Relationship of Body Mass Index and Psychosocial Factors on PhysicalActivity in Underserved Adolescent Boys and Girls

Heather Kitzman-UlrichUniversity of North Texas Health Science Center

Dawn K. Wilson, M. Lee Van Horn,and Hannah G. LawmanUniversity of South Carolina

Objective: Previous research indicates that body mass index (BMI) and sex are important factors inunderstanding physical activity (PA) levels. The present study examined the influence of BMI onpsychosocial variables (self-efficacy, social support) and PA in underserved (ethnic minority, lowincome) boys in comparison with girls. Methods: Participants (N � 669; 56% girls; 74% AfricanAmerican) were recruited from the “Active by Choice Today” trial. Main Outcome Measures: BMI zscore was calculated from objectively collected height and weight data, and PA was assessed with 7-dayaccelerometry estimates. Self-report questionnaires were used to measure self-efficacy and social support(family, peers) for PA. Results: A 3-way interaction between BMI z score, sex, and family support onPA was shown such that family support was positively associated with PA in normal-weight but notoverweight or obese boys, and was not associated with PA in girls. Self-efficacy had the largest effectsize related to PA in comparison with the other psychosocial variables studied. Conclusions: Self-efficacy was found to be an important variable related to PA in underserved youth. Future studies shouldevaluate possible barriers to PA in girls, and overweight youth, to provide more effective family supportstrategies for underserved adolescents’ PA.

Keywords: adolescents, physical activity, BMI, sex, African American

African American adolescents exhibit higher rates of over-weight than do non-Hispanic Whites (38% vs. 33%, respectively),with nearly 45% of African American girls and 32% of AfricanAmerican boys classified as overweight or obese nationally(Ogden, Carroll, & Flegal, 2008). These trends are particularlyalarming, given that African American populations have higherrates of diabetes and cardiovascular disease (Bassett, Fitzhugh,Crespo, King, & McLaughlin, 2002; McBean, Li, Gilbertson, &Collins, 2004; Mensah, Mokdad, Ford, Greenlund, & Croft, 2005).Lifestyle factors such as increasing physical activity (PA) havebeen associated with reduced rates of chronic disease and weightcontrol (Bauman, 2004; Jakicic, 2002). Despite the importance ofPA, only 8% of adolescents are currently meeting daily guidelinesof 60 min of moderate-to-vigorous PA (MVPA), with girls con-sistently demonstrating lower levels of PA than do boys (Troianoet al., 2008; Whitt-Glover et al., 2009). Some evidence suggeststhat adolescents from underserved backgrounds engage in lowerlevels of PA than do Caucasian adolescents or those from highersocioeconomic backgrounds (Butcher, Sallis, Mayer, & Woodruff,

2008; Kantomaa, Tammelin, Nayha, & Taanila, 2007; Sallis,Prochaska, & Taylor, 2000). In particular, African American girlshave demonstrated less PA, and report more barriers to participa-tion in PA, than do their nonminority peers (Felton et al., 2002;McGuire, Hannan, Neumark-Sztainer, Cossrow, & Story, 2002).Because youth behaviors often track into adulthood, understandingdeterminants of youth PA is critical to preventing chronic diseasetrajectories (Braveman & Barclay, 2009). Thus, understandingpredictors of PA in adolescents is a priority, especially for under-served youth who have lower levels of PA and higher rates ofobesity.

Social Cognitive Theory (SCT) provides a framework for ex-amining psychosocial variables related to PA across multiple lev-els of influence including intrapersonal, environmental, and be-havioral factors (Bandura, 1986). This study examined variablesfrom SCT including receiving social support, defined as emo-tional, instrumental, or financial support to achieve a goal such asincreasing PA. Self-efficacy is defined as a person’s belief regard-ing his or her confidence to perform a specific action such asengaging in regular PA (Bandura, 1986, 2004; Baranowski, Perry,& Parcel, 1997). Previous studies indicate that self-efficacy andsocial support are important determinants of PA behavior in bothboys and girls (Dishman et al., 2004; Dowda, Dishman, Pfeiffer, &Pate, 2007; Springer, Kelder, & Hoelscher, 2006; Van Der Horst,Paw, Twisk, & Van Mechelen, 2007), with some studies suggest-ing that these relationships are stronger for boys (DiLorenzo,Stucky-Ropp, Vander Wal, & Gotham, 1998; Sallis, Alcaraz,McKenzie, & Hovell, 1999). Given that girls are less active thanare boys (Troiano et al., 2008; Van Der Horst et al., 2007) and atgreater risk for being overweight (Ogden et al., 2008), research is

Heather Kitzman-Ulrich, Department of Family Medicine, Primary CareResearch Institute, University of North Texas Health Science Center; andDawn K. Wilson, M. Lee Van Horn, and Hannah G. Lawman, Departmentof Psychology, University of South Carolina.

