researchers of a longitudinal study found a significantly increasing trend of disordered eating behaviors from adolescence to young adulthood (Neumark-Sztainer et al., 2011). While overweight and obesity remained prevalent (30.4%) among adolescents and the prevalence rate had increased more than 6% since 2001 (Centers for Disease Control and Prevention [CDC], 2019), healthy and unhealthy weight management also became prevalent. Although Healthy People 2020 recommended interventions to prevent unhealthy weight gain and facilitate weight loss among obese people (Office of Disease Prevention and Health Promotion, 2019), UWCB is prevalent among U.S. adolescents (Loth et al., 2015; Neumark-Sztainer et al., 2011; Stephen et al., 2014). The latest statistics suggested that, in 2013, 13% of high school students did not eat for 24 or more hours; 5% had taken diet pills, powders, or liquids without a doctor’s advice; and 4% had induced vomiting or taken laxatives to lose weight or to keep from gaining (Kann et al., 2014).
Researchers have identified several risk factors of UWCB including gender, race/ethnicity, weight status, depression, and body image discrepancy (BID), that is, discrepancy between perceived and actual weight status (Liechty, 2010). In terms of gender difference, young females were around four times as likely as young males to engage in UWCB (Liechty & Lee, 2013; Stephen et al., 2014; Utter, Denny, Percival, et al., 2012). When comparisons were made by race/ethnicity, the strength of association between UWCB and race/ethnicity varied, but minority adolescents, especially girls, were more likely to engage in UWCB (Arcan et al., 2014; Bucchianeri et al., 2016; Rodgers, Peterson, et al., 2017; Rodgers, Watts, et al., 2017). While the authors of the four studies reported minority adolescents, especially girls, tend to have UWCB, it is not clear what health risk behaviors are associated with UWCB. In this study, we included gender and race/ethnicity in our multivariate analysis to control the effects from gender and race/ethnicity to identify other modifiable significant body weight–related risk factors and lifestyle-related risk factors. We hypothesized that such tendencies might relate to a girl’s elevated prevalence of depression and other unidentified health risk behaviors that can be modifiable by intervention and thus warranted further investigation.
When examining the relationship between weight status and UWCB, studies indicated that higher body mass index (BMI) predicts UWCB. For example, overweight adolescents had 3.6-fold likelihood to engage in UWCB when compared to those who were normal weight or underweight (Almenara et al., 2014; Cruz-Saez et al., 2015; de Santana et al., 2016; Liechty & Lee, 2013; Lim et al., 2017; Som & Mukhopadhyay, 2015). In regard to psychological aspects, those who exhibited depressive symptoms had around two times higher odds of engaging in UWCB when compared with their counterparts (Armstrong et al., 2014; Davila et al., 2014; Gonsalves et al., 2014; Kim et al., 2008; Liechty & Lee, 2013; Stephen et al., 2014; Utter, Denny, Robinson, et al., 2012). Overestimation of body weight perception was related to two to four times higher level of UWCB (Armstrong et al., 2014; Cho et al., 2012; Claro et al., 2014; Cruz-Saez et al., 2015; de Santana et al., 2016; Fan & Jin, 2015; Kim et al., 2008; Lee & Lee, 2016; Liechty, 2010). Yet, one study showed that BID was not a risk factor of UWCB (Liechty & Lee, 2013).
UWCB is also associated with some lifestyle behaviors such as watching TV and playing video games, dietary behaviors, and total hours of sleep. To be specific, adolescents whose screen time was greater than or equal to 2 hr a day exhibited 1.55 times higher odds, and those who adopted a restrictive diet had a 2.8 times odds of engaging in UWCB (de Santana et al., 2016). In addition, adolescents who consumed fried food every day and ate night-time snacks were reported as risk factors of UWCB (OR = 2.1 and 1.5, respectively; Liou et al., 2012). Short sleep duration was associated with UWCB (Wheaton et al., 2013). In contrast, eating breakfast every day (OR = 0.43) and sleeping for at least 8 hr per day (OR = ←0.86) act as protective factors against UWCB (Liou et al., 2012).
