Volume
8: No. 2, March 2011
Debra Haire-Joshu, PhD; Byron W. Yount, MA; Elizabeth L. Budd, MPH; Cynthia Schwarz,
MPH, MS, RD; Rebecca Schermbeck, MPH, MS, RD; Scoie Green, MPH; Michael Elliott, PhD
Suggested citation for this article: Haire-Joshu D, Yount BW, Budd EL, Schwarz C, Schermbeck R, Green S, et al. The
quality of
school wellness policies and energy-balance behaviors of adolescent mothers. Prev Chronic Dis 2011;8(2):A34.
http://www.cdc.gov/pcd/issues/2011/mar/10_0021.htm. Accessed [date].
PEER REVIEWED
Abstract
Introduction
In this study, we 1) compared the quality of school wellness policies among schools participating in Moms
for a Healthy Balance (BALANCE), a school- and home-based weight loss study conducted with postpartum adolescents
in 27 states; and 2) assessed the relationship between policy quality with energy-balance behaviors and body mass index
z scores of postpartum adolescents.
Methods
As a part of BALANCE, we collected data on high-calorie food and beverage
consumption, minutes
spent walking, and height and weight for 647 participants. The School Wellness Policy Coding Tool was used to assess the strength and comprehensiveness of school district wellness policies from 251 schools attended by participating adolescent mothers.
Results
Schools averaged low scores for wellness policy comprehensiveness and strength. When compared with participants in schools with the lowest policy comprehensiveness scores, adolescent mothers in schools with the highest scores reported consuming
significantly fewer daily calories from sweetened beverages while reporting
higher consumption of water (P = .04 and P = .01, respectively). School wellness policy strength was associated with lower BMI
z scores
among adolescent mothers (P = .01).
Conclusion
School wellness policies associated with BALANCE may be limited in their ability
to promote a healthy school environment. Future studies are needed to evaluate the
effect of the strength and comprehensiveness of policy language on energy balance in high-risk postpartum adolescents. Evidence from this work can provide additional guidance to federal or state government in mandating not only policy content, but
also systematic evaluation.
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Introduction
Approximately 18% of adolescents aged 12-19 years or 9 million youth in the
United States are overweight (1). The risk of
overweight is significantly heightened for the approximately 500,000 adolescents
who become pregnant each year (2). Postpartum weight retention exacerbates the
risk of development of overweight, impaired glucose tolerance, type 2 diabetes,
and other diseases (3-7). Strategies addressing high-risk patterns among
adolescent mothers may have important public health implications, as postpartum
weight retention may compound with future pregnancies and timely interventions
may mitigate the intergenerational transfer of high-risk behaviors (4,8).
Environmental and policy interventions for food and activity environments may be effective strategies for preventing childhood obesity (9). Policy interventions create population access to environments that promote healthy options (10,11). Some policy initiatives have targeted schools (12). Children may spend up to 10 hours per day at school, which accounts for much of their physical activity and as many as 2 meals and 2 snacks per day. The Child Nutrition and
WIC (Women, Infants, and Children)
Reauthorization Act of 2004 (Public Law 108-265), which went into effect in 2006-2007, required all local education agencies participating in the National School Lunch Program to create a school wellness policy that included goals for achieving energy balance through healthy dietary intake and physical activity behaviors (13-15).
To date, preliminary data have shown mixed results regarding the quality of school wellness policies (12). Variations in measures used in evaluating policies make interpretation of findings challenging and limit the opportunity for comparative analyses of school wellness policies across communities and states (16,17). Schwartz and colleagues (18) developed a measure to evaluate the quality of school wellness policies across common criteria for comprehensiveness (ie, breadth of areas covered)
and strength (ie, degree to which policies included specific and firm language).
In this study, we
1) compared the quality of school wellness policies of schools participating in Moms
for a Healthy Balance (BALANCE) (19), a school-
and home-based weight loss study conducted with postpartum adolescents across 27 states; and 2) assessed the relationship
between policy quality with energy-balance behaviors and body mass index (BMI)
z scores of postpartum adolescents.
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Methods
Design and sample
BALANCE was a group-randomized, nested-cohort study developed and designed in partnership with Parents As Teachers (PAT), a national parenting and child development program (20). We recruited postpartum adolescents who retained their pregnancy weight to participate in the BALANCE weight-reduction protocol.
We used data from BALANCE baseline assessments that participants completed
between January 2007 and April 2008. As part of our BALANCE
study during 2008-2009, we collected school wellness policies from the websites of schools or school districts attended by our participants. If the policy was unavailable on the website, we contacted the school and requested a copy. We also verified that collected policies were in effect in 2006-2007.
