What Is Native Body Type Z

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NIHMS25983

Ethnic Differences in BMI, Weight Concerns, and Eating Behaviors: Comparison of Native American, White, and Hispanic Adolescents

Abstract

Evidence suggests that substantial proportions of adolescents, regardless of ethnicity or gender, are engaged in excessive weight control behaviors. Crago and Shisslak (2003), all the same, accept noted that small samples and poorly validated instruments have limited the value of previous indigenous difference studies. Using the McKnight Take a chance Factor Survey, nosotros compared Native American, White, and Hispanic adolescents. Native students were divided into groups with one (NA-mixed) or two (NA) Native American biological parents. Surveys were completed by 5th
through 10th
class students. BMI z-scores were significantly higher for boys and girls in the NA group, and boys in this grouping were significantly more engaged in weight control behaviors, including purging. A higher percentage of Native and Hispanic girls preferred a larger body size. BMI was positively correlated with weight and shape concerns and with weight command behaviors, regardless of ethnicity or gender. Overweight amongst Native adolescents may put them at greater risk for eating problems than their White peers.

Keywords:

BMI, torso prototype, weight business concern, eating disorders, risk factors, weight control behaviors, size preference, McKnight Risk Factor Survey

Ethnic Differences in BMI, Weight Concerns, and Eating Behaviors: Comparison of Native American, White, and Hispanic Adolescents

Body dissatisfaction, fright of weight gain, appearance concerns, weight and shape concerns, and higher BMIs among adolescents are associated with increased risk for eating disorders (Killen et al., 1994; Shisslak et al., Stice, 1998; 1998; Story et al., 1991; Striegel-Moore, Silberstein, & Rodin, 1986). In improver, recent studies suggest that substantial proportions of most ethnic groups and both genders are engaged in sometimes-excessive weight control behaviors (e.thousand., Croll, Neumark-Sztainer, Story, & Ireland, 2002; Taylor et al., 2003). In a recent review, yet, Crago et al. (2003) noted that small sample sizes and poorly validated cess instruments have limited the usefulness of many studies of ethnic differences. In i of the few studies of Native American eating issues using validated behavioral measures, Smith and Krejci (1991) studied Native adolescents (~15 years old) from Pueblos in Southwestern USA and plant that, compared to their Caucasian peers, a greater percentage of Native participants reported binge eating, vomiting and fear of gaining weight. In a contempo large-scale survey of several adolescents groups, including Native Americans, Croll and colleagues (2002) found that Native American and Hispanic girls had the highest prevalence of weight control behaviors, including fasting or skipping meals, binge eating, vomiting intentionally, using diet pills and laxatives, or smoking cigarettes. Similarly, in a small sample of adolescent girls living in Montana, we constitute that Native girls (~14 years erstwhile) scored significantly higher than their White peers on both the restricting/purging and social force per unit area/oral control factors of the children’s eating attitudes exam (Lynch, Eppers, & Sherrodd, 2004).

Why Native American adolescents may be at such high risk for eating issues remains unclear. Despite a surge of contempo interest in ethnic and cultural differences in eating problems, there is piffling consensus regarding underlying mechanisms. In an early on report, Bulik (1987) described the cases of two Russian immigrants who developed anorexic symptoms shortly later arriving in the US. She suggested that rapid acculturation to the sparse ideal of beauty in the US or disruption of traditional family unit roles might exist involved. Around this same time, Nasser (1988) argued that anorexia and bulimia should be considered “civilisation-bound” syndromes because they appeared to be linked to “…a recent change in Western values in relation to female shape with more emphasis on thinness…” (p. 574).

More than recently, reviewers take offered a plethora of tentative hypotheses about the sources of these civilisation-bound differences, including differences in self-esteem or identification with the White middle-class (Crago, Shisslak, & Estes, 1996), differences in “…coping with diverse traumas…” (Thompson, 1992,
p.76), cultural differences in dietary habits, family structures or parent-kid relationships (Pate, Pumariega, Hester, & Garner, 1992; Yates, 1990), variations in attitudes toward eating, the significant of food and meals, culturally related eating behaviors, or cultural influences on individuation, maintenance of command, or emotional expression (Cummins, Simmons, & Zane, 2005). Others accept implicated the irresolute social, economic, and professional status of women in not-western cultures or indigenous groups (Crago et al., 2003), unique cultural beliefs, values, and practices regarding food, or unique perceptions about health (Markey, 2004). Unfortunately, systematic cross-cultural studies of these variables are not currently available.

The idea that cultural conflict associated with affiliation with more one culture – the so-called “2-world hypothesis” (Katzman & Lee, 1997) – may lead to an increased risk of eating disorders (EDs) has been supported by studies showing that Black girls who accepted White values and behavior were significantly more than probable to have a college drive for thinness and engage in restrictive eating behaviors than those who did non have these White values (Abrams, Allen, & Gray (1993). However, despite such testify, a recent meta-analysis by Wildes, Emery, and Simons (2001) constitute little support for this differential acculturation hypothesis.

