6512 Discussion 3Amblerchick
RE S E A R C H AR T I C L E
Weight Status Misperception as Related to Selected Health Risk Behaviors Among Middle School Students BRIAN C. MARTIN, PhD, MBAa WILLIAM T. DALTON, III PhDb STACEY L. WILLIAMS, PhDc DEBORAH L. SLAWSON, PhD, RD, LDNd MICHAEL S. DUNN, PhD, MPHe REBECCA JOHNS-WOMMACK, EdDf
ABSTRACT BACKGROUND: Weight misperception has been documented among children although the impact on health risk behaviors is less understood, particularly among middle school students. The goals of this study were to describe sociodemographic differences in actual and perceived weight, correspondence between actual and perceived weight, and weight-related health risk behaviors, as well as to examine weight misperception and interactions with sociodemographic variables in explaining weight-related health risk behaviors.
METHODS: Participants were recruited at 11 public school districts participating in the Tennessee Coordinated School Health (CSH) pilot program. A total of 10,273 middle school students completed the Centers for Disease Control and Prevention’s Youth Risk Behavior Survey administered by teachers in the school setting.
RESULTS: Findings revealed sociodemographic differences in actual and perceived weight as well as weight misperception. Although overestimating one’s weight was significantly related to greater likelihood of weight-related health risk behaviors, significant interactions showed this relationship to be especially pronounced in females. Additional distinctions based on sociodemographic variables are indicated.
CONCLUSIONS: Results highlight the importance of screening for health risk behaviors including weight misperception among middle school students. The CSH program offers an opportunity to understand health risk behaviors among students while also informing and evaluating methods for intervention.
Keywords: health risk behavior; middle school students; obesity; weight misperception.
Citation: Martin BC, Dalton WT III, Williams SL, Slawson DL, Dunn MS, Johns-Wommack R. Weight status misperception as related to selected health risk behaviors among middle school students. J Sch Health. 2014; 84: 116-123.
Received on March 7, 2012 Accepted on November 26, 2012
The United States has seen an increase in theprevalence of overweight and obesity over the past 30 years that currently remains high in both adult and child/adolescent popultions.1-3 The prevalence for overweight and obesity among the pediatric populations increased from approximately 15% in the 1980s to more than 30% by 2004,3,4 and 31.8% were overweight or obese in 2009 to 2010.2
The economic consequences of an obese society are staggering. Medical cost estimates for obesity in the adult population were as high as $78.5 billion in 1998, increased $40 billion through 2006, and were estimated to be $147 billion in 2008.5 Annual medical costs for obese children were $2.9 billion per year more
aAssociate Professor, MPH Coordinator, ([email protected]), Department of Health Services Management and Policy, East Tennessee State University, P.O. Box 70264, Johnson City, TN 37614. bAssistant Professor, ([email protected]), Department of Psychology, East Tennessee State University, P.O. Box 70649, Johnson City, TN 37614. cAssistant Professor, ([email protected]), Department of Psychology, East Tennessee State University, P.O. Box 70649, Johnson City, TN 37614.
than costs for normal and underweight children due to increased prescription drugs, emergency department utilization, and outpatient expenditures in 2002 to 2005. These costs were in addition to obesity- associated hospitalization costs, approximately $237.6 million in 2005.6
The majority of states with high obesity rates are in the south. From 2008 to 2010, Tennessee (TN) was one of 12 states with adult obesity rates above 30%, and one of 9 states with childhood obesity rates greater than 20%.7 In 2007, almost 21% of TN children aged 10 to 17 years were obese (#6 national ranking) and slightly less than 30% of children aged 6 to 17 years engaged in physical activity on
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a daily basis. Rural areas have been associated with higher rates of pediatric obesity8 and poor health behaviors.9
In addition to the measurable prevalence of overweight and obese youth, there is a significant segment of the population who maintain a perception of being overweight or obese. Western cultural pressure to be thin is believed to contribute to nonoverweight adolescents perceiving themselves as overweight, thereby leading to engagement in weight change behaviors.10,11 This perception is more related to body dissatisfaction than to actual body size, but puts social pressure on adolescents, particularly girls, to maintain an ‘‘ideal’’ body weight.11-13 Therefore, girls are more likely to compare their body type to the culturally accepted body image of being thin, which is typically below average for weight. One study found weight status perception predicted weight loss intent more than actual body fat.14
Whether overweight/obese status is actual or perceived, a large percentage of adolescents engage in weight loss behaviors. For instance, approximately 36% of normal weight high school students report engaging in weight-loss activities.15 Attempts to lose weight do not always result in healthier diets or recommended participation in physical activity.16 In fact, some dieting behaviors are potentially deadly (eg, laxatives, diet pills, fasting, vomiting), and are markers for depressed mood and eating disorders.12 In addition, research has found body dissatisfaction correlates with risk factors for eating disorders17 as well as psychosocial disorders.18