This study was guided by theories of adolescent risktaking behavior (Igra & Irwin, 1996). Since 1980s, researchers noticed the major morbidity and mortality during the second decade of life was primarily behavior related. Risk-taking behaviors include, but are not limited to, substance use, risky sexual behavior, reckless vehicle use, homicidal and suicidal behavior, eating disorders, and delinquency. Adolescent risk-taking behaviors possess serious threats because they often contribute to the health problems in the adulthood (U.S. Preventive Services Task Force, 1989). Because risk-taking behaviors are often developed out of similar psychological, environmental, and/or biological attributes, researchers suggested more inclusive interventions targeting groups of risk behaviors rather than multiple, more narrowly targeted interventions. Although some risk/protective behaviors have been identified separately, no study has included them all in one study of sufficiently large sample size. Given the consistently high prevalence (20.5%) of adolescent obesity in the United States (Ogden et al., 2015) and the consistently high proportion of adolescents engaging in UWCB (Kann et al., 2014), it has become a growing public health concern. Thus, recognition of the UWCB risk factors can help identify high-risk adolescents and subsequently provide proper education for healthy weight loss options. In addition, some inconsistent results in the literature can be further clarified. This study aimed to analyze the latest Youth Risk Behavior Survey (YRBS) data when the three UWCB items (Q69–Q71: fasting, nonprescribed diet pills/powders/liquids, and vomit or take laxatives) were asked (in 2013) to examine its risk factors and protective factors. Findings of the study can help provide discerning information for planning prevention and intervention programs.
The protocol of this study was submitted to the Institutional Review Board of the University of Toledo and was determined as exempt from human subject review. We conducted a secondary data analysis on data obtained from the National YRBS administered in 2013, the latest year when UWCB items were included. In order to represent the youth of the United States, YRBS used stratified random sampling and applied weighting factor to adjust for nonresponse and the oversampling of African American and Hispanic students. A detailed description of survey methodology is available elsewhere (CDC, 2013; Kann et al., 2014).
Variable examined in this study came from YRBS and was recoded according to YRBS methodology manual (CDC, 2013). UWCB was assessed by participants engaging in at least one of the following weight management behaviors: fasting; taking diet pills, powders, or liquids; or selfinduced vomit or take laxatives. Hence, UWCB was recoded into a dichotomous variable in this study.
Demographic variables including age, sex, grade, and race/ethnicity were self-reported. In consideration of sufficient sample sizes, the recoded race/ethnicity categories included non-Hispanic White, non-Hispanic Black, Hispanic/Latino, or all other races/ethnicities. For clarity, we provided Table 1 to display the original questions, their original response options, the recode conditions, and the recoded options.
BID was determined by self-reported weight/height and perceived weight status. Body weight status was identified by BMI percentile according to CDC’s definition: less than the 5th percentile being underweight, between 5th and 85th percentile being normal weight, and greater than 85th percentile being overweight/obese (CDC, 2014). Perceived weight was classified into perceived underweight, perceived normal weight, and perceived overweight. Those who perceived themselves at the same weight category as their actual weight status were labeled as no BID. The rest were further grouped into BID under (normal or overweight but perceived underweight or overweight perceived normal weight) and BID over (underweight or normal weight but perceived overweight or underweight perceived normal weight). Suicidal behavior was determined by three items and categorized into four levels: never thought about it, suicidal ideation, planned suicide, and attempted suicide.
Recent cigarette smoking was classified into nonsmokers if participants did not smoke in the past 30 days. The participants who smoked 20 or more days were classified as current frequent smokers (Kann et al., 2014). The remainder were classified as current smokers.
Alcohol use was classified as binge drinking if students drank five or more drinks in a row, casual drinking if drink at least once in the past 30 days, and abstinence for students who did not drink in the past 30 days. Marijuana use during the past 30 days was classified as nonuser, 1–19 times, 20–39 times, and 40þ times categories.
Adolescents who responded with at least one time taking prescription drugs without a doctor’s prescription were coded as ever misuse of prescription drugs. Others were coded as never misuse. Sexual behavior was coded into four levels: never had sexual intercourse, had sexual intercourse but not in the past 3 months, had sex with one partner, and had sex with multiple partners.
Dietary behaviors included fruit, vegetable, juice, milk, and soda consumptions and skipping breakfast in past 7 days. The variables such as ate three or more times of fruits and vegetable and drank three or more times of juice and milk during the past 7 days were defined in 2013 YRBS data user’s guide (CDC, 2014) and were used to determine whether adolescents met the dietary recommendations.