In the instance of Native Americans, Doane (1992) has suggested that cultural pressures to consume at family and tribal gatherings, coupled with high-fat diets, due in part to government commodities supplanting traditional foods and a sedentary life-style, may contribute to the high levels of obesity and diabetes in many contemporary Native communities. Perhaps such cultural pressures and dietary atmospheric condition combined with media images of thinness coming from the majority White culture, increase weight and shape concerns among Native adolescents.

Despite the lack of consensus on the source of cultural or indigenous differences in eating problems, there is clear evidence of a link between BMI, body concerns, and eating disorders chance across widely diverse cultural and indigenous groups. For example, Mumford and Choudry (2000) found that White and south Asian women living in London, too as south Asian women living in Pakistan, all showed strong associations between BMI, trunk dissatisfaction, and total scores on the Eating Attitudes Examination. Such evidence suggests that despite cultural and geographic differences, increases in BMI can lead to increases in body dissatisfaction and to increases in the risk for eating problems. The association of BMI with ED risk may be especially relevant for the present written report given the serious obesity problem among Native Americans of both sexes and all ages (Broussard et al., 1991) and the fact that obesity prevalence in Native communities has increased chop-chop in the past half century to nigh-epidemic proportions (Story et al., 1999). Consistent with this idea, Stevens et al. (1999) noted that “…a gamble factor for weight dissatisfaction, dieting, and unhealthy weight control practices amongst American Indian adolescents is beingness or feeling overweight” (p. 35). The clan between BMI and trunk dissatisfaction appears to be a common finding beyond ethnic groups, although the force of this clan may vary substantially from 1 ethnic grouping to another (Yates, Edman, & Aruguete, 2004). Other studies support the idea that differences in body dissatisfaction may business relationship, at least in function, for indigenous differences in eating disturbances (e.g., Caradas, Lambert, & Charlton, 2001; Neumark-Sztainer et al., 2002; Stice, 2003).

The present study began every bit an endeavour to empathise the risk factors for eating disturbance among several adolescent ethnic groups with substantial representation in s-central Montana, The states. We assessed several putative hazard factors for eating disorders including BMI-for-historic period (and gender), torso size preference, weight and shape concerns, and several high-risk eating behaviors among male person and female adolescents. Based on available inquiry, we predicted that BMI would be positively correlated with measures of weight and shape business organisation and with high-run a risk eating behaviors among all ethnic groups. Further, based on the few available studies of Native Americans (e.g., Croll et al., 2002; Lynch et al., 2004; Smith et al., 1991), we predicted that Native participants would show college levels of BMI, more than weight and shape concerns, and more bingeing and purging behaviors than their White peers. Based on the work of Yates and colleagues (2004) nosotros predicted that correlations betwixt BMI and weight concerns would vary from one indigenous group to another. However, existing data did non let united states of america to predict which ethnic groups would testify the strongest associations or whether such differences would be statistically significant. Finally, in accord with the “two-world” hypothesis mentioned above, we expected that Native American females who were more acculturated to the White norms of thinness, would written report more weight and shape concerns and more risky eating behaviors than their more traditional, less acculturated, peers.

Method

Participants

Students from 13 public schools in south-cardinal Montana participated in the study (n
= 2558). Schools were selected on the footing of their historically high enrollment of Native American students. Eight schools were located in the Billings, MT schoolhouse district, four in the Hardin, MT schoolhouse commune, and one (St. Labre Loftier) was a individual parochial school located in Ashland, MT. All students in grades 5–10 were eligible to participate. Parental consent was obtained using a passive consent method approved by the Institutional Review Lath (IRB) at Montana Country Academy, Bozeman, MT and past the schoolhouse board (Billings School District) or past individual school administrators (Hardin and St. Labre Schools). Among the Native American and Native-mixed indigenous groups, the tribes represented were those of the central plains, primarily Crow and Northern Cheyenne.

Ethnic group and gender distributions of participants in the study were as follows: 59.4% were White, 19.i% had ii biological parents who were Native American (NA), 7.7% had one Native American biological parent (NA-mixed), vii.3% were Hispanic, and half-dozen.5% were of other or mixed ethnic backgrounds (Other). The “Other” group consisted of Black (north
= 23), Asian (n
= 24), and mixed-parent ethnic groups, other than NA–mixed (n
= 119). Participants in the Other group were combined because of their small numbers. Of the total sample, 48.0% were female.

Instruments

The following items and instruments were included in the survey packet which was completed over a two-day menses.

Demographic

Age (based on date of birth), gender, ethnicity, number of biological parents in household, number of adults in household who act as parents, and main linguistic communication spoken at abode, were cocky-reported.
Table ane
summarizes these statistics.


Tabular array ane

Sample descriptive statistics for five ethnic groups

Ethnic group northward Historic period
M (sd)
% Female % two-biological % 2-adult % English language
White 1520 13.eight (1.7) 46.6 55.6 77.viii 99.1
NA 489 xiii.6 (1.8) 51.7 39.viii 65.7 eighty.four
NA-mixed 197 13.iii (i.viii) 54.3 34.vii 62.9 92.9
Hispanic 186 xiii.5 (1.7) 39.2 43.vi 66.3 82.9
Other 166 xiii.5 (1.half-dozen) 51.8 38.7 64.4 88.four

Native American cultural identity

NA and NA-mixed participants were asked to indicate which i of the following four descriptions about their beliefs and behaviors best described them: a) Traditional: “I maintain the behavior and behaviors that take persisted for generations.” b) Transitional: “I maintain some of the beliefs and behaviors that have persisted for generations merely I’ve likewise developed some new behavior and behaviors that are consistent with the electric current ways of life.” c) Mod: “I’ve mainly developed new behavior and behaviors that are consistent with the electric current ways of life.” d) Unsure: “I’k undecided now.”

