Weight Management Behaviors Among Mexican American Youth: Cross-Sectional Variation by Timing of Growth and Maturation

Abstract

Purpose:

To assess the association between growth and maturation with weight management behaviors (WMBs) among Mexican American youth.

Design:

A cross-sectional design was used to measure timing of growth and maturation as well as WMBs.

Sample:

Students were recruited through physical education classes in south Texas schools. The sample included 623 participants (52.3% female; 49.8% with weight ≥85th percentile) in grades 4 through 12. Students in middle school were purposely oversampled to examine questions around timing of growth and maturation.

Measures:

Growth was measured as maturity offset, an estimate of age at peak height velocity (PHV). Maturity offset is derived from chronological age, height, and sitting height measurements. Participants were classified as pre-PHV or post-PHV. Girls also were categorized as premenarche or early, average, or late maturing based on age at menarche. Weight was measured to calculate body mass index (BMI) percentile. Weight management behavior and timing of menarche were self-reported via a survey.

Analysis:

Descriptive characteristics were calculated for boys and girls separately. χ² Tests of proportion were used to test WMB by BMI percentile. Logistic regression analyses were conducted to examine the likelihood of engaging in WMB by maturity offset and, for girls, timing of menarche.

Results:

Students with weight ≥85th percentile were more likely to describe themselves as overweight and report trying to lose weight through exercise or calorie restriction (P < .0001). A 1-year increase in maturity offset was associated with youth being 31% more likely to perceive themselves as overweight but less likely to report calorie restriction (odds ratio [OR] = 0.87). Average maturing girls were more likely than premenarcheal girls to exercise, restrict calories, or fast to lose weight (OR = 3.27, 2.11, and 3.27, respectively).

Conclusion:

Mexican American youth are engaging in WMB, even when their weight status is <85th percentile. The appropriateness of weight management counseling may need to consider a child’s stage of growth.

Keywords

adolescence hispanic overweight development

Purpose

Almost 48% of high school students in the United States report trying to lose weight.¹ Weight loss attempts may be related to actually being overweight or obese, although attempts also may be due to concern about body size independent of actual body size.² Little is known about when youth begin weight management behaviors (WMBs) such as calorie restriction, taking diet pills, or excessive exercise. Surveillance data are limited to primarily high school students, a time after which WMB initiation likely has occurred for many students.³

Changes in body shape from growth and maturation may be a possible explanation for this discrepancy between body size and WMB among adolescents. Growth in height typically occurs about 9 months before weight gain for children and adolescents,⁴ where increases in stature may result in short-term improvement in physical self-perceptions, and body image satisfaction generally decreases throughout adolescence.⁵ However, less is known about participation in WMB among youth and whether weight management is related to measured weight status. Although weight gain is associated with normal growth, weight management is prevalent among high school students in the United States.¹ Thus, an examination of WMB at younger ages and potential relationships with growth and maturation is warranted.

Differences in body size and weight loss behavior may vary by race or ethnicity, although these differences are unclear. African American and Latino youth appear to have higher rates of overweight and obesity compared to white youth,⁶ but differences in body image perception among youth are conflicting,^7,8 with some studies finding African American youth less likely to perceive themselves as overweight.⁷ Weight loss behaviors among Latino youth are even less clear. Latino high school students report more attempts to lose weight than white students in national samples¹ and less attempts in others.⁹ Among high school students, Latino youth report higher prevalence of trying to lose weight, higher rates of not eating for 24 hours, higher rates of using diet pills or liquids, and higher rates of vomiting or laxative use than either white or black students.^1,10 Among a relatively large and ethnically diverse group of fifth grade students, Latino students also were found to report more weight loss attempts than white students.¹¹ Weight dissatisfaction in Mexican American middle school–age students was associated with overweight and obesity, and these children are also less likely to lose weight in traditional weight management programs.^12,13

Actual overweight or obesity may or may not be related to WMB. Nationwide, almost 14% of high school students are obese, with highest rates among white and Latino males. The prevalence of obesity is higher among black females (16.7%) than Latino females (11.2%). Almost 17% of high school students are overweight, with higher rates among black (19.1%) and Hispanic (18.3%) students than white (15.6%) students.¹ Yet, nearly half (48%) of youth report weight management activities.¹