Adolescents who responded 8hr, 9hr, and 10 or more hours were recoded as having 8 or more hours of sleep while others were recoded as less than 8 hr. Physical education attendance was coded into 0 day, 1–2 days, and 3 or more days. TV and PC leisure time was coded into less than 1 hr per day, 1–2 hr per day, and 3 or more hours per day.
In this study, we hypothesized that race, weight loss intention, BID, weight status, depression, suicidal behavior, cigarette smoking, alcohol drinking, prescription drug misuse, marijuana use, risky sexual behavior, dietary behavior, skipping breakfast, sleep hours, attend physical education class, and TV and PC leisure time are statistically significant predictor of high school student’s UWCB.
We applied the weighting factor provided by the original YRBS data prior to all analyses and conducted descriptive statistics for all variables. To validate the quality of analysis, we compared the descriptive statistics with the official 2013 YRBS statistics on the Youth Online (CDC, 2020). To explore the relationships between UWCB and each of the selected risk behaviors individually, bivariate binary logistic regression was used to calculate the odds ratio and its 95% confidence interval. The selected risk behaviors included alcohol use, cigarette smoking, marijuana use, multiple sex partners, suicidal behavior, physical activity, and sedentary lifestyle, depression, weight loss intention, sleeping time, dietary behaviors, and misuse of prescription drugs. Stepwise multiple binary logistic regression using backward elimination procedures was conducted to determine the odds ratios for the main effects while controlling the other covariates. Due to apparent gender difference in UWCB, all analyses were conducted by gender. We used IBM SPSS Statistics Version 25.0 software to conduct the data analysis and to account for the complex sampling design and weighting of data.
Among the 13,583 participants, about 50% were female. Age distribution aggregated at 15 (24.1%), 16 (25.3%), and 17 (24.6%) years old. Grade levels were fairly evenly distributed with slightly more (27.3%) ninth graders and fewer (23.1%) 12th graders. Most students were White (55.6%), followed by Hispanic and multiple races with Hispanic origin (21.1%), African American (14.3%), and all other races/ethnicities (9%). Among females, Hispanic students had the highest prevalence rate (29.2%) of UWCB while African American students had the highest prevalence rate (13.3%) among males.
Table 2 has the table of UWCB and the selected health risk factors by sex. Females (22.7%) had a 2-fold prevalence rate than males (10.1%) to engage in UWCB. In general, UWCB became more prevalent while the strength or severity of most health risk behaviors was increased in both females and males. This was true in the associations of UWCB and the selected risk behaviors including suicidal behavior and marijuana, alcohol, and tobacco use with a dose–response relationship. In addition, the results revealed that UWCB and individual risk factors were highly correlated with an odds ratio up to 8.83 in male adolescents who ever attempted suicide when compared with those who never thought about suicide.
Female adolescents who were depressed reported a higher prevalence rate (37.7%) of UWCB compared to those females who were not depressed (13.2%). A higher prevalence rate of UWCB was also found among depressed male adolescents (21.5%). Students who intended to lose weight had higher prevalence rates of UWCB in both female (31.8%) and male (17.2%). Students with BID who over perceived their weight reported 34.1% and 16.8% of UWCB among females and males, respectively. In addition, overweight and obese students presented higher prevalence rates of UWCB among females (30.8%) and males (13.4%).
Having 8 or more hours of sleep acts as a protective factor against UWCB for both females (OR = 0.62) and males (OR = ←0.7). With respect to dietary behaviors, high proportions of females (37.0%) and males (20.1%) who skipped breakfast engaged in UWCB. Additionally, UWCB was prevalent among females (30.9%) and males (15.7%) who consumed the recommended amount of vegetables. Male students who watched TV, played video games, or used computer for 1–2 hr per day exhibited a low prevalence rate (7.7%) of UWCB. Males who attended physical education (PE) class 3 or more days per week showed a lower UWCB prevalence (8.9%) while a higher UWCB prevalence rate (23.9%) was observed among females who attended 3 or more days per week. In fact, females who attended more days of PE class tended to have UWCB while males were the opposite with a dose–response relationship.