Efforts have begun to identify the frequency and effect of weight misperception. Boys and girls contrast in the manner they overestimate or underestimate their weight, with approximately 60% of adolescent boys accurately perceiving their weight compared to 50% of adolescent girls in 1 study18 and one-third of boys misrepresenting their weight versus one-quarter of girls in another study.19 Other studies have found as many as 1 in 3 overweight adolescents underreport their weight4 and 16% of normal weight high school students perceive themselves as overweight.15 A recent study assessing high school students suggested accurate perception may be important for overweight and obese adolescents to engage in weight control practices.20
dAssistant Professor, ([email protected]), Department of Community and Behavioral Health, East Tennessee State University, P.O. Box 70674, Johnson City, TN 37614. eAssociate Professor, ([email protected]), Department of Health Promotion, Coastal Carolina University, P.O. Box 261954, Conway, SC 29528. fExecutiveDirector, ([email protected]), TennesseeDepartment of Education, Officeof CoordinatedSchool Health, 710James RobertsonParkway, AndrewJohnson Tower, 6th Floor, Nashville, TN 37243.
Address correspondence to: Brian C. Martin, Associate Professor, MPH Coordinator, ([email protected]), Department of Health Services Management and Policy, East Tennessee State University, P.O. Box 70264, Johnson City, TN 37614.
The authors would like to thank Amal Khoury, PhD, WilliamS. Frye, BS, and Brittany Williams, MPH, for assistance with preparing the manuscript. Everyone who contributed significantly to this work has been listed.
Limited research has examined the relationship between weight misperception and health risk behav- iors, especially among middle school students. One study examined a sample of overweight adolescents and found those with accurate weight perception reported greater engagement in healthy weight man- agement strategies such as trying to maintain or lose weight, exercise, and/or eat less for weight control.4
When adolescents participate in risky health behav- iors such as unhealthy eating habits and insufficient physical activity, they may be putting themselves at risk for immediate and lifelong medical, mental, and social problems.2,11,12 Further understanding of the link between weight misperception and weight-related health behaviors may inform prevention/intervention efforts.
The goals of this study were (1) to examine sociodemographic differences in actual weight, per- ceived weight, and the correspondence between actual and perceived weight; (2) to examine the sociodemographic differences in weight-related health risk behaviors; and (3) to examine the predictive value of weight misperception and the interaction of weight misperception with sociodemographic fac- tors in explaining health risk behavior in a sample of middle school students participating in the Coordi- nated School Health (CSH) pilot program in TN. We hypothesized greater weight misperception would be found in girls as compared to boys and those chil- dren who misperceived their weight, especially girls and those misperceiving themselves as overweight or obese, would be more likely to engage in health risk behaviors.
The Centers for Disease Control and Prevention’s (CDC) Youth Risk Behavior Survey (YRBS) was used in this study. The YRBS is designed to determine health risk behaviors of middle school students21 and measures demographics, height and weight, uninten- tional injury, tobacco use, drug/alcohol use, sexual risk taking, weight control, and physical activity.
Participants All 11,046 middle school students (6th to 8th grade,
approximately 12 to 14 years) attending 11 public
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school districts in TN were invited to take part in the YRBS. The schools were selected based on their participation in a CSH pilot program in TN. The 11 school districts represented diversity throughout TN—5 districts were located in west TN, 3 districts were located in middle TN, and 3 districts were located in east TN. All students in the 11 selected schools districts were eligible to participate.
Procedure Data collection took place during April and May of
2008 at participating schools. Prior to administering the questionnaire, a consent process comprised of passive parental consent with oversight by each school district’s CSH Coordinator and school administrator was implemented by each school.
Teachers familiar with the administration protocol were responsible for administering the survey to their students during class. These teachers collected the completed questionnaires and mailed them directly to a third-party data management company whose personnel electronically scanned the survey forms and created a data set without student identifiers. This data set was then returned to researchers for analysis. The response rate was 93%, based on the number of students who did not complete the survey due to not having parental permission, refusing to participate, or being absent on the day the survey was administered.