Because of the lack of data specifically on Hispanic or Latino populations, particularly across a wide age range, the purpose of the present study was to examine the likelihood of engaging in WMB among Hispanic youth. More specifically, associations of WMB with the timing of growth and maturation were considered, as were differences between boys and girls. It was expected that as children grew and matured, they would be more likely to engage in WMB. Even with overweight and obese children, weight management is not always appropriate,¹⁴ as categorizing youth during a growth spurt for height or fatness may lead to misclassification (ie, early maturer as overweight). Growing children are usually counseled to maintain weight as they grow.¹⁵ Consideration of growth and maturation may provide more accurate assessments of whether a child is overweight, particularly for physicians who can track development over time. Furthermore, timing and tempo of growth may vary by race, ethnicity, or geographic origin.¹⁶ For example, Mexican American youth may have younger ages at the largest growth spurt and timing of the first period for girls (ie, peak height velocity [PHV] and menarche) relative to their non-Hispanic white peers.¹⁶ Therefore, the purpose of this study was to assess the association between cross-sectional markers of growth and maturation (ie, maturity offset and age at menarche) with WMB among Mexican American youth. It was expected that WMB would be greater in youth who were classified as overweight, were past PHV, and for girls who had attained menarche.

Methods

Design

A cross-sectional study was performed in partnership with an evaluation of school physical education programming at elementary, middle, and high schools. Schools were selected by the district as representatives of geographic and socioeconomic characteristics (eg, location within the district, proportion of students receiving free or reduced price lunch). Approximately 3800 students received study information. Parent permission forms were sent home with all children in elementary schools. Students in grades 6 to 12 self-selected into taking home a parent permission form. Reasons why parents did not return signed permission forms were not ascertained. Students who returned signed parent permission forms also provided child assent or written informed consent for participants aged 18 years or older. Participants then completed a cross-sectional survey and had anthropometric measures taken by trained study personnel. All procedures and measures were approved by the Committee for the Protection of Human Subjects at the University of Texas Health Science Center Houston prior to beginning recruitment and enrollment.

Sample

Students enrolled in grades 4 through 12 in a school district in south Texas were recruited to participate in the study. Students in middle school (grades 6-8) were oversampled to capture the variation in growth and maturation. The majority of students enrolled in the district schools were Hispanic (99%). A total of 826 students participated in the study (response rate of 21.7%), 236 from elementary schools, 434 from middle schools, and 156 from high schools. Additional information on variables collected in the study has been published previously.¹⁷

Measures

Anthropometrics

Height (cm) and sitting height (cm) were measured using a portable stadiometer (ShorrBoard; Weigh and Measure, LLC, Olney, Maryland). Weight (kg) was measured using a portable digital scale (Health-O-Meter HM-753KL, McCook, IL). The scale was periodically calibrated for accuracy. All measures and reliability estimates were taken following the protocol by Lohman et al.¹⁸ The technical error of measurement (TEM) for each variable was calculated to establish intra- and interrater reliability prior to data collection. The TEM% for intrarater reliability ranged from 0.07 to 0.40, was generally higher for sitting height, and was below the acceptable limit of 1.5%. The TEM% for interrater reliability was 0.11 for height and 0.40 for sitting height, below the acceptable limit of 2.0%. Staff were checked periodically for drift and reestablished reliability as needed. Percentage body fat was measured via bioelectrical impedance analyzer (BIA; Tanita TBF-300A, Tokyo, Japan). The mean percentage error rates for BIA fat-free mass range from −7.0% to 10.7%.¹⁹ However, BIA has a strong correlations with dual-energy X-ray absorptiometry ranging from 94%²⁰ to more than 98%.¹⁹ Sitting height was subtracted from total height to calculate leg length (cm).

Maturity offset

Maturity offset was calculated using the formula inclusive of sitting height by Moore et al.²¹ Participants were classified as pre-PHV (negative maturity offset values) or post-PHV (positive values). Participants in the error zone (−0.5 to 0.5) were excluded. Body mass index (BMI) percentile was determined using clinical growth charts from the Centers for Disease Control and Prevention. In analyses using maturity offset category or estimated age at PHV, 59 participants were excluded for being too young (<8 years) or too old (≥17 years) for the maturity offset calculations, 15 were excluded for being within the error region, and 77 were excluded for having maturity offset values outside the valid range.²² Negative maturity offset values indicate the number of years until estimated PHV, whereas positive values suggest the number of years since estimated PHV.

