Differences In Obesity Rates Research Articles

Association Between Objectively Measured Body Fat Percentage And Two Indirect Measures Of Adiposity

Body mass index (BMI), calculated using height and weight, is used clinically to diagnose obesity. The ability of BMI to estimate adiposity is limited in the general population and unknown in college aged individuals. Relative fat mass (RFM) has been proposed as an alternative technique to BMI for diagnosis of obesity. RFM accounts for mass stored in the lower portion of the torso by incorporating height and waist circumference into the equation. PURPOSE: The purpose of this study was to compare rates of obesity determined by BMI, RFM and objectively measured percent body fat (BF%) via bioelectrical impedance analysis (BIA) in a large cohort of college aged men and women. METHODS: 3804 college students completed an objective fitness assessment, where they self-reported their age and sex, and height, weight, waist circumference, and BF%, were assessed. Correlation and chi-square tests for independence analyses examined the relationships and differences in rates of obesity between each method. RESULTS: The mean age of the sample was 21.2±1.1, and the majority (n = 2406, 63%) identified as male. Significant correlations were found between BMI and BF% for men (r=0.79, p<0.001) and women (r=0.84,p<0.001); BMI and RFM for men (r= 0.85, p<0.001) and women (r=0.83,p<0.001); and, BF% and RFM for men (r= 0.74, p<0.001) and women (r= 0.76,p<0.001). Differences were found between the observed and expected classification of normal adiposity or obesity by BMI, RFM and BF% for men and women (for all p<0.001). Among men, comparing BF% vs. BMI and RFM vs. BMI, more obese men via BF% or RFM were classified as normal via BMI (BF%; χ2=665, p<0.001; RFM; χ2=1189, p<0.001). For women, comparing BF% vs. BMI and RFM vs. BMI, more women who were obese via %BF and RFM were classified as normal via BMI (%BF χ2=576,p<0.001; RFM χ2=108, p<0.001). Comparing RFM and BF%, more men and women classified as obese by RFM were considered normal by %BF (χ2=626, p<0.001; χ2=246.5, p<0.001). CONCLUSION: Strong associations are observed among BMI, RFM and objectively measured %BF in college students. Despite these strong relationships, discrepancies were observed between obesity classifications between BF%, BMI and RFM.

Obesity Kuznets curve: international evidence

ObjectivesThe obesity epidemic has prevailed worldwide and is currently recognized as a global pandemic disease. Given the argument that various socio-economic features contribute to substantial differences in obesity rates across countries, economic development can also be considered a crucial factor of such variation. This study examines the relationship between economic development and each of three weight-related health statuses (rates of overweight, obesity, and morbid obesity). Study designThis study uses panel data analysis. MethodsUsing country-level panel data of 130 countries during the period from 1975 to 2010, we apply dynamic panel data analysis to mitigate possible endogeneity problems. ResultsThe main results show a clear pattern of the obesity Kuznets curve, i.e. a non-linear relationship between a country's income per capita and its weight-related health status, for both males and females. For low-income countries, as incomes increase, the weight-related health status deteriorates; thus, an increase in incomes raises the health risk. In contrast, for high-income countries, as incomes increase, the weight-related health status improves; thus, an increase in incomes reduces the health risk. ConclusionsThe policy implications from our analysis include the argument that a strong initiative for health policy targeting obesity prevention is required for middle-income countries, many of which are currently experiencing high economic growth.

Assessment of dietary patterns, physical activity and obesity from a national survey: Rural-urban health disparities in older adults.