McKnight Risk Factor Survey (MRFS, 67)

The MRFS is a self-report questionnaire originally designed to assess risk factors for the development of eating disorders among pre- and mail service-adolescents girls (Shisslak et al., 1999). An before version of the MRFS (version Iii) has been psychometrically validated with individuals ranging in age from 8–18 (grades 4–12). Although three forms of the MRFS-IV were available at the time of this report (Shisslak, personal communication), only the form designed for grades vi–12 was used. Items included in the complete survey packet were those roofing the following putative adventure domains: Eating behaviors and attitudes (e.g., dieting, exercising, bingeing, purging, social eating, appearance appraisal, and self-reported ED chance), social influences on eating behavior (e.g., weight teasing past adults or peers, adult support/sharing, sexual pressure, media modeling, and sports force per unit area), and personal attributes (e.k., self-confidence, attributes for success, and maturity level). Items such as, “In the past year, how often have you lot worried about having fatty on your body?” were rated on 5-point Likert scales ranging from never (1) to always (v). An unweighted score for each participant and each domain was calculated equally the mean of all items making upwardly that domain. For the purpose of the present study, only selected domains were used (McKnight Take a chance Factor Survey, 2006)
1. Considering our primary interest was in indigenous differences in the relationships among body size, trunk prototype, and potentially risky eating behaviors, the present paper focuses on those domains straight related to these issues. The specific MRFS-IV domains included were: Domain 2, appearance appraisal (AA, 3 items), domain 4, binge eating (Be, 2items), domain fifteen, overconcern with weight and shape (OWS, 5 items), domain 18, purging beliefs (PB, three items), and domain 24, weight control behaviors (WCB, 7 items). Moderate to fantabulous internal reliability has been reported previously for all five of these domains. One of the three items making upwards appearance appraisal (Q31) was modified for males every bit follows: Males: “In the past year, how oftentimes have yous felt bonny or handsome?” Females: “In the past year, how oftentimes have you felt attractive or pretty?” Convergent validity, internal reliability, and test-retest reliability have been reported for the OWS domain for girls (Shisslak et al., 1999). Previous studies employing the WCB domain have shown it to correlate significantly with various measures of ED run a risk (Sherwood, et al., 2004; Shisslak et al., 1998).

Figure Rating Calibration (FRS)

The FRS was originally designed to measure out body shape satisfaction (Stunkard, Sorenson, & Schulsinger, 1983). In the present study we used the FRS to assess size preference by asking participants to circumvolve one of ix gender-specific trunk shape figures perceived to be “most like” to her or him self and so, using a second set of figures, to circumvolve the figure that she or he “nearly preferred” to look similar. A divergence score (about similar minus most preferred) indicated the preference for a smaller (positive difference) or larger size (negative difference). Although numerous concerns have previously been raised regarding the psychometric properties of the FRS (e.g., Gardner, Friedman, & Jackson, 1998), especially for assessing torso dissatisfaction among adolescents (e.yard., Sherman, Iacono, & Donnelly, 1995) and males (Cafri, Thompson, & Barbau, 2004), our information revealed significant correlations between FRS difference scores and OWS scores both for males (r
= .368,
p
< .01) and for females (r
= .507,
p
< .01).

Anthropometric measures

Height and weight measurements were derived from front- and side-view photos of each participant taken while the student stood barefoot on a digital balance. Each photo included the epitome of a calibrated meter stick, which was subsequently used to determine height. ImageJ software, available from the National Institute of Mental Wellness, Inquiry Services Branch (2006), was used to derive height measurements from the photos. Weight was read straight from the digital balance (Tanita BWB-800S). Body mass index was calculated from measured values of trunk weight (kilograms) and body superlative (meters) every bit kg/m2. We employed this photographic method in order to facilitate rapid and efficient non-subjective data collection within the restricted time schedule of students and schools. To our knowledge this method of calculating BMI has non previously been reported
2. BMI is mostly considered the only practical noninvasive measure out of relative body size for survey methods and thus is generally preferred over measures of body composition. For the purpose of ethnic grouping and gender comparisons, each participant’southward BMI was transformed to an historic period- and gender-specific
z-score co-ordinate to the CDC’s BMI-for-age and –gender growth charts. For the purpose of comparing with the CDC norms, data from the electric current participants were sorted into ane of iii established BMI categories: Normal (</= 85th
percentile), At risk for overweight (> 85th
and < 95thursday
percentile), or Overweight (>/= 95th
percentile).

