February 2018

NCCOR: A Decade of Transforming the Field of Childhood Obesity Research

February 22, 2018, NCCOR

Launched in 2009, NCCOR brought together the nation’s four largest childhood obesity research funders—CDC, NIH, USDA, and RWJF—in a public-private collaboration to accelerate progress in reducing childhood obesity. In the ensuing 10 years, NCCOR has transformed the field of childhood obesity research through strategic initiatives, comprehensive tools for researchers, and innovative rapid-response funding mechanisms, among other efforts.

To provide insights into its formation, operations, and accomplishments, NCCOR published two papers in the American Journal of Preventive Medicine. The papers are accompanied by a commentary by senior leaders of NCCOR’s member organizations and an editorial by Dr. Jim Sallis, a member of NCCOR’s External Scientific Panel. A list of the papers and NCCOR’s 10 years of accomplishments can be found at nccorstg.wpengine.com/accomplishments.

Developing A Partnership for Change: The National Collaborative on Childhood Obesity Research

The first paper, Developing A Partnership for Change: The National Collaborative on Childhood Obesity Research, highlights the formation, structure, and operations of NCCOR and discusses benefits of using a collaborative model to more quickly build a field of research. The paper aims to answer common queries from public health leaders seeking innovative approaches for understanding and addressing other complex public health problems. The paper also shares the benefits of NCCOR’s public-private research funder model, including optimizing the strategic use of partner resources, avoiding duplication of efforts, and jointly filling research gaps. http://www.ajpmonline.org/article/S0749-3797(17)30712-2/fulltext

A National Collaborative for Building the Field of Childhood Obesity Research

The companion paper, A National Collaborative for Building the Field of Childhood Obesity Research, details several principles for successful partnerships and how NCCOR followed these principles to advance the field of childhood obesity research, evaluation, and surveillance. The paper highlights many of NCCOR’s accomplishments, including the development of three key tools for researchers—the Measures Registry, the Catalogue of Surveillance Systems, and the Youth Compendium of Physical Activities. http://www.ajpmonline.org/article/S0749-3797(17)30738-9/fulltext

Research on Childhood Obesity: Building the Foundation for a Healthier Future

Griffin Rodgers, Director of the National Institute of Diabetes and Digestive and Kidney Diseases at the National Institutes of Health; William Dietz, the former Director of the Division of Nutrition, Physical Activity, and Obesity at the Centers for Disease Control and Prevention; and Risa Lavizzo-Mourey, President Emerita and former CEO of the Robert Wood Johnson Foundation, authored a commentary entitled Research on Childhood Obesity: Building the Foundation for a Healthier Future, in which they extol NCCOR’s ability to maximize efficiency and impact to advance each agency’s mission and efforts. Beyond collaborative projects, NCCOR has provided a venue for cross-agency collaboration that has been invaluable for furthering each organization’s agenda. http://www.ajpmonline.org/article/S0749-3797(17)30711-0/fulltext

NCCOR’s work is not yet done. To explore NCCOR’s tools for researchers and learn more about NCCOR’s current initiatives, visit our website at nccorstg.wpengine.com.

Original source

Back to Top

Connect & Explore: Preventing Childhood Obesity in Latin America: An Agenda for Regional Research and Strategic Partnerships

February 22, 2018, NCCOR

The increasing prevalence of childhood obesity in Latin America poses a major public health challenge. Limited scientific evidence inhibits development and implementation of novel, effective interventions across the region. To address these gaps, the National Institutes of Health’s (NIH) Fogarty International Center conducted a workshop to determine the state of the science and future directions regarding obesity research in the region. The two-day workshop addressed many factors relating to childhood obesity in Latin America and led to a series of articles published in an Obesity Reviews supplement, “Preventing Childhood Obesity in Latin America: An Agenda for Regional Research and Strategic Partnerships.”

On February 27, NCCOR is hosting a Connect & Explore webinar, “Preventing Childhood Obesity in Latin America: An Agenda for Regional Research and Strategic Partnerships.” The webinar will share key areas for research and critical lessons learned in Latin America that can inform future obesity prevention efforts.