BackgroundObesity is a critical public health issue, affecting over one-third of all Americans, and is an underlying cause of numerous health issues across the lifespan. For older adults, obesity is linked to premature declines in physical and mental health and cognitive functioning. The occurrence of obesity and related health behaviors and chronic diseases are higher in rural areas than in urban areas. Furthermore, rural areas of the United States have a higher proportion of older adults than urban areas. Few studies, to date, have explored rural-urban differences in the relationships between dietary patterns and obesity among older adults. Therefore, the purpose of this study is to assess rural-urban differences in obesity rates in older adults, and the potential for the associations between obesity and physical activity and dietary patterns to vary by rural-urban status.MethodsData were abstracted from respondents aged 65 and above from the 2012 Behavioral Risk Factor Surveillance System (BRFSS) database linked to Census-based county-level information on rural-urban status and socioeconomic status. Generalized linear models were utilized to assess rural-urban disparities in obesity, and the potential for associations between obesity and known risk factors (fruit consumption, green vegetable consumption and physical activity) to vary by rural-urban status, accounting for complex sampling and confounders.ResultsObesity rates were highest and fruit consumption was lowest in the most rural areas. However, for older adults in the most urban areas, there was a significant negative association between obesity and fruit and green vegetable consumption. This association was not observed in more rural older adults.ConclusionThese findings underscore the need to take into account place-based factors such as rural-urban status, when designing and implementing policies and interventions designed to reduce obesity through risk factor mitigation in older adults. To reduce rural-urban disparities in older adults, all policies, programs, and interventions should address the unique barriers and needs specific to rural and urban older adults.

Aetiology of eating behaviours: A possible mechanism to understand obesity development in early childhood

Childhood obesity is an issue of public health concern that is understood to emerge due to disequilibrium in energy homeostasis. This commentary explores literature regarding neuro-biological mechanisms of energy homeostasis and the relationship between subjective measures of children’s eating behaviours and objective measures of appetite, in order to better understand the aetiology of childhood obesity. Early life influences, such as in utero exposure, breastfeeding, and general disadvantage, appear to have an important influence on neuro-biological mechanisms of appetite and may contribute to inequitable distributions of obesity within the population. Subject measures of eating behaviours appear to capture various aspects of neuro-biologically driven (objective) appetite systems, however, these systems are complex, interdependent and not yet fully understood. Future research focusing attention on early life influences on appetite and eating behaviours is warranted to increase understanding of differences in rates of obesity within the population, to determine opportunities for targeted obesity prevention initiatives, and to explore the potential to measure change in eating behaviours as a marker of appetite and obesity risk.

Clinical and molecular characteristics of younger versus older patients with colorectal cancer.

630 Background: Although overall incidence of colorectal cancer is declining, the incidence for young patients (age &lt; 50) with colon cancer is increasing. Reasons for this rise are unclear. Understanding clinical and molecular differences between younger and older cohorts can help guide both patient education strategies and future research into the mechanisms of this phenomenon. Methods: A retrospective analysis of patients diagnosed with colon cancer between 2008 and 2015 who underwent molecular tumor profiling via next-gen sequencing of 26 commonly mutated genes at the University of Colorado. Data collected by chart review includes demographic, pathologic, treatment course, and outcomes. Age group cutoffs for data analysis were set at &lt; 50, 50-65, and &gt; 65 based on screening guidelines and average age of diagnosis Results: We evaluated a total of 242 patients, stage I (n = 1), stage II (n = 65), stage III (n = 68), stage IV (n = 105). Mean age was 59.5 (range 27 to 89). A higher percentage of younger patients were non-smokers (77% of youngest cohort vs 46% of oldest cohort, p &lt; 0.001) and had a non-significant trend towards male gender (youngest cohort 63.8% male, oldest cohort 43.4% male, p = 0.065). Younger patients had similar body mass index (BMI) compared to older patients (BMI 27 vs 25.7, p = 0.35). Younger patients had higher rates of rectal cancer (42% vs 21%, p = 0.01) and lower rates of proximal/right sided colon cancer (20% vs 46.5%, p = 0.014). Younger patients also had lower rates of MSI-H tumors (8% vs 14%, p = 0.01). Finally, younger patients had significantly lower rates of APC (43.1% vs 69.3%, p = 0.009) and BRAF (3.5% vs 19.7%, p = 0.004) mutations. Conclusions: Younger patients ( &lt; 50 years old) with colorectal cancer had lower rates of tobacco use and no difference in obesity rates compared to older patients. In addition, although APC and BRAF mutations were lower in younger patients, there were no mutations that were more prevalent in the young cohort. Therefore, further research into lifestyle factors (specific diet/exercise patterns) or alternative molecular mechanisms are needed.

