Minute level smartphone derived exposure to greenness and consumer wearable derived physical activity in a cohort of US women.

BACKGROUND: Inconsistent results have been found in the literature on associations of greenness, or vegetation quantity, and physical activity. However, few studies have assessed associations between mobility-based greenness and physical activity from mobile health data from smartphone and wearable devices with fine spatial and temporal resolution. METHODS: We assessed mobility-based greenness exposure and wearable accelerometer data from participants in the US-based prospective Nurses' Health Study 3 cohort Mobile Health (mHealth) Substudy (2018-2020). We recruited 500 female participants with instructions to wear devices over four 7-day sampling periods equally spaced throughout the year. After restriction criteria there were 337 participants (mean age 36 years) with n = 639,364 unique observations. Normalized Difference Vegetation Index (NDVI) data were derived from 30 m x 30 m Landsat-8 imagery and spatially joined to GPS points recorded every 10 min. Fitbit proprietary algorithms provided physical activity summarized as mean number of steps per minute, which we averaged during the 10-min period following a GPS-based greenness exposure assessment. We utilized Generalized Additive Mixed Models to examine associations (every 10 min) between greenness and physical activity adjusting for neighborhood and individual socioeconomic status, Census region, season, neighborhood walkability, daily mean temperature and precipitation. We assessed effect modification through stratification and interaction models and conducted sensitivity analyses. RESULTS: Mean 10-min step count averaged 7.0 steps (SD 14.9) and greenness (NDVI) averaged 0.3 (SD 0.2). Contrary to our hypotheses, higher greenness exposure was associated non-linearly with lower mean steps per minute after adjusting for confounders. We observed statistically significant effect modification by Census region and season. DISCUSSION: We utilized objective physical activity data at fine temporal and spatial scales to present novel estimates of the association between mobility-based greenness and step count. We found higher levels of greenness were inversely associated with steps per minute.

State-Specific Prevalence of Severe Obesity Among Adults in the US Using Bias Correction of Self-Reported Body Mass Index.

INTRODUCTION: Adults with severe obesity are at increased risk for poor metabolic health and may need more intensive clinical and community supports. The prevalence of severe obesity is underestimated from self-reported weight and height data. We examined severe obesity prevalence among US adults by sociodemographic characteristics and by state after adjusting for self-report bias. METHODS: Using a validated bias-correction method, we adjusted self-reported body mass index (BMI) data from the 2020 Behavioral Risk Factor Surveillance System (BRFSS) by using measured data from the National Health and Nutrition Examination Survey. We compared bias-corrected prevalence of severe obesity (BMI ≥40) with self-reported estimates by sociodemographic characteristics and state. RESULTS: Self-reported BRFSS data significantly underestimated the prevalence of severe obesity compared with bias-corrected estimates. In 2020, 8.8% of adults had severe obesity based on the bias-corrected estimates, whereas 5.3% of adults had severe obesity based on self-reported data. Women had a significantly higher prevalence of bias-corrected severe obesity (11.1%) than men (6.5%). State-level prevalence of bias-corrected severe obesity ranged from 5.5% (Massachusetts) to 13.2% (West Virginia). Based on bias-corrected estimates, 16 states had a prevalence of severe obesity greater than 10%, a level not seen in the self-reported estimates. CONCLUSION: Self-reported BRFSS data underestimated the overall prevalence of severe obesity by 40% (5.3% vs 8.8%). Accurate state-level estimates of severe obesity can help public health and health care decision makers prioritize and plan to implement effective prevention and treatment strategies for people who are at high risk for poor metabolic health.

Use of Evidence-Based Interventions to Promote Healthy Weight, Nutrition, and Physical Activity in Community Health Improvement Plans from Large Local Health Departments.

