Abstract
Objectives. We investigated the body mass index (BMI; weight in pounds/[height in inches]2 × 703) of parents whose children participated in Shape Up Somerville (SUS), a community-based participatory research study that altered household, school, and community environments to prevent and reduce childhood obesity.
Methods. SUS was a nonrandomized controlled trial with 30 participating elementary schools in 3 Massachusetts communities that occurred from 2002 to 2005. It included first-, second-, and third-grade children. We used an inverse probability weighting estimator adjusted for clustering effects to isolate the influence of SUS on parent (n = 478) BMI. The model’s dependent variable was the change in pre- and postintervention parent BMI.
Results. SUS was significantly associated with decreases in parent BMIs. SUS decreased treatment parents’ BMIs by 0.411 points (95% confidence interval = −0.725, −0.097) relative to control parents.
Conclusions. The benefits of a community-based environmental change childhood obesity intervention can spill over to parents, resulting in decreased parental BMI. Further research is warranted to examine the effects of this type of intervention on parental health behaviors and health outcomes.
Acknowledging that childhood overweight and obesity are influenced by a multitude of factors, including a child’s environment, the Institute of Medicine recommends implementing multicomponent childhood obesity prevention efforts that involve the whole community.1 One approach is a school-centered, community-based environmental change (SCCB) intervention.2–5 This type of approach aims to alter the environments in which children live, learn, and play to help support and sustain physically active lifestyles and healthy dietary habits.
Shape Up Somerville (SUS) was a community-based participatory research study in Somerville, Massachusetts,2 that altered children’s household, school, and community environments to prevent and reduce childhood obesity. Over the 2–school year study, the body mass index (BMI; weight in pounds/[height in inches]2 × 703) z scores of children exposed to SUS decreased by −0.06 (95% confidence interval [CI] = −0.08, −0.04) relative to children residing in control communities.3 Although previous investigators speculated that the effects of SCCB or obesity interventions similar to SUS may spill over to other communities through regional networking6 and that after-school program benefits may spill over to nonexposed children,7 whether SCCB interventions influence the parents of exposed children has not been examined and merits investigation.
It is known that parental involvement may enhance the impact of obesity prevention efforts on child outcomes8,9 and that child obesity interventions targeting parents as the change agent reduce childhood obesity10; however, the question is whether SCCB interventions, such as SUS, may result in a reverse pathway, in which the child-focused intervention influences parent health outcomes. If SCCB interventions positively influence parent health outcomes, the public health benefits and return on investment of SCCB interventions are underestimated; society receives additional, adult-based benefits from resources expended to change children’s health behaviors. We investigated whether SUS influenced the BMI of parents whose children attended the schools involved in the SUS intervention.
The plausibility of SUS influencing parents’ BMIs arises from the community-based environmental change nature of the SUS intervention.2,3 By changing children’s environments, SUS altered adults’ environments as well. Adults residing in Somerville may have been exposed, intentionally or inadvertently, to many SUS components that could have affected their health behaviors and potentially their BMIs. For instance, opportunities to engage in physical activity that materialized from new city walkability and bikeability ordinances were accessible to all community members, not just children. Likewise, all Somerville residents could select healthier menu options at Somerville restaurants that materialized from the SUS restaurant component. SUS also included numerous education-based components that community members could have been exposed to, such as a regular column in the Somerville Journal and resource guides.
Although many SUS components were available to all community members, parents and guardians of school-aged children were more likely to be exposed to SUS school-based components than were adults without school-aged children. Parents of school-aged children were able to participate in school-based SUS events, whereas adults without school-aged children may not have been aware of or had access to these activities. For example, family newsletters with coupons and recipes, developed from formative work, were available only to parents of children attending SUS schools. Parents’ health behaviors may also have been indirectly influenced because of their child’s participation in SUS school-based components. Heim et al. found that school-based food taste testing events influence household fruit and vegetable availability.11
Despite the plausibility of SCCB interventions influencing adult health behaviors, to our knowledge, this study is the first to examine whether a SCCB intervention influenced adults’ BMIs. Specifically, we estimated SUS’s effect on parents’ BMIs with an ordinary least squares regression–inverse probability weighting (OLS-IPW) estimator.12–14 The OLS-IPW estimator adjusted for the selection bias that arose from SUS’s research design structure.