Process

Prior to the start of data collection trained graduate enquiry administration met with Health Enhancement (HE) teachers in each of the targeted schools to discuss logistics and distribute parental information sheets forth with copies of the survey materials to exist used for parental review. A brief letter explaining the goals of the project and requesting parental cooperation accompanied these materials. Passive consent or “opt-out” forms were sent to all parents by school administrators at to the lowest degree two weeks prior to the beginning of data collection. Completed “opt-out” forms were returned by parents to each schoolhouse and forwarded by the school to HE teachers, who were responsible for re-assigning these students to alternative locations and activities prior to the offset of data collection.

Graduate and advanced undergraduate research assistants administered the surveys and gathered all other required information. Inquiry administration administered the surveys during two form periods in all HE classes at each schoolhouse during the autumn 2002 and spring 2003 semesters. Private participant data were coded to maintain confidentiality. All data collection procedures were approved past the IRB of Montana State University-Bozeman and by the Billings District School Board or individual school administrators in Hardin and Ashland, MT.

The surveys were administered within HE classes at each school at a pre-arranged date user-friendly to teachers in that school. On the designated date inquiry assistants (2 males to piece of work with boys and 2 females to work with girls in each classroom) brought paper-and-pencil survey materials to the schools in advance of scheduled HE classes. At the showtime of class, following a cursory introduction by the teacher, students were divided past gender and males were moved temporarily to a vacant classroom or other area with seating and writing surfaces (eastward.chiliad., cafeteria or gymnasium). This separation was necessary because some materials were gender-specific. Demographic and MRFS information were collected on Day 1. FRS and anthropometric information were collected on Mean solar day two.

Results

Analysis of the demographic data revealed no significant age differences among ethnic groups or between genders. At that place was a significant difference in gender distribution across indigenous groups when all five groups were considered; however, the degree of association of gender with ethnicity was small (χtwo
(4) = 14.xc,
p
< .005,
Cramér’due south V
= .077). As tin be seen in
Table 1, this group difference was largely due to the lower percentage of females in the Hispanic group. When only the 3 groups of principal interest were included (W, NA, and NA-mixed) there were significant differences in terms of the percent of households with two biological parents (χii
(two) = 80.78,
p
< .001,
Cramér’due south 5
= .193) and the pct of households with two adults interim every bit parents (χ2
(two) = 39.67,
p
< .001,
Cramér’s V
= .136). Both these latter differences were due to the smaller pct of two parent families (biological or otherwise) among the NA and NA-mixed groups. Not surprisingly, when asked to signal the main language spoken at home, there were significant differences between ethnic groups, with the lowest percentage speaking English at home among the NA and Hispanic groups (χ2
(12) = 382.65,
p
< .001,
Cramér’s V
= .332). When merely the NA and NA-mixed groups were compared, 12.ii% (40 of 327) of NA participants reported speaking mainly their native linguistic communication at home, while only 0.8% (1 in 127) of the NA-mixed grouping did so.

Table 2
shows internal reliability scores (Cronbach’s α) for each of the five MRFS domains. Reliability measures were calculated get-go for all males and all females then separately for each of the 8 primary subgroups. In the following analyses only comparisons for which the Cronbach’southward
α
was at to the lowest degree 0.65 are reported. As
Table 2
shows, OWS and WBC had good internal reliability for both genders and for all subgroups. All the same, the AA domain had poor reliability for about of the male subgroups and for the NA female grouping. The Atomic number 82 domain was only reliable for the NA male group and the NA-mixed and Hispanic female groups. The BE domain was reliable for all female groups except Hispanic females, but only for the NA-mixed and Hispanic males.


Table 2

Internal reliability scores (Cronbach’s Blastoff) for five domains of the McKnight Risk Factor Survey, version 4, by ethnic group

Cronbach’s α for selected MRFS domains


Gender Ethnic group AA (Dom2) BE (Dom4) OWS (Dom15) PB (Dom18) WCB (Dom24)
Male White .607 .585 .801 .573 .878
NA .335 .580 .744 .692 .874
NA-mixed .384 .706 .792 .423 .877
Hispanic .487 .691 .788 .281 .891
All males .531 .611 .790 .646 .876

Female White .747 .717 .891 .616 .905
NA .565 .673 .850 .505 .885
NA-mixed .664 .708 .863 .752 .892
Hispanic .717 .580 .838 .711 .890
All females .690 .696 .873 .625 .898

Table 3
shows the number and percentage of male and female participants, by indigenous group, within each of three BMI ranges based on BMI-for-age (and gender) charts of the Centers for Illness Control (2006). Based on these information it is clear that NA boys had substantially higher BMIs than boys of all other ethnic groups, with 43.0% in the overweight category ( 95thursday
percentile), compared to 24.9% of White boys, and 27.8% of all boys. This difference was similar for female person groups in which 31.5% of NA girls were in the overweight category compared to 15.vii% of White girls and less than 20% of all girls. Equally suggested by these results, chi-square analyses confirmed highly meaning ethnic group differences among both male (χii
(8) = 31.52,
p
< .001,
Cramér’south 5
= .121) and female (χ2
(8) = 27.63,
p
= .001,
Cramér’s V
= .119) groups.