The Differences in Obesity Rates According to Status of Co-Residence with Their Parents in Korean Adolescents: The Implication of the Gender of Single Parent Living with Adolescents

The Differences in Obesity Rates According to Status of Co-Residence with Their Parents in Korean Adolescents: The Implication of the Gender of Single Parent Living with Adolescents

The weight of networks: the role of social ties and ethnic media in mitigating obesity and hypertension among Latinas

ABSTRACTObjectives: Latinos have a disproportionately high risk for obesity and hypertension. The current study analyzes survey data from Latin American women to detect differences in rates of obesity and hypertension based on their number of health-related social ties. Additionally, it proposes individuals’ health-related media preference (ethnic/ mainstream) as a potential moderator.Design: The dataset includes 364 Latinas (21–50 years old) from the greater Los Angeles metropolitan area, who responded to a series of sociodemographic, physiological, health-related, and media-related questions.Results: Controlling for various sociodemographic and health variables, each additional health-related tie in a Latina’s social network significantly decreased her likelihood of being obese OR = .79, p = .041, 95% CI [.66, .95], but did not affect hypertension. Further, the analysis revealed a significant interaction between media preference and health-related social ties, such that exposure to ethnic media tended to compensate for the absence of social ties for the likelihood of obesity OR = .75, p = .041, 95% CI [.52, .97], as well as hypertension OR = .79, p = .045, 95% CI [.55, .98].Conclusion: In concurrence with the literature, increases in health-related ties reduced the likelihood of obesity in this population. Moreover, ethnic media preference may play an important role in mitigating the likelihood of obesity and hypertension among Latinas.

Maternal testosterone and reproductive outcome in a rat model of obesity

Global sex differences in obesity rates are persistent, suggesting the involvement of sex steroids. In addition, adipose tissue is a metabolic site for steroidogenesis. Here, we compared female reproductive parameters in a rat model of obesity, with the same parameters in its lean control strain, and tested for an association with integrated measures of corticosterone and testosterone. Steroids were extracted and quantified from 17 Otsuka Long Evans Tokushima Fatty (OLETF; an animal model for obesity) and 13 Long Evans Tokushima Otsuka (LETO; the lean control strain) hair samples that were collected after weaning offspring. The obese OLETF mothers had higher hair testosterone levels than the control LETO strain. Overall, testosterone, but not corticosterone, predicted litter sex ratios. Younger mothers with large litters and older mothers with small litters tended to have the highest sex ratios (i.e., male-biased litters). In the lean LETO strain, but not in the obese OLETF, maternal testosterone was positively associated with litter size and number of male pups. Corticosterone did not differ between the two strains and was not associated with testosterone or with reproductive parameters. This study suggests that long-term circulating testosterone is associated with female reproduction in multiple ways. The possible trade-off between litter size and sex ratio may be mediated by testosterone and influenced by body fat and composition, which influence the individual's well-being. Exploring the multiple roles of testosterone in females may also help explain the complex relationship between obesity and reproduction.