Demographics and age at menarche

Students self-reported their date of birth, sex, and grade in school. Girls self-reported if they had attained menarche, and if so, at what age (in years). Girls were categorized as early (<11.8 years), average (11.8-13.8 years), or late maturing (>13.8 years) based on age at menarche.

Weight management behaviors

Participants responded to 7 items on body weight. Questions were from the 2009 Youth Risk Behavior Survey²³ and included: “How do you describe your weight?,” with response options from “very underweight” to “very overweight”; “Which of the following are you trying to do about your weight?,” with response options of “lose weight,” “gain weight,” “stay the same weight,” or “I am not trying to do anything about my weight.” Five yes/no items assessed weight control behaviors during the past 30 days: exercise to lose weight; eat less food/fewer calories, foods low in fat; go without eating for 24 hours or more; take any diet pills/powders/liquids; and vomit or take laxatives. Forty-six participants did not provide complete weight management strategy data. χ² Tests of proportions with sex, BMI category, and maturation category (ie, pre- vs post-PHV) were run to examine whether nonresponders to these items differed from responders, and independent samples t tests were used to check differences in chronological age. Students who did not respond to these items were more likely to be pre-PHV (χ² = 6.289, P = .012) and were approximately 0.9 years younger (t = 3.60, P = .000). No other differences were detected. Students missing these data were excluded from analyses.

Analysis

Means, standard deviations, and independent samples t tests by sex were calculated for chronological age, BMI percentile, maturity offset, estimated age at PHV, and age at menarche (girls only). Frequencies and χ² tests of proportion were calculated by sex for weight status (≥85 percentile of weight for sex and age), proportion post-PHV, and maturation status (pre, early, average, or late age at menarche). χ² Tests of proportion also were used to examine the differences in WMB by sex. As weight is confounded with growth, χ² tests of proportion were used to test the associations of weight status (ie, BMI percentile) with WMB, growth timing, and maturational timing. Separate multiple logistic regression analyses were conducted to examine the likelihood of engaging in WMB by estimated age at PHV and, for girls, timing of menarche. Logistic regression analyses controlled for sex, maturity offset, and BMI percentile category. Age was not included as a covariate because it is part of the maturity offset equations and, in the present sample, shared 63.4% of the variance with maturity offset. The significant relationships between BMI percentile and WMB justify the inclusion of BMI percentile as a covariate in the regression analyses.

Results

Sample characteristics for the 623 included participants are shown in Table 1. Briefly, participants had a mean age of 11.69 years, were 52.3% female, and 49.8% were in the 85th percentile or higher for weight for height. The majority of participants were in middle school (grades 6-8, 63.6%), with 29.2% in grades 4 to 5 and 7.2% in high school. More girls than boys were post-PHV (35.3% vs 13.8%, respectively, P < .0001). Overall, the girls in the sample were early maturing (11.01). Very few participants indicated taking diet pills or vomiting or taking laxatives to lose weight (n = 10, n = 12, respectively). Even though the boys were chronologically older (P < .0001), they were further away from attaining their PHV (P < .0001).

Table 1.

Sample Characteristics by Gender Including Weight Management Behaviors.^a

Variable	Girls (n = 326)		Boys (n = 297)		T
Variable	M	SD	M	SD	T
Chronological age	11.38	1.44	12.02	1.82	4.81^b
BMI percentile	70.14	28.70	73.89	29.87	1.60
Maturity offset	−0.53	1.21	−1.69	1.46	−10.67^b
Estimated age at PHV	11.92	0.42	13.71	0.53	46.54^b
Premenarche (n = 170)	11.82	0.34	–	–	–
Postmenarche (n = 137)	12.04	0.46	–	–	–
Age at menarche (n = 141)	11.01	1.18	–	–	–
	%	N	%	N	χ²
≥85% of weight for sex and age	45.4	148	54.6	162	5.201^c
Post-PHV	35.3	115	13.8	41	38.172^b
Premenarche	55.4	170	–	–	–
Early maturation (<11.8 years at menarche)	28.7	88	–	–	–
Average maturation (11.8 to 13.8 years)	16.0	49	–	–	–
Late maturation (>13.8 years at menarche)	0	0	–	–	–
Describe self as slightly or very overweight	33.2	108	33.7	100	0.014
Trying to change weight					16.561^d
Lose weight	57.7	188	54.2	161
Gain weight	3.7	12	12.1	36
Exercising to lose weight	73.3	239	75.7	225	0.487
Restricting calories	51.5	167	53.2	157	0.174
	Girls (n = 223)		Boys (n = 215)
Fasted for 24 hours or more to lose weight^e	15.7	35	11.2	24	0.165
Taken diet pills, powders, or liquids^e	2.2	5	2.3	5	0.942
Vomited or taken laxatives^e	1.8	4	3.7	8	0.217

Abbreviations: BMI, body mass index; M, mean; PHV, peak height velocity; SD, standard deviation.