Tabular array 3

Number and per centum (%) of participants in each of three BMI ranges by ethnic group

BMI range (percentile)


Gender Indigenous grouping Normal (≤85th) % At-take a chance (> 85thursday) % Over (≤95th) % Total
Male White 379 56.2 127 18.eight 168 24.9 674
NA 67 36.0 39 21.0 eighty 43.0 186
NA-mixed 44 56.iv 16 20.v 18 23.i 78
Hispanic 49 52.vii 20 21.five 24 25.viii 93
Other 30 58.8 10 19.6 xi 21.6 51
All Boys 569 52.6 212 19.half dozen 301 27.viii 1082

Female White 350 60.two 140 24.1 91 fifteen.vii 581
NA 96 48.7 39 nineteen.8 62 31.5 197
NA-mixed forty 48.8 24 29.3 xviii 22.0 82
Hispanic 35 66.0 nine 17.0 nine 17.0 53
Other 33 55.0 14 23.iii 13 21.seven lx
All Girls 554 56.ix 226 23.ii 193 xix.8 973

Tabular array iv
shows the pct distribution of preferences for smaller, same, or larger body sizes based on FRS difference scores for each of the ethnicity and gender subgroups. Chi-square analyses based on the data in
Tabular array 4
revealed no ethnic group differences in preferred body size for males (χ2
(viii) = eight.57,
p
= .380,
Cramér’s 5
= .088), merely a significant divergence for females (χ2
(8) = xix.38,
p
= .013,
Cramér’s V
= .103), which was mainly due to the much smaller per centum of White girls (4.vi%) who reported wanting to be larger, compared to NA (ix.6%), NA-mixed (14.1%), and Hispanic girls (15.0%). Regardless of ethnicity, boys consistently reported wanting to exist larger more frequently than girls.


Table four

Size preference percentages based on Figure Rating Scale (FRS) deviation scores

Pct inside gender


Gender Indigenous group Smaller Same Larger
Male White 34.3 twoscore.iii 25.four
NA 39.8 44.five 15.7
NA-mixed 31.vii 42.7 25.6
Hispanic 36.0 40.0 24.0
Other 32.7 41.8 25.five
Mean % 35.2 41.3 23.6

Female White 50.8 44.half dozen 4.6
NA 51.8 38.vi ix.half dozen
NA-mixed 48.7 37.2 fourteen.ane
Hispanic 47.5 37.five 15.0
Other 47.1 49.0 3.9
Hateful % l.5 42.6 6.ix

Group differences

Table 5
shows ethnic group and gender differences in the ways and standard deviations of the five MRFS domain scores as well every bit BMI-for-age (and gender)
z-scores. To test for ethnic group and gender difference in the magnitude of each of these dependent variables, univariate ANOVAs were carried out for BMI
z-scores (BMI) besides as each of the v MRFS domain scores with gender and ethnic group as independent variables. Post-hoc multiple comparisons (Bonferroni-adjusted Educatee’south
t) assessed differences among individual ethnic groups. For BMI there were no meaning gender differences nor ethnic grouping by gender interactions, but at that place were meaning ethnic grouping differences (F
(4, 2054) = 13.55,
p
< .001). Post-hoc tests confirmed that Native Americans equally a group had significantly college hateful BMI
z-scores than all other ethnic groups (Table five,
p
< .001 for each pair-wise comparing). None of the other ethnic group differences was statistically pregnant.


Tabular array five

Grouping mean and standard deviations of BMI z-scores and McKnight Risk Factor Survey (MRFS) domain scores

Gender Ethnic grouping BMI
Chiliad
(SD)
AA
M
(SD)
Exist
M
(SD)
OWS
M
(SD)
PB
Thousand
(SD)
WCB
1000
(SD)
Male White 0.79 (1.ten) iii.66 (0.88) 1.86 (0.91) i.lxx (0.79) i.06 (0.30) ane.59 (0.72)
NA 1.33 (0.99) iii.56 (0.82) 1.77 (0.87) one.90 (0.81) 1.14 (0.39) i.92 (0.84)
NA-mixed 0.77 (1.09) 3.47 (0.80) 1.74 (0.90) one.fourscore (0.83) 1.thirteen (0.43) 1.74 (0.80)
Hispanic 0.87 (1.05) 3.86 (0.91) two.05 (1.eleven) 1.83 (0.89) 1.13 (0.38) one.68 (0.83)
Other 0.71 (1.37) 3.81 (0.84) 1.85 (1.05) 1.70 (0.88) one.x (0.55) 1.58 (0.72)
All Boys 0.89 (one.11) 3.65 (0.87) ane.85 (0.93) 1.75 (0.81) 1.09 (0.35) one.66 (0.77)

Female White 0.74 (0.88) 3.26 (0.92) i.94 (0.91) 2.53 (1.09) one.13 (0.forty) ii.09 (0.89)
NA 1.05 (0.93) 3.23 (0.87) one.94 (0.94) 2.51 (1.01) 1.17 (0.forty) 2.12 (0.87)
NA-mixed 0.81 (one.01) 3.nineteen (0.99) 1.95 (0.97) 2.58 (1.10) i.23 (0.63) 2.08 (0.94)
Hispanic 0.61 (one.01) 3.21 (1.01) two.05 (0.97) 2.55 (1.08) i.17 (0.49) 2.07 (0.93)
Other 0.86 (0.93) 3.16 (1.02) one.82 (0.82) ii.46 (ane.04) 1.19 (0.51) 2.10 (0.89)
All Girls 0.81 (0.92) 3.24 (0.93) ane.94 (0.92) 2.53 (one.07) one.16 (0.44) 2.10 (0.89)