This article was supported by a grant (R01 HD 045693) funded by theNational Institute of Child Health and Human Development to Dawn K.Wilson.

Correspondence concerning this article should be addressed to HeatherKitzman-Ulrich, Department of Family Medicine, University of NorthTexas Health Science Center, 855 Montgomery Street, Ft. Worth, TX76107. E-mail: heather.kitzman-ulrich@unthsc.edu

Health Psychology © 2010 American Psychological Association2010, Vol. 29, No. 5, 506–513 0278-6133/10/$12.00 DOI: 10.1037/a0020853

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needed to understand how body mass index (BMI) may relate topsychosocial determinants of PA in girls in comparison with boys.

There is an increasing interest in understanding how BMI maybe a barrier for engaging in daily health behaviors such as PA(Zabinski, Saelens, Stein, Hayden-Wade, & Wilfley, 2003). Pre-vious research indicates that overweight youth engage in lowerlevels of PA than do normal-weight youth (Byrd-Williams, Kelly,Davis, Spruijt-Metz, & Goran, 2007; Hughes, Henderson, Ortiz-Rodriguez, Artinou, & Reilly, 2006; Must & Tybor, 2005; Trost,Kerr, Ward, & Pate, 2001; Ward et al., 2006) and that BMI mayinfluence the relationship of psychosocial determinants on PA. Forexample, a study in 7th–12th graders demonstrated that psychos-ocial determinants including family and peer support were posi-tively associated with PA in normal-weight youth but not inoverweight youth (Taylor et al., 2002). In another study, psycho-social variables were positively associated with change in PA over20 months in girls and boys with lower levels of BMI but not inthose with higher levels of BMI (Sallis et al., 1999). Another studydemonstrated that self-efficacy was a significant determinant ofPA in boys regardless of BMI but was not for girls (Sallis et al.,1999). Overall, these studies suggest that higher levels of BMI areassociated with lower levels of social support and self-efficacy forPA in both boys and girls.

Developing a better understanding of social and cognitive fac-tors that are associated with PA in groups at high risk for inactiv-ity—girls, overweight youth, and underserved populations—areessential for improving PA behaviors and reducing health dispar-ities. This study expands on previous research by evaluating dif-ferences in PA by sex and BMI in relation to family social support,peer social support, and self-efficacy for PA in a large sample ofunderserved adolescents. It was hypothesized that family support,peer support, and self-efficacy would be stronger predictors of PAfor adolescents with lower levels of BMI than for those with higherlevels of BMI. In addition, some evidence indicates that thesevariables may be more strongly related to PA in boys rather thanin girls and that racial differences in these relationships should beexplored.

Method

Participants

Participants were 669 adolescents who completed baseline mea-sures in a randomized school-based trial, “Active by Choice To-day” (ACT), evaluating the effects of a motivational and behav-ioral intervention on increasing PA in underserved 6th graders(Wilson, Kitzman-Ulrich, Williams, et al., 2008). Participantswere recruited from 12 middle schools that were considered un-derserved (�50% ethnic minority and �50% free or reduced lunchstatus) through letters sent to parents, school orientations, specialevents (pep rallies), visits to classrooms, and regular announce-ments. Participation was open to all 6th graders enrolled in schoolswho participated in the ACT study. Inclusion criteria included (a)being currently enrolled in 6th grade, (b) having parental consentto participate, (c) agreeing to study participation and randomassignment, and (d) being available for a 6-month follow-up (Wil-son et al., 2008). This study was approved by the University ofSouth Carolina Institutional Review Board. Parental informedconsent and adolescent informed assent were obtained from study

participants prior to data collection. Baseline measures were col-lected prior to randomization from trained measurement staff.