We recruited 1,330 ethnically diverse participants into BALANCE who were enrolled in PAT Teen Parent Programs
from 27 states
(Appendix A). In addition to enrollment in the PAT Teen Parent Program (for ages 13-19 y),
eligibility criteria included 1) a willingness to participate throughout the study period,
2) being less than 1 year postpartum, and 3) not being pregnant or planning to become pregnant during the study period. For our analysis, we further excluded participants who had either graduated or withdrawn from school (n = 275), were currently breastfeeding (n = 109), or were missing residential zip code and school
information (n = 299). In total, 647 postpartum adolescents located in 251 schools from 203 school districts in 27 states, contributed to our findings. The institutional review board of Washington University in St. Louis approved this study.
Our sample had a mean age of 17.2
(standard deviation 1.1 y). Forty-eight percent were white, 30% were black, and
22% were other; most were receiving some form of aid from either WIC (91%) or the federally sponsored free or reduced-lunch program (40%),
and they were approximately
6 months postpartum (182 days). Approximately half of participants were at a normal
weight and half were overweight or obese.
Measures
Participants’ height and weight were collected by trained PAT staff to determine BMI
z score classification according to criteria specified for adolescents
by National Health and Nutrition Examination Survey procedures (21).
Adolescents then completed the online Snack and Beverage Food Frequency Questionnaire (SBFFQ), which was used to measure specific high-calorie snack and beverage
consumption patterns of participants. Following a similar format to that of the Diet History Questionnaire (22), the SBFFQ examined each participant’s intake of 31 items during the previous 7 days by asking
on how many days, how many times per day, and how much of the item the participant consumed. Food items were assessed by subgroups:
sweetened beverages (eg, soda and fruit juice), salty snacks (eg, potato chips), sweet snacks (eg, hard candy), meal-type snacks (eg, french fries), fruits and vegetables, and water consumption. Intake was converted into the total calories consumed for each individual food item and summed to obtain the daily calorie total. The test–retest reliability for the separate measures ranged from moderate to substantial with the following intraclass correlation coefficients: water (.71), sweetened
beverages (.68), salty snacks (.43), meal-type snacks (.64), and fruits and vegetables (.46) (23). The test–retest reliability for the composite measure of total calories was acceptable (.63).
Physical activity was measured with 3 items asking participants how many minutes they spent walking at a slow, brisk, or very brisk pace on the 2 weekdays preceding completion of the measure, and
on 1 weekend day (24). Participants reported their age,
race/ethnicity, education level, breastfeeding status, and postpartum status. They also reported their participation in aid programs (WIC and the National School Lunch Program),
which we used as indicators of socioeconomic
status.
We used the 96-item School Wellness Policy Coding Tool developed by Schwartz and colleagues (18) to assess the strength and comprehensiveness of the school wellness policies in each school district (Appendix
B). Each of the 96 content items was coded with a score of 0, if the item
was not mentioned; 1, if the item was a “weak” statement making it hard to
enforce because of vague, unclear, or confusing language; or 2, meaning the item
“meets or exceeds expectations” since it was mentioned in a specific and
directive manner suggesting commitment to enforcement
(Table 1).
Data analysis
Data analyses were conducted in 2 stages. First, we sought to determine the comprehensiveness and strength scores of school wellness policy language for school districts attended by our participants. Second, we sought to relate the overall comprehensiveness and strength of school wellness policy language to the measured energy-balance behaviors and BMI
z scores of BALANCE participants. All analyses were conducted by using SPSS version 17.0
(SPSS, Inc, Chicago, Illinois).
We evaluated the language quality for each policy item of the coding tool by the percentage of school districts with a rating of “meets or exceeds expectations.” For assessing the language quality of the 7 policy sections and the overall district policy score, we computed the sample mean and standard deviation for both comprehensiveness and strength with methods suggested by Schwartz
and colleagues (18).
The school wellness policy language scores for both comprehensiveness and strength were split into low, middle, and upper tertiles. We compared demographic characteristics of BALANCE participants among school wellness policy language tertiles
with χ2, Kruskal-Wallis, or 1-way analysis of variance tests, as indicated by measurement level. Univariate, general linear models were constructed to assess the relationship between school wellness policy
comprehensiveness and strength tertiles and measured energy-balance behaviors.
We explored the possibility that relationships between policy language quality
and energy-balance behaviors may vary by either race/ethnicity or BMI, by
testing the race/ethnicity × policy score tertile and BMI
× policy score tertile
cross-product terms. Final models were adjusted for race/ethnicity, as both the
scoring of policy quality and energy consumption of snacks appeared to vary by
race/ethnicity in our sample. The statistical assumptions underlying each test were checked for violations (eg, homogeneity of variances and outlying and influential
cases). Given that our sample had little variation regarding school wellness policy comprehensiveness
or strength scores, we selected the 40 highest and 40 lowest scoring districts
for further analysis.