^aNineteen girls did not complete the age at menarche question. One girl reported an age at menarche in the late maturing range but did not complete the weight-related questions and therefore was not included in the analyses.

^b P < .0001.

^c P < .05.

^d P < .01.

^eElementary school students (n = 182) were not asked about fasting, taking diet pills, vomiting, or laxative use. Three additional students did not answer these questions.

Table 2 presents the results of WMB by the BMI percentile group. There were consistent trends across items such that a greater proportion of students in the higher BMI percentiles engaged in WMB. Students who were in the 85th percentile or higher for weight were more likely to describe themselves as slightly or very overweight (χ² = 181.85), report trying to lose weight (χ² = 198.80), and trying to lose weight through exercise (χ² = 59.92) or calorie restriction (χ² = 76.27; P < 0.0001 for all tests).

Table 2.

Proportion of Students Engaging in Weight Management Behaviors by BMI Percentile.^a

	BMI Percentile		χ²
	<85.0 (n = 313)	≥85.0 (n = 310)	χ²
Growth status			3.861^b
Pre-PHV	71.6	78.4
Post-PHV	28.4	21.6
Sitting height to height			5.023^b
Legs longer than torso	11.2	6.1
Legs shorter than torso	88.8	93.9
Maturational Timing (Girls Only)	<85.0 (n = 158)	≥85.0 (n = 149)	χ²
Premenarche	55.6	55.1	4.905
Early maturation (<11.8 years at menarche)	24.9	33.3
Average maturation (11.8 to 13.8 years)	19.5	11.6
Weight Management Behaviors	<85.0 (n = 258)	≥85.0 (n = 382)	χ²
Describe self as slightly or very overweight	8.0	59.0	181.850^c
Trying to lose weight	28.1	84.2	198.798^c
Exercising to lose weight	61.0	88.1	59.919^c
Restricting calories	34.8	69.9	76.273^c
	<85.0 (n = 229)	≥85.0 (n = 209)	χ²
Fasted for 24 hours or more to lose weight^d	8.73	18.7	9.238^e
Taken diet pills, powders, or liquids^d	1.3	3.4	2.037
Vomited or taken laxatives^d	0.9	4.8	6.190^b

Abbreviations: BMI, body mass index; PHV, peak height velocity.

^aProportions are interpreted as the percentage within a BMI percentile category that engages in each weight management behavior or is in a given growth or maturation category.

^b P < 0.05.

^c P < 0.0001.

^dElementary school students (n = 195) were not asked about fasting, taking diet pills, vomiting, or laxative use. Three additional students chose not to answer these questions.

^e P < 0.01.

A smaller proportion of students in the 85th percentile or higher for weight were post-PHV. There were no differences in timing of menarche by BMI percentile (Table 2). The sitting height to stature ratio was significantly different by BMI percentile, where participants in the 85th percentile or higher for weight had slightly higher ratios (ie, shorter leg length) relative to students below the 85th percentile for weight (0.52 ± 0.03 and 0.52 ± 0.01, respectively, P = .043).

Maturity offset (ie, estimated years until or since PHV) was significantly associated with participants perceiving themselves as overweight and with eating less to lose weight. As shown in Table 3, for every 1-year increase in maturity offset, students were 1.313 times more likely to perceive themselves as overweight (95% confidence interval [CI]: 1.13-1.54). However, for eating less to lose weight, for every year increase in maturity offset, participants were 0.87 times less likely to report eating less to lose weight (CI: 0.76-0.98).

Table 3.

Logistic Regression Models Predicting Weight Management Behaviors From Growth Status.

Variable	Perceive Self as Overweight		Trying to Lose Weight		Exercising to Lose Weight		Eating Less to Lose Weight
Variable	OR	95% CI	OR	95% CI	OR	95% CI	OR	95% CI
Sex, females (ref = males)	0.98	0.63-1.51	1.53	1.00-2.36	0.89	0.59-1.36	1.26	0.87-1.82
BMI percentile ≥85th (ref ≤ 85th)	19.05	11.71-31.01	15.10	10.05-22.70	4.77	3.16-7.22	4.36	3.10-6.13
Maturity offset	1.318	1.13-1.54	1.09	0.95-1.26	1.10	0.95-1.27	0.87	0.76-0.98

Abbreviations: BMI, body mass index; CI, confidence interval; OR, odds ratio.