We sought to identify evidence-based healthy weight, nutrition, and physical activity strategies related to obesity prevention in large local health department (LHD) Community Health Improvement Plans (CHIPs). We analyzed the content of the most recent, publicly available plans from 72 accredited LHDs serving a population of at least 500 000 people. We matched CHIP strategies to the County Health Rankings and Roadmaps' What Works for Health (WWFH) database of interventions. We identified 739 strategies across 55 plans, 62.5% of which matched a "WWFH intervention" rated for effectiveness on diet and exercise outcomes. Among the 20 most commonly identified WWFH interventions in CHIPs, 10 had the highest evidence for effectiveness while 4 were rated as likely to decrease health disparities according to WWFH. Future prioritization of strategies by health agencies could focus on strategies with the strongest evidence for promoting healthy weight, nutrition, and physical activity outcomes and reducing health disparities.

Projected U.S. State-Level Prevalence of Adult Obesity and Severe Obesity.

BACKGROUND: Although the national obesity epidemic has been well documented, less is known about obesity at the U.S. state level. Current estimates are based on body measures reported by persons themselves that underestimate the prevalence of obesity, especially severe obesity. METHODS: We developed methods to correct for self-reporting bias and to estimate state-specific and demographic subgroup-specific trends and projections of the prevalence of categories of body-mass index (BMI). BMI data reported by 6,264,226 adults (18 years of age or older) who participated in the Behavioral Risk Factor Surveillance System Survey (1993-1994 and 1999-2016) were obtained and corrected for quantile-specific self-reporting bias with the use of measured data from 57,131 adults who participated in the National Health and Nutrition Examination Survey. We fitted multinomial regressions for each state and subgroup to estimate the prevalence of four BMI categories from 1990 through 2030: underweight or normal weight (BMI [the weight in kilograms divided by the square of the height in meters], <25), overweight (25 to <30), moderate obesity (30 to <35), and severe obesity (≥35). We evaluated the accuracy of our approach using data from 1990 through 2010 to predict 2016 outcomes. RESULTS: The findings from our approach suggest with high predictive accuracy that by 2030 nearly 1 in 2 adults will have obesity (48.9%; 95% confidence interval [CI], 47.7 to 50.1), and the prevalence will be higher than 50% in 29 states and not below 35% in any state. Nearly 1 in 4 adults is projected to have severe obesity by 2030 (24.2%; 95% CI, 22.9 to 25.5), and the prevalence will be higher than 25% in 25 states. We predict that, nationally, severe obesity is likely to become the most common BMI category among women (27.6%; 95% CI, 26.1 to 29.2), non-Hispanic black adults (31.7%; 95% CI, 29.9 to 33.4), and low-income adults (31.7%; 95% CI, 30.2 to 33.2). CONCLUSIONS: Our analysis indicates that the prevalence of adult obesity and severe obesity will continue to increase nationwide, with large disparities across states and demographic subgroups. (Funded by the JPB Foundation.).

Changes in the calorie and nutrient content of purchased fast food meals after calorie menu labeling: A natural experiment.

BACKGROUND: Calorie menu labeling is a policy that requires food establishments to post the calories on menu offerings to encourage healthy food choice. Calorie labeling has been implemented in the United States since May 2018 per the Affordable Care Act, but to the best of our knowledge, no studies have evaluated the relationship between calorie labeling and meal purchases since nationwide implementation of this policy. Our objective was to investigate the relationship between calorie labeling and the calorie and nutrient content of purchased meals after a fast food franchise began labeling in April 2017, prior to the required nationwide implementation, and after nationwide implementation of labeling in May 2018, when all large US chain restaurants were required to label their menus. METHODS AND FINDINGS: We obtained weekly aggregated sales data from 104 restaurants that are part of a fast food franchise for 3 national chains in 3 US states: Louisiana, Mississippi, and Texas. The franchise provided all sales data from April 2015 until April 2019. The franchise labeled menus in April 2017, 1 year prior to the required nationwide implementation date of May 2018 set by the US Food and Drug Administration. We obtained nutrition information for items sold (calories, fat, carbohydrates, protein, saturated fat, sugar, dietary fiber, and sodium) from Menustat, a publicly available database with nutrition information for items offered at the top revenue-generating US restaurant chains. We used an interrupted time series to find level and trend changes in mean weekly calorie and nutrient content per transaction after franchise and nationwide labeling. The analytic sample represented 331,776,445 items purchased across 67,112,342 transactions. Franchise labeling was associated with a level change of -54 calories/transaction (95% confidence interval [CI]: -67, -42, p < 0.0001) and a subsequent 3.3 calories/transaction increase per 4-week period (95% CI: 2.5, 4.1, p < 0.0001). Nationwide implementation was associated with a level decrease of -82 calories/transaction (95% CI: -88, -76, p < 0.0001) and a subsequent -2.1 calories/transaction decrease per 4-week period (95% CI: -2.9, -1.3, p < 0.0001). At the end of the study, the model-based predicted mean calories/transaction was 4.7% lower (change = -73 calories/transaction, 95% CI: -81, -65), and nutrients/transaction ranged from 1.8% lower (saturated fat) to 7.0% lower (sugar) than what we would expect had labeling not been implemented. The main limitations were potential residual time-varying confounding and lack of individual-level transaction data. CONCLUSIONS: In this study, we observed that calorie labeling was associated with small decreases in mean calorie and nutrient content of fast food meals 2 years after franchise labeling and nearly 1 year after implementation of labeling nationwide. These changes imply that calorie labeling was associated with small improvements in purchased meal quality in US chain restaurants.