Childhood Attention-Deficit/Hyperactivity Disorder, Sex, and Obesity: A Longitudinal Population-Based Study

ObjectiveTo assess obesity rates during childhood and young adulthood in patients with attention-deficit/hyperactivity disorder (ADHD) and age- and sex-matched controls derived from a population-based birth cohort because cross-sectional studies suggest an association between ADHD and obesity. Patients and MethodsStudy subjects included patients with childhood ADHD (n=336) and age- and sex-matched non-ADHD controls (n=665) from a 1976 to 1982 birth cohort (N=5718). Height, weight, and stimulant treatment measurements were abstracted retrospectively from medical records documenting care provided from January 1, 1976, through August 31, 2010. The association between ADHD and obesity in patients with ADHD relative to controls was estimated using Cox models. ResultsPatients with attention-deficit/hyperactivity disorder were 1.23 (95% CI, 1.00-1.50; P<.05) times more likely to be obese during the follow-up period than were non-ADHD controls. This association was not statistically significant in either sex (female participants: hazard ratio [HR], 1.49; 95% CI, 0.98-2.27; P=.06; male participants HR, 1.17, 95% CI, 0.92-1.48; P=.20). Patients with ADHD who were not obese as of the date ADHD research diagnostic criteria were met were 1.56 (95% CI, 1.14-2.13; P<.01) times more likely to be obese during the subsequent follow-up than were controls. This association was statistically significant in female study subjects (HR, 2.02; 95% CI, 1.13-3.60; P=.02), but not in male participants (HR, 1.41; 95% CI, 0.97-2.05; P=.07). A higher proportion of patients with ADHD were obese after the age of 20 years compared with non-ADHD controls (34.4% vs 25.1%; P=.01); this difference was observed only in female patients (41.6% vs 19.2%). There were no differences in obesity rates between stimulant-treated and nontreated patients with ADHD. ConclusionChildhood ADHD is associated with obesity during childhood and young adulthood in females. Treatment with stimulant medications is not associated with the development of obesity up to young adulthood.

Diet-related chronic disease in the northeastern United States: a model-based clustering approach.

BackgroundObesity and diabetes are global public health concerns. Studies indicate a relationship between socioeconomic, demographic and environmental variables and the spatial patterns of diet-related chronic disease. In this paper, we propose a methodology using model-based clustering and variable selection to predict rates of obesity and diabetes. We test this method through an application in the northeastern United States.MethodsWe use model-based clustering, an unsupervised learning approach, to find latent clusters of similar US counties based on a set of socioeconomic, demographic, and environmental variables chosen through the process of variable selection. We then use Analysis of Variance and Post-hoc Tukey comparisons to examine differences in rates of obesity and diabetes for the clusters from the resulting clustering solution.ResultsWe find access to supermarkets, median household income, population density and socioeconomic status to be important in clustering the counties of two northeastern states. The results of the cluster analysis can be used to identify two sets of counties with significantly lower rates of diet-related chronic disease than those observed in the other identified clusters. These relatively healthy clusters are distinguished by the large central and large fringe metropolitan areas contained in their component counties. However, the relationship of socio-demographic factors and diet-related chronic disease is more complicated than previous research would suggest. Additionally, we find evidence of low food access in two clusters of counties adjacent to large central and fringe metropolitan areas. While food access has previously been seen as a problem of inner-city or remote rural areas, this study offers preliminary evidence of declining food access in suburban areas.ConclusionsModel-based clustering with variable selection offers a new approach to the analysis of socioeconomic, demographic, and environmental data for diet-related chronic disease prediction. In a test application to two northeastern states, this method allows us to identify two sets of metropolitan counties with significantly lower diet-related chronic disease rates than those observed in most rural and suburban areas. Our method could be applied to larger geographic areas or other countries with comparable data sets, offering a promising method for researchers interested in the global increase in diet-related chronic disease.Electronic supplementary materialThe online version of this article (doi:10.1186/s12942-015-0017-5) contains supplementary material, which is available to authorized users.

Measuring obesity in the absence of a gold standard

Reliable measures of body composition are essential to develop effective policies to tackle obesity. The lack of an acceptable gold-standard for measuring fatness has made it difficult to evaluate alternative measures of obesity. We use latent class analysis to characterise existing diagnostics. Using data on US adults we show that measures based on body mass index and bioelectrical impedance analysis misclassify large numbers of individuals. For example, 45% of obese White women are misclassified as non-obese using body mass index, while over 50% of non-obese White women are misclassified as being obese using bioelectrical impedance analysis. In contrast the misclassification rates are low when waist circumference is used to measure obesity. These results have important implications for our understanding of differences in obesity rates across time and groups, as well as posing challenges for the econometric analysis of obesity.