Bivariate analyses revealed that UWCB was significantly associated with sexual behavior; suicidal behavior; alcohol, tobacco, and marijuana use; and prescription drug misuse. Among the selected risk behaviors, the highest UWCB prevalence rates were observed in both females (53.9%) and males (38.8%) who attempted suicide. Moreover, UWCB was observed among females (37.1%) and males (15.9%) who binge drank. High UWCB prevalence rates were found among female current smokers (42.8%) and current frequent smokers (34.7%) and male current (14.4%) and current frequent smokers (25.1%). High UWCB prevalence rates were observed among females (33.1% ~ 40.2%) and males (13.3% ~ 23.7%) who ever used marijuana. A dose–response relationship was identified between alcohol drinking and UWCB when the prevalence rates ranged from 12.4% to 37.1% among females and 6.1% to 15.9% among males. Females (41.4%) and males (19.6%) who misused prescription drugs also had higher prevalence rates of UWCB. Regarding the sexual behaviors, females (32.8%) and males (18.5%) who had multiple sex partners exhibited higher prevalence rates of UWCB.
Table 3 depicts the relationships between UWCB and the selected risk/protective factors by gender. The stepwise multiple binary logistic regression model revealed that, after controlling for covariates, the strongest predictor was weight loss intention among females and attempted suicide among males. Among females, when compared with those who did not consider losing weight, those who intended to lose weight exhibited significantly elevated risk to engage in UWCB (OR = ←5.58, 95% CI [4.37, 7.13]). On the other hand, male students who attempted suicide exhibited 3.54 times (95% CI [2.38, 5.26]) significantly higher risk of UWCB when comparing with those male students who never thought about suicide.
Among females, when compared with those who never thought about suicide, those who had suicidal ideation (OR = ←1.77, 95% CI [1.31, 2.39]), those who had planned suicide (OR = ←1.76, 95% CI [1.36, 2.78]), and those who attempted suicide (OR = ←2.82, 95% CI [2.20, 3.62]) exhibited significantly elevated risk to engage in UWCB. Compared with abstinence females, female casual drinkers tended to engage in UWCB with OR at 1.62 (95% CI [1.31, 2.00]), and female binge drinkers were at an even higher risk (OR = ←2.41, 95% CI [1.85, 3.13]). In addition, females who misused prescription drug exhibited a 1.8 times higher risk of UWCB (95% CI [1.47, 2.21]) than those who did not. Female overweight and obese students portrayed a 1.27 times higher risk (95% CI [1.05, 1.54]) when compared with females with normal weight. In comparison with those who perceived their body weight correctly, females with BID and over perceived their body weight tend to engage in UWCB (OR = 1.62, 95% CI [1.29, 2.02]). Moreover, females who felt depressed exhibited a 2.24 times (95% CI [1.88, 2.68]) higher risk of engaging in UWCB than those who did not. Regarding dietary behaviors, a 2.21 times (95% CI [1.79, 2.74]) higher risk existed when comparing females who skip breakfast with those who eat breakfast. Interestingly, females consumed vegetables three or more times per day demonstrated a 1.52 times (95% CI [1.22, 1.89]) higher risk compared with those who did not eat enough vegetables. In addition, females who attended PE class 3 or more days per week tended to engaged in UWCB (OR = ←1.42, 95% CI [1.13, 1.77]). Females who had sexual intercourse but not during the past 3 months exhibited an elevated risk of UWCB (OR = ←1.45, 95% CI [1.13, 1.86]) compared with abstinent females. The logistic regression excluded four significant variables in the bivariate analysis including race/ethnicity, marijuana use, smoking, and sleep 8þ hr per day. The final model explained 32% and 20% of the variances in predicting female’s and male’s engagement in UWCB, respectively.
Conversely, the logistic regression model revealed seven significant risk factors and a preventive factor for UWCB among males. After controlling for other health risk behaviors, males who planned suicide in the past 12 months exhibited a 1.79 times higher risk of engaging in UWCB (95% CI [1.23, 2.62]), and those who attempted suicide demonstrated a 3.54 times higher risk (95% CI [2.38, 5.26]) when compared with those who never think about suicide. Males who intended to lose weight exhibited a 3.26 times higher risk of UWCB compared with those males who did not (95% CI [2.58, 4.12]). In reference to abstinence, male binge drinkers showed an elevated of 1.67 times risk of UWCB (95% CI [1.17, 2.40]). Moreover, male current frequent smokers presented a 1.73 times higher risk of UWCB (95% CI [1.15, 2.61]). Male students who ever misused prescription drug tended to engage in UWCB by 1.37 times compared with those who never misused (95% CI [1.02, 1.86]). Males who skipped breakfast exhibited a 2.07 times higher risk of UWCB (95% CI [1.56, 2.73]). Although the vegetable consumption was included in the model, it did not reach the significant level. Male students with depression symptoms portrayed a 1.89 times higher risk engaging in UWCB compared with their counterparts (95% CI [1.43, 2.50]). Finally, PE class participation was presumed a protective factor against UWCB. Male students who participated 1 ~ 2 days and 3 or more days of PE class per week illustrated approximately 50% lower odds of engaging in UWCB (OR = ←0.55, 95% CI [0.36, 0.85]; OR = ←0.51, 95% CI [0.37, 0.70], respectively). Variables such as BID, weight status, sex partners, and sleep 8þ hr per day were excluded for the final model due to no statistical significance.