In contrast to BMI, there were no significant ethnic grouping differences or ethnic group by gender interactions for AA, OWS, or BE. Notwithstanding, there were meaning gender differences for both torso image variables (AA and OWS) and for all three eating-related behaviors (BE, Pb, and WCB (p
< .001). In all cases, females were significantly more than dissatisfied with appearance, more concerned about weight and shape, and more than engaged in risky eating behaviors than males. In the example of PB, at that place were also significant ethnic group differences. Post-hoc comparisons showed that the both the NA and NA-mixed groups had significantly higher PB scores than their White peers. Finally, at that place were significant ethnic group differences, as well as a meaning ethnicity by gender interaction in the case of WCB scores (p
< .001). Group differences in WCB scores are shown in
Figure 1, which illustrates that girls uniformly had significantly higher WCB scores than males and that NA males had significantly higher scores, on average, than their peers.


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Object name is nihms25983f1.jpg

Group mean Weight Control Beliefs (WCB) scores (± 1
SD) for each of five ethnicity and gender subgroups. Analysis of variance confirmed meaning chief effects for ethnic group and gender likewise as a significant interaction, as illustrated mainly past male group differences (all
p
< .001).

Correlations among BMI and MRFS domain scores

In order to assess the degree of association among BMI
z-scores and the five MRFS domain scores, bivariate (Pearson’south) correlations were calculated separately for each ethnicity and gender subgroup also equally for all males and all females. The post-obit correlations were considered meaning if
p
< .01.

Because females starting time, BMI was significantly correlated with OWS and WCB for all five female person groups. BMI was also significantly correlated with AA for four of the v female groups, with the exception of Hispanic girls. BMI was not significantly correlated with Be for any of the female groups. OWS and AA were significantly positively correlated for all girls combined and for four of the v female person subgroups, with the exception of the NA girls (for whom the AA domain was not reliable). It may be noteworthy that bingeing (Exist) and purging (PB) were positively correlated with each other but for the White girls, although the PB, in this case, had only moderate internal reliability (r
= .616). BE was significantly correlated with WCB scores amid females in full general (p
< .001) and amid the White and NA-mixed but not the NA female groups. Finally, OWS was significantly correlated with Pb for females in general and for each of the individual female subgroups. Although there were many differences between groups in the magnitudes of the above correlations, none of these differences were statistically significant.

Amongst males, regardless of ethnicity, BMI was significantly correlated with the OWS and WCB. In this regard males were similar to females. Somewhat more surprising was the fact that amidst the NA boys BMI was significantly positively correlated with purging behavior (Atomic number 82) and that purging was significantly positively correlated both with weight and shape concerns (OWS) and with weight control behaviors (WCB).

Native American cultural identity

A number of previous studies accept suggested that individuals who identify more than with the White cultural ideal of thinness may be at greater risk for body dissatisfaction and eating disorders than individuals who maintain more than traditional cultural values. Perhaps differences in cultural identity between the NA and NA-mixed groups might account, at least in part, for the differences between these groups in BMI and ED risk. As noted higher up, a much smaller per centum of participants in the NA-mixed grouping reported speaking English equally their chief language at home. This might suggest a greater level of acculturation to the White, English-speaking culture amid members of this group. Consistent with this idea, when we compared these two groups in terms of their Native American Cultural Identity (NACI), we plant a highly significant divergence (χ2
(3) = fourteen.62,
p
= .002,
Cramér’s 5
= .152) with a smaller percentage of the NA-mixed grouping holding traditional Native cultural values. To make up one’s mind whether NACI significantly predicted differences in ED risk, we carried out additional analyses (ANOVAs) using information from the NA and NA-mixed groups, with NACI and gender equally independent variables and each of the MRFS domain scores and BMI as dependent variables. In the case of BMI, there were marginally significant main effects both of NACI (F
(1, 499) = 3.10,
p
= .026) and gender (F
(i, 499) = five.12,
p
= .024), but no significant interaction. In full general, males and those who reported more than traditional Native American values tended to have higher BMI
z-scores. In that location were as well highly significant main furnishings of NACI on WCB scores (F
(1, 627) = 4.34,
p
< .005) and gender (F
(1, 627) = viii.xiv,
p
= .004) but no NACI-by-gender interaction. In this instance, girls and those reporting more traditional values had college average WCB scores. In the case of weight and shape concerns (OWS), the effect of NACI was not significant (F
(3, 627) = 2.52,
p
= .057). At that place were no meaning effects of NACI on either binge eating (Exist) or purging behaviors (PB).