Demographic Variables

Eligibility for free or reduced lunch was collected from schoolpersonnel for each cohort. Ethnicity was collected from adoles-cents during baseline measures with a 5-item scale coded for thepresent study as African American or Other (Caucasian, Hispanic,Asian, or Other).

Anthropometric Measures

Height was measured with a Shorr Height Measuring Board andweight was measured with a SECA 880 digital scale (SECA,Hamburg, Germany) by trained measurement staff. Two measuresof height and weight were collected on each participant, and theaveraged variable of height and weight was used. BMI was cal-culated as weight (in kilograms) divided by height (in meters2).Interrater reliability for height was r � .98–0.99 and for weightwas r � 1.00. BMI age for sex percentiles and z scores werecalculated with EpiInfo (Version 3.5.1) with the Centers for Dis-ease Control and Prevention (CDC) 2000 growth reference curves.

Psychosocial Variables

Social support for physical activity. Social support for PAwas measured with the Social Support for Exercise Behaviors, aself-report questionnaire that has demonstrated acceptable test–retest reliability, internal consistency, and construct validity (Sal-lis, Grossman, Pinski, Patterson, & Nader, 1987). Participantsrated the support that they received from family and peers for PAseparately over the past month on a 3-point scale ranging from 1(none) to 3 (many times). In the present study, the positive andnegative subscales demonstrated internal consistency of � � .80for the positive family support subscale, � � .81 for the negativefamily support subscale, � � .78 for positive peer support sub-scale, and � � .82 for the negative peer support subscale, and wereused in the analyses. The positive subscale has 6 items related tosupport from family and 6 items related to support from peers.Example items include “How often has a friend (or family mem-ber) said they would be active with you” and “How often has afriend (or family member) reminded you to be active.” The neg-ative subscale also has 6 items for support from family and 6 itemsfor support from peers. Example items include “How often has afriend (or family member) made fun of you for being active,” and“How often has a friend (or family member) said no to being activewith you.” Items were averaged to create scores for each subscale(e.g., positive family, negative family, positive peer, and negativepeer support for PA).

Self-efficacy for physical activity. Self-efficacy for PA wasmeasured with a modified version of the Self-Efficacy Scale (Saun-ders et al., 1997), which consists of 10 self-report items that use a3-point Likert scale with response options ranging from not like me toa lot like me. The scale has demonstrated adequate reliability and waspositively correlated with intentions for PA (Saunders et al., 1997).Alpha reliability in the present study sample was � � .70. Items wereaveraged for the data analyses. Examples of scale items include “I can

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be active in my free time on most days,” and “I have the skills I needto be active in my free time on most days.”

Physical activity measure. PA was measured with Acticalomnidirectional accelerometers (Mini-Mitter, Bend, Oregon) worn bystudy participants for 7 consecutive days. Adolescents were instructedto wear the accelerometer continuously during this time period duringthe day and at night while sleeping. Actical data reduction wasconducted by the study statistician using SAS (9.2) statistical soft-ware. The program was developed to read 1-min epoch data begin-ning on midnight of the first day of wear through midnight of theseventh day of wear. Data collected with accelerometers were con-verted into MET (metabolic equivalent) values (moderate PA 3–5.9METS, vigorous PA 6–8.9 METS, and MVPA 3–8.9 METS) withpreviously established cut-off estimates (Puyau, Adolph, Vohra, Zak-eri, & Butte, 2004). Amount of PA for each day (18-hour day from6 a.m. to 12 a.m.) was broken into five periods that correspond todistinct portions of the day (before school [6–9 a.m.], morning atschool [9–2 p.m.], afternoon at school [2–5 p.m.], after school [5–8p.m.], and evening [8 p.m. to midnight]). Periods were consideredmissing for which the Actical was worn by at least 70% of partici-pants for less than 80% of the time, and 20 consecutive zero countswere used to indicate nonwear. Single imputation methods wereapplied to missing accelerometer data (Catellier et al., 2005). Onaverage, 37% of the accelerometry data were missing. Only 3% ofadolescents were missing all baseline accelerometry data. Data weremissing because of noncompliance, lost accelerometers, and acceler-ometer malfunction. After data imputation, the five periods weresummed for each day, and the seven daily estimates of PA wereaveraged to create one variable of average daily minutes of moderate-to-vigorous PA (MVPA).