Demographics. Information collected about respondents included sex, region, age, grade level, and race. Region was categorized as less or more rural based on the county of the school categorized using the United States Depart- ment of Agriculture Economic Research Service Rural-urban Continuum Codes (RUUC) (http:// www.ers.usda.gov/Briefing/Rurality/RuralUrbCon/), with 1 to 3 representative of ‘‘less rural’’ and above 3 indicating ‘‘more rural.’’ Dummy variables were created for the 3 grade levels and for racial/ethnic categories of white, black, Hispanic, and Other (comprised of Asian, American Indian, and Pacific Islander).
Self-reported weight. Self-reported weight was determined using self-reported height and weight. Body mass index (BMI; kg/m2) was calculated using a SAS® macro provided by the CDC that took into account sex, age in months, weight in kilograms, and height in centimeters. This application used sex- and age-specific 2000 CDC growth charts22
to assign participants to underweight (sex-specific BMI-for-age < 5th percentile), healthy weight (sex- specific BMI-for-age 5th to <85th percentile), and overweight or obese (sex-specific BMI-for-age ≥ 85th
percentile) categories. We refer to self-reported weight as actual weight.
Perceived weight. Perceived weight was determined using a self-reported item which asked respondents to self-identify whether they were very underweight, slightly underweight, about the right weight, slightly overweight, and very overweight. The response categories were collapsed from 5 to 3 categories prior to analysis. Very overweight and very underweight were collapsed within overweight and underweight, respectively. This was due to the fact that very overweight and very underweight participants had low responses, less than 5% and 2%, respectively. Previous research has similarly collapsed weight perception categories.19
Weight misperception. Weight misperception was assessed by determining the correspondence between actual and perceived weight status. Respondents were categorized as having an ‘‘adequate or correct’’ view of their weight if their perceived status matched with their actual weight. They were categorized as ‘‘underestimating’’ or ‘‘overestimating’’ their weight if they perceived their weight to be lower or greater than their actual weight, respectively. Such categorization of weight misperception has been used in prior research.18,19
Weight-related health risk behaviors. Weight- related health risk behaviors were assessed using 6 items from the YRBS. Five items used a dichotomous response scale of yes or no and one item used a spe- cific response option that was further dichotomized based on the Expert Committee’s recommendations regarding television viewing.23
Data Analysis Descriptive analyses were first conducted on the
main study variables of actual and perceived weight status (underweight, normal, and overweight) and the correspondence between actual and perceived status (underestimate, adequate, an overestimate). Chi-square analyses were conducted to determine dif- ferences in these variables by demographic categories of sex, region, grade, and race. Similarly, chi-square tests determined sociodemographic differences in the reporting of a variety of health risk behaviors. Next, logistic regression analyses were conducted to deter- mine the predictive value of weight misperception and the interaction of misperception with sociode- mographic variables (sex, region, grade, and race) in explaining health risk behaviors. All regression analyses were hierarchical, and controlled for sociode- mographics of sex, region, grade, and racial/ethnic categories in the first regression step. Main effects were added to the second step of the regression, followed by the respective interaction terms in the third step. The adequate actual/perceived weight correspondence