Discussion

BMI-related differences

Based on previous research we expected Native American students, irrespective of gender, to have significantly higher BMI
z-scores than their peers. To our surprise the rates of overweight amid the NA participants in the present study exceeded even those reported in previous large-scale studies. Zephier, Himes, and Story (1999), for instance, surveyed more than 12,000 Native American children and adolescents from 16 tribes in Iowa, Nebraska, North, and S Dakota and found that 38% of girls and 39% of boys were above the 85thursday
percentile for historic period and gender, while 18% of girls and 22% of boys were above the 95th
percentile. By comparing we plant that 51% of NA girls and 54% of NA boys were above the 85th
percentile, while 31% of NA girls and 43% of NA boys were above the 95th
percentile. Remarkably, well-nigh twice as many students in the NA group were at or above the 95th
percentile of BMI-for-age and gender compared to all other groups, including the NA-mixed group (Tabular array 3).

The fact that participants in the NA-mixed group, despite identifying themselves as Native American, had BMI
z-scores similar to their not-Native peers, suggests that these individuals differ substantially from their peers with two Native parents. The failure to separate participants according to the number of Native American parents may, in part, account for the lower reported BMI
z-scores for Native Americans in previous large-scale surveys (e.chiliad., Zephier et al., 1999). However, the greater overweight in our study may also reflect truthful differences among tribal groups or across geographic locations. Conspicuously there is a crucial need for additional data on this result derived from representative national samples that are assess periodically over fourth dimension.

Although the BMI differences associated with differences in Native American Cultural Identity suggest that Native adolescents holding more “traditional” values have significantly college BMI
z-scores, these differences were rather small-scale – on the order of about 0.3
z-score units compared to the CDC norms – and probably cannot business relationship for the large BMI differences between the NA and NA-mixed groups. Clearly, acculturation is only one of many potentially important differences between NA and NA-mixed groups that may account for some part of this BMI departure. Other factors such every bit degree of Native inheritance, socioeconomic status, family unit cohesion, strength of social back up networks, and other factors may as well contribute to this difference. Sorting out the relative contributions of these factors volition crave a great deal more careful research.

Torso Size Preference

Although we made no
a priori
predictions, we plant significant ethnic group and gender differences in terms of body size preference as indicated by FRS deviation scores (Table 4). Most striking was the difference among female person groups in the percentages who reported wanting a larger body size. While only four.6% of White girls reported wanting to be larger, more than twice this percentage of NA girls (ix.6%), and more than 3 times as many NA-mixed (14.1%) and Hispanic (15%) girls said they wanted to be larger. Differences in size preference among male groups were less pronounced and it is specially notable that fewer NA males indicated a desire to be larger compared to all other male person groups. This is probably related to the fact that, on boilerplate, NA boys were already substantially larger than their not-Native peers (Table iii). Consistent with previous research (Rinderknecht & Smith, 2002), a significantly larger percentage of boys than girls reported wanting to exist a larger size and nearly 60% of both genders reported a preference for a size unlike than their electric current body size.

BMI and ED Chance

One of the main purposes of the nowadays study was to investigate the relationships amid BMI, body concerns, and potentially risky eating behaviors. Every bit noted in the introduction, previous enquiry has suggested that the relationship between BMI and body dissatisfaction may vary amid ethnicity and gender groups. For instance, Yates et al., (2004) found that BMI was strongly correlated with torso dissatisfaction among some groups, including White females and Filipino males, merely less strongly correlated amid others, including White males and Japanese females. Similarly, Caradas et al. (2001) in a study of Black and White South African girls, reported that although Black girls had significantly higher BMIs than White girls, White girls had significantly more body shape concerns than Blackness girls.

Based on such evidence, we predicted that BMI would be positively correlated with weight and shape concerns and with risky eating behaviors for all indigenous groups and both genders and, further, that the forcefulness of this association would vary amid groups. Our data revealed a more than circuitous picture than predicted with many similarities but also some notable differences amidst ethnicity and gender subgroups. As expected, BMI was strongly positively correlated with weight and shape concerns (OWS) and with dieting and exercising to control weight (WCB) among all ethnic groups and both genders. Among females BMI was too significantly correlated with negative appearance appraisement (AA) for all but the Hispanic girls. In contrast to dieting and exercising behaviors (assessed by WCB), BMI was non associated with binge eating or purging behaviors among most male or female groups. One exception was the surprising finding that BMI was significantly positively correlated with purging behavior (PB) amid the NA boys. Further research will be needed to confirm (and brainstorm to sympathize) this unexpected event for NA boys. Also unexpected was the finding that binge eating and purging were significantly positively correlated with each other only among White girls. The fact that a stiff binge-purge association was not establish for Native American girls, may suggest that Native girls are less likely to develop bulimic symptoms. However this is simply speculation at nowadays, since no studies of prevalence rates for clinical eating disorders among Native Americans are currently bachelor.

Within female groups we found ethnic grouping differences similar to those reported previously by others (east.k., Caradas et al., 2001; Stevens et al., 1999; Yates et al., 2004). Thus, it appears that although they are thinner than other female person groups in this study, White females are less likely to want to be larger, are equally or more dissatisfied with their current body size, and are equally likely to be engaging in risky weight control behaviors than their not-White peers. Finally, consequent with previous research, we found many indigenous and gender differences in the forcefulness of association between BMI and measures of ED risk; notwithstanding, none of these differences reached the level of statistical significance.