Statistical Analyses

A series of ordinary least-squares (OLS) regressions were used toevaluate the three-way interactions among (a) BMI z scores (BMIz),sex, and psychosocial determinant; (b) race, BMIz, and psychosocialdeterminant; and (c) race, sex, and psychosocial determinant. Becauseof multicollinearity, separate regression models were conducted foreach psychosocial determinant of PA of interest including positivefamily support, negative family support, negative peer support, pos-itive peer support, and self-efficacy. All models controlled for socio-economic status (SES; free or reduced lunch status), and necessarylower-order terms were included (i.e., main effects and two-wayinteractions). An example of the regression equation used to test themodels is as follows:

MVPA � intercept � ß1sex � ß2lunch status � ß3BMIz � ß4race

� ß5family support � ß6BMIz�sex � ß7BMIz�family support

� ß8race�family support � ß9race�sex � ß10race�BMIz

� ß11sex�family support � ß12race�BMIz�family support

� ß13race�sex�family support � ß14BMIz�sex�family support,

where positive family support was replaced with each psychoso-cial determinant of interest. For each model, sex and race werebinary variables indicating girls and African Americans, respec-tively. All independent variables were centered (Aiken & West,1991). To assess effect size for variables of interest, partial r wascalculated by dividing the coefficient’s Type III sum of squares bythe corrected total sum of squares. Post hoc tests of significant

interactions ( p � .05) were conducted to determine significance ofsimple slopes. All analyses were conducted with SAS 9.2 statisti-cal software.

Results

Demographic Characteristics

Adolescents (N � 669) had a mean age of 11.4 (SD � 0.7)years, BMI z score of 1.1 (SD � 1.1), and BMI of 23.4 (SD � 6.1);46.9% (N � 314) were considered normal weight (BMI � 85thpercentile), 16.9% (N � 113) were considered overweight (BMI85th–95th percentile), and 36.2% (N � 242) were consideredobese (BMI � 95th percentile); 56.1% were girls, 74.0% wereAfrican American, and 75.6% received free or reduced lunch atschool. Mean minutes of daily MVPA for the entire sample were47.8 (SD � 22.8). Demographics, MVPA, and psychosocial vari-ables (family and peer social support, and self-efficacy) are shownby BMI percentile category (normal weight, overweight, andobese) for boys in Table 1. Boys (N � 294) had a mean BMI of22.9 (SD � 6.1), height of 150.9 (SD � 8.3) cm, and weight of52.9 (SD � 17.0) kg. Table 2 displays demographics, MVPA, andpsychosocial variables by BMI percentile category for girls. Girls(N � 375) had a mean BMI of 23.7 (SD � 6.2), height of 152.7(SD � 7.6) cm, and weight of 56.0 (SD � 17.4) kg.

Demographics for African American adolescents (N � 495)included a mean BMI of 23.4 (SD � 6.1) and MVPA of 47.2(SD � 23.2) min/day; 46.5% were normal weight, 18.0% wereoverweight, and 35.6% were obese; and 82.0% received free orreduced lunch. Adolescents in the other racial categories combinedhad a mean BMI of 23.3 (SD � 6.2) and MVPA of 49.4 (SD � 21.8)min/day; 48.3% were normal weight, 13.8% were overweight, 37.9%were obese, and 57.2% received free or reduced lunch.

Correlations Between MVPA and PsychosocialVariables by BMI Category and Sex

Correlations between MVPA, positive and negative family andpeer social support, and self-efficacy are shown for boys and girlsin Table 3 by BMI percentile category. Self-efficacy was posi-tively correlated with MVPA for normal-weight girls. In addition,self-efficacy was positively correlated with MVPA across BMIpercentile categories for girls and boys. Correlations by race indi-cated that self-efficacy was also positively correlated with MVPAfor African American adolescents.