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Table 1. Actual Weight, Perceived Weight, and Weight Misperception by Sociodemographics
Sex Region Grade
Boys Girls χ2 Rural Non-Rural χ2 6th 7th 8th χ2
Actual Weight Underweight 3.1% (161) 3.6% (183) 1.78 2.9% (131) 3.7% (200) 5.19* 3.4% (113) 3.6% (123) 2.9% (92) 3.51 Normal 57.8% (2991) 67.1% (3422) 93.27*** 61.4% (2811) 62.8% (3417) 2.19 62.4% (2065) 61.8% (2102) 62.4% (1998) .36 Overweight 39.0% (2019) 29.3% (1497) 107.41*** 35.8% (1639) 33.5% (1824) 5.59* 34.2% (1130) 34.6% (1175) 34.7% (1112) .26 Perceived Weight Underweight 16.2% (817) 16.5% (801) .14 16.5% (750) 16.3% (874) .04 17.7% (571) 16.9% (568) 14.3% (455) 21.89*** Normal 53.9% (2712) 56.2% (2728) 5.57* 55.6% (2528) 54.5% (2916) 1.07 56.4% (1825) 54.4% (1829) 54.4% (1729) 13.11** Overweight 29.9% (1505) 27.3% (1322) 8.46* 28.0% (1272) 29.1% (1558) 1.67 25.9% (839) 28.7% (966) 31.2% (992) 23.36*** Weight Misperception Underestimate 36.8% (1851) 33.3% (1614) 13.28*** 36.1% (1638) 34.2% (1827) 3.77 37.2% (1202) 34.4% (1174) 32.7% (1039) 15.30** Adequate view 43.5% (2189) 45.2% (2192) 2.90 44.2% (2009) 44.4% (2372) .03 43.7% (1413) 44.5% (1495) 45.2 (1436) 9.41* Overestimate 19.7% (994) 21.5% (1045) 4.87* 19.7% (895) 21.4% (1144) 4.37* 19.2% (620) 20.6% (694) 22.1% (701) 12.49**
White Black Hispanic Other χ2
Actual Weight Underweight 3.3% (272) 4.1% (30) 4.0% (17) 1.9% (8) 4.70 Normal 63.1% (5144) 60.4% (437) 58.3% (250) 54.2% (230) 17.97*** Overweight 33.6% (2738) 35.5% (257) 37.8% (162) 43.9% (186) 21.82*** Perceived Weight Underweight 16.2% (1310) 20.4% (146) 11.2% (47) 19.8% (83) 20.31*** Normal 54.3% (4382) 57.8% (413) 60.9% (255) 53.2% (223) 10.05* Overweight 29.4% (2375) 21.7% (155) 27.9% (117) 27.0% (113) 19.96*** Weight Misperception Underestimate 34.3% (2765) 40.6% (289) 33.3% (139) 41.0% (170) 18.77*** Adequate view 44.2% (3561) 43.2% (307) 46.7% (195) 42.7% (177) 1.71 Overestimate 21.5% (1736) 16.2% (115) 20.1% (84) 16.4% (68) 16.85**
∗∗∗p < .001; **p < .01; *p < .05.
category was used as the reference group. Significant interactions were decomposed by conducting simple regression analyses stratified by respective sociodemo- graphic category.
Participants consisted of 10,273 students; 50.3% male, 82.5% white, 8.1% black, 5.1% Hispanic, and 4.4% other racial/ethnic groups. Students were distributed relatively equally across grades, with 33.4% in the 6th grade, 34.3% in the 7th grade, and 32.3% in the 8th grade.
Results of sociodemographic comparisons for actual weight, perceived weight, and correspondence between actual and perceived are presented in Table 1, and significant findings are discussed here. Consider- ing the correspondence between actual and perceived weight status, girls were more likely to overesti- mate their weight status (21.5%) than boys (19.7%), whereas boys were more likely to underestimate their weight status (36.8%) than girls (33.28%). Those clas- sified as less rural were more likely to overestimate their weight (21.4% versus 19.7%). Participants in the 6th grade were most likely to underestimate their weight (37.2%), and as participants increased in grade
level they were more likely to have an adequate view of or to overestimate their weight. Whites were most likely (21.5%), and blacks least likely (16.2%), to overestimate their weight when comparing actual and perceived weight status. Results of sociodemographic comparisons for health risk behaviors are presented in Table 2.