To indicate the degree of consistency or inconsistency, we compared some results with the literature. By doing so, we suggest further research and practical strategies to reduce UWCB. The unique contribution of this study is to quantitatively assess the odds of each significant risk factor and preventive factor for boys and girls separately when multiple variables are being controlled (using stepwise multiple logistic regression). No study in the literature was able to include this number of variables in one regression with a large nationally representative high school student sample.
This study uncovered the risk and protective factors of UWCB among adolescents. Our findings suggested UWCB is moderately more prevalent among females (twice as high as males), consistent from the existing studies (Liechty & Lee, 2013; Stephen et al., 2014; Utter, Denny, Percival, et al., 2012). In addition, the regression models revealed different risk/protective factors among males and females. Although not significant among overweight males, overweight females were more likely to engage in UWCB, which is consistent from the literature (Cruz-Saez et al., 2015; Som & Mukhopadhyay, 2015).
To prevent weight gain, people voluntarily engage in various healthy or unhealthy weight control practices. The significant association between skipping breakfast and UWCB is consistent from in the literature (Liou et al., 2012). We also found that females were more eager to lose weight, so they engaged in both UWCB and healthy weight control behaviors. In contrast, the more males attended PE class, the less UWCB was reported. Although not a variable in this study, health literacy can play a significant role in weight control behavior in a specific race and gender such as African American women (James et al., 2015). Further studies are suggested to investigate the weight control behaviors, knowledge dissemination, and obstacles to healthy weight control behaviors to provide insights for weight control program planning specifically when targeting adolescents.
In regard to psychological perspective, we verified depressive symptoms as a strong risk factor toward UWCB, same as exhibited in the literature (Armstrong et al., 2014; Davila et al., 2014; Gonsalves et al., 2014; Kim et al., 2008; Liechty & Lee, 2013; Stephen et al., 2014; Utter, Denny, Robinson, et al., 2012) in both males and females. In our regression model, females with BID and who perceived themselves at a heavier category tended to engage in UWCB, consistent with the literature (Cruz-Saez et al., 2015; Fan & Jin, 2015; Kim et al., 2008; Liechty, 2010). In contrast, researchers identified that lower body dissatisfaction, higher self-esteem, and lower depressive symptoms were influential factors on the adolescents who engage exclusively in healthy weight control behaviors such as healthy eating and physical activity for the purpose of weight management (Lampard et al., 2016).
Co-occurrence of UWCB and the selected risk behaviors were found in both males and females. However, our multivariate analyses suggested a different list of significant risk behavior associations among males and females. Among females, alcohol drinking, multiple sex partners, misuse of prescription drugs, and suicidal behaviors were associated with UWCB, while male’s UWCB exhibited significant association with alcohol drinking, smoking, misuse of prescription drugs, and suicidal behaviors. Our study confirmed that females with multiple sex partners tended to engage in UWCB (Eisenberg et al., 2005). Consistent with the finding from previous studies (Patte & Leatherdale, 2016; Sim et al., 2017; Thorlton et al., 2014; Vidot et al., 2016), alcohol drinking and cigarette smoking coexist with UWCB. Our study even discovered a dose–response relationship, that is, the more the substance was used, the higher the risk of engaging in UWCB would be. In regard to prescription drug misuse, studies have reported that nonmedical use of prescription stimulants for weight loss is common and were more likely to report engaging in other UWCB (Jeffers & Benotsch, 2014; Jeffers et al., 2013). Our study also confirmed that adolescents with UWCB were more likely to endorse prescription drug misuse, especially among females (Striley et al., 2017). Finally, the suicidal behavior is significantly associated with UWCB among youth in Finland, Korea, and the United States (Crow et al., 2008; Johnson et al., 2016; Kim et al., 2009; Laakso et al., 2013; Manzo et al., 2015). Further research is suggested to determine the underlying psychological and socio-environmental mechanisms behind the co-occurrence of these health risk behaviors for use in developing more effective interventions that address multiple risk behaviors.