Regression Models

MVPA and positive family social support. The overall re-gression model for positive family support on MVPA was signif-icant, F(14, 652) � 12.2, p � .0001, and explained 21% of thevariance in MVPA (see Table 4). Significant main effects werefound for BMI z score and sex, indicating that adolescents withhigher BMIz were less active than were adolescents with lowerBMIz, and girls were less active than were boys. A significantinteraction was found for BMIz � Sex. Plots of this interactionindicate that declines in MVPA by BMI level were more pro-nounced in boys than in girls. A significant Race � Sex interactionwas also found. Plots of this interaction indicated that MVPA

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levels were similar for boys regardless of race, but lower levels ofPA were demonstrated in African American girls in comparisonwith other races. A significant three-way interaction was found forBMIz � Sex � Positive Family Social Support, which is demon-strated in Figure 1. Post hoc tests were conducted to determine thesignificance of the simple slopes. For girls, positive family supportwas not associated with MVPA at any BMI percentile level. Forboys, positive family support was positively associated withMVPA for boys at the 50th percentile for BMI ( p � .05), but notfor boys at the 85th or 95th BMI percentile levels. Partial r forvariables of interest ranged from 0.003 to 0.12. None of the othermain effects or interaction terms was significant.

MVPA and negative family social support. The overallmodel for negative family social support was significant, F(14,652) � 11.7, p � .0001, and accounted for 20% of the variancein MVPA. As with the model for positive family support onMVPA, significant main effects were found for BMIz (B ��5.2, SE � 0.8, t � �6.7, p � .0001, partial r � .06) and forsex (B � �15.5, SE � 1.6, t � �9.5, p � .0001, partial r �.11), indicating that youth with higher BMI levels and girlsengaged in less PA than did youth with lower BMI levels andboys. A significant two-way interaction was found for Race �Sex (B � �8.6, SE � 3.7, t � �2.3, p � .05), indicating that

African American girls have lower levels of MVPA than dogirls from other races, whereas MVPA was similar in AfricanAmerican boys in comparison with other races. None of theother terms were significant.

MVPA and positive peer support. The overall model forpositive peer support was significant, F(14, 652) � 11.9, p �.0001, and explained 20% of the variance in MVPA. As with theother models, significant main effects were found for BMIz(B � �5.6, SE � 0.8, t � �7.1, p � .0001, partial r � .06) andfor sex (B � �15.3, SE � �1.63, t � �9.4, p � .0001, partialr � .11), demonstrating that youth with higher BMI and girlsengaged in less PA than did youth with lower BMI and boys. Atrend for positive peer support (B � 3.0, SE � 1.6, t � 1.92,p � .055, partial r � .004) on MVPA was found, indicating thatyouth with higher levels of positive peer support engaged inmore MVPA than did youth with lower levels of positive peersupport. A significant two-way interaction was found forRace � Sex (B � �8.5, SE � 3.7, t � �2.3, p � .05),indicating that African American girls have lower levels ofMVPA than do girls from other races, whereas MVPA wassimilar in African American boys in comparison with otherraces. None of the other terms were significant.

Table 1Mean (SD) and Frequency (%) for Boys by BMI Percentile Category (Normal Weight,Overweight, Obese)

VariableNormal weight

(�85th percentile)Overweight

(85th–95th percentile)Obese

(�95th BMI percentile) Total

N 138 (47%) 58 (20%) 98 (33%) 294African American 100 (47%) 46 (22%) 65 (31%) 211 (72%)Free or reduced lunch 105 (49%) 41 (19%) 68 (32%) 214 (73%)MVPA 64.85 (27.2) 54.1 (20.5) 46.1 (19.5) 56.5 (25.0)Positive family SS 1.8 (0.5) 1.8 (0.5) 1.8 (0.5) 1.8 (0.5)Negative family SS 1.2 (0.4) 1.2 (0.3) 1.2 (0.4) 1.2 (0.4)Positive peer SS 1.9 (0.5) 1.9 (0.5) 1.8 (0.5) 1.9 (0.5)Negative peer SS 1.3 (0.4) 1.2 (0.3) 1.3 (0.4) 1.2 (0.4)Self-efficacy 2.4 (0.4) 2.3 (0.3) 2.9 (0.3) 2.3 (0.3)

Note. The 85th and 95th body mass index (BMI) percentiles correspond to BMI z scores of 1.036 and 1.645,respectively. MVPA � moderate-to-vigorous physical activity; SS � social support.