Detailed descriptions of SUS’s research design and components are provided elsewhere.2,3,15–18 Briefly, SUS used a community-based participatory research process2; the intervention components were designed to influence the physical activity levels and dietary habits of early elementary school children by altering the environments in which they interacted on a daily basis. Adults residing in the SUS community were exposed to numerous SUS components, including 100 SUS-sponsored, SUS-led, or SUS-initiated community-level events (e.g., the SUS 5-K family fitness fair), 21 SUS-approved restaurants,16 regular local media placements, and city walkability and bikeability ordinances. Parents of children attending SUS schools were also exposed to the intervention through parent forums, newsletters, family events, and their children. To encourage parent participation in the school-based events and components, SUS materials were printed in Somerville’s 4 dominant languages (Portuguese, Haitian-Creole, Spanish, and English), parent forums were held in each language, and opportunities to participate in SUS activities were offered in various formats. The box on the next page lists SUS’s components.
| Community Components | Household Components | School Components |
| SUS community advisory council | Parent outreach and education | Walk to school campaign |
| Ethnic minority group collaborations | Bimonthly newsletter | Walking to school bus |
| Support from local community champions | Coupons for free and reduced-price food products | Traffic calming tactics |
| Walking and pedestrian training | Family events | Walking contests |
| City of Somerville health events collaboration | Family nutrition forums | International walk to school day |
| City employee wellness campaign | Child’s health report card mailed each y | Safe routes to school maps |
| Farmers market initiative | Breakfast program before school | |
| Local physician and clinic staff training | Increase fresh fruits, low-fat milk, whole grains | |
| SUS-approved restaurantsa | Taste tests | |
| City ordinances on walkability and bikeability | Adult monitors | |
| Annual SUS 5-K family fitness fair | School health office | |
| Regular local media placement | Anthropometric equipment | |
| Monthly SUS column in the Somerville Journal | Height and weight data collection for children | |
| Resource guides | During-school food service | |
| Physical activity guide | Increase whole grains, fruits and vegetables, low-fat dairy | |
| Health meeting guide | Healthier a la carte snacks | |
| Health message translation booklet | Monthly taste tests | |
| New vegetarian recipes | ||
| Ice cream sold only 1 d/wk | ||
| New equipment to enhance food presentation | ||
| SUS classroom curriculum that included: 10-min daily “cool moves,” 30-min nutrition and physical activity lesson (∼1 wk), and fun and healthy giveaways | ||
| Enhance recess with new play equipment and game cards | ||
| School wellness policy development | ||
| School food service | ||
| Classroom environment | ||
| Physical education environment | ||
| Structured day environment | ||
| After-school environment | ||
| School health environment | ||
| To and from school environment | ||
| Professional development (nutrition and physical activity) for all school staff | ||
| Professional development for after-school program staff | ||
| Walk from school campaign | ||
| SUS after-school curriculum | ||
| Increase physical activity | ||
| Cooking lessons | ||
| Promote healthy snacks | ||
| Farm trips |
Note. SUS = Shape Up Somerville. SUS is a child-focused, school-centered, community-based environmental change obesity intervention.
a Criteria for SUS restaurant approval were having smaller-sized portions; having fruits and vegetables available as side dishes or entrees; having low-fat or nonfat dairy products (Asian restaurants exempted); highlighting healthier options on a menu board, the menu, a laminated sign, or a table tent; and displaying the SUS seal of approval on the restaurant door or window.
SUS was a nonrandomized controlled research trial with 30 participating elementary schools in 3 Massachusetts communities. The intervention spanned from the start of the 2003–2004 school year to the conclusion of the 2004–2005 school year.2 The treatment and control communities had similar socioeconomic characteristics, such as non–English-speaking households (range = 28%–36%), median household income (range = $39 507–$46 315), and percentage of households below the US Census Bureau–determined poverty level (range = 12.5%–14.5%).2 Researchers drew observations from children enrolled in first, second, and third grade. Treatment group children attended Somerville elementary schools (10 elementary schools). Control group children attended elementary schools in 2 communities (1 with 15 and the other with 5 elementary schools) outside the Somerville media market. Parents of treatment and control group children in all 3 communities were the units of analysis.