There were no differences in trying to lose weight or exercising to lose weight by maturity offset values. Also, there were no differences in likelihood of WMB in females compared to males. As expected, students who were in the 85th percentile or higher were significantly more likely to report weight loss behaviors relative to students whose weight for height was less than the 85th percentile (Table 2).

Table 4 provides the multiple logistic regression results assessing the relationship between menarcheal timing and WMB. Average maturing girls were 2.85 times more likely than premenarcheal girls (95% CI: 1.22-6.67) to perceive themselves as overweight. Similarly, girls who were average maturing were 3.27 times more likely than premenarcheal girls (95% CI: 1.40-7.65) to indicate they exercised to lose weight and 2.11 times more likely to indicate eating less to lose weight (95% CI: 1.07-4.17). Both early maturers (OR = 3.63, 95% CI: 1.35-9.73) and average maturers (OR = 3.27, 95% CI: 1.07-9.99) were more likely than premenarcheal girls to report fasting. There were no significant differences by maturation category in reports of trying to lose weight nor were there any significant differences between early and average maturing girls.

Table 4.

Multiple Logistic Regression Models Predicting Weight Management Behaviors From Maturation Status.^a

Variable	Perceive Self as Overweight		Trying to Lose Weight		Exercising to Lose Weight		Eating Less to Lose Weight		Fasting
Variable	OR	95% CI	OR	95% CI	OR	95% CI	OR	95% CI	OR	95% CI
BMI percentile ≥85th	16.68	8.72-31.94	12.53	6.99-22.49	4.47	2.47-8.12	3.70	2.28-6.01	2.38	1.09-5.17
Menarcheal timing
Early	1.17	0.61-2.24	1.02	0.55-1.90	1.87	0.99-3.54	1.34	0.77-2.31	3.63	1.35-9.73
Average	2.85	1.22-6.67	1.98	0.94-4.15	3.27	1.40-7.65	2.11	1.07-4.17	3.27	1.07-9.99

Abbreviations: BMI, body mass index; CI, confidence interval; OR, odds ratio.

^aReference group for BMI ≤ 85th. Reference group for menarcheal timing = premenarcheal.

Discussion

The purpose of this study was to examine the association of growth and maturation timing with WMB in a sample of Mexican American youth. Students in this sample who were normal or underweight for height and age engaged in WMB, more so than in other studies.^24,25 Interestingly, there were no differences in the proportion of students engaging in WMB by weight status. This may be problematic for healthy growth and maturation, particularly for adolescent girls who gain body fat as a normal part of puberty. Although all students reported WMBs, regardless of weight status, the proportion of participants using more extreme weight loss strategies such as laxatives or pills was lower than in other large-scale studies of Minnesota and Connecticut high school students.^24,25 It is unclear why this may be the case as access to these methods is unlikely to be different from 1 large city to another.

Maturity offset, a cross-sectional indicator of growth timing, was related to perceptions of being overweight. As students got closer to, or passed, PHV, the likelihood of perceiving oneself to be overweight increased. This finding may be explained by the increase in body fat as part of the normal process of development. Body shapes and sizes change throughout adolescence, and body image dissatisfaction are known to increase during this period.²⁶ This finding is similar to those in athletic samples where body image dissatisfaction, such as perception of overweight, increases as children grow and mature.²⁷ Interestingly, increases in maturity offset were associated with being less likely to eat less to lose weight. Students who were closer to, or past, PHV also were chronologically older. Therefore, they may have access to other types of weight management strategies, such as opportunities for unsupervised exercise, fasting that goes unnoticed, or taking laxatives or pills. However, the number of students reporting those behaviors in this sample was small, precluding inferences on this point. Future research may consider examining the changes in weight management strategies over time in adolescent populations.