Despite the need for further research, findings of this study demonstrated significant school nursing implications for prevention of health risk behaviors and intervention programming with adolescents in a number of important areas. First, UWCB is moderately prevalent. As a result, early identification and intervention are recommended to prevent the progression into disordered eating behaviors. School nurses are suggested to offer BMI screening with new student physical exam reports. Second, it is rational to believe a brief assessment of depressive symptoms, and BID can help identify adolescents at risk. By strengthening the efforts to such an at-risk population, a lower risk of UWCB can be projected. School nurses are suggested to offer weight control consultation opportunity either by phone, mail, or faceto-face, especially for the students who express weight loss intention, have BID, exhibit depressive symptoms, or planned/attempted for suicide. Third, a combination of encouraging physical activity and healthy diet can yield great benefits in healthy weight control behaviors and prevent UWCB. School nurses are encouraged to offer educational interventions such as a point-earning system to promote physical activity and healthy diet. Finally, adolescents who engaged in UWCB also possess a high risk of engaging in many different health-compromising behaviors (co-occurrence of health risk behaviors). As suggested by theories of adolescent risk-taking behavior (Igra & Irwin, 1996), school nurses and practitioners working in school, community, and clinical site to combat substance abuse, sexual risk behavior, and suicidal behavior are suggested to keep UWCB in their radar screen and include UWCB in intervention programs. Intervention programs with comprehensive strategies that cover multiple health risk behaviors are highly recommended.
Particularly in high schools, school nurses are suggested to relate UWCB with weight loss intention, suicide ideation/planning/attempt, excessive alcohol use, misuse of prescription drugs, and depression in their periodic screening and surveillance. Moreover, girls who think their body weight is more than their actual weight are at a higher risk. We recommend that a brief assessment of depressive symptoms and BID can help identify adolescents at risk early. When such biased body weight perception is discovered, school nurses are suggested to provide an educational intervention and/or a referral to a psychologist. Because attending physical education class is a protective factor for boys, school nurses are suggested to encourage males to attend physical education classes.
This study had several limitations. First, the data were obtained from a cross-sectional survey; therefore, no causal relationship can be identified through the analysis. In addition, the results do not represent adolescents who did not attend school. Because CDC does not collect UWCB data after 2013, even though our analysis represents the latest UWCB patterns, certain societal movements after 2013 (such as social media, Pokémon GO) could influence adolescent’s engagement in UWCB.
Chung-Bang Weng contributed to conception or design; contributed to acquisition, analysis, or interpretation; drafted the manuscript; critically revised the manuscript; gave final approval; and agreed to be accountable for all aspects of work ensuring integrity and accuracy. Jiunn-Jye Sheu contributed to acquisition, analysis, or interpretation; critically revised the manuscript; gave final approval; and agreed to be accountable for all aspects of work ensuring integrity and accuracy. Huey-Shys Chen contributed to acquisition, analysis, or interpretation; critically revised the manuscript; gave final approval; and agreed to be accountable for all aspects of work ensuring integrity and accuracy.
The author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.
The author(s) received no financial support for the research, authorship, and/or publication of this article.
Huey-ShysChen, PhD, MSN, MCHES, RN, FAAN https://orcid.org/0000-0002-4080-3911
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Chung-Bang Weng, PhD, MA, MSCS, is the director at Student Health Center, National Taipei University, New Taipei City, Taiwan (ROC).
Jiunn-Jye Sheu, PhD, MSPH, MCHES, is a professor at School of Population Health, University of Toledo, OH, USA.
Huey-Shys Chen, PhD, MSN, MCHES, RN, FAAN, is a professor and dean at College of Medical and Health Care, Hungkuang University, Taichung City, Taiwan (ROC).
1 Student Health Center, National Taipei University, New Taipei City, Taiwan
2 School of Population Health, The University of Toledo, OH, USA3 College of Medical and Health Care, Hungkuang University, Taichung City, Taiwan
Corresponding Author:Huey-Shys Chen, PhD, MSN, MCHES, RN, FAAN, College of Medical and Health Care, Hungkuang University, Taichung City 43302, Taiwan.Email: hueyshys@hk.edu.tw