We obtained information pertaining to parents of treatment and control group children from pre- and postintervention self-administered questionnaires mailed to participating households. Researchers collected preintervention questionnaires at the beginning of the 2003–2004 school year and postintervention questionnaires at the end of the 2004–2005 school year. In addition to household and child physical activity and dietary habits, parents reported their anthropometric information and household sociodemographic information. SUS parents also responded to questions about their familiarity and exposure to SUS as well as questions regarding SUS-induced behavioral changes (e.g., dining out options, walking, reading more health material). Of the 975 households that returned the preintervention questionnaire, 335 were exposed to SUS.
The dependent variable was the change between parents’ pre- and postintervention BMIs. We calculated parents’ pre- and postintervention BMIs from self-reported height and weight provided on the pre- and postintervention questionnaires. We excluded parents whose reported height changed by more than 1.61 inches during the intervention from the data set for presumed reporting error. The 1.61-inch figure represents the SD of the mean difference between parents’ pre- and postintervention heights; the mean pre- and postintervention height difference was −0.006.
We measured the effect of SUS on parents’ BMIs with a binary treatment status variable that indicated whether parents belonged to the treatment group or the control group. We generated the model’s covariates from the pre- and postintervention questionnaires, which included preintervention BMI, marital status (married or not married), respondent’s age group (18–24, 25–29, 30–39, 40–49, or 50–59 years), gender (female or male), education (did or did not attend or graduate from college), nativity (was or was not born in the United States), primary household language (English or another language), and the child’s race (White or non-White).
The preintervention questionnaire focused on children and asked only for the responding parent’s age group. In 2-parent households, the responding parent’s age group served as a proxy for the other parent’s age group. Supporting this proxy, the mean age difference among 2-parent households of 14 794 children included in the 2006 to 2010 Medical Expenditure Panel Surveys19 was −2.3 years (95% CI = −2.5, −2.1). Although this difference falls within the age group gaps on the SUS questionnaire, it could result in parents being classified 1 group above or below their actual age group. Additionally, parent race was not included on the questionnaire. The race of the child served as a proxy for parent’s race. To reduce the noise this assumption may create, the race category in the model is White or non-White. In the Medical Expenditure Panel Surveys sample, 98.1% of children classified as White had parents who were also classified as White.
The model’s sample consisted of parents with pre- and postintervention BMIs. On the preintervention questionnaire, 293 treatment and 567 control households provided sufficient information to calculate the preintervention BMIs of 527 treatment parents and 1003 control parents. Among these parents, there was sufficient postintervention questionnaire information to calculate the postintervention BMIs of 162 treatment and 507 control parents. The primary focus of SUS data collection was children. For example, SUS researchers collected the anthropometric information of children at their schools, whereas adult anthropometric data were collected with a self-report, self-administered survey that parents had to mail back to SUS. The self-administered, mail-in survey coupled with the child focus on data collection helps to explain the low follow-up response rate of parents (treatment = 30.7%; control = 50.5%). The low follow-up response rates are a limitation of this study; however, the data provide a unique opportunity to explore whether a SCCB intervention also influences parents’ BMIs.
Relative to the preintervention treatment and control group samples, the postintervention treatment and control group samples had greater proportions of persons who attended or graduated from college, were White, were born in the United States, and spoke English as the primary household language.
We excluded parents whose children did not have pre- and postintervention anthropometric information (treatment, n = 20; control, n = 87) from the sample to help ensure that parents were exposed to SUS throughout the 2–school year study. Additionally, we excluded treatment and control parents because of missing covariate data (treatment, n = 6; control, n = 10) and unrealistic height changes (treatment, n = 14; control, n = 54). The final sample of 478 parents consisted of 122 treatment group parents and 356 control group parents.
Selection bias is inherent in nonrandomized research designs such as that used with SUS. We used an OLS-IPW estimator to isolate SUS’s treatment effect on parents’ BMIs while accounting for selection bias.12–14 The model adjusted for household-level clustering effects with the Huber–White sandwich estimator. The model estimates SUS’s treatment effect from the binary treatment status variable indicating whether a parent belonged to the treatment group or the control group.
The OLS-IPW estimator consists of an OLS in which the population is weighted with the inverse of the propensity score. Propensity score weights are commonly used to adjust treatment and control groups so the groups are similar on all covariates except treatment status20–23; this process reduces the likelihood of selection bias. Propensity scores represent the probability that an observation was assigned to the treatment group relative to the control group. We calculated observations’ propensity scores with a logistic regression using all the covariates except the treatment status variable, which served as the logistic regression’s dependent variable.