The results of this study also suggest a relationship between timing of menarche and WMB. Interestingly, the findings did not support our hypothesis. In the present sample, girls who were average maturers were more likely to engage in weight management strategies, as opposed to early maturers, perhaps because they had more recently experienced PHV and beginning to notice peak weight velocity at the time of the study. There were no late maturers in this sample, an interesting finding on its own, but Mexican American girls do mature earlier on average than their non-Hispanic white peers.²⁸ Being overweight or obese may be associated with earlier maturation.²⁹ And although nearly half of the girls in this sample were in the 85th percentile or higher for weight, there were no differences in the proportion of early or average maturing girls above the 85th percentile. Thus, this does not fully explain the absence of late maturers. However, being overweight or obese may mask physical changes in body shape and size. Menarche generally occurs approximately 1 year after PHV and is associated with changes in body shape such as widening of the hips and an increase in fat tissue.

In this sample where early maturation was prominent, estimated age at PHV occurred approximately 1 year after menarche. This finding may be indicative of previous assertions questioning the validity of maturity offset in early maturing populations.^30
–32 However, the difference in estimated age at PHV between girls who were pre- and postmenarche was 0.22 years (2.64 months). Similarly, a closer look at relative leg to torso length (sitting height to stature ratio) by proportion of above and below 85th percentile indicated those above the 85th percentile had proportionately shorter legs, a typical characteristic of earlier maturation associated with earlier closure of growth plates. Nevertheless, these characteristics may be associated with the perception of being overweight and therefore increase WMB.

The reason for such early ages at menarche (31% reported age at menarche of 10 years or younger) in a sizeable portion of the sample is unclear. The literature on weight status and menarche appears to be mixed, with some studies showing that overweight and obesity can bring on early menarche and others finding no differences.^33,34 In a review of growth and maturation among Mexican American youth, the average age at menarche in south Texas girls is about the same as in other populations.¹⁶ But, Malina et al¹⁶ consistently state that the Mexican American youth are shorter and lighter than their non-Mexican origin counterparts. Given the rates of overweight and obesity in this area among adults (currently around 80%),³⁵ it may be possible that the youth in this area are still shorter but now heavier than their peers. A question for future consideration is whether this potential for increased weight status is enough to bring on early menarche, and if so, what impact is there on WMB. This question though should be asked relative to the familial connection of maturational timing as evidenced by mother–daughter correlations between ages at menarche.^36,37

Also of interest was that there were no differences in WMB between boys and girls. More boys than girls reported trying to gain weight, yet in total these participants represented less than 8% of the sample (Table 2). The proportion of youth who were overweight or obese in this sample was much higher than in a sample from the same geographic region from more than 30 years ago.³⁸ One possible explanation may be that in the adult population in this area, approximately 4 of 5 adults are overweight or obese.³⁵ It is possible that because the social normative weight status is heavier, cultural expectations of thinness for girls³⁹ may not be the same in this area of the country.

This study contributes to the evidence by considering the role of WMB in the context of growth and maturation. Although this is one of the few studies to examine weight management among Mexican American youth, these findings are not without limitations. The cross-sectional design precludes discussion of causation. Even with the sample including students across a wide age range, future studies utilizing a longitudinal design will provide stronger data of the link between growth, maturation, and weight management strategies. Furthermore, although maturity offset can be a reliable measure of growth at a single point in time,^21,22 there are some limitations to this measure, particularly for early maturers.^30,31 Also, the reliability of this measure for Mexican American youth has not yet been assessed. Children may grow in the same pattern of height first then weight. However, the equations estimating age at PHV may be different for Hispanic versus non-Hispanic adolescents.²¹

The findings from this study suggest that weight management strategies are being used by Mexican American youth, even for those with a normal weight status. Timing of growth was associated with WMB, particularly for youth who were past their estimated growth spurt, suggesting PHV and associated peak weight velocity typically occurring approximately 9 months after PHV⁴ may trigger WMB. Future studies may consider using a longitudinal design to assess the timing of when Mexican American youth begin to monitor and try to lose weight relative to their current growth status and physical characteristics. Contextual factors such as pressure or expectations from friends, family, or cultural values also may be assessed. As the adult population in this area has a high prevalence of overweight and obesity, changes in societal expectations may be the reason that more than half of participants reported trying to lose weight. School personnel and public health practitioners may be more cognizant of weight management strategies among growing children and whether weight loss is appropriate in the context of typical changes associated with growth and maturation. Talking points can include the following: (1) Changes in body shape and size are a normal part of growth and maturation and (2) The growth spurt has 2 noticeable components, height, which is likely associated with positive self-perceptions, and weight, associated with negative perceptions, particularly among girls but not boys who more often strive to gain weight.

So What? Implications for Health Promotion Practitioners and Researchers

What is already known on this topic?