Join us on Tuesday, February 27 at 3:00 p.m. ET, for the one-hour webinar. Guest speakers include the following researchers:

• Juan Rivera, PhD, is the general director at the National Institute of Public Health in Mexico and professor of nutrition in the School of Public Health of Mexico. Dr. Rivera will provide an overview of the supplement and its development, and present a research agenda for the prevention of childhood obesity in Latin America.
• Camila Corvalán, MD, PhD, MPH, is an assistant professor at the Institute of Nutrition and Food Technology at the University of Chile. Dr. Corvalán will discuss the current nutritional status of Latin American children and the drivers of the obesity epidemic in Latin America.
• Rafael Pérez-Escamilla, PhD, is a professor of epidemiology and public health, director of the Office of Public Health Practice, and director of global health at Yale University School of Public Health. Dr. Pérez-Escamilla will share lessons learned from Latin American countries to successfully implement obesity prevention policies.
• Michael Pratt, MD, MSPE, MPH, is a professor in the Division of Global Health at the University of California San Diego. Dr. Pratt will highlight opportunities for childhood obesity prevention research and research capacity in Latin America.

Please register to receive webinar access. The event is free, but attendance is limited. Register today!

Invite a colleague, and consider sharing this information on your social media networks using the hashtag #ConnectExplore. We will also be live tweeting the event, so be sure to follow the conversation at @NCCOR. For those who cannot attend, the webinar will be recorded and archived on nccorstg.wpengine.com.

Original source

Back to Top

All of Us Research Program

The All of Us Research Program, led by the National Institutes of Health, is a historic effort to gather data from one million or more people living in the United States to accelerate research and improve health. By taking into account individual differences in lifestyle, environment, and biology, researchers will uncover paths toward delivering precision medicine.

Access the website

Back to Top

Healthy Communities Policy Guide

The American Planning Association’s Healthy Communities Policy Guide addresses challenges derived from our built, social, and natural environment; provides recommendations for policies to address the social determinants of health by improving opportunities for physical activity and access to healthy food, which enables numerous social equity benefits; and helps policy makers at all levels of government better integrate health considerations into planning processes and outcomes.

Access the guide

Back to Top

Prevalence of Obesity Among Youths by Household Income and Education Level of Head of Household — United States 2011–2014

February 16, 2018, CDC

Obesity prevalence varies by income and education level, although patterns might differ among adults and youths. Previous analyses of national data showed that the prevalence of childhood obesity by income and education of household head varied across race/Hispanic origin groups. CDC analyzed 2011–2014 data from the National Health and Nutrition Examination Survey (NHANES) to obtain estimates of childhood obesity prevalence by household income (≤130%, >130% to ≤350%, and >350% of the federal poverty level [FPL]) and head of household education level (high school graduate or less, some college, and college graduate). During 2011–2014 the prevalence of obesity among U.S. youths (persons aged 2–19 years) was 17.0%, and was lower in the highest income group (10.9%) than in the other groups (19.9% and 18.9%) and also lower in the highest education group (9.6%) than in the other groups (18.3% and 21.6%). Continued progress is needed to reduce disparities, a goal of Healthy People 2020. The overall Healthy People 2020 target for childhood obesity prevalence is <14.5%.

NHANES is a cross-sectional survey designed to monitor the health and nutritional status of the civilian noninstitutionalized U.S. population. The survey consists of in-home interviews and standardized physical examinations conducted in mobile examination centers. The NHANES sample is selected using a complex, multistage probability design. During 2011–2014, non-Hispanic black, non-Hispanic Asian, and Hispanic persons, among other groups, were oversampled. Any non-Hispanic person reporting more than one race was included in an “other” category and included in the total estimates but not reported separately. The NHANES response rate for youths aged <20 years was 77.6% during 2011–2012 and 76.1% during 2013–2014. During the physical examination, standardized measurements of weight and height were obtained. Body mass index (BMI) was calculated as weight in kilograms divided by height in meters squared, rounded to the nearest 10th. Obesity among youths was defined as a BMI at or above the age- and sex-specific 95th percentile of the 2000 CDC growth charts (https://www.cdc.gov/growthcharts/cdc_charts.htm).

Household income was defined using FPL information, which accounts for inflation and family size (https://aspe.hhs.gov/prior-hhs-poverty-guidelines-and-federal-register-references) and categorized as ≤130%, >130% to ≤350%, and >350% of FPL. The cut-off point for participation in the Supplemental Nutrition Assistance Program is 130% of FPL, and 350% provides relatively equal sample sizes for each income group. Education was defined using education level of head of household and was categorized as a high school graduate or less, some college, and college graduate.

All estimates accounted for the complex survey design including examination sample weights. Confidence intervals for estimates were constructed using the Korn and Graubard method. Differences between groups were tested using a 2-sided univariate t statistic (p<0.05). Linear and quadratic trends from 1999–2002 to 2011–2014 were conducted using 4-year survey cycles. Pregnant females and persons with missing weight or height were excluded (139) for a total sample size of 6,878 during 2011–2014. For estimates by FPL another 517 persons were missing data and were excluded from analyses of FPL; for estimates by education level, 224 persons were missing data and were excluded from analyses of education.

Overall, 17.0% of youths aged 2–19 years had obesity during 2011–2014. The prevalence was 18.9% among those in the lowest income group, 19.9% among those in the middle group, and 10.9% among those in the highest income group. Among females, patterns in non-Hispanic white, non-Hispanic Asian, and Hispanic youths were similar, with the prevalence of obesity lower in the highest income group than in both other groups, but the differences by income were statistically significant only among non-Hispanic white females. Obesity prevalence did not differ by income among non-Hispanic black females. Among males, there was a lower obesity prevalence in the highest income group only in non-Hispanic Asian youths (compared with the lowest income group) and Hispanic youths (compared with both other income groups).

Among youths, the prevalence of obesity decreased with increasing level of education of the head of household: 21.6% (high school graduate or less), 18.3% (some college), and 9.6% (college graduate). The same pattern was seen overall and in females and males in all race-Hispanic origin groups, but differences were not significant for non-Hispanic black youths (total, male, or female) or non-Hispanic Asian males or females.

From 1999–2002 to 2011–2014 the prevalence of obesity increased among females in the two lowest income groups. There was a nonsignificant decrease in obesity prevalence among females in the highest income group, and the difference in childhood obesity prevalence between the lowest and highest income groups increased over time. Among males, a quadratic trend was observed in the lowest income group: obesity prevalence was 16.9% during 1999–2002, increased to 21.0% during 2007–2010, and then declined to 18.1% during 2011–2014. The difference in prevalence between the lowest and highest income groups did not change over time for males.

Obesity prevalence among youths increased from 1999–2002 to 2011–2014 among females and males in households headed by persons with the least education (high school graduate or less) and among females in households headed by persons with some college education. There were no other significant trends. In addition, the difference in childhood obesity prevalence between the lowest and highest head of household education groups increased over time for females but not for males.

Discussion

During 2011–2014, the relationships between childhood obesity and income and childhood obesity and education of household head were complex, differing depending upon the subgroup of the population. The prevalence of obesity among youths living in households headed by college graduates was lower than that among those living in households headed by less educated persons for each race-Hispanic origin group. The same was not true for those living in the highest income group. Moreover, differences by income and education of household head are widening among females.

Similar to results based on data from 2005 to 2008, during 2011–2014 childhood obesity prevalence was lower among youths living in households in the highest income group. However, this was not the pattern seen in all subgroups. For example, obesity prevalence was lower in the highest income group compared with the other groups among non-Hispanic white females, but not among non-Hispanic black females, non-Hispanic white males, or non-Hispanic black males. Obesity prevalence decreased as head of household education increased in all subgroups examined. The prevalence of obesity was consistently lowest among children in households headed by college graduates, which differed from the pattern seen by income level. This difference in the relationship between obesity and income versus education has been observed in at least one other study. In addition, some relationships changed since 2005–2008. For example, there was a significant decreasing trend in obesity prevalence by income among non-Hispanic white males during 2005–2008 but there were no differences during 2011–2014.

This report also presents differences in childhood obesity prevalence by income and education among non-Hispanic Asian youths in the United States. It has been suggested that the cut-off point that typically defines obesity might underestimate associated health risks among Asian persons.

The findings in this report are subject to at least one limitation. The sample size was small among some subgroups, such as non-Hispanic Asian females living in households with income above 350% of the FPL, where the prevalence of obesity is very low (1.3%) and the sample size is small (138). Additional years of data might provide more information about obesity prevalence by income, especially among non-Hispanic Asian youths.

Trends in childhood obesity prevalence by income and education level of head of household indicate that disparities have existed at least since NHANES III, 1988–1994. These differences have widened since 1999–2002 among females but not among males, where differences in obesity prevalence by income and education of the head of household have remained relatively constant from 1999–2002 to 2011–2014.

These findings demonstrate that lower levels of income are not universally associated with childhood obesity. The association is complex and differs by sex, race, and Hispanic origin, and possibly over time. Differences by education are more consistent across subgroups than differences by income. More progress is needed to reduce disparities in childhood obesity prevalence, an important Healthy People 2020 objective.

Original source

Back to Top

Childhood Obesity Treatment; Effects on BMI SDS, Body Composition, and Fasting Plasma Lipid Concentrations

February 14, 2018, PLOS ONE

Abstract

Objective

The body mass index (BMI) standard deviation score (SDS) may not adequately reflect changes in fat mass during childhood obesity treatment. This study aimed to investigate associations between BMI SDS, body composition, and fasting plasma lipid concentrations at baseline and during childhood obesity treatment.

Methods

876 children and adolescents (498 girls) with overweight/obesity, median age 11.2 years (range 1.6–21.7), and median BMI SDS 2.8 (range 1.3–5.7) were enrolled in a multidisciplinary outpatient treatment program and followed for a median of 1.8 years (range 0.4–7.4). Height and weight, body composition measured by dual-energy X-ray absorptiometry, and fasting plasma lipid concentrations were assessed at baseline and at follow-up. Lipid concentrations (total cholesterol (TC), low-density lipoprotein (LDL), high-density lipoprotein (HDL), non-HDL, and triglycerides (TG)) were available in 469 individuals (264 girls). Linear regressions were performed to investigate the associations between BMI SDS, body composition indices, and lipid concentrations.

Results

At baseline, BMI SDS was negatively associated with concentrations of HDL (p = 6.7*10−4) and positively with TG (p = 9.7*10−6). Reductions in BMI SDS were associated with reductions in total body fat percentage (p<2*10−16) and percent truncal body fat (p<2*10−16). Furthermore, reductions in BMI SDS were associated with improvements in concentrations of TC, LDL, HDL, non-HDL, LDL/HDL-ratio, and TG (all p <0.0001). Changes in body fat percentage seemed to mediate the changes in plasma concentrations of TC, LDL, and non-HDL, but could not alone explain the changes in HDL, LDL/HDL-ratio or TG. Among 81 individuals with available lipid concentrations, who increased their BMI SDS, 61% improved their body composition, and 80% improved their lipid concentrations.

Conclusion

Reductions in the degree of obesity during multidisciplinary childhood obesity treatment are accompanied by improvements in body composition and fasting plasma lipid concentrations. Even in individuals increasing their BMI SDS, body composition and lipid concentrations may improve.

Original source

Back to Top

Effectiveness of a Childhood Obesity Prevention Programme Delivered Through Schools, Targeting 6 and 7 Year Olds: Cluster Randomised Controlled Trial (WAVES Study)

February 7, 2018, The BMJ

Abstract

Objective

To assess the effectiveness of a school and family based healthy lifestyle programme (WAVES intervention) compared with usual practice, in preventing childhood obesity.

Design

Cluster randomised controlled trial.

Setting

UK primary schools from the West Midlands.

Participants

200 schools were randomly selected from all state run primary schools within 35 miles of the study centre (n=980), oversampling those with high minority ethnic populations. These schools were randomly ordered and sequentially invited to participate. 144 eligible schools were approached to achieve the target recruitment of 54 schools. After baseline measurements 1467 year 1 pupils aged 5 and 6 years (control: 28 schools, 778 pupils) were randomised, using a blocked balancing algorithm. 53 schools remained in the trial and data on 1287 (87.7%) and 1169 (79.7%) pupils were available at first follow-up (15 month) and second follow-up (30 month), respectively.

Interventions

The 12 month intervention encouraged healthy eating and physical activity, including a daily additional 30 minute school time physical activity opportunity, a six week interactive skill based programme in conjunction with Aston Villa football club, signposting of local family physical activity opportunities through mail-outs every six months, and termly school led family workshops on healthy cooking skills.

Main outcome measures

The protocol defined primary outcomes, assessed blind to allocation, were between arm difference in body mass index (BMI) z score at 15 and 30 months. Secondary outcomes were further anthropometric, dietary, physical activity, and psychological measurements, and difference in BMI z score at 39 months in a subset.

Results

Data for primary outcome analyses were: baseline, 54 schools: 1392 pupils (732 controls); first follow-up (15 months post-baseline), 53 schools: 1249 pupils (675 controls); second follow-up (30 months post-baseline), 53 schools: 1145 pupils (621 controls). The mean BMI z score was non-significantly lower in the intervention arm compared with the control arm at 15 months (mean difference −0.075 (95% confidence interval −0.183 to 0.033, P=0.18) in the baseline adjusted models. At 30 months the mean difference was −0.027 (−0.137 to 0.083, P=0.63). There was no statistically significant difference between groups for other anthropometric, dietary, physical activity, or psychological measurements (including assessment of harm).

Conclusions

The primary analyses suggest that this experiential focused intervention had no statistically significant effect on BMI z score or on preventing childhood obesity. Schools are unlikely to impact on the childhood obesity epidemic by incorporating such interventions without wider support across multiple sectors and environments.

Original source

Back to Top

Low Maternal Vitamin D Status in Pregnancy Increases the Risk of Childhood Obesity

January 28, 2018, Pediatric Obesity

Summary

Background

Vitamin D may modulate adipogenesis. However, limited studies have investigated the effect of maternal vitamin D during pregnancy on offspring adiposity or cardiometabolic parameters with inconclusive results.

Objectives

The objective of this study is to examine the association of maternal 25(OH)-vitamin D [25(OH)D] status with offspring obesity and cardiometabolic characteristics in 532 mother–child pairs from the prospective pregnancy cohort Rhea in Crete, Greece.

Methods

Maternal 25(OH)D concentrations were measured at the first prenatal visit (mean: 14 weeks, SD: 4). Child outcomes included body mass index standard deviation score, waist circumference, skin-fold thickness, blood pressure and serum lipids at ages 4 and 6 years. Body fat percentage was also measured at 6 years. Body mass index growth trajectories from birth to 6 years were estimated by mixed effects models with fractional polynomials of age. Adjusted associations were obtained via multivariable linear regression analyses.

Results

About two-thirds of participating mothers had 25(OH)D concentrations

Conclusions

Exposure to very low 25(OH)D concentrations in utero may increase childhood adiposity indices. Given that vitamin D is a modifiable risk factor, our findings may have important public health implications.

Original source

Back to Top

Commentary: Linking Biology to the Environment: Novel Methods for Understanding Pediatric Obesity

January 19, 2018, Journal of Pediatric Psychology

Pediatric obesity is a complex, seemingly intransient public health concern that has spurred research to identify causes and potential solutions. Both obesity-related behaviors and outcomes are affected by dynamic processes of many factors across multiple levels of the social ecological model. The environmental–behavioral relationship is reciprocal, dynamic, and dominated by temporally dependent feedback. Pediatric psychology and public health have generated substantial literature on predictors of obesity, with pediatric psychology focusing on individual social determinates and public health focusing on environmental determinants. Only limited research has integrated environment and individual predictors, despite calls for integration (Black & Hager, 2013; McGuire, 2012). The study by Gartstein and colleagues (Gartstein, Seamon, Thompson, & Lengua, 2018), published in this issue, successfully integrated individual biological data and environmental context. Comprehending and mitigating the complexity of obesity will likely require a combination of environmental and individual data.

Original source

Back to Top