We conducted diagnostic regressions to examine pre- and postestimation covariate differences between treatment and control groups (covariate balance). Additionally, we conducted tests to verify that treatment and control parents had similar covariate distributions. To investigate whether the results were sensitive to the OLS-IPW method, we also estimated treatment effects with OLS as well as matching estimators.12,13,24,25 We estimated all models in Stata version 13.26
Table 1 lists covariate descriptive statistics for the 122 treatment and 356 control parents. The descriptive statistics illustrate the demographic diversity in both the treatment and control groups. Close to a quarter of the parents were born outside the United States and only 75.4% of treatment group parents and 63.5% of control group parents were classified as White. As illustrated in Table 2, statistical differences existed between the treatment and control groups across many covariates; these differences justify using OLS-IPW estimators to calculate SUS’s effect on parent BMI changes.
TABLE 1— Descriptive Statistics: Shape Up Somerville, MA
| Covariate | Treatment (n = 122) | Control (n = 356) |
| Female, % | 54.1 | 56.7 |
| Age, y, % | ||
| 18–24 | 0.0 | 0.8 |
| 25–29 | 4.1 | 11.5 |
| 30–39 | 45.1 | 49.4 |
| 40–49 | 48.4 | 36.0 |
| 50–59 | 2.5 | 2.2 |
| English is household language, % | 94.3 | 91.9 |
| White race, % | 75.4 | 63.5 |
| Married, % | 83.6 | 71.6 |
| US nativity, % | 77.9 | 76.7 |
| Attended or graduated from college, % | 73.8 | 43.8 |
| Preintervention body mass index | 25.1 | 26.8 |
| Treatment group onlya | ||
| Always or sometimes read the SUS newsletterb, % | 95.8 | |
| If received Somerville Journal, read SUS articles in the publication,c % | 86.2 | |
| Paid more attention to health-related material because of SUS,d % | 53.5 | |
| Started to walk more because of SUS,d % | 32.2 | |
| Selected healthier options when eating out because of SUS,d % | 56.5 | |
| Selected healthier snacks for their children because of SUS,d % | 59.7 |
Note. SUS = Shape Up Somerville. Body mass index is calculated as weight in pounds/(height in inches)2 × 703.
a Among treatment group parents who responded to the question.
b Possible responses were (a) always, (b) sometimes, (c) rarely, (d) never, (e) don’t know, (f) other.
c Possible responses were (a) yes; (b) no, I read the Somerville Journal but I didn’t see any articles about Shape Up Somerville; (c) no, I do not read the Somerville Journal. We considered only a response of (a) or (b).
d The question asked respondents if they made this change because of their child’s participation in SUS. Possible responses were (a) yes, (b) no, (c) don’t remember.
TABLE 2— Covariate Imbalance Before and After Propensity Score Weighting (PSW): Shape Up Somerville, Massachusetts
| P Value of Treatment Status Variable’s Coefficient | ||
| Covariate Used as Dependent Variable in Regression | Before PSW | After PSW |
| Female | .316 | .878 |
| Age, y | ||
| 18–24 | . . .a | . . .a |
| 25–29 | .086 | .966 |
| 30–39 | .53 | .948 |
| 40–49 | .068 | .933 |
| 50–59 | .903 | .987 |
| English is household language | .488 | .752 |
| White race | .064 | .977 |
| Married | .038* | .778 |
| US nativity | .812 | .839 |
| Attended or graduated from college | <.001* | .998 |
| Preintervention body mass index | .001* | .979 |
Note. Body mass index is calculated as weight in pounds/(height in inches)2 × 703. The covariate balance checks consisted of a series of regressions in which each covariate served as a dependent variable. Treatment status, along with a constant term, was the only independent variable in each covariate’s model. We used ordinary least squares to estimate covariate balance checks for continuous dependent variables and a logistic regression for binary dependent variables. A significant coefficient for the treatment status variable at a 5% significance level indicates covariate imbalance.
a There were no treatment parents in the aged 18–24 y group, preventing a model for this age group.
*Treatment group and control group differed at P < .05.
The descriptive statistics (Table 1) also demonstrate the familiarity of treatment parents with SUS material and that SUS resulted in self-reported behavioral changes for many of these parents. For instance, 95.8% of treatment parents either sometimes or always read the SUS newsletter; 86.2% of treatment parents who received the Somerville Journal read SUS articles in the newspaper; and 56.5% of the sample stated that they selected healthier options while eating out because of SUS.