Results of regression analyses testing the predictive value of weight misperception and the interaction of misperception with gender in explaining health risk behaviors are presented in Table 3. Results of main effects indicated that regardless of specific health risk behavior, those who overestimated their weight were more likely, compared to those who adequately per- ceived their weight, to perform one or more health risk behaviors. Individuals overestimating weight were approximately 2 to 3 times as likely to perform the health risk behaviors of exercising to lose weight (EXP(B) = 3.0), eating fewer calories (EXP(B) = 2.9), fasting (EXP(B) = 1.9), taking diet pills (EXP(B) = 2.0), and taking laxatives (EXP(B) = 2.1). Furthermore, those who underestimated their weight were less likely, compared to those who adequately perceived their weight, to exercise to lose weight (EXP(B) = .548) and eat fewer calories (EXP(B) = .602). Results of mod- erated regression analyses testing sociodemographic
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Table 2. Health Risk Behaviors by Sociodemographics
Sex % (N) Region % (N) Grade % (N)
Boys Girls χ2 Rural Less Rural χ2 6th 7th 8th χ2
Exercised to Lose Weight 75.0 (3792) 71.6 (3469) 14.89*** 73.8 (3353) 73.0 (3915) .87 71.2 (2311) 73.5 (2477) 75.6 (2396) 16.49** Ate Fewer Calories 53.8 (2717) 48.0 (2325) 33.33*** 51.5 (2337) 50.5 (2711) .88 47.7 (1546) 51.6 (1739) 53.6 (1701) 23.76*** Fasted 20.8 (1053) 16.4 (794) 31.41*** 19.6 (891) 17.9 (959) 5.09* 13.9 (450) 19.9 (671) 22.1 (699) 89.81*** Took Diet Pills 7.2 (363) 5.6 (272) 9.86** 6.5 (294) 6.3 (341) .08 4.0 (130) 6.4 (217) 8.6 (275) 82.11*** Took Laxatives/ Vomited 8.0 (402) 6.4 (308) 9.86** 7.6 (341) 6.9 (369) 1.56 4.6 (148) 7.8 (262) 9.1 (288) 82.76*** Watched TV 43.5 (2027) 39.0 (1766) 19.23*** 39.7 (1653) 42.6 (2143) 8.12** 43.5 (1295) 42.1 (1324) 38.1 (1127) 20.17***
Race % (N)
White Black Hispanic Other χ2
Exercised to Lose Weight 74.0 (5895) 68.7 (530) 73.0 (352) 68.0 (282) 16.88**** Ate Fewer Calories 51.5 (4096) 45.8 (353) 49.5 (241) 47.2 (196) 11.52** Fasted 18.2 (1451) 21.6 (165) 19.0 (92) 21.4 (90) 7.31 Took Diet Pills 6.1 (489) 6.9 (53) 7.0 (34) 9.5 (40) 8.16* Took Laxatives/Vomited 6.8 (539) 8.6 (65) 7.8 (37) 10.3 (43) 10.24* Watched TV 39.1 (2892) 62.0 (445) 47.9 (209) 41.5 (156) 149.08***
***p < .001, **p < .01, *p < .05. Note: Five items used a dichotomous response scale of yes or no 1. ‘‘Have you ever exercised to lose weight or to keep from gaining weight?’’ 2. ‘‘Have you ever eaten less food, fewer calories, or foods low in fat to lose weight or to keep from gaining weight?’’ 3. ‘‘Have you ever gone without eating for 24 hours or more (also called fasting) to lose weight or to keep from gaining weight?’’ 4. ‘‘Have you ever taken any diet pills, powders, or liquids without a doctor’s advice to lose weight or to keep from gaining weight? (Do not include meal replacement products such as Slim Fast)’’ 5. ‘‘Have you ever vomited or taken laxatives to lose weight or to keep from gaining weight?’’ The other remaining item asked about television viewing ‘‘On an average school day, how many hours do you watch TV? (I do not watch TV on an average school day, Less than 1 hour per day, 1 hour per day, 2 hours per day, 3 hours per day, 4 hours per day, 5 or more hours per day). This item was dichotomized so that ‘yes’ indicated 3 or more hours of television on an average school day and ‘no’ indicated less than 3 hours on an average school day.’’
interactions revealed significant interactions between gender and overestimating weight in predicting health risk behaviors. A decomposition analysis using simple regression indicated females who overestimated their weight were significantly more likely than males to perform all of the health risk behaviors except for watching television (TV). Still, the relations between overestimating weight and health risk were significant for both boys and girls. By contrast, the one signifi- cant interaction for underestimating weight revealed boys who underestimate their weight are less likely to exercise to lose weight than girls. Limited significant interactions were found for the remaining sociodemo- graphic moderators.
This study found approximately 55% of both girls and boys to misperceive their weight status. Approximately 35% of the sample underestimated their weight whereas 20% overestimated their weight. Previous studies have found inconsistent results; for example, Yan et al19 found approximately 33% of boys and 25% of girls to misperceive their weight, whereas Bogt et al18 found approximately 40% of boys and 50% of girls to misperceive their weight status. We found middle school girls were more likely
to overestimate their weight, and boys were more likely to underestimate their weight. These findings are consistent with literature reporting greater pressure to be thinner among girls, which may explain their overestimation of weight.19,24,25
It is well documented in the literature that certain groups of adolescents are disproportionately affected by overweight and obesity.2,7,8,10,16 Our findings support these studies, indicating whites were more likely to be of normal weight and Hispanics were more likely to be overweight. Students attending school in more rural areas were more likely to be overweight than those in less rural areas. In addition, our results show small increases in overweight status with increases in grade level.