Table 2Mean (SD) and Frequency (%) for Girls by BMI Percentile Category (Normal Weight,Overweight, Obese)

VariableNormal weight

(�85th percentile)Overweight

(85th–95th percentile)Obese

(�95th BMI percentile) Total

N 176 (47%) 55 (15%) 144 (38%) 375African American 130 (46%) 43 (15%) 111 (39%) 284 (76%)Free or reduced lunch 144 (50%) 39 (13%) 107 (37%) 290 (77%)MVPA 45.6 (19.5) 38.9 (17.9) 35.9 (15.4) 40.9 (18.3)Positive family SS 1.8 (0.5) 1.9 (0.5) 2.0 (0.5) 1.9 (0.5)Negative family SS 1.2 (0.3) 1.2 (0.3) 1.2 (0.4) 1.2 (0.3)Positive peer SS 1.8 (0.5) 1.9 (0.5) 1.9 (0.5) 1.8 (0.5)Negative peer SS 1.2 (0.3) 1.3 (0.5) 1.2 (0.4) 1.2 (0.4)Self-efficacy 2.3 (0.4) 2.3 (0.4) 2.3 (0.4) 2.3 (0.4)

Note. The 85th and 95th body mass index (BMI) percentiles correspond to BMI z scores of 1.036 and 1.645,respectively. MVPA � moderate-to-vigorous physical activity; SS � social support.

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MPVA and negative peer support. The overall model fornegative peer support on MVPA was significant, F(14, 652) �11.5, p � .0001, and accounted for 20% of the variance in MVPA.As with the previous findings, significant main effects were foundfor BMIz (B � �5.4, SE � 0.7, t � �7.1, p � .0001) and for sex(B � �15.1, SE � 1.6, t � �9.3, p � .0001), indicating that youthwith higher levels of BMI and girls engaged in less PA than didyouth with lower levels of BMI and boys. There was also asignificant two-way interaction found for Race � Sex (B � �8.8,SE � 3.7, t � �2.4, p � .05), indicating that African Americangirls have lower levels of MVPA than girls from other races,whereas MVPA was similar in African American boys in compar-ison with other races. None of the other main effects or interactionterms was significant.

MVPA and self-efficacy. The overall model for self-efficacy on MVPA was significant, F(14, 652) � 12.5, p �.0001, and accounted for 21% of the variance in MVPA. Aswith other models, main effects were found for BMIz (B ��5.5, SE � 0.8, t � �7.2, p � .0001, partial r � .06) and for

sex (B � �14.8, SE � 1.6, t � �9.2, p � .0001, partial r �.10), demonstrating less PA in youth with higher BMI and girlsthan in youth with lower BMI and boys. A main effect wasfound for self-efficacy on MVPA (B � 8.11, SE � 2.3, t � 3.5,p � .0001, partial r � .02), demonstrating that adolescents withhigher levels of self-efficacy for PA engaged in higher levels ofMVPA than did adolescents with lower levels of self-efficacy.As with the other models, a significant two-way interaction wasfound for Race � Sex (B � �9.0, SE � 3.7, t � �2.5, p � .05),indicating that African American girls have lower levels ofMVPA than do girls from other races, whereas MVPA wassimilar in African American boys in comparison with otherraces. None of the other interaction terms or main effects wassignificant.

Discussion

The purpose of the present study was to assess the relationshipof BMI and psychosocial (self-efficacy and social support) factors

Table 3Correlations Between Psychosocial Variables and MVPA by BMI Percentile Category and Sex

Variable Self-efficacy Positive family SS Negative family SS Positive peer SS Negative peer SS

MVPA (boys)

Normal weight (�85th percentile) 0.13 0.15 �0.10 0.03 0.05Overweight (85th–95th percentile) 0.23 0.07 �0.02 0.07 0.15Obese (�95th percentile) 0.08 �0.09 �0.10 0.09 0.09All boys 0.15� 0.06 �0.07 0.09 0.07

MVPA (girls)

Normal weight (�85th percentile) 0.17� 0.06 �0.02 0.06 0.03Overweight (85th–95th percentile) �0.04 �0.06 �0.01 0.09 0.02Obese (�95th percentile) 0.11 0.00 0.01 0.14 �0.05All girls 0.11� �0.03 �0.02 0.07 0.01

Note. MVPA � moderate-to-vigorous physical activity; BMI � body mass index; SS � social support.� p � .05.