Comparing shopper characteristics by online grocery ordering use among households in low-income communities in Maine.

OBJECTIVE: Online grocery shopping could improve access to healthy food, but it may not be equally accessible to all populations - especially those at higher risk for food insecurity. The current study aimed to compare the socio-demographic characteristics of families who ordered groceries online v. those who only shopped in-store. DESIGN: We analysed enrollment survey and 44 weeks of individually linked grocery transaction data. We used univariate χ2 and t-tests and logistic regression to assess differences in socio-demographic characteristics between households that only shopped in-store and those that shopped online with curbside pickup (online only or online and in-store). SETTING: Two Maine supermarkets. PARTICIPANTS: 863 parents or caregivers of children under 18 years old enrolled in two fruit and vegetable incentive trials. RESULTS: Participants had a total of 32 757 transactions. In univariate assessments, online shoppers had higher incomes (P < 0 0001), were less likely to participate in Special Supplemental Nutrition Program for Women, Infants, and Children or Supplemental Nutrition Assistance Program (SNAP; P < 0 0001) and were more likely to be female (P = 0·04). Most online shoppers were 30-39 years old, and few were 50 years or older (P = 0·003). After controlling for age, gender, race/ethnicity, number of children, number of adults, income and SNAP participation, female primary shoppers (OR = 2·75, P = 0·003), number of children (OR = 1·27, P = 0·04) and income (OR = 3·91 for 186-300 % federal poverty line (FPL) and OR = 6·92 for >300 % FPL, P < 0·0001) were significantly associated with likelihood of shopping online. CONCLUSIONS: In the current study of Maine families, low-income shoppers were significantly less likely to utilise online grocery ordering with curbside pickup. Future studies could focus on elucidating barriers and developing strategies to improve access.

Simulation of Growth Trajectories of Childhood Obesity into Adulthood.

BACKGROUND: Although the current obesity epidemic has been well documented in children and adults, less is known about long-term risks of adult obesity for a given child at his or her present age and weight. We developed a simulation model to estimate the risk of adult obesity at the age of 35 years for the current population of children in the United States. METHODS: We pooled height and weight data from five nationally representative longitudinal studies totaling 176,720 observations from 41,567 children and adults. We simulated growth trajectories across the life course and adjusted for secular trends. We created 1000 virtual populations of 1 million children through the age of 19 years that were representative of the 2016 population of the United States and projected their trajectories in height and weight up to the age of 35 years. Severe obesity was defined as a body-mass index (BMI, the weight in kilograms divided by the square of the height in meters) of 35 or higher in adults and 120% or more of the 95th percentile in children. RESULTS: Given the current level of childhood obesity, the models predicted that a majority of today's children (57.3%; 95% uncertainly interval [UI], 55.2 to 60.0) will be obese at the age of 35 years, and roughly half of the projected prevalence will occur during childhood. Our simulations indicated that the relative risk of adult obesity increased with age and BMI, from 1.17 (95% UI, 1.09 to 1.29) for overweight 2-year-olds to 3.10 (95% UI, 2.43 to 3.65) for 19-year-olds with severe obesity. For children with severe obesity, the chance they will no longer be obese at the age of 35 years fell from 21.0% (95% UI, 7.3 to 47.3) at the age of 2 years to 6.1% (95% UI, 2.1 to 9.9) at the age of 19 years. CONCLUSIONS: On the basis of our simulation models, childhood obesity and overweight will continue to be a major health problem in the United States. Early development of obesity predicted obesity in adulthood, especially for children who were severely obese. (Funded by the JPB Foundation and others.).