Changes in body shape and size are a normal part of growth and maturation. Studies among girls suggest that weight management behaviors may be related to the timing of development.

What does this article add?

This study examined the relationship between estimated growth and timing of maturation among Mexican American youth, an underrepresented group in the weight management literature. Perceptions of overweight were correlated with estimated age at peak height velocity, whereas timing of menarche was associated with more weight management behaviors.

What are the implications for health promotion practice or research?

Mexican American youth may be engaging in weight management behaviors at young ages when they are still developing. Schools and youth organizations may provide opportunities to discuss healthy weight status and management.

Footnotes

Authors’ Note

All procedures performed in studies involving human participants were in accordance with the ethical standards of the institutional and/or national research committee and with the 1964 Helsinki declaration and its later amendments or comparable ethical standards.

Declaration of Conflicting Interests

The author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Funding

The author(s) received no financial support for the research, authorship, and/or publication of this article.

References

Kann

Kinchen

Shanklin

; Centers for Disease Control and Prevention (CDC). Youth risk behavior surveillance—United States, 2013. MMWR Suppl. 2014;63(suppl 4):1–168.

Calzo

Sonneville

Haines

Blood

Field

Austin

. The development of associations among body mass index, body dissatisfaction, and weight and shape concern in adolescent boys and girls. J Adolesc Health. 2012;51(5):517–523.

Eaton

Kann

Kinchen

; Centers for Disease Control and Prevention (CDC). Youth risk behavior surveillance—United States, 2011. MMWR Suppl. 2012;61(4):1–162.

Haywood

Getchell

. Life Span Motor Development. Champaign, IL: Human Kinetics; 2014.

Eisenberg

Neumark-Sztainer

Paxton

. Five-year change in body satisfaction among adolescents. J Psychosom Res. 2006;61(4):521–527.

Huh

Stice

Shaw

Boutelle

. Female overweight and obesity in adolescence: developmental trends and ethnic differences in prevalence, incidence, and remission. J Youth Adolesc. 2012;41(1):76–85.

Martin

May

Frisco

. Equal weights but different weight perceptions among US adolescents. J Health Psychol. 2010;15(4):493–504.

van den Berg

Mond

Eisenberg

Ackard

Neumark-Sztainer

. The link between body dissatisfaction and self-esteem in adolescents: similarities across gender, age, weight status, race/ethnicity, and socioeconomic status. J Adolesc Health. 2010;47(3):290–296.

Chao

Pisetsky

Dierker

. Ethnic differences in weight control practices among U.S. adolescents from 1995 to 2005. Int J Eat Disord. 2008;41(2):124–133.

10.

Demissie

Lowry

Eaton

Nihiser

. Trends in weight management goals and behaviors among 9th-12th grade students: United States, 1999-2009. Matern Child Health J. 2015;19(1):74–83.

11.

Epperson

Song

Wallander

. Associations among body size, body image perceptions, and weight loss attempts among African American, Latino, and White youth: a test of a mediational model. J Pediatr Psychol. 2014;39(4):394–404.

12.

Dalton

III Johnston

Foreyt

Tyler

. Brief report: weight dissatisfaction, weight status, and weight loss in Mexican-American children. J Pediatr Psychol. 2008;33(6):673–677.

13.

Johnston

Moreno

Regas

Tyler

Foreyt

. The application of the Yerkes-Dodson law in a childhood weight management program: examining weight dissatisfaction. J Pediatr Psychol. 2012;37(6):674–679.

14.

National Heart, Lung and Blood Institute. Integrated Guidelines for Cardiovascular Health and Risk Reduction in Children and Adolescents, Overweight and Obesity. U.S. Department of Health and Human Services. http://www.nhlbi.nih.gov/health-pro/guidelines/current/cardiovascular-health-pediatric-guidelines/full-report-chapter-10. Published October 2012. Updated January 2013. Accessed June 27, 2016.

15.

Division of Nutrition, Physical Activity, and Obesity, National Center for Chronic Disease Prevention and Health Promotion Tips for Parents—Ideas to Help Children Maintain a Healthy Weight. 2015. http://www.cdc.gov/healthyweight/children/. Updated May 15, 2015. Accessed June 27, 2016.

16.

Malina

Martorell

Mendoza

. Growth status of Mexican American children and youths: historical trends and contemporary issues. Am J Phys Anthropol. 1986;29(S7):45–79.