Racial differences among adolescents have also been observed in the area of weight misperception. Hispanic and African American adolescents are considerably more likely than white adolescents to misperceive their actual weight.4,26,27 Our findings show that white middle school students were most likely to overestimate their weight; black students were most likely to underestimate their weight, and Hispanics were most likely to accurately perceive their weight.
In contrast to previous studies documenting greater weight loss attempts among girls,19 boys were more likely than girls to participate in all health risk
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Table 3. Weight Misperception Predicting Health Risk Behaviors
Exercised to Lose Weight Ate Fewer Calories Fasted Took Diet Pills
B (SE) EXP (B) B (SE) EXP (B) B (SE) EXP (B) B (SE) EXP (B)
Model 2 Overestimate 1.099(.083)** 3.000 1.061(.060)*** 2.888 .666(.066)*** 1.947 .701 (.102)*** 2.016 Underestimate −.601 (.051)** .548 −.508 (.048)*** .602 −.046 (.064) .955 −.007 (.105) .993 Sex −.281(.051)*** .755 −.324 (.045)*** .724 -.329 (.056)*** .720 −.241 (.090)** .786
Model 3 Overestimate × Gender .825 (.167)** 2.281 .701 (.121)*** 2.015 .829 (.133)*** 2.292 .612 (.206)** 1.845 Underestimate × Sex .336 (.102)** 1.399 .167 (.096) 1.182 .215 (.129) 1.240 -.185 (.215) .831
Took Laxatives or Vomited Watched TV
B (SE) EXP (B) B (SE) EXP (B)
Model 2 Overestimate .721(.098)* 2.056 .134 (.058) 1.144 Underestimate .071 (.098) 1.073 −.036 (.050) .965 Sex −.215 (.085)* .807 −.147(.046)*** .864
Model 3 Overestimate × Gender .542 (.197)** 1.294 .004 (.116) 1.004 Underestimate × Sex −.137 (.201) .872 .129 (.100) 1.138
All sociodemographics were controlled for in Model 1 of the regressions. ***p < .001; **p < .01; *p < .05.
behaviors. Additionally, 8th graders were more likely to participate in these behaviors (except for watching TV) than students in the 6th and 7th grades, and students from more rural schools were more likely to fast and watch TV when compared to those from less rural schools. These findings, coupled with the finding that students attending school in less rural areas were more likely to overestimate their weight, may directly and indirectly support research documenting poorer health behaviors among rural populations.9 However, one recent study27 suggested youth in rural Appalachia may have a greater acceptance of higher body weight and another study15 of normal weight adolescents found no differences in overweight misperception across geographic regions. Clearly, additional research is needed to understand regional influences.
We found those who overestimated their weight were more likely to engage in all health risk behaviors, and those who underestimated their weight were less likely to exercise or eat fewer calories. Furthermore, we found significant interactions between sex and overestimating weight in predicting health risk behaviors. The relationship between overestimating weight and health risk behaviors was significant for both sexes, with girls who overestimated their weight being more likely to engage in all health risk behaviors except watching TV. In general, our findings build on those of another study5 examining this relationship in overweight and obese youth. Those authors found misperception of overweight to be associated with less healthy behavior.
We also tested whether sociodemographic charac- teristics other than sex moderated the relation between
weight misperception and health risk behaviors. Over- estimating weight was associated with a higher like- lihood of rural students eating fewer calories, of 7th- and 8th-grade students fasting, and students whose race was ‘‘other’’ of avoiding eating fewer calories and exercising. Blacks also do not eat fewer calories when they underestimate weight. There is a need for future research to further examine these sociode- mographic factors and whether they play a role in the link between weight misperception and health risk.
Limitations Results should be interpreted in light of some
limitations. First, we were unable to discern the extent to which some of the weight-related health risk behaviors may be unhealthy. Our findings suggest overestimation of weight is related to greater engagement in health risk behaviors, some of which could be moderate in nature. However, that individuals are more likely to perform these behaviors when they overestimate their weight leads us to think that therein exists the risk. In other words, the performance of the behavior is deemed less essential given weight is being overestimated inaccurately. Second, consistent with previous studies, our height and weight data were collected via student self-report. Adolescents may not report their weight accurately.28,29 However, this method has been generally accepted for large-scale studies.30,31 Finally, this study is based on a sample of convenience from Tennessee; results may or may not generalize to other schools and other locations.