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Results
District school wellness policies
Appendix B displays the 96 items measured by the policy coding tool and the percentage of districts with policies that received a rating of
2 (meets or exceeds expectations). In general, federally mandated statements accounted for a high percentage of items that met or exceeded expectations in each section. Five school districts had policies that did not address any of the 7 sections of the policy coding tool. The section that received the highest number of zero ratings
was nutrition standards for competitive and other foods and beverages (n = 101 school districts); the least number of zero ratings was
for standards for US Department of Agriculture child nutrition programs and school meals (N = 16 school districts).
Relationship of policy quality to dietary intake, physical activity, and BMI
z score
When assessed for group differences across tertiles of school wellness policy comprehensiveness and strength scores, race/ethnicity and BMI
z score were unbalanced
(Table 2). Specifically, white mothers were more commonly found in districts with the highest policy rating, while black mothers were more commonly found in districts with the lowest policy rating. Additionally, the lower tertiles of both comprehensiveness and strength scores included adolescents with higher BMI
z scores, though
the group comparison was not significant for policy strength. We found no evidence of effect modification for either race/ethnicity or BMI when considering the relationship between school wellness policy quality and energy-balance behavior outcomes. In our initial adjusted models assessing snack and physical activity behaviors of participants, we found no significant relationships between policy comprehensiveness or strength tertile and energy-balance behaviors.
In the 40 school districts that had the highest scores for policy comprehensiveness, adolescent mothers reported consuming fewer daily calories from sweetened beverages
and more water
(Table 3). There was an
inverse relationship between policy comprehensiveness and strength and salty,
sweet, and meal-type snacks and total snack calories. Policy strength was
significantly associated with a lower BMI z score and was also inversely related
to sweetened beverage consumption.
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Discussion
Four findings from this study can expand research related to policy initiatives associated with promoting energy-balance behaviors among adolescent mothers. First, our study suggests that items that are mandated in school wellness policies are most likely to meet or exceed expectations for quality language when compared with nonmandated items. This study also supports previous studies that have found that strong mandatory language, as opposed to recommended language, has the greatest
effect on food access (12,25). Clarification of school wellness policy language by the federal government to address both strength and scope of content may further enhance the
effect of school wellness policies for adolescent mothers. State governments have the best knowledge of needs, possible incentive programs, and the financial situation of their state when crafting the model policies for school districts.
Second, our study suggests there are differences in the quality of policies that have
an educational focus compared with those focused on behavioral outcomes. Previous studies have reported variations in the extent to which nutrition or physical activity topics are included in school wellness policies (26). We were able to expand on this work and systematically measure and compare both the comprehensiveness and strength of nutrition and physical activity focused topics in policies
among multiple states and school districts (18). Of particular note was that 2 of the sections (establishing nutrition standards for competitive and other foods and beverages, physical education) requiring language for policy actions directly related to regulating food access and time to be physically active scored the lowest for comprehensiveness and strength. In contrast, sections scoring the highest included evaluation and nutrition education, which each focused on establishing goals
or documenting a plan for implementation as opposed to mandating immediate changes in the environment (25,27,28). Further study is warranted to describe reasons for these differences, barriers to the development and implementation of strong and comprehensive policies, and the extent to which they may
affect behavior (9,29-31).
Third, our study found that schools associated with PAT
programs for adolescent parents have generally weak wellness policies in place. Additionally, there appeared to be a relationship between the presence of weak policies and energy-balance behaviors of adolescent mothers. For example, the most comprehensive policies were associated with adolescent mothers consuming 136 fewer calories from sweetened drinks per day
and by 17 ounces more water per day. Indeed,
substantial literature suggests a relationship of sweetened beverages to obesity (32,33). Others have also found sweetened beverage intake was altered by school environmental changes (11,14). Our study contributes to this literature by further suggesting the value of policy quality in addressing beverage intake in schools as a possible mechanism for preventing obesity.
Finally, from a translational perspective, our findings suggest the importance of defining the model content of quality school wellness policies, and effectively communicating to parents as to whether this content is present in school policies (9,34,35). Currently, adolescents or their parents have no way of adequately judging the quality of the wellness policy
that directly influences the school environment. The overwhelming presence of
weak school wellness policies might mislead parents or adolescents into thinking their educational environment practices and reinforces positive eating and activity behaviors. Our results, consistent with those of other studies, suggest that in fact this may be the case (12,26). Wellness report cards or other strategies for communicating the strength and comprehensiveness of school policies to parents in easily understandable ways
are needed (36-38).