Ethnic and Gender Differences in ED Risk

Equally expected, pregnant gender differences were found for all of the MRFS risk domains, with females at higher apparent take a chance than males. Even so, there were as well ii notable ethnic group differences. In the showtime instance, a pregnant gender difference and a significant ethnicity by gender interaction was found in the case of the WCB variable.
Figure 1
shows that the interaction was due mainly to Native American males engaging in more weight command efforts than all other male groups. Another potentially important ethnicity difference was the finding that NA and NA-mixed groups had significantly higher hateful purging (Lead) scores than their White counterparts. This difference together with the finding of a significant positive correlation betwixt BMI and purging amid NA boys, suggests that purging behavior may be a serious problem for Native adolescents, particularly for overweight boys. This may foreshadow fifty-fifty greater future issues if the obesity epidemic in Native American communities continues to grow.

Native American Cultural Identity

Many factors associated with cultural or indigenous differences accept been proposed as possible sources of differences in eating bug or ED risk. Although the current study was non specifically designed to investigate such factors, we expected that Native Americans, specially girls, who were more than acculturated to the White norms and values, might show more weight concerns and more risky eating behaviors than their more traditional peers. Although Native American Cultural Identity significantly associated with two ED chance factors, the direction of these associations was non as predicted. In the first example, we establish a small but meaning difference in BMI
z-scores with higher scores amongst individuals belongings more than traditional Native values. This may reflect an credence of larger trunk sizes by more than traditional Native participants. In addition, participants holding more traditional Native values reported significantly college WCB scores. Thus, contrary to the “two-world” hypothesis, information technology appears that greater ED run a risk is associated with
less, rather than more, acceptance of modern or White majority values among Native adolescents.

Summary of Results

Regardless of ethnicity or gender, BMI was positively correlated with body concerns and weight control behaviors. The electric current study institute a much higher percentage of Native American adolescents of both genders who were overweight than in previous studies. Further, more twice as many Native American and Hispanic girls, as White girls, reported wanting a larger torso size. Boys with two Native parents were more likely than other boys to be engaged in weight command behaviors, including purging behaviors, to command their weight. Although girls reported more body concerns and more risky behaviors than boys, regardless of ethnicity, boys indicated substantial weight and shape concerns and were just slightly less likely than girls to engage in risky weight control behaviors. A particularly notable and robust finding was that Native participants from families with merely i Native parent were much
less likely
to be overweight, to accept weight and shape concerns, or to engage in risky eating behaviors than their peers with two Native American parents. Finally, Native participants who were more acculturated to White majority values (i.e., held less traditional values) were significantly
less likely
to be overweight, to express body weight concerns, or be engaged in risky eating behaviors.

Strengths and Limitations

1 of the major strengths of the present study is the size of the Native American sample. Although some large school-based surveys have previously obtained measures of BMI and weight control behaviors in multiethnic samples including Native adolescents (e.g., French et al., 1997; Neumark-Sztainer et al., 2002), none to our knowledge, have carefully examined the relationships among BMI, weight and shape concerns and weight control behaviors. In this sense, the present results confirm and extend previous findings suggesting that Native American adolescents may be at particularly loftier gamble of eating-related problems.

A serious limitation of this report was the poor reliability of some MRFS measures for some ethnicity or gender subgroups. We chose the McKnight Gamble Factor Survey because information technology had been used previously in multiethnic boyish studies and covered a wide range of potential risk factor domains (Taylor et al., 2003). Unfortunately, some of these domains proved unreliable with our sample. Given the multifaceted nature of the body epitome concept (Thompson, 2004), future research will be needed to further clarify the most important cognitive and behavioral dimensions of torso image and how best to assess them given the credible diversity of ethnicity and gender differences. This is peculiarly important when non-English speakers are involved. In add-on, more robust measures of restrictive eating, exercising to command weight, as well as binge eating and purging may be needed for hereafter cantankerous-cultural and cantankerous-gender research. Some other limitation is that we were non able to explore a larger range of the many potentially of import determinants of indigenous differences in ED risk. Although our data suggest that Native Americans with ane versus 2 Native parents are quite dissimilar in term of BMI and some measures of ED risk, much more needs to exist done to determine the relative roles of genetics and environment. Aside from genetic heritage, environmental factors such as socioeconomic condition, family dynamics, acceptance of Western values, and availability of social support systems need to be examined in much more item.

Acknowledgments

This work was supported by a grant from the National Institutes of Wellness, MH062050. We wish to thank the many undergraduate and graduate students at Montana Land University-Billings and Montana State University-Bozeman who assisted in the data collection and preliminary assay.

Footnotes

1Individual items making upwardly specific domains from the McKnight Hazard Factor Survey (version four for grades vi-12), were used to assess torso image concerns and eating behaviors, can me seen by accessing the link to the to the appropriate “survey” and the “scoring guide” at the Stanford University, Laboratory for the Report of Behavioral Medicine website: http://bml.stanford.edu/mcknight/. To correct the scoring guide, Advent Appraisal items should be Q19 reverse scored, Q31, and Q54.

2An unpublished manuscript describing the procedures used to validate the photographic method used to assess height and weight in the present study, and comparing the results to standard anthropometric methods, is available from the corresponding author upon request.

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