Assessing the effectiveness of training models for national scale-up of an evidence-based nutrition and physical activity intervention: a group randomized trial.

BACKGROUND: There is a great need to identify implementation strategies to successfully scale-up public health interventions in order to achieve their intended population impact. The Out-of-school Nutrition and Physical Activity group-randomized trial previously demonstrated improvements in children's vigorous physical activity and the healthfulness of foods and beverages consumed. This implementation study aimed to assess the effects and costs of two training models to scale-up this evidence-based intervention. METHODS: A 3-arm group-randomized trial was conducted to compare effectiveness of in-person and online training models for scaling up the intervention compared to controls. One-third of sites were randomized to the in-person train-the-trainer model: local YMCA facilitators attended a training session and then conducted three learning collaborative meetings and technical assistance. One-third were assigned to the online model, consisting of self-paced monthly learning modules, videos, quizzes, and facilitated discussion boards. Remaining sites served as controls. Fifty-three afterschool sites from three YMCA Associations in different regions of the country completed baseline and follow-up observations using a validated tool of afterschool nutrition and physical activity practices. We used multivariable regression models, accounting for clustering of observations, to assess intervention effects on an aggregate afterschool practice primary outcome, and conducted secondary analyses of nine intervention goals (e.g. serving water). Cost data were collected to determine the resources to implement each training model. RESULTS: Changes in the primary outcome indicate that, on average, sites in the in-person arm achieved 0.44 additional goals compared to controls (95%CI 0.02, 0.86, p = 0.04). Increases in the number of additional goals achieved in sites in the online arm were not significantly greater than control sites (+ 0.28, 95% CI -0.18, 0.73, p = 0.24). Goal-specific improvements were observed for increasing water offered in the in-person arm and fruits and vegetables offered in the online arm. The cost per person trained was $678 for the in-person training model and $336 for the on-line training model. CONCLUSIONS: This pilot trial presents promising findings on implementation strategies for scale-up. It validated the in-person training model as an effective approach. The less expensive online training may be a useful option for geographically disbursed sites where in-person training is challenging. TRIAL REGISTRATION: Although this study does not report the results of a health care intervention on human subjects, it is a randomized trial and was therefore retrospectively registered in ClinicalTrials.gov on July 4, 2019 in accordance with the BMC guidelines to ensure the complete publication of all results (NCT04009304).

Integrating children's physical activity enjoyment into public health dialogue (United States).

Physical activity engagement during childhood is associated with positive health outcomes in adulthood. Exercise and sport science research links physical activity enjoyment with physical activity adoption and maintenance, among other positive health behaviors. However, public health researchers rarely measure enjoyment or discuss its role in interventions or theory. In this paper, we present the rationale for bringing enjoyment to the forefront of public health dialogue and action to increase physical activity in children and across the life course. We outline five potential explanations for the lack of physical activity enjoyment research in public health, and offer solutions and action steps for each. Enjoyment research has the potential to improve people's health by working on multiple levels, from individuals to schools to public sectors, and could have positive implications for various health behaviors.

Source of bias in sugar-sweetened beverage research: a systematic review.