Table 4Regression Model for MVPA and Positive Family Social Support (SS)

Variable

Coefficients

t p Partial rB SE

Intercept 47.9 0.8 58.9 �.0001Lunch status �3.1 1.9 �1.6 .10 0.003Race �3.2 1.9 �1.7 .10 0.003BMI z score (z) �6.0 0.8 �7.6 �.0001 0.07Sex �15.9 1.6 �9.8 �.0001 0.12Positive family SS 2.6 1.6 1.7 .09 0.003BMIz � Sex 3.1 1.6 2.0 .04BMIz � Positive Family SS �2.2 1.6 �1.5 .15Race � Positive Family SS �0.6 3.8 �0.2 .88Race � Sex �7.8 3.7 �2.1 .04Race � BMIz 1.0 1.9 0.5 .60Sex � Positive Family SS �3.6 3.2 �1.1 .26Race � BMIz � Positive Family SS 2.9 3.8 0.8 .45Race � Sex � Positive Family SS 11.0 7.5 1.5 .15BMIZ � Sex � Positive Family SS 6.1 3.1 2.0 .05

Note. Overall model F(14, 652) � 12.2, p � .0001, R2 � .21.

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on PA in underserved adolescent boys in comparison with girls.Possible differences by race were also explored. Key findings werethat positive family support for PA was associated with PA fornormal-weight boys, but not for overweight or obese boys, or forgirls across BMI categories. Self-efficacy was associated with PAfor both boys and girls regardless of BMI, and demonstrated thegreatest effect size on MVPA in comparison with the other psycho-social variables studied. Findings also indicate that African Americangirls have lower levels of PA than do girls from other races, whereasthis was not found in boys. As was expected, boys had significantlyhigher levels of PA than did girls, and overweight youth demonstratedlower levels of PA than did normal-weight youth.

As was hypothesized, there was a significant interaction of sex,BMI, and positive family support on MVPA. For girls, perceivedlevels of positive family support were not associated with PA atany BMI level. This is inconsistent with a previous study thatfound that parental engagement was the strongest predictor ofachieving recommended levels of PA in a multiethnic (Caucasian,African American, and Hispanic) sample of adolescents (Ornelas,Perreira, & Ayala, 2007). In this underserved population, positivefamily support may not have the expected impact on PA becauseof individual and environmental barriers. For example, girls havereported greater body-related, resource, and social barriers to en-gaging in PA than do boys, and thus they may need more familysupport for PA behavior than do boys (Zabinski et al., 2003).Furthermore, environmental barriers to participation in PA havebeen noted in African American girls. For example, in one study,Caucasian girls reported more sports equipment at home, feelingsafer to exercise in their neighborhood, and fewer barriers (e.g.,traffic and lack of sidewalks) to exercise than did African Amer-ican girls (Felton et al., 2002). Taken together, these findingssuggest that addressing individual and environmental barriers toparticipation in PA, in addition to increasing family support, maybe necessary to improve girls’ PA.

In contrast, family social support was positively associatedwith PA in normal-weight boys, but not in overweight or obeseboys. This is consistent with a previous study that found that

parent engagement in PA was positively associated with changein PA over 20 months in boys with lower levels of BMI but notfor boys with higher levels of BMI (Sallis et al., 1999). Indi-vidual barriers to PA participation in overweight and obeseboys may influence the impact of family support on PA. Forexample, in one study, overweight boys reported more body-related barriers to PA than did normal-weight boys (Zabinski etal., 2003). Moreover, athletic coordination has been shown topredict PA in boys (Sallis, Taylor, Dowda, Freedson, & Pate,2002). Overweight and obese boys who experience body-related barriers to PA may have lower levels of perceivedathletic coordination, resulting in less PA participation, evenwith adequate amounts of family support. Therefore, as withgirls, individual barriers to PA participation should be exploredto provide families with effective strategies to support PA inoverweight and obese boys.

Of the psychosocial variables examined in this study, self-efficacy had the largest magnitude of effect on PA and waspositively associated with PA in both boys and girls across BMIcategories. Self-efficacy has consistently been a determinant of PAin several populations (Sallis et al., 1999; Van Der Horst et al.,2007). With regard to sex differences, some studies have suggesteda stronger relationship between self-efficacy and PA in boys thanin girls (DiLorenzo et al., 1998; Sallis et al., 1999), althoughseveral studies of girls have found that self-efficacy is stronglyrelated to PA (Barr-Anderson et al., 2007; Dishman et al., 2004;Sallis et al., 2000). Higher levels of self-efficacy may lead to moreself-regulation for PA, and the confidence to overcome barriers toparticipation in PA, and thus should be relevant for both boys’ andgirls’ PA behaviors, as is suggested in the present study.

Race did not have an independent, significant association withPA levels in this study. This is consistent with a recent studyexamining NHANES (National Health and Nutrition ExaminationSurvey) data, which found no significant differences in meetingpublic health guidelines for PA by race or ethnicity (Whitt-Gloveret al., 2009). A recent review indicated that the greatest disparitiesin PA are by age and sex, and not ethnicity (Whitt-Glover et al.,

Figure 1. Moderate to vigorous physical activity (PA) (mean minutes per day) for normal weight, overweight,and obese girls and boys with low (�1 SD) or high (�1 SD) levels of positive family support for PA. BMI �body mass index; SS � social support.

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2009). However, there was a Race � Sex interaction in all of theregression models, indicating that African American girls hadlower levels of MVPA than did girls from other races, whereas forboys, MVPA levels were similar for African American and otherraces. This adds to the growing body of literature highlighting theneed to better understand factors related to PA in African Amer-ican girls, who often report the lowest levels of PA in comparisonwith other racial groups and have among the highest rates ofobesity.

Limitations of the present study include the cross-sectionalnature of the data and the inability to determine causal relation-ships. In addition the effect sizes were relatively small. Moderateamounts of variance (�20%) in MVPA levels were accounted forby the regression models in this study. As with other studies, theeffect sizes (partial rs ranging from 0.003 to 0.12) for the variablesof interest were rather small (Sallis et al., 1999). The largest effectsizes were found for sex followed by BMI z score, with psycho-social variables demonstrating the lowest effect sizes (0.003–0.02). These findings are consistent with those in previous litera-ture demonstrating the role of sex on MVPA levels and the criticalneed to intervene in girls. Although higher levels of BMI z scorewere associated with lower levels of MVPA, the effect size wassmall in magnitude, indicating that BMI may not be a strongbarrier to PA participation in this underserved sample. Thestrengths of the present study include a large sample of primarilyAfrican American youth and the use of objective measures of PA.To our knowledge, this is one of the first studies to assess theinfluence of BMI on the relationship between psychosocial vari-ables and accelerometry estimates of PA in boys in comparisonwith girls from an underserved sample.

In order to reduce health disparities it is critical to evaluatepossible determinants of health behavior change in underservedadolescents. This study provides insight into the influence of sex,BMI, and race on psychosocial determinants of PA, and highlightsareas that warrant further investigation. Because several largereviews have pointed to the importance of parental engagementand family support in relation to youth PA (Ornelas et al., 2007;Whitt-Glover et al., 2009), additional research is needed to deter-mine what factors might mediate this relationship in underservedyouth, particularly for girls, and overweight youth. For girls,environmental and home barriers to participation in PA may alsoneed to be targeted, and families may need to provide additionalencouragement to girls for PA. Similarly, in overweight and obeseboys, evaluating possible barriers to PA may provide families withmore effective support strategies. This study also highlights theimportance of self-efficacy in underserved youths’ PA behavior.Overall, this study indicates variables to consider in future obesityprevention and PA programs for underserved youth, such as self-efficacy, and highlights areas that need further study, such aspossible barriers to PA and effective types of family support forgirls and overweight youth.

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New Editor Appointed for Health Psychology, 2011–2016

Division 38 (Health Psychology) of the American Psychological Association is pleased toannounce the appointment of a new editor for Health Psychology for a 6-year term beginning in2011. As of July 1, 2010, all new manuscripts should be directed to:

Anne E. Kazak, PhDThe Children’s Hospital of Philadelphia andUniversity of Pennsylvania34th and Civic Center Blvd.Room 1486 CHOP NorthPhiladelphia, PA 19104-4399

Electronic manuscript submission: As of July 1, 2010, manuscripts should be submittedelectronically to the new editor via the journal’s Manuscript Submission Portal: http://www.apa.org/journals/hea/submission.html

Manuscript submission patterns make the precise date of completion of the 2010 volumesuncertain. The current editor, Robert M. Kaplan, PhD will receive and consider new manuscriptsthrough June 30, 2010. Should 2010 volumes be completed before that date, manuscripts will beredirected to the new editor for consideration in the 2011 volume.

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