The OLS-IPW results indicate that SUS was associated with BMI decreases in parents with school-aged children who participated in the SUS intervention relative to BMI changes among control group parents. The estimated treatment effect (the binary treatment status variable) of SUS on parents’ BMIs was a −0.411 BMI point change (95% CI = −0.725, −0.097). The statistically significant association between SUS and parent BMI decreases was not sensitive to the selected estimation method. When we used the alternative estimation models (OLS and matching estimator), a significant decrease was also present (data available upon request). Additionally, as illustrated in Table 2, the postestimation covariate balance check verified that the OLS-IPW estimator resulted in more balanced covariates.
SUS was associated with decreased BMIs among treatment group parents relative to control group parents. This illustrates that the benefits of a school-centered, community-based, childhood obesity environmental change intervention can spill over to parents. The magnitude of SUS’s parent treatment effect size corresponded with the upper range of 46 adult obesity interventions in a systematic review in which effect size calculations (i.e., BMI changes) were determined by weight changes and the Cohen d.27 However, in population-level interventions even a modest effect size is notable; the intervention targets multiple groups and may result in population-level changes.5 For instance, a mean BMI reduction of 0.5 points was estimated to reduce Australia’s projected 10-year population-wide increase in obesity from 5% to 1%.28 Similarly, SUS’s estimated treatment effect size would reduce the mean BMI of treatment parents from overweight to healthy weight. This population-level BMI shift accomplishes 1 of the Institute of Medicine’s adult obesity prevention goals: to reduce mean population-level BMIs to counter the deleterious effects of unhealthy weight status on adult health.1
SUS could influence parents’ BMIs by increasing parent physical activity levels, by altering parent dietary intake levels and content, or through both these mechanisms simultaneously. The SUS questionnaire asked treatment group parents whether they walked more or selected healthier options when eating out because of their child’s SUS participation. Among the treatment group parents that answered these 2 questions, 56.5% selected healthier options while eating out and 32.2% walked more (Table 1). Control group parents were not surveyed on these items, precluding comparisons and further analysis. Although these 2 questions do not adequately capture how SUS altered parent behavior, it appears many treatment group parents adjusted their physical activity habits and dietary choices during the SUS intervention.
SUS’s components were implemented as part of a multicomponent synergistic intervention and were not meant to be examined individually. SUS’s treatment effect on parents’ BMIs may have been because of the synergistic nature of the intervention in which each component was reinforced and magnified by its interaction with other SUS components.1 For instance, healthy dietary practice messaging in a school newsletter or the local media may have amplified parents’ selection of healthier menu items at local SUS-approved restaurants. Similarly, alterations in children’s preferences, brought about by SUS school-based components, might have indirectly amplified SUS-induced changes in parents’ physical activity levels and food-purchasing decisions; research has shown that children influence household consumption decisions29,30 as well as parental physical activity levels.31
The plausible interaction of SUS components across environments illustrates the importance of establishing consistent SCCB messaging and intervention components throughout a community. Stakeholder engagement and participation is critical to this practice. SUS used a community-based research participatory process to engage stakeholders from across school, government, community, and business sectors to help formulate and implement SUS and ensure consistent messaging throughout these sectors. For instance, by working with local restaurateurs, SUS researchers established the restaurant intervention,16 and by working with local government officials new city ordinances were passed, a government employee wellness program was established, and the City of Somerville created employment positions to oversee the SUS program.
By demonstrating that the benefits of SUS extended beyond the youths of Somerville, the results of this study illustrate that local firms and governments may benefit from investing in and supporting SCCB interventions in their communities. Empirical evidence illustrates that obesity is associated with increased health care expenditures and workplace absenteeism.32,33 Accordingly, the decrease in parents’ BMIs associated with SUS may translate into reduced health care costs as well as increased worker productivity—changes that directly affect the operating costs of local governments and firms. Additionally, SUS’s spillover effect on parents’ BMIs increased the community’s return on investment from SUS. The investment in SUS was the same regardless of whether SUS influenced parents’ BMIs; that SUS was associated with parent BMI changes indicates that society’s benefits from SUS increased although its investment remained constant.