What money can buy: Family income and childhood obesity

This paper investigates the relationship between family income and childhood obesity. Using the Early Childhood Longitudinal Study, Kindergarten Class of 1998-99 (ECLS-K), I report three new findings. First, family income and childhood obesity are generally negatively correlated, but for children in very low-income families, they are positively correlated. Second, the negative association between family income and Body Mass Index (BMI) is especially strong and significant among high-BMI children. Third, the difference in obesity rates between children from low- and high-income families increases as children age. This study further investigates potential factors that might contribute to a rapid increase in the obesity rate among low-income children. I find that their faster weight gain, rather than slower height growth, is a greater contributor to the rapid increase in their BMI over time. On the other hand, I also find that the faster weight gain by low-income children cannot be attributed to any single factor, such as participation in school meal programs, parental characteristics, or individual characteristics. These findings add to the current obesity debate by demonstrating that the key to curbing childhood obesity may lie in factors generating different obesity rates across income levels.

Census tract income levels and outdoor physical activity opportunities for families with preschoolers (806.19)

The near home environment influences the PA and sedentary behaviors of adults and children. A valid, reliable, and easy to use self‐report assessment of the PA environment of homes with preschoolers was used to determine availability and accessibility of PA equipment and space in yards (areas immediately outside the home) and neighborhood PA facilities (e.g., playgrounds, low‐cost recreation centers). Scores for yard and neighborhood PA availability and accessibility were compared to the CTIL of the home’s address using 1‐way ANOVA. Homes (n=44) were categorized in low, middle, moderate, and upper CTIL (9%, 9%, 57%, 25%). Significant (p&lt;.05) group differences were found for yard accessibility score and neighborhood availability score, but not for others. Post hoc tests indicated that the highest CTIL homes had more accessible yard PA equipment and space than lower CTIL homes. Highest CTIL homes also had significantly more neighborhood PA availability than lowest CTIL homes and neared significance for neighborhood accessibility (p=0.08). CTIL, as proxies for income, indicate that income disparities affect the PA availability and accessibility of families with preschoolers, and likely are a contributor to differences in obesity rates by income. Thus, eliminating “playground deserts” could be an important step in reducing obesity rates in CTIL areas.Grant Funding Source: Supported by USDA, National Institute of Food and Agriculture, Grant Number 2011‐68001‐30170

Relationships between Overweight and Obesity with Preferred Mode of Transportation and Use of Neighborhood Facilities in Riyadh, Saudi Arabia

Purpose: To examine possible associations of obesity with mode of transportation to neighborhood facilities, social environment, type of work, and physical activity at neighborhood facilities and at home. Methods: This cross-sectional descriptive survey included a total of 312 respondents aged 18 years or older who attended three family medicine centers in the National Guard Hospital, Riyadh, for routine heath care from January 2012 to April 2012. The following measures were analyzed: Body Mass Index (BMI), self-reported modes of transportation to neighborhood facilities, physical activity, social environment, and socio-demographic status. Results: One-third of participants (33.7%) were overweight and just over one-third (39.2%) were obese. The majority of participants drove to work (98%), school/college (90.2%), shopping malls (95.7%), restaurants (91.5%), and social visits (84%) but walked to mosque (84.3%) and to grocery stores (50.2%). The rate of obesity was higher among participants who drove (45%) than in participants who walked (30%) to grocery store (X2=7, p=0.03). No other significant differences in rate of obesity noted for other destinations. Conclusions: Obesity rate was higher among participants who used car to reach grocery store (45%) than participants who used to walk to the grocery store (30%) (X2=7, p=0.03). No other significant differences in rates of obesity noted for other destinations. Further investigation is warranted in order to establish whether this relationship is causal.

