INTRODUCTION: This study examined the prevalence and correlates of 6 healthy behaviors among preschool-age children in the United States. METHODS: Data from the 2021 and 2022 National Survey of Children's Health were used to examine daily fruit consumption, daily vegetable consumption, no sugary beverage consumption in the past week, frequent outdoor play (≥2 hours/day), limited screen time (≤1 hour/weekday), and adequate sleep (≥10 hours/day) among children ages 3-5 years (N=23,123). Relationships between healthy behaviorss and child, family, community characteristics, and state of residence were examined using logistic regression modeling, accounting for the complex survey design. Analyses were conducted in 2024 using SAS-callable SUDAAN. RESULTS: Prevalence of healthy behaviors varied from 32.4% having no sugary drinks in the past week to 65.3% eating fruit daily. Only 20% engaged in all or nearly all (5-6) healthy behaviors. After adjustment, children engaging in 5-6 HBs were more likely to be younger, non-Hispanic White, have parents with higher education and income, excellent/very good parental mental health, frequent family meals, household food sufficiency, and live in safe neighborhoods, yet prevalence rose to only 30% across any characteristic. The proportion of children engaging in 5-6 healthy behaviors ranged from 6.5% in Mississippi to 46.4% in Vermont, with child, family, and community factors accounting for 43% of the variance between states. CONCLUSIONS: There is a need to increase healthy behaviors among preschool-age children and address disparities. Family and community factors associated with healthy behaviors can inform pediatric care, public policy, programmatic investments, and additional research to foster improvement.

Child care programs can be one setting for promoting physical activity (PA). To support technical assistance providers in promoting PA best practices, Nemours Children's Health with the Centers for Disease Control and Prevention developed a set of trainings known as Physical Activity Learning Sessions (PALS). PALS centers on PA best practices, and state partners are encouraged to embed the program into early care and education (ECE) systems, such as training and TA networks. From 2019 to 2023, 22 states and 802 individuals completed a PALS train-the-trainer (TTT) course. This brief highlights findings from the 2022-2023 PALS evaluation, examining the extent to which PALS provided ECE trainers with effective training materials, affected trainer confidence in providing PA trainings to ECE providers, and was integrated into state systems. The PALS evaluation included a mixed-methods design consisting of pre-, post-, and 6-month post-TTT surveys of trainers. Among trainers, 87% of 125 respondents said they were confident training ECE providers on PA practices after completing the PALS TTT. Nearly 67% of participants planned to deliver a PALS training to ECE providers within 6 months of completing the TTT. Surveys from 16 of 18 PALS state leads suggested PALS has been embedded in state ECE systems. PALS counts for training credit of some type in 10 states, including licensing, provider credentials, and Quality Rating and Improvement Systems. Additional evaluation efforts could determine the impact of PALS on PA practices and policies among ECE providers and programs.

INTRODUCTION: Because limited data exist about factors related to sugar-sweetened beverage (SSB) intake among younger children, we investigated factors associated with SSB intake among US children aged 1 to 5 years. METHODS: We examined SSB intake (0, 1-3, or ≥4 times/week) by using data from the 2021 National Survey of Children's Health. We performed a multinomial logistic regression to calculate adjusted odds ratios (aORs) for select sociodemographic and household factors associated with moderate (1-3 times/week) and high (≥4 times/week) SSB intake. RESULTS: Overall, 36% of children consumed SSBs 1 to 3 times/week and 21% consumed 4 or more times/week. Both moderate and high SSB intake were associated with child's age, child's race and ethnicity, highest caregiver education level, household income, primary household language, and frequency of family meals. For example, children who lived in households with caregiver education level of high school graduate or less were significantly more likely to have moderate (aOR, 2.06) and high (aOR, 2.81) SSB intake than those who lived in households with caregiver education level of college degree or higher. High SSB intake was also associated with marginal household food sufficiency, nonmetropolitan statistical area status, and receipt of government food benefits. CONCLUSION: Several sociodemographic and household factors were significantly associated with SSB intake among children aged 1 to 5 years. Public health initiatives designed to address SSB intake among young children in various settings including pediatric health care, early care and education, and the child's home could consider key associated factors.

To describe child, caregiver, and household characteristics associated with fruit and vegetable intakes among US children aged 1-5 years, we examined fruit and vegetable intakes (less than daily vs. daily) using data from the 2021 National Survey of Children's Health among children aged 1-5 years. Multiple logistic regression provided adjusted odds ratios for factors associated with (1) daily fruit and (2) daily vegetable intakes. Among children aged 1-5 years, 68% (n = 11,124) consumed fruit daily, and 51% (n = 8292) consumed vegetables daily. Both daily fruit and daily vegetable intake were associated with child age, child race and ethnicity, and frequency of family meals. For example, children who ate a family meal 4-6 days/week (aOR 0.69; 95% CI 0.57, 0.83) or 0-3 days/week (aOR 0.57; 95% CI 0.46, 0.72) were less likely to consume fruit daily compared to children who had a family meal every day. Participation in food assistance programs, food insufficiency, and household income were not significantly associated with odds of daily fruit or daily vegetable intake in the adjusted models. Several factors were associated with daily fruit and vegetable intake among children aged 1-5. Strategies aimed at increasing fruit and vegetable consumption in early childhood may consider these child, caregiver, and household characteristics. Pediatric healthcare providers, early childhood education centers, and families of young children may be important partners in this work.

INTRODUCTION: Federal guidelines recommend physical activity throughout the day for preschool-aged children. Time playing outdoors can support physical activity participation, health, and development. Estimates of time playing outdoors among US children aged 3-5 years have not been published. METHODS: Parent/caregiver-reported data on children aged 3-5 years from the 2021 National Survey of Children's Health were analyzed in 2022-23. Chi-square tests were used to identify differences in time playing outdoors by sociodemographic and neighborhood characteristics. Multiple logistic regression analyses were conducted with significant characteristics for weekdays and weekend days. RESULTS: Among 11,743 children aged 3-5 years, 37% played outdoors for ≤1 hour on weekdays, and 24% played outdoors for ≤1 hour on weekend days. In 9 states, ≥40% of children played outdoors for ≤1 hour on weekdays. Adjusted models for weekdays and weekend days showed a greater likelihood of ≤1 hour playing outdoors among those in all racial/ethnic groups compared to Non-Hispanic White, those who lived in metropolitan statistical areas, those who did not participate in child care, and those whose adult proxy disagreed with "we watch out for each other's children in this neighborhood." The weekday model showed additional differences by sex, with girls more likely to have ≤1 hour of time playing outdoors. CONCLUSIONS: Nearly 40% of preschool-aged children play outdoors for ≤1 hour per day on weekdays, with differences by sociodemographic and neighborhood characteristics. Further study and interventions focused on building supportive, equitable communities might increase the amount of time preschool-aged children spend playing outdoors.

We appreciate the interest of Ichikawa et al and Jabarkheel et al, and we agree that the prevention of childhood obesity begins early in life with the provision of anticipatory guidance relating to healthy behaviors and the assessment of weight status, using weight-for-length and body mass index (BMI), as indicated. Our analysis indicates that a greater proportion of pediatricians reported using either of these measures in 2017 compared with in 2006. There is room for improvement and continued quality of care; providers can be encouraged to use these measures as an approach to identifying children with increases in weight indices who may benefit from additional efforts to support healthy growth and prevent obesity.

Childhood obesity in the United States is a serious problem that puts children at risk for poor health. Effective state-wide interventions are needed to address childhood obesity risk factors. Embedding evidence-based initiatives into state-level Early Care and Education (ECE) systems has the potential to improve health environments and promote healthy habits for the 12.5 million children attending ECE programs. Go NAPSACC, an online program that was adapted from an earlier paper version of Nutrition and Physical Activity Self-Assessment for Child Care (NAPSACC or NAP SACC), provides an evidence-based approach that aligns with national guidance from Caring for Our Children and the Centers for Disease Control and Prevention. This study describes approaches undertaken across 22 states from May 2017 to May 2022 to implement and integrate Go NAPSACC into state-level systems. This study describes challenges encountered, strategies employed, and lessoned learned while implementing Go NAPSACC state-wide. To date, 22 states have successfully trained 1,324 Go NAPSACC consultants, enrolled 7,152 ECE programs, and aimed to impact 344,750 children in care. By implementing evidence-based programs, such as Go NAPSACC, ECE programs state-wide can make changes and monitor progress on meeting healthy best practice standards, increasing opportunities for all children to have a healthy start.

Good nutrition in early childhood supports optimal growth, development, and health (1). Federal guidelines support a dietary pattern with daily fruit and vegetable consumption and limited added sugars, including limited consumption of sugar-sweetened beverages (1). Government-published dietary intake estimates for young children are outdated at the national level and unavailable at the state level. CDC analyzed data from the 2021 National Survey of Children's Health (NSCH)* to describe how frequently, according to parent report, children aged 1-5 years (18,386) consumed fruits, vegetables, and sugar-sweetened beverages, nationally and by state. During the preceding week, approximately one in three (32.1%) children did not eat a daily fruit, nearly one half (49.1%) did not eat a daily vegetable, and more than one half (57.1%) drank a sugar-sweetened beverage at least once. Estimates of consumption varied by state. In 20 states, more than one half of children did not eat a vegetable daily during the preceding week. In Vermont, 30.4% of children did not eat a daily vegetable during the preceding week, compared with 64.3% in Louisiana. In 40 states and the District of Columbia, more than one half of children drank a sugar-sweetened beverage at least once during the preceding week. The percentage of children drinking sugar-sweetened beverages at least once during the preceding week ranged from 38.6% in Maine to 79.3% in Mississippi. Many young children are not consuming fruits and vegetables daily and are regularly consuming sugar-sweetened beverages. Federal nutrition programs and state policies and programs can support improvements in diet quality by increasing access to and availability of fruits and vegetables and healthy beverages in places where young children live, learn, and play.

Background: Quality Rating and Improvement Systems (QRISs) are used to assess, improve, and communicate quality in early care and education (ECE) programs. One strategy for supporting healthy growth in early childhood is embedding nutrition, physical activity, infant feeding, and screen time content into state QRIS standards, using the Caring for Our Children high-impact obesity prevention standards (HIOPS) and the CDC Spectrum of Opportunities framework (CDC Spectrum). We assessed the number of obesity prevention standards in QRISs in 2020 and compared results to an analysis published in 2015. Methods: We collected state QRIS standards for ECE centers from March to April 2020. Two analysts coded documents for standards related to 47 HIOPS and 6 Spectrum areas. Results: Thirty-nine states and the District of Columbia had statewide QRISs in early 2020. Of these, 21 QRISs (53%) embedded 1 or more HIOPS, and 26 (65%) embedded 1 or more Spectrum components. On average, 6.9% of HIOPS were embedded in QRIS standards in 2020, an increase from 4.6% in 2015. Nine QRISs included more HIOPS in 2020 than in 2015. Five QRISs added 10% or more of the 47 HIOPS between 2015 and 2020. Physical activity and screen time standards continued to be most often included; infant feeding standards were least included. Conclusion: Obesity prevention components were embedded in three-quarters of state QRISs, and more were embedded in 2020 than in 2015, suggesting that QRISs can be levers for supporting healthy weight in ECE settings.

Early childhood is a critical period in the development, growth, and health of children. Many infants and toddlers in the United States spend time in nonparental early care and education (ECE) arrangements, which include care from child-care centers, family child-care homes, family members, and neighbors, or a combination of these providers. As of 2019, 14% of infants (0–12 months of age) and 27% of toddlers (1–2 years) participated in a center-based care arrangement; however, these statistics do not account for children cared for in family child-care homes, which are also an important source of care for this age group.1

The first 1000 days begins with pregnancy and ends at the child's second birthday. Nutrition throughout the life course, and especially during the first 1000 days, supports maternal health and optimal growth and development for children. We give a high-level summary of the state of nutrition in the first 1000 days in the United States. We provide examples where continued efforts are needed. We then discus select opportunities to strengthen federal research and surveillance, programs, and communication and dissemination efforts aimed at improving nutrition and positively, and equitably, influencing the health and well-being of mothers and children. (Am J Public Health. Published online ahead of print September 19, 2022::e1-e9. https://doi.org/10.2105/AJPH.2022.307028).

Many public health challenges face our world today, including systemic racism, the opioid epidemic, and the COVID-19 pandemic. Nurses are well-qualified and well-positioned to respond to these challenges, as nurses represent 50% of the global health workforce and are leaders not only in clinical settings but also in public health.1 The professions of nursing and public health have been closely intertwined since the founding of the modern-day nursing profession by Florence Nightingale, a pioneer in the field of epidemiology.2

Fourteen million US children are affected by obesity, including 4.4 million with severe obesity.1,2 Excess weight can put children and adolescents at risk for serious and costly short- and long-term adverse health outcomes, including, but not limited to, cardiovascular disease, type 2 diabetes mellitus, and nonalcoholic fatty liver disease.3,4 Disparities in prevalence of obesity exist among different populations of children and adolescents. From 2015 to 2018, non-Hispanic black children and Mexican American youth 6–11 years of age had a higher prevalence of obesity (22.7% and 28.2%, respectively) than non-Hispanic white children (15.5%).5 These disparities are often related to contextual differences and social determinants of health, including poverty and socioeconomic status, parental education, early adverse childhood events, and access to healthier food options and safe and affordable physical activity opportunities.6–9

Background: Obesity remains a significant public health issue in the United States. Each week, millions of infants and children are cared for in early care and education (ECE) programs, making it an important setting for building healthy habits. Since 2010, 39 states promulgated licensing regulations impacting infant feeding, nutrition, physical activity, or screen time practices. We assessed trends in ECE regulations across all 50 states and the District of Columbia (D.C.) and hypothesized that states included more obesity prevention standards over time. Methods: We analyzed published ratings of state licensing regulations (2010-2018) and describe trends in uptake of 47 high-impact standards derived from Caring for Our Children's, Preventing Childhood Obesity special collection. National trends are described by (1) care type (Centers, Large Care Homes, and Small Care Homes); (2) state and U.S. region; and (3) most and least supported standards. Results: Center regulations included the most obesity prevention standards (∼13% in 2010 vs. ∼29% in 2018) compared with other care types, and infant feeding and nutrition standards were most often included, while physical activity and screen time were least supported. Some states saw significant improvements in uptake, with six states and D.C. having a 30%-point increase 2010-2018. Conclusions: Nationally, there were consistent increases in the percentage of obesity prevention standards included in ECE licensing regulations. Future studies may examine facilitators and barriers to the uptake of obesity prevention standards and identify pathways by which public health and health care professionals can act as a resource and promote obesity prevention in ECE.

OBJECTIVE: The Mind, Exercise, Nutrition, Do It! 7-13 (MEND 7-13) program was adapted in 2016 by five Denver Health federally qualified health centers (DH FQHC) into MEND+, integrating clinician medical visits into the curriculum and tracking health measures within an electronic health record (EHR). We examined trajectories of body mass index (BMI, kg/m(2)) percentile, and systolic and diastolic blood pressures (SBP & DBP) among MEND+ attendees in an expanded age range of 4-17 years, and comparable non-attendees. METHODS: Data from April 2015 to May 2018 were extracted from DH FQHC EHR for children eligible for MEND+ referral (BMI ≥85(th) percentile). The sample included 347 MEND+ attendees and 21,061 non-attendees. Mixed-effects models examined average rate of change for BMI percent of the 95(th) percentile (%BMIp95), SBP, and DBP, after completion of the study period. RESULTS: Most children were ages 7-13 years, half were male, and most were Hispanic. An average of 4.2 MEND+ clinical sessions were attended. Before MEND+, %BMIp95 increased by 0.247 units/month among MEND+ attendees. After attending, %BMIp95 decreased by 0.087 units/month (p<0.001). Eligible non-attendees had an increase of 0.084/month in %BMIp95. Before MEND+ attendance, SBP and DBP increased by 0.041 and 0.022/month, respectively. After MEND+ attendance, SBP and DBP decreased by 0.254 /month (p<0.001) and 0.114/month (p<0.01), respectively. SBP and DBP increased by 0.032 and 0.033/month in eligible non-attendees, respectively. CONCLUSIONS: %BMIp95, SBP, and DBP significantly decreased among MEND+ attendees when implemented in community-based clinical practice settings at DH FQHC.

PURPOSE: Determine prevalence of overweight and obesity as reported in Head Start Program Information Reports. DESIGN: Serial cross-sectional census reports from 2012-2018. SETTING: Head Start programs countrywide, aggregated from program level to state and national level. SUBJECTS: Population of children enrolled in Head Start with reported weight status data. MEASURES: Prevalence of overweight (body mass index [BMI] ≥85th percentile to <95th percentile) and obesity (BMI ≥95th percentile). ANALYSIS: Used descriptive statistics to present the prevalence of overweight and obesity by state. Performed unadjusted regression analysis to examine annual trends or average annual changes in prevalence. RESULTS: In 2018, the prevalence of overweight was 13.7% (range: 8.9% in Alabama to 20.4% in Alaska). The prevalence of obesity was 16.6% (range: 12.5% in South Carolina to 27.1% in Alaska). In the unadjusted regression model, 34 states and the District of Columbia did not have a linear trend significantly different from zero. There was a statistically significant positive trend in obesity prevalence for 13 states and a negative trend for 3 states. CONCLUSION: The prevalence of obesity and overweight in Head Start children remained stable but continues to be high. Head Start reports may be an additional source of surveillance data to understand obesity prevalence in low-income young children.

OBJECTIVE: To compare primary care pediatricians' practices and attitudes regarding obesity assessment, prevention, and treatment in children 2 years and older in 2006 and 2017. STUDY DESIGN: National, random samples of American Academy of Pediatrics members were surveyed in 2006, 2010, and 2017 on practices and attitudes regarding overweight and obesity (analytic n = 655, 592, and 558, respectively). Using logistic regression models (controlling for pediatrician and practice characteristics), we examined survey year with predicted values (PVs), including body mass index (BMI) assessment across 2006, 2010, and 2017 and practices and attitudes in 2006 and 2017. RESULTS: Pediatrician respondents in 2017 were significantly more likely than in 2006 and 2010 to report calculating and plotting BMI at every well-child visit, with 96% of 2017 pediatricians reporting they do this. Compared with 2006, in 2017 pediatricians were more likely to discuss family behaviors related to screen time, sugar-sweetened beverages, and eating meals together, P < .001 for all. There were no observed differences in frequency of discussions on parental role modeling of nutrition and activity-related behaviors, roles in food selection, and frequency of eating fast foods or eating out. Pediatricians in 2017 were more likely to agree BMI adds new information relevant to medical care (PV = 69.8% and 78.1%), they have support staff for screening (PV = 45.3% and 60.5%), and there are effective means of treating obesity (PV = 36.3% and 56.2%), P < .001 for all. CONCLUSIONS: Results from cross-sectional surveys in 2006 and 2017 suggest nationwide, practicing pediatricians have increased discussions with families on several behaviors and their awareness and practices around obesity care.

Background: Childhood obesity care management options can be delivered in community-, clinic-, and hospital-settings. The referral practices of clinicians to these various settings have not previously been characterized beyond the local level. This study describes the management strategies and referral practices of clinicians caring for pediatric patients with obesity and associated clinician characteristics in a geographically diverse sample. Methods: This cross-sectional study used data from the DocStyles 2017 panel-based survey of 891 clinicians who see pediatric patients. We used multivariable logistic regression to estimate associations between the demographic and practice characteristics of clinicians and types of referrals for the purposes of pediatric weight management. Results: About half of surveyed clinicians (54%) referred <25% of their pediatric patients with obesity for the purposes of weight management. Only 15% referred most (>/=75%) of their pediatric patients with obesity for weight management. Referral types included clinical referrals, behavioral referrals, and weight management program (WMP) referrals. Within these categories, the percentage referrals ranged from 19% for behavioral/mental health professionals to 72% for registered dieticians. Among the significant associations, female clinicians had higher odds of referral to community and clinical WMP; practices in the Northeast had higher odds of referral to subspecialists, dieticians, mental health professionals, and clinical WMP; and clinics having >/=15 well child visits per week were associated with higher odds of referral to subspecialists, mental health professionals, and health educators. Not having an affiliation with teaching hospitals and serving low-income patients were associated with lower odds of referral to mental health professionals, and community and clinical WMP. Compared to pediatricians, family practitioners, internists, and nurse practitioners had higher odds of providing referrals to mental health professionals and to health educators. Conclusion: This study helps characterize the current landscape of referral practices and management strategies of clinicians who care for pediatric patients with obesity. Our data provide insight into the clinician, clinical practice, and reported patient characteristics associated with childhood obesity referral types. Understanding referral patterns and management strategies may help improve care for children with obesity and their families.

INTRODUCTION: The U.S. Preventive Services Task Force recommends clinicians screen children aged 6 years or older for obesity and offer or refer children with obesity to intensive weight management programs. This study explores clinician awareness of weight management programs meeting the recommendation, adherence to the recommendation of screening and referral, and associations between provider and practice characteristics and weight management program referrals. METHODS: This cross-sectional study used data from the DocStyles survey 2017, a web-based panel survey, analyzed in 2017. Among 1,023 clinicians who see pediatric patients, this study examined clinician awareness of weight management programs in their communities that met the recommendation, practice of screening for childhood obesity, and referral to weight management programs. Multivariable logistic regression estimated associations between the demographic and practice characteristics of clinicians and weight management program referrals. RESULTS: Only 24.6% of surveyed clinicians were aware of a weight management program that met the U.S. Preventive Services Task Force recommendation in their community; of those aware, 88.9% referred patients to these weight management programs. Most (83.6%) clinicians screened children for obesity in >/=75% of visits. Overall, 53.5% of clinicians provided referrals to weight management programs. Referral was higher among female clinicians and clinicians serving mostly middle-income patients. Providers without teaching hospital privileges had lower odds of referral. CONCLUSIONS: Adherence to clinical recommendations is essential to curbing the childhood obesity epidemic. Only one in four surveyed clinicians were aware of weight management programs in their community meeting U.S. Preventive Services Task Force criteria. Half of clinicians referred pediatric patients with obesity to a weight management program. Results suggest efforts are needed to increase awareness of, and referral to, weight management programs meeting the recommendation.

BACKGROUND: The evidence for and our understanding of community-level strategies such as policies, system, and environmental changes that support healthy eating and active living is growing. However, researchers and evaluation scientists alike are still not confident in what to recommend for preventing or sustaining declines in the prevalence of obesity. METHODS: The Systematic Screening and Assessment (SSA) methodology was adapted as a retrospective process to confirm obesity declines and to better understand what and how policies and programs or interventions may contribute as drivers. The Childhood Obesity Declines (COBD) project's adaptation of the SSA methodology consisted of the following components: (1) establishing and convening an external expert advisory panel; (2) identification and selection of sites reporting obesity declines; (3) confirmation and review of what strategies occurred and contextual factors were present during the period of the obesity decline; and (4) reporting the findings to sites and the field. RESULTS/DISCUSSION: The primary result of the COBD project is an in-depth examination of the question, "What happened and how did it happen in communities where the prevalence of obesity declined?" The primary aim of this article is to describe the project's methodology and present its limitations and strengths. CONCLUSIONS: Exploration of the natural experiments such that occurred in Anchorage, Granville County, New York City, and Philadelphia is the beginning of our understanding of the drivers and contextual factors that may affect childhood obesity. This retrospective examination allows us to: (1) describe targeted interventions; (2) examine the timeline and summarize intervention implementation; (3) document national, state, local, and institutional policies; and (4) examine the influence of the reach and potential multisector layering of interventions.

BACKGROUND: State- and local-level policies can influence children's diet quality and physical activity (PA) behaviors. The goal of this article is to understand the enacted state and local policy landscape in four communities reporting declines in childhood obesity. METHODS AND RESULTS: State-level policies were searched within the CDC's online Chronic Disease State Policy Tracking System. Local level policies were captured during key informant interviews in each of the sites. Policies were coded by setting [i.e., early care and education (ECE) also known as child care, school, community], jurisdictional level (i.e., state or local) and policy type (i.e., legislation or regulation). The time period for each site was unique, capturing enacted policies 5 years before the reported declines in childhood obesity in each of the communities. A total of 39 policies were captured across the 4 sites. The majority originated at the state level. Two policies pertaining to ECE, documented during key informant interviews, were found to be adopted at the local level. CONCLUSION: Similarities were noted between the four communities in the types of polices enacted. All four communities had state- and/or local-level policies that aimed to improve the nutrition environment and increase opportunities for PA in both the ECE and K-12 school settings. This article is a step in the process of determining what may have contributed to obesity declines in the selected communities.

BACKGROUND: Recent findings show that national childhood obesity prevalence overall is improving among some age groups, but that disparities continue to persist, particularly among populations that have historically been at higher risk of obesity and overweight. Over the past several years, many jurisdictions at the city or county level across the nation have also reported declines. Little evaluation has focused on understanding the factors that influence the implementation of efforts to reduce childhood obesity rates. This article summarizes the rationale, aims, and overall design of the Childhood Obesity Declines Project (COBD), which was the first of its kind to systematically study and document the what, how, when, and where of community-based obesity strategies in four distinct communities across the nation. METHODS: COBD was initiated by the National Collaborative on Childhood Obesity Research (NCCOR), was led by a subset of NCCOR advisors and a research team at ICF, and was guided by external advisors made up of researchers, decision makers, and other key stakeholders. The research team used an adapted version of the Systematic Screening and Assessment method to review and collect retrospective implementation data in four communities. RESULTS: COBD found that sites implemented strategies across the many levels and environments that impact children's well being (akin to the social-ecological framework), building a Culture of Health in their communities. CONCLUSIONS: COBD demonstrates how collaboratives of major funders with the support of other experts and key stakeholders, can help to accelerate progress in identifying and disseminating strategies that promote healthy eating and physical activity.

BACKGROUND: Although childhood obesity rates have been high in the last few decades, recent national reports indicate a stabilization of rates among some subpopulations of children. This study examines the implementation of initiatives, policies, and programs (referred to as strategies) in four communities that experienced declines in childhood obesity between 2003 and 2012. METHODS AND RESULTS: The Childhood Obesity Decline project verified obesity declines and identified strategies that may have influenced and supported the decline in obesity. The project used an adaptation of the Systematic Screening and Assessment method to identify key informants in each site. Four settings were highlighted related to childhood: (1) communities, (2) schools, (3) early care and education, and (4) healthcare. The findings indicate that programs and policies were implemented across local settings (primarily in schools and early childhood settings) and at the state level, during a timeframe of supportive federal policies and initiatives. CONCLUSIONS: Multilevel approaches were aimed to improve the nutrition and physical activity environments where children spend most of their time. We hypothesized that other, more distal strategies amplified and reinforced the impact of the efforts that more directly targeted children. The simultaneous public health messaging and multilayered initiatives, supported by cross-sector partnerships and active, high-level champions, were identified as likely important contributors to success in attaining declines in rates of childhood obesity.

BACKGROUND: The social ecological model (SEM) is a framework for understanding the interactive effects of personal and environmental factors that determine behavior. The SEM has been used to examine childhood obesity interventions and identify factors at each level that impact behaviors. However, little is known about how those factors interact both within and across levels of the SEM. METHODS: The Childhood Obesity Declines (COBD) project was exploratory, attempting to capture retrospectively policies and programs that occurred in four communities that reported small declines in childhood obesity. It also examined contextual factors that may have influenced initiatives, programs, or policies. Data collection included policy and program assessments, key informant interviews, and document reviews. These data were aggregated by the COBD project team to form a site report for each community (available at www.nccor.org/projects/obesity-declines ). These reports were used to develop site summaries that illustrate how policies, programs, and activities worked to address childhood obesity in each study site. RESULTS/CONCLUSIONS: Site summaries for Anchorage, AK; Granville County, NC; Philadelphia, PA; and New York City, NY, describe those policies and programs implemented across the levels of the SEM to address childhood obesity and examine interactions both across and within levels of the model to better understand what factors appear important for implementation success.

BACKGROUND: Childhood obesity remains prevalent and is increasing in some disadvantaged populations. Numerous research, policy and community initiatives are undertaken to impact this pandemic. Understudied are natural experiments. The need to learn from these efforts is paramount. Resulting evidence may not be readily available to inform future research, community initiatives, and policy development/implementation. METHODS: We discuss the implications of using an adaptation of the Systematic Screening and Assessment (SSA) method to evaluate the Childhood Obesity Declines (COBD) project. The project examined successful initiatives, programs and policies in four diverse communities which were concurrent with significant declines in child obesity. In the context of other research designs and evaluation schemas, rationale for use of SSA is presented. Evidence generated by this method is highlighted and guidance suggested for evaluation of future studies of community-based childhood obesity prevention initiatives. Support for the role of stakeholder collaboratives, in particular the National Collaborative on Childhood Obesity Research, as a synergistic vehicle to accelerate research on childhood obesity is discussed. RESULTS/DISCUSSION: SSA mapped active processes and provided contextual understanding of multi-level/component simultaneous efforts to reduce rates of childhood obesity in community settings. Initiatives, programs and policies were not necessarily coordinated. And although direct attribution of intervention/initiative/policy components could not be made, the what, by who, how, to whom was temporally associated with statistically significant reductions in childhood obesity. CONCLUSIONS: SSA provides evidence for context and processes which are not often evaluated in other data analytic methods. SSA provides an additional tool to layer with other evaluation approaches.

Childhood obesity continues to be a local, state, and national problem affecting not only children but their families, schools, employers, and communities. Obesity affects approximately 12.5 million (17%) US children and adolescents aged 2 to 19 years, with higher levels among some groups of children, including those living in low-income households. Obesity can have harmful effects during childhood. Children who have obesity are more likely to have high blood pressure and high cholesterol, which are risk factors for cardiovascular disease. They are more likely to have asthma, sleep apnea, fatty liver, insulin resistance, and type 2 diabetes. Obesity is also related to psychosocial problems in children, such as anxiety, depression, low self-esteem, and social problems such as bullying and stigma (1). To address obesity, the National Academy of Medicine (formerly the Institute of Medicine), among other groups, has called for interventions to alter nutrition and physical activity environments and promote behavior change in multiple settings to reach adults and children. For children, in addition to the home setting, other settings that can help support obesity prevention and aid healthy child growth include early care and education (ECE) or child care, schools, community, and health care (2).

INTRODUCTION: A quality rating and improvement system (QRIS) is a fundamental component of most states' early care and education infrastructures. States can use a QRIS to set standards that define high-quality care and award child care providers with a quality rating designation based on how well they meet these standards. The objective of this review was to describe the extent to which states' QRIS standards include obesity prevention content. METHODS: We collected publicly available data on states' QRIS standards. We compared states' QRIS standards with 47 high-impact obesity prevention components in Caring for Our Children: National Health and Safety Performance Standards; Guidelines for Early Care and Education Programs, 3rd Edition, and 6 additional topics based on the Centers for Disease Control and Prevention's Spectrum of Opportunities for Obesity Prevention in the Early Care and Education Setting. RESULTS: Thirty-eight states operated a state-wide QRIS in early 2015. Of those, 27 states' QRIS included obesity prevention standards; 20 states had at least one QRIS standard that aligned with the high-impact obesity prevention components, and 21 states had at least one QRIS standard that aligned with at least one of the 6 additional topics. QRIS standards related to the physical activity high-impact obesity prevention components were the most common, followed by components for screen time, nutrition, and infant feeding. CONCLUSION: The high proportion of states operating a QRIS that included obesity prevention standards, combined with the widespread use of QRISs among states, suggests that a QRIS is a viable way to embed obesity prevention standards into state early care and education systems.

PURPOSE: To compare the performance of a 1-question survey screener measuring total sugar-sweetened beverage (SSB) intake to a screener measuring SSB types separately using 4 questions. DESIGN: Cross-sectional. SETTING: Web-based 2014 SummerStyles survey. PARTICIPANTS: A total of 4167 US adults (≥18 years). MEASURES: Frequency of SSB intake measured using a 1-question screener was compared to frequency using a 4-question screener (regular soda, fruit drinks, sports/energy drinks, sweetened coffee/tea). SSB intake (number of time/day) was categorized as 0, >0 to <1, and ≥1 time/day; difference in mean intake was calculated between 4 questions versus 1. ANALYSIS: Paired t tests were used, and agreement was evaluated using weighted kappa and Lin's concordance correlation coefficient (CCC). RESULTS: Mean SSB intake was 1.7 (95% confidence interval [CI]: 1.65-1.79) times/day using 4 questions and 0.6 (95% CI: 0.56-0.62) times/day using 1 question ( P < .001). Intake frequency based on 4 questions versus 1 was 16.0% versus 38.5% for 0 time/day, 15.6% versus 42.5% for >0 to <1 time/day, and 68.4% versus 18.9% for ≥1 time/day. There was fair agreement for the 3 SSB intake categories (kappa: .27) and poor absolute agreement between the 2 continuous measures (Lin's CCC: 0.31). CONCLUSION: Daily SSB intake was significantly lower using a 1-question screener versus a 4-question screener. Researchers should assess SSB types separately or consider that daily SSB intake is likely underestimated with 1 question.

Chronic disease, which is linked to unhealthy nutrition environments, is highly prevalent in Guam. The nutrition environment was assessed in 114 stores and 63 restaurants in Guam. Stores had limited availability of some healthier foods such as lean ground meat (7.5%) and 100% whole-wheat bread (11.4%), while fruits (81.0%) and vegetables (94.8%) were more commonly available; 43.7% of restaurants offered a healthy entree or main dish salad, 4.1% provided calorie information, and 15.7% denoted healthier choices on menus. Improving the nutrition environment could help customers make healthier choices.

PURPOSE: This study examined associations between sugar-sweetened beverage (SSB) intake and acculturation among a sample representing civilian noninstitutionalized U.S. adults. DESIGN: Quantitative, cross-sectional study. SETTING: National. SUBJECTS: The 2010 National Health Interview Survey data for 17,142 Hispanics and U.S.-born non-Hispanic whites (≥18 years). MEASURES: The outcome variable was daily SSB intake (nondiet soda, fruit drinks, sports drinks, energy drinks, and sweetened coffee/tea drinks). Exposure variables were Hispanic ethnicity and proxies of acculturation (language of interview, birthplace, and years living in the United States). ANALYSIS: We used multivariate logistic regression to estimate adjusted odds ratios (ORs) for the exposure variables associated with drinking SSB ≥1 time/d after controlling for covariates. RESULTS: The adjusted odds of drinking SSB ≥1 time/d was significantly higher among Hispanics who completed the interview in Spanish (OR = 1.65) than U.S.-born non-Hispanic whites. Compared with those who lived in the United States for <5 years, the adjusted odds of drinking SSB ≥1 time/d was higher among adults who lived in the United States for 5 to <10 years (OR = 2.72), those who lived in the United States for 10 to <15 years (OR = 2.90), and those who lived in the United States for ≥15 years (OR = 2.41). However, birthplace was not associated with daily SSB intake. CONCLUSION: The acculturation process is complex and these findings contribute to identifying important subpopulations that may benefit from targeted intervention to reduce SSB intake.