OBJECTIVE: Financial conflicts of interest involving the food industry have been reported to bias nutrition studies. However, some have hypothesized that independently funded studies may be biased if the authors have strong a priori beliefs about the healthfulness of a food product ('white hat bias'). The extent to which each source of bias may affect the scientific literature has not been examined. We aimed to explore this question with research involving sugar-sweetened beverages (SSB) as a test case, focusing on a period during which scientific consensus about the adverse health effects of SSB emerged from uncertainty. DESIGN: PubMed search of worldwide literature was used to identify articles related to SSB and health risks published between 2001 and 2013. Financial relationships and article conclusions were classified by independent groups of co-investigators. Associations were explored by Fischer's exact tests and regression analyses, controlling for covariates. RESULTS: A total of 133 articles published in English met inclusion criteria. The proportion of industry-related scientific studies decreased significantly with time, from approximately 30 % at the beginning of the study period to <5 % towards the end (P=0·003). A 'strong' or 'qualified' scientific conclusion was reached in 82 % of independent v. 7 % of industry-related SSB studies (P<0·001). Industry-related studies were overwhelmingly more likely to reach 'weak/null' conclusions compared with independent studies regarding the adverse effects of SSB consumption on health (OR=57·30, 95 % CI 7·12, 461·56). CONCLUSION: Industry-related research during a critical period appears biased to underestimate the adverse health effects of SSB, potentially delaying corrective public health action.

United States Adolescents' Television, Computer, Videogame, Smartphone, and Tablet Use: Associations with Sugary Drinks, Sleep, Physical Activity, and Obesity.

OBJECTIVE: To quantify the relationships between youth use of television (TV) and other screen devices, including smartphones and tablets, and obesity risk factors. STUDY DESIGN: TV and other screen device use, including smartphones, tablets, computers, and/or videogames, was self-reported by a nationally representative, cross-sectional sample of 24 800 US high school students (2013-2015 Youth Risk Behavior Surveys). Students also reported on health behaviors including sugar-sweetened beverage (SSB) intake, physical activity, sleep, and weight and height. Sex-stratified logistic regression models, adjusting for the sampling design, estimated associations between TV and other screen device use and SSB intake, physical activity, sleep, and obesity. RESULTS: Approximately 20% of participants used other screen devices for ≥5 hours daily. Watching TV ≥5 hours daily was associated with daily SSB consumption (aOR = 2.72, 95% CI: 2.23, 3.32) and obesity (aOR = 1.78, 95% CI: 1.40, 2.27). Using other screen devices ≥5 hours daily was associated with daily SSB consumption (aOR = 1.98, 95% CI: 1.69, 2.32), inadequate physical activity (aOR = 1.94, 95% CI: 1.69, 2.25), and inadequate sleep (aOR = 1.79, 95% CI: 1.54, 2.08). CONCLUSIONS: Using smartphones, tablets, computers, and videogames is associated with several obesity risk factors. Although further study is needed, families should be encouraged to limit both TV viewing and newer screen devices.

Racial/Ethnic and Socioeconomic Disparities in Hydration Status Among US Adults and the Role of Tap Water and Other Beverage Intake.

OBJECTIVES: To evaluate whether differences in tap water and other beverage intake explain differences in inadequate hydration among US adults by race/ethnicity and income. METHODS: We estimated the prevalence of inadequate hydration (urine osmolality ≥ 800 mOsm/kg) by race/ethnicity and income of 8258 participants aged 20 to 74 years in the 2009 to 2012 National Health and Nutrition Examination Survey. Using multivariable regression models, we estimated associations between demographic variables, tap water intake, and inadequate hydration. RESULTS: The prevalence of inadequate hydration among US adults was 29.5%. Non-Hispanic Blacks (adjusted odds ratio [AOR] = 1.44; 95% confidence interval [CI] = 1.17, 1.76) and Hispanics (AOR = 1.42; 95% CI = 1.21, 1.67) had a higher risk of inadequate hydration than did non-Hispanic Whites. Lower-income adults had a higher risk of inadequate hydration than did higher-income adults (AOR = 1.23; 95% CI = 1.04, 1.45). Differences in tap water intake partially attenuated racial/ethnic differences in hydration status. Differences in total beverage and other fluid intake further attenuated sociodemographic disparities. CONCLUSIONS: Racial/ethnic and socioeconomic disparities in inadequate hydration among US adults are related to differences in tap water and other beverage intake. Policy action is needed to ensure equitable access to healthy beverages.