The support SUS received and continues to receive from the Somerville community was a critical element in SUS’s success and sustainability.15 SUS was also a model intervention in terms of a coordinated approach. SUS contained 5 of 7 recommendations included in the Centers for Disease Control and Prevention’s School Health Guidelines to Promote Healthy Eating and Physical Activity34 at the school level as well as other community-based, place-specific components in alignment with the Institute of Medicine’s recommendations.1 Both the Centers for Disease Control and Prevention and the Institute of Medicine recommendations postdate the SUS intervention. The multicomponent, synergistic nature of SUS and the strong community support SUS received may explain our results. The results must be interpreted within this context. It is unknown how the intervention components behave when implemented individually or what the effectiveness of SUS would be in a community where local support is weaker than that found in Somerville.
The longitudinal comparison of treatment and control parents—from different communities—over 2 school years and the methods used to isolate SUS’s influence on parents’ BMIs in the presence of selection bias are key strengths of this study. SUS’s multicomponent nature is also a strength of this study, as it provided the first opportunity to examine whether the public health benefits of SCCB interventions, as recommended by the Institute of Medicine,1 spill over to adults.
Numerous statistical limitations are present. First, likely critical covariates remained unmeasured and therefore uncontrolled. For instance, we used proxy measures for parent race and for 1 parent’s age group in 2-parent households. The loss of observations over the course of the study is also a limitation, which in part is explained by the child-focused nature of the data collection. Additionally, information on changes in specific physical activity and dietary behaviors of adults was not sufficient to examine how SUS influenced these items. Next, we calculated parents’ BMIs from self-reported measures that could result in more conservative BMI calculations for treatment group and control group parents.35
Furthermore, various forms of respondent bias could influence the results. For instance, if treatment group parents wanted SUS to continue, they may have underestimated their postintervention weight to make SUS appear effective (respondent bias); if this occurred, the estimation of SUS’s treatment effect is likely liberal. Conversely, if treatment group parents more accurately reported their postintervention weight because they became more aware of their weight during the intervention, the estimation of SUS’s treatment effect is likely conservative. Lastly, despite the estimation methods we used and the quasiexperimental nature of the SUS research project, the results remain estimates and should be interpreted accordingly.
Our results highlight the need to further investigate the relationship between SCCB childhood obesity interventions and parent health behaviors and outcomes. Future SCCB intervention research should focus on adult outcomes as a primary research objective to address many of our study’s limitations that arose from a data collection process focused on children as well as to verify the relationship between SCCB interventions and adult health outcomes in other communities. Such studies should use clinically measured height and weight and investigate how SCCB interventions influence adults’ health outcomes and behaviors. Lastly, future SCCB intervention research should examine whether the influence of SCCB interventions extends to adults not connected to the local school system and how the effectiveness of SUS differs across racial/ethnic and socioeconomic status. Although this research agenda is ambitious, questions answered by it will provide insight into developing community-based, child-focused environmental change interventions that maximize intervention exposure and effect on adults and broad communities without reducing the intervention’s effectiveness on children.
Our results imply that the benefits of a community-based, child-focused environmental change obesity intervention extend to parent BMIs. Allocating resources to parent or child obesity prevention efforts is not necessarily a zero-sum game. Without any additional investment, society may influence parent BMIs by allocating resources to properly structured child-focused environmental change obesity prevention efforts. Further research is warranted to examine the effects of this type of intervention on parental health behaviors and health outcomes.
Acknowledgments
This study was conducted independently of any outside funding, including any previously allocated funds from the Centers for Disease Control and Prevention (CDC) and other sources to the Shape Up Somerville (SUS) research study. The SUS research study was funded by the CDC (grant R06/CCR121519-01 to C. D. E.). Additional unrestricted support for the SUS research study was provided by Blue Cross Blue Shield of Massachusetts, United Way of Mass Bay, the US Potato Board, Stonyfield Farm, and Dole Foods.
We would like to thank Tufts University and City of Somerville collaborators for their efforts with study design, intervention implementation, data collection, entry, and management. We also wish to thank the 2 control communities and the community of Somerville for their cooperation, participation, and commitment.
Note. The findings and conclusions in this study are those of the authors and do not necessarily represent the official position of the CDC.
Human Participant Protection
No protocol approval was required because the CDC received secondary, de-identified data from the Shape Up Somerville research study to investigate the questions addressed in this article.