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Conclusions Our study expands the literature base on weight
misperception by including a large sample of mid- dle school students and examining the role of weight misperception as related to weight manage- ment behaviors32 among students of varying weight categories. In addition to sex, grade, and ethnicity, we examined region by way of rurality as it has been cited as an area in need of additional research, especially among middle school students.33-35 Overall, the findings suggest weight misperception, specifically overestimation among girls, may indicate participation in a number of health risk behaviors. While previous studies with high school students document greater engagement in weight control behaviors among girls,15
our findings call attention to the need to screen for health risk behaviors including weight misperception among both girls and boys. Future research could focus on effective ways to implement these practices in pri- mary care and other settings. The CSH program is an example of one program that offers both an oppor- tunity to better understand health behaviors among students while also informing and evaluating methods for addressing these behaviors.
IMPLICATIONS FOR SCHOOL HEALTH
Our study highlights the need to screen for unhealthy weight loss behaviors among middle school students, which can be coordinated by school health professionals. Moreover, results show a need to incorporate the concept of perceived weight versus actual weight when educating students about healthy lifestyles. This should enhance efforts to promote healthy weight management among overweight and underweight youth.
Human Subjects Approval Statement This study was deemed exempt by the Institutional
Review Board at East Tennessee State University.
1. Flegal KM, Carroll MD, Kit BK, Ogden CL. Prevalence of obesity and trends in the distribution of body mass index among US adults, 1999-2010. JAMA. 2012;307(5):491-497.
2. Ogden CL, Carroll MD, Kit BK, Flegal KM. Prevalence of obesity and trends in body mass index among US children and adolescents, 1999-2010. JAMA. 2012;307(5):483-490.
3. Centers for Disease Control and Prevention. (2010). U.S. obesity trends: Trends by state 1985-2009. Available at: http://www.cdc.gov/obesity/data/trends.html. Accessed May 15, 2012.
4. Edwards N, Pettingell S, Borowsky I. Where perception meets reality: self-perception of weight in overweight adolescents. Pediatrics. 2010;125(3):e452-e458.
5. Finkelstein EA, Trogdon JG, Cohen JW, Dietz W. Annual medical spending attributable to obesity: payer- and service- specific estimates. Health Aff . 2009;29(5):w822-w831.
6. Trasande L, Chatterjee S. The impact of obesity on health service utilization and costs in childhood. Obesity. 2009 Sep;17(9):1749-54. Erratum in Obesity. 2009;17(7):1473.
7. Trust for America’s Health & Robert Wood Johnson Foun- dation. (XXXX). F as in fat: how obesity threatens Amer- ica’s future. Available at: http://healthyamericans.org/assets/ files/TFAH2011FasInFat10.pdf. Accessed May 15, 2012.
8. Lutfiyya MN, Lipsky MS, Wisdom-Behounek J, Inpanbutr- Martinkus M. Is rural residency a risk factor for overweight and obesity for U.S. children? Obesity. 2007;15(9):2348-2356.
9. Jones CA, Parker TS, Ahearn M, Mishra AK, Variyam JN. (2009). Health status and health care access of farm and rural populations. United States Department of Agriculture. Eco- nomic Research Service. Bulletin Number 57, 1-72. Available at: http://www.ers.usda.gov/Publications/EIB57/. Accessed May 15, 2012.
10. Wang Y, Liang H, Chen X. Measured body mass index, body weight perception, dissatisfaction and control practices in urban, low-income African American adolescents. BMC Public Health. 2009;9:183.
11. Ojala K, Vereecken C, Valimaa R, et al. Attempts to lose weight among overweight and non-overweight adolescents: a cross- national survey. Int J Behav Nutr Phys Act. 2007;4:50.
12. Zaborkskis A, Petronyte G, Sumskas L, Kuzman M, Iannottie RJ. Body image and weight control among adolescents in Lithuania, Croatia, and the United States in the context of global obesity. Croat Med J. 2008;49(2):233-242.
13. Zenzen W, Kridli S. Integrative review of school-based childhood obesity prevention programs. J Pediatr Health Care. 2009;23(4):242-258.
14. Duncan JS, Duncan EK, Schofield G. Associations between weight perceptions, weight control and body fatness in a multiethnic sample of adolescent girls. Public Health Nutr. 2001;14(1):93-100.