Sex differences in rates of obesity in bipolar disorder: postulated mechanisms

The increased standardized mortality ratio (SMR) from cardiovascular disease (CVD) in women with bipolar disorder (BD), relative to men with BD and individuals of both sexes in the general population, provides the impetus to identify factors that contribute to the differential association of obesity with BD in women. We conducted a selective PubMed search of English-language articles published from September 1990 to June 2012. The key search terms were bipolar disorder and metabolic syndrome cross-referenced with gender, sex, obesity, diabetes mellitus, hypertension, and dyslipidemia. The search was supplemented with a manual review of relevant article reference lists. Articles selected for review were based on author consensus, the use of a standardized experimental procedure, validated assessment measures, and overall manuscript quality. It is amply documented that adults with BD are affected by the metabolic syndrome at a rate higher than the general population. Women with BD, when compared to men with BD and individuals of both sexes in the general population, have higher rates of abdominal obesity. The course and clinical presentation of BD manifest differently in men and women, wherein women exhibit a higher frequency of depression predominant illness, a later onset of BD, more seasonal variations in mood disturbance, and increased susceptibility to relapse. Phenomenological factors can be expanded to include differences in patterns of comorbidity between the sexes among patients with BD. Other factors that contribute to the increased risk for abdominal obesity in female individuals with BD include reproductive life events, anamnestic (e.g., sexual and/or physical abuse), lifestyle, and iatrogenic. A confluence of factors broadly categorized as broad- and sex-based subserve the increased rate of obesity in women with BD. It remains a testable hypothesis that the increased abdominal obesity in women with BD mediates the increased SMR from CVD. A clinical recommendation that emerges from this review is amplified attention to the appearance, or history, of factors that conspire to increase obesity in female patients with BD.

Estimating Obesity Rates in the Presence of Measurement Error

Reliable measures of obesity are essential in order to develop effective policies to tackle the costs of obesity. In this paper we examine what, if anything, we can learn about obesity rates using self-reported BMI once we allow for possible measurement error. We combine self-reported data on BMI with estimated misclassification rates obtained from auxiliary data to derive upper and lower bounds for the population obesity rate for ten European countries.For men it is possible to obtain meaningful comparisons across countries even after accounting for measurement error. In particular the self-reported data identifies a set of low obesity countries consisting of Denmark, Ireland, Italy, Greece and Portugal and a set of high obesity countries consisting of Spain and Finland. However, it is more difficult to rank countries by female obesity rates. Meaningful rankings only emerge when the misclassification rate is bounded at a level that is much lower than that observed in auxiliary data. A similar limit on misclassification rates is also needed before we can begin to observe meaningful gender differences in obesity rates within countries.

Differences in Obesity Rates Between People With and Without Disabilities and the Association of Disability and Obesity: A Nationwide Population Study in South Korea

ObjectivesThe objective of this study was to identify the differences in obesity rates among people with and without disabilities, and evaluate the relationship between obesity rates and the existence of disabilities or characteristics of disabilities.MethodsMass screening data from 2008 from the National Disability Registry and National Health Insurance (NHI) are used. For analysis, we classified physical disability into three subtypes: upper limb disability, lower limb disability, and spinal cord injury. For a control group, we extracted people without disabilities by each subtype. To adjust for the participation rate in the NHI mass screening, we calculated and adopted the weight stratified by sex, age, and grade of disability. Differences in obesity rates between people with and without disabilities were examined by a chi-squared test. In addition, the effect of the existence of disabilities and grade of disabilities on obesity was examined by multiple logistic regression analysis.ResultsPeople with disabilities were found to have a higher obesity rate than those without disabilities. The obesity rates were 35.2% and 35.0% (people with disabilities vs. without disabilities) in the upper limb disability, 44.5% and 34.8% in the lower limb disability, 43.4% and 34.6% in the spinal cord injury. The odds for existence of physical disability and grade of disability are higher than the non-disabilities.ConclusionsThese results show that people with physical disability have a higher vulnerability to obesity.