17.

Shelnutt

Gay

Monsma

. The relationship between substance use, body image, and social physique anxiety amongst school-aged adolescents on theTexas/Mexico border. J Behav Health. 2015;4(2):33–38.

18.

Lohman

Roche

Martonell

. Anthropometric Standardization Reference Manual. Champaign, IL: Human Kinetics; 1988.

19.

Horlick

Arpadi

Bethel

. Bioelectrical impedance analysis models for prediction of total body water and fat-free mass in healthy and HIV-infected children and adolescents. Am J Clin Nutr. 2002;76(5):991–999.

20.

Rubiano

Nunez

Heymsfield

. A comparison of body composition techniques. Ann N Y Acad Sci. 2000;904:335–338.

21.

Moore

McKay

Macdonald

. Enhancing a somatic maturity prediction model. Med Sci Sports Exerc. 2015;47(8):1755–1764.

22.

Mirwald

Baxter-Jones

ADG

Bailey

Beunen

. An assessment of maturity from anthropometric measurements. Med Sci Sports Exerc. 2002;34(4):689–694.

23.

Centers for Disease Control and Prevention. Youth Risk Behavior Survey (YRBS) Item Rationale for the 2009 Core Questionnaire. 2012. http://www.cdc.gov/healthyyouth/yrbs/questionnaire_rationale.htm. Accessed April 27, 2009. Updated April 28, 2016.

24.

Boutelle

Neumark-Sztainer

Story

Resnick

. Weight control behaviors among obese, overweight, and nonoverweight adolescents. J Pediatr Psychol. 2002;27(6):531–540.

25.

Neumark-Sztainer

Story

Hannan

Perry

Irving

. Weight-related concerns and behaviors among overweight and nonoverweight adolescents: implications for preventing weight-related disorders. Arch Pediatr Adolesc Med. 2002;156(2):171–178.

26.

Thompson

Chad

. The relationship of pubertal status to body image, social physique anxiety, preoccupation with weight and nutritional status in young females. Can J Public Health. 2000;91(3):207–211.

27.

Gay

Monsma

Torres-McGehee

. Developmental and contextual risks of social physique anxiety among female athletes. Res Q Exerc Sport. 2011;82(2):168–177.

28.

Himes

. Examining the evidence for recent secular changes in the timing of puberty in US children in light of increases in the prevalence of obesity. Mol Cell Endocrinol. 2006;(254-255):13–21.

29.

Ahmed

Ong

Dunger

. Childhood obesity and the timing of puberty. Trends Endocrinol Metab. 2009;20(5):237–242.

30.

Gay

Monsma

Smith

DeFreese

Torres-McGehee

. Assessment of growth and maturation in female athletes at a single point in time. Women Sport Phys Act J. 2014;22(2):76–82.

31.

Malina

Claessens

Van Aken

. Maturity offset in gymnasts: application of a prediction equation. Med Sci Sports Exerc. 2006;38(7):1342–1347.

32.

Malina

Kozieł

. Validation of maturity offset in a longitudinal sample of Polish boys. J Sports Sci. 2014;32(5):424–437.

33.

Currie

Ahluwalia

Godeau

Nic Gabhainn

Due

Currie

. Is obesity at individual and national level associated with lower age at menarche? Evidence from 34 countries in the health behaviour in school-aged children study. J Adolesc Health. 2012;50(6):621–626.

34.

Demerath

Towne

Chumlea

. Recent decline in age at menarche: the Fels Longitudinal Study. Am J Hum Biol. 2004;16(4):453–457.

35.

Fisher-Hoch

Rentfro

Salinas

. Socioeconomic status and prevalence of obesity and diabetes in a Mexican American community, Cameron County, Texas, 2004-2007. Prev Chronic Dis. 2010;7(3):A53.

36.

Damon

Reed

Valadian

. Age at menarche of mothers and daughters, with a note on accuracy of recall. Hum Biol. 1969;41(2):160–175.

37.

Towne

Czerwinski

Demerath

Blangero

Roche

Siervogel

. Heritability of age at menarche in girls from the Fels Longitudinal Study. Am J Phys Anthropol. 2005;128(1):210–219.

38.

Zavaleta

Malina

. Growth, fatness, and leanness in Mexican-American children. Am J Clin Nutr. 1980;33(9):2008–2020.

39.

Swami

. Cultural influences on body size ideals. Eur Psychol. 2015;20(1):44–51.