15. Talamayan KS, Springer AE, Kelder SH, Gorospe EC, Joye KA. Prevalence of overweight misperception and weight control behaviors among normal weight adolescents in the United States. ScientificWorldJournal. 2006;6:365-373.
16. Wang Y, Beydoun MA. The obesity epidemic in the United States gender, age, socioeconomic, racial/ethnic, and geographic characteristics: a system review and meta-regression analysis. Epidemiol Rev. 2007;29:6-28.
17. Cattarin J, Thompson JK. A three-year longitudinal study of body image, eating disturbance, and general psychological functioning in adolescent females. Eat Disord. 1994;2(2):114- 125.
18. ter Bogt T, Dorsselaer S, Monshouwer K, Verdurmen J, Engels R, Vollebergh W. Body mass index and body weight perception as risk factors for internalizing and externalizing problem behavior among adolescents. J Adolesc Health. 2006;39(1):27-34.
19. Yan A, Guangyu Z, Wang M, Stoesen C, Harris M. Weight perception and weight and control practice in a multiethnic sample of US adolescents. South Med J. 2009;102(4):354-360.
20. Brener ND, Eaton DK, Lowry RL, McManus T. The association between weight perception and BMI among high school students. Obes Res. 2004;12(11):1866-1874.
21. Centers for Disease Control and Prevention. Youth risk behavior surveillance - United States, Surveillance Summaries, 2005. MMWR Morb Mortal Wkly Rep. 2006;55(SS-5):1-112.
22. Kuczmarski RJ, Ogden CL, Guo SS, et al. 2000 CDC growth charts for the United States: methods and development. National Center for Health Statistics. Vital Health Stat. 2002;11(246):1-190.
23. Barlow S. Expert committee recommendations regarding the prevention, assessment, and treatment of child and adolescent overweight and obesity: summary report. Pediatrics. 2007;120(suppl 4):S164.
24. Strauss RS. Self-reported weight status and dieting in a cross- sectional sample of young adolescents: National Health and
122 • Journal of School Health • February 2014, Vol. 84, No. 2 • © 2014, American School Health Association
Nutrition Examination Survey III. Arch Pediatr Adolesc Med. 1999;153(7):741-747.
25. Gustafson-Larson AM, Terry RD. Weight-related behaviors and concerns of fourth-grade children. J Am Diet Assoc. 1992;92(7):818-822.
26. Standley R, Sullivan V, Wardle J. Self-perceived weight in adolescents: over-estimation or under-estimation? Body Image. 2009;6(1):56-59.
27. Williams KJ, Taylor CA, Wolf KN, Lawson RF, Crespo R. Cultural perceptions of healthy weight in rural Appalachian youth. Rural Remote Health. 2008;8(2):932. Available at: http://www.rrh.org.au/articles/showarticlenew.asp?ArticleID =932. Accessed May 15, 2012.
28. Sherry B, Jefferds ME, Grummer-Strawn LM. Accuracy of adolescent self-report of height and weight in assessing overweight status: a literature review. Arch Pediatr Adolesc Med. 2007;161(12):1154-1161.
29. Shannon B, Smiciklas-Wright H, Wang MQ. Inaccuracies in self-reported weights and heights of a sample of sixth-grade children. J Am Diet Assoc. 1991;91(6):675-678.
30. Elgar FJ, Roberts C, Tudor-Smith C, Moore L. Validity of self- reported height and weight and predictors of bias in adolescents. J Adolesc Health. 2005;37(5):371-375.
31. Spencer EA, Appleby PN, Davey GK, Key TJ. Validity of self- reported height and weight in 4808 EPIC-Oxford participants. Public Health Nutr. 2002;5(4):561-565.
32. Taliaferro LA, Rienzo BA, Donovan KA. Relationships between youth sport participation and selected health risk behaviors from 1999 to 2007. J Sch Health. 2010;80(8):399-410.
33. Yost J, Miller-Krainovich B, Budin W, Norman R. Assessing weight perception accuracy to promote weight loss among US female adolescents: a secondary analysis. BMC Public Health. 2010;10:465.
34. Jones L, Fries E, Danish S. Gender and ethnic differences in body image and opposite sex figure preferences of rural adolescents. Body Image. 2007;4(1):103-108.
35. Stockton MB, Lanctot JQ, McClanahan BS, et al. Self- perception and body image associations with body mass index among 8-10-year old African American girls. J Pediatr Psychol. 2009;34(10):1144-1154.
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