Limitations
Our study had several limitations. First, this is a cross-sectional study that does not allow for assessment of temporal relationships.
We did not assess policy effect or implementation which may vary by school district. We had limited information on the school districts in our sample, so were unable to address heterogeneity and generalizability issues. Many of the policies under observation were not required until the start of the
2006-2007 academic year, which may not provide enough time to see the full effect of the policies on measured behaviors. We also present information on
a group that may not be generalizable to broader school-district populations. Finally, interpretation of our findings should be considered within the limitations of self-report measures.
Conclusion
School wellness policies associated with PAT programs for adolescent mothers
in multiple states may be limited in their ability to promote a healthy school environment. Improvements in the quality of school wellness policies may help to enhance the school environment and, in turn, energy-balance behaviors of adolescents. Future studies, reflecting naturalistic or prospective designs, are needed to evaluate the
effect of the strength and comprehensiveness of policy language on energy
balance in high-risk postpartum teenagers. Evidence from this work can provide additional guidance to federal or state government in mandating not only policy content, but systematic evaluation. To
be active advocates for their adolescent, parents need to be accurately informed about the quality of the wellness policies in their adolescent’s school. Quality assurances are needed so that school wellness policies are not missed opportunities for encouraging energy-balance
behaviors and preventing obesity among adolescent mothers.
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Acknowledgments
This project was funded by the National Cancer Institute
of the National Institutes of Health (grant no. USPHS 1 R01 CA121534).
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Author Information
Corresponding Author: Debra Haire-Joshu, PhD, Center for Obesity Prevention and Policy Research, George Warren Brown School of Social Work and School of Medicine, Washington University in St. Louis, 660 S Euclid, Campus Box 8109, St. Louis, MO 63110. Telephone: 314-362-9554. E-mail:
djoshu@wustl.edu.
Author Affiliations: Byron W. Yount, Elizabeth L. Budd, Cynthia Schwarz, Rebecca Schermbeck, Scoie Green, Michael Elliott, Washington University in St. Louis, St. Louis,
Missouri.
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References
- Health United States, 2008 with chartbook. Hyattsville (MD): National
Center for Health Statistics; 2009.
- Martin JA, Hamilton BE, Sutton PD, Ventura SJ, Menacker F, Kirmeyer S,
et al. Births: final data for 2006.
Natl Vital Stat Rep 2009;57(7).
- Crowell DT.
Weight
change in the postpartum period. A review of the literature. J Nurse
Midwifery 1995;40(5):418-23.
- Gunderson EP, Abrams B.
Epidemiology of gestational weight gain and body weight changes after
pregnancy. Epidemiol Rev 2000;22(2):261-74.
- Rössner S, Ohlin A.
Pregnancy as a risk factor for obesity: lessons from the Stockholm Pregnancy
and Weight Development Study. Obes Res 1995;3 Suppl 2:267s-75s.
- Ohlin A, Rössner S.
Trends
in eating patterns, physical activity activity and socio-demographic factors
in relation to postpartum body weight development. Br J Nutr
1994;71(4):457-70.
- Galtier-Dereure F, Boegner C, Bringer J.
Obesity and pregnancy: complications and cost. Am J Clin Nutr
2000;71(5):1242S-8S.
- Lederman S.
Pregnancy weight gain and postpartum loss: avoiding obesity while optimizing
the growth and development of the fetus. J Am Med Womens Assoc
2001;56(2):53-8.
- McKinnon RA, Orleans CT, Kumanyika SK, Haire-Joshu D, Krebs-Smith SM, Finkelstein EA, et al.
Considerations for an obesity policy research agenda. Am J Prev Med 2009;36(4):351-7.
- Story M, Kaphingst KM, French S.
The role of schools in obesity prevention. Future Child 2006;16(1):109-42.
- Story M, Kaphingst KM, Robinson-O’Brien R, Glanz K.
Creating healthy food and eating environments: policy and environmental approaches. Annu Rev Public Health 2008;29:253-72.
- Story M, Nanney MS, Schwartz MB.
Schools and obesity prevention: creating school environments and policies to promote healthy eating and physical activity. Milbank Q 2009;87(1):71-100.
- Friedman RR, Schwartz MB.
Public policy to prevent childhood obesity, and the role of pediatric endocrinologists. J Pediatr Endocrinol Metab 2008;21(8):717-25.
- Gostin LO.