Socio-economic Status, Forms of Capital and Obesity

While the relationships among socio-economic status (SES) and obesity are powerful and synergistic, the SES construct is insufficient to describe some of the cultural influences on status production in society, and therefore on obesity production. Socio-economic status has two closely related dimensions. The economic one is represented by financial wealth while the social one can incorporate education, occupational prestige, authority and community standing. These are, however, incomplete explanations for the relationships between societal inequalities and obesity. Cultural factors associated with SES and obesity are examined here by using Bourdieu and Boltanski's theory of practice, which links economic, social and cultural forms of capital (or value) in an overarching category of symbolic capital. These represent categories through which power relationships within society are negotiated. This construct permits a more complete examination of societal stratification and its human biological consequences and amplifiers, since it incorporates the notion of cultural value in different groups of, for example, preferences in body size and shape. The focus is primarily on the USA, although it draws on literature from elsewhere in the industrialized world where appropriate. Differences in obesity rates across major ethnic groups are discussed, because this is an area in which forms of capital differ, and may offer new insights into obesity and factors that predispose to it, as forms of symbolic capital.

Do women with PCOS have a unique predisposition to obesity?

Women with PCOS are often obese and there is debate in the literature regarding whether women are obese because of their PCOS status or if those who become obese are more predisposed to PCOS. There is support for a predisposition to obesity by some data indicating impaired metabolism in PCOS women compared to weight matched controls but this data is limited. Contrary data also exist that adiposity rates do not vary between women with PCOS and those without, and that differences in obesity rates between countries are more likely due to environmental and lifestyle factors. Until further data are available, lifestyle recommendations for weight reduction in women with PCOS should be similar to those for women without PCOS.

Student public commitment in a school-based diabetes prevention project: impact on physical health and health behavior.

BackgroundAs concern about youth obesity continues to mount, there is increasing consideration of widespread policy changes to support improved nutritional and enhanced physical activity offerings in schools. A critical element in the success of such programs may be to involve students as spokespeople for the program. Making such a public commitment to healthy lifestyle program targets (improved nutrition and enhanced physical activity) may potentiate healthy behavior changes among such students and provide a model for their peers. This paper examines whether student's "public commitment"--voluntary participation as a peer communicator or in student-generated media opportunities--in a school-based intervention to prevent diabetes and reduce obesity predicted improved study outcomes including reduced obesity and improved health behaviors.MethodsSecondary analysis of data from a 3-year randomized controlled trial conducted in 42 middle schools examining the impact of a multi-component school-based program on body mass index (BMI) and student health behaviors. A total of 4603 students were assessed at the beginning of sixth grade and the end of eighth grade. Process evaluation data were collected throughout the course of the intervention. All analyses were adjusted for students' baseline values. For this paper, the students in the schools randomized to receive the intervention were further divided into two groups: those who participated in public commitment activities and those who did not. Students from comparable schools randomized to the assessment condition constituted the control group.ResultsWe found a lower percentage of obesity (greater than or equal to the 95th percentile for BMI) at the end of the study among the group participating in public commitment activities compared to the control group (21.5% vs. 26.6%, p = 0.02). The difference in obesity rates at the end of the study was even greater among the subgroup of students who were overweight or obese at baseline; 44.6% for the "public commitment" group, versus 53.2% for the control group (p = 0.01). There was no difference in obesity rates between the group not participating in public commitment activities and the control group (26.4% vs. 26.6%).ConclusionsParticipating in public commitment activities during the HEALTHY study may have potentiated the changes promoted by the behavioral, nutrition, and physical activity intervention components.Trial RegistrationClinicalTrials.gov number, NCT00458029