A Community-Level Sodium Reduction Intervention, Boston, 2013-2015.

OBJECTIVES: To evaluate a community-level sodium-reduction intervention in Boston, Massachusetts. Reducing sodium in the food offerings of community settings may help reduce hypertension disparities. METHODS: We examined changes in the proportion of prepackaged foods with greater than 200 milligrams of sodium in 7 hospitals, 8 YMCAs, 4 community health centers, and 2 organizations serving homeless populations. Research assistants documented prepackaged items in cafeterias, kiosks, and vending machines before and after the intervention (2013-2015). We assessed intervention change via linear mixed models accounting for repeated observations. RESULTS: There were 161 access points at baseline (4347 facings) and 171 (4996 facings) at follow-up. The percentage of prepackaged products with greater than 200 milligrams of sodium decreased from 29.0% at baseline to 21.5% at follow-up (P = .003). Changes were driven by improvements in hospital cafeterias and kiosks (P = .003). The percentage of products with greater than 200 milligrams of sodium in YMCA vending decreased 58% (from 27.2% to 11.5%; P = .017); other organizations had nonsignificant declines. CONCLUSIONS: We found modest reductions in the percentage of higher-sodium prepackaged products across community institutions. Community-level interventions may increase availability of lower-sodium products in the food supply.

Using cost-effectiveness analysis to prioritize policy and programmatic approaches to physical activity promotion and obesity prevention in childhood.

Participation in recommended levels of physical activity promotes a healthy body weight and reduced chronic disease risk. To inform investment in prevention initiatives, we simulate the national implementation, impact on physical activity and childhood obesity and associated cost-effectiveness (versus the status quo) of six recommended strategies that can be applied throughout childhood to increase physical activity in US school, afterschool and childcare settings. In 2016, the Childhood Obesity Intervention Cost Effectiveness Study (CHOICES) systematic review process identified six interventions for study. A microsimulation model estimated intervention outcomes 2015-2025 including changes in mean MET-hours/day, intervention reach and cost per person, cost per MET-hour change, ten-year net costs to society and cases of childhood obesity prevented. First year reach of the interventions ranged from 90,000 youth attending a Healthy Afterschool Program to 31.3 million youth reached by Active School Day policies. Mean MET-hour/day/person increases ranged from 0.05 MET-hour/day/person for Active PE and Healthy Afterschool to 1.29 MET-hour/day/person for the implementation of New Afterschool Programs. Cost per MET-hour change ranged from cost saving to $3.14. Approximately 2500 to 110,000 cases of children with obesity could be prevented depending on the intervention implemented. All of the six interventions are estimated to increase physical activity levels among children and adolescents in the US population and prevent cases of childhood obesity. Results do not include other impacts of increased physical activity, including cognitive and behavioral effects. Decision-makers can use these methods to inform prioritization of physical activity promotion and obesity prevention on policy agendas.

Using School Staff Members to Implement a Childhood Obesity Prevention Intervention in Low-Income School Districts: the Massachusetts Childhood Obesity Research Demonstration (MA-CORD Project), 2012-2014.

INTRODUCTION: Although evidence-based interventions to prevent childhood obesity in school settings exist, few studies have identified factors that enhance school districts' capacity to undertake such efforts. We describe the implementation of a school-based intervention using classroom lessons based on existing "Eat Well and Keep Moving" and "Planet Health" behavior change interventions and schoolwide activities to target 5,144 children in 4th through 7th grade in 2 low-income school districts. METHODS: The intervention was part of the Massachusetts Childhood Obesity Research Demonstration (MA-CORD) project, a multisector community-based intervention implemented from 2012 through 2014. Using mixed methods, we operationalized key implementation outcomes, including acceptability, adoption, appropriateness, feasibility, implementation fidelity, perceived implementation cost