Law as a tool to facilitate healthier lifestyles and prevent obesity. JAMA 2007;297(1):87-90.
- Jaime PC, Lock K.
Do school based food and nutrition policies improve diet and reduce obesity? Prev Med 2009;48(1):45-53.
- Longley CH, Sneed J.
Effects of federal legislation on wellness policy formation in school districts in the United States. J Am Diet Assoc 2009;109(1):95-101.
- Swinburn B.
Obesity prevention in children and adolescents. Child Adolesc Psychiatr Clin N Am 2009;18(1):209-23.
- Schwartz MB, Lund AE, Grow HM, McDonnell E, Probart C, Samuelson A, et al.
A comprehensive coding system to measure the quality of school wellness policies. J Am Diet Assoc 2009;109(7):1256-62.
- Center for Obesity Prevention and Policy Research: projects. Washington University in St. Louis; 2009.
http://opc.wustl.edu/projects.html. Accessed May 20, 2010.
- Parents as Teachers. Parents as Teachers National Center, Inc. St. Louis; 2005.
http://www.parentsasteachers.org/. Accessed May 20, 2010.
- National Health and Nutrition Examination Survey: anthropometry procedures
manual; 2008.
http://www.cdc.gov/nchs/data/nhanes/nhanes_07_08/manual_an.pdf. Accessed May 20, 2010.
- Subar AF, Thompson FE, Kipnis V, Midthune D, Hurwitz P, McNutt S, et al.
Comparative validation of the Block, Willett, and National Cancer Institute food frequency questionnaires: the Eating at America’s Table Study. Am J Epidemiol 2001;154(12):1089-99.
- Landis JR, Koch GG.
The measurement of observer agreement for categorical data. Biometrics 1977;33(1):159-74.
- Pate RR, Koch GG, Ross R, Dowda M, Trost SG, Sirard JR. Validation of a 3-day physical activity recall instrument in female youth. Pediatr Exerc Sci 2003;15(3):257-65.
- Metos J, Nanney MS.
The strength of school wellness policies: one state’s experience. J Sch Health 2007;77(7):367-72.
- Nanney MS, Nelson T, Wall M, Haddad T, Kubik M, Laska M, et al.
State school nutrition and physical activity policy environments and youth obesity. Am J Prev Med 2010;38(1):9-16.
- Probart C, McDonnell E, Weirich JE, Schilling L, Fekete V.
Statewide assessment of local wellness policies in Pennsylvania public school districts. J Am Diet Assoc 2008;108(9):1497-502.
- Nanney MS, Davey C.
Evaluating the distribution of school wellness policies and practices: a framework to capture equity among schools serving the most weight-vulnerable children. J Am Diet Assoc 2008;108(9):1436-9.
- Larson N, Story M. A review of environmental influences on food choices. Ann Behav Med 2009;38(Suppl):S56-73.
- Sallis JF, Linton LS, Kraft MK, Cutter CL, Kerr J, Weitzel J, et al.
The Active Living Research program: six years of grantmaking. Am J Prev Med 2009;36(2 Suppl):S10-21.
- Taylor WC, Sallis JF, Lees E, Hepworth JT, Feliz K, Volding DC, et al.
Changing social and built environments to promote physical activity: recommendations from low-income, urban women. J Phys Act Health 2007;4(1):54-65.
- Nelson MC, Story M.
Food environments in university dorms: 20,000 calories per dorm room and counting. Am J Prev Med 2009;36(6):523-6.
- Wang YC, Bleich SN, Gortmaker SL.
Increasing caloric contribution from sugar-sweetened beverages and 100% fruit juices among US children and adolescents, 1988-2004. Pediatrics 2008;121(6):e1604-14.
- Haire-Joshu D, Elliott MB, Caito NM, Hessler K, Nanney MS, Hale N, et al.
High 5 for Kids: the impact of a home visiting program on fruit and vegetable intake of parents and their preschool children. Prev Med 2008;47(1):77-82.
- Owen N, Glanz K, Sallis JF, Kelder SH.
Evidence-based approaches to dissemination and diffusion of physical activity interventions. Am J Prev Med 2006;31(4 Suppl):S35-44.
- Greves HM, Rivara FP.
Report card on school snack food policies among the United States’ largest school districts in 2004-2005: room for improvement. Int J Behav Nutr Phys Act 2006;3:1.
- Presswood RF.
School health report card. School Nurse News 2005;22(4):27-32.
- Wisdom JP, Michael YL, Ramsey K, Berlin M.
Women’s health policies associated with obesity, diabetes, high blood pressure, and smoking: a follow-up on the
Women’s Health Report Card. Women Health 2008;48(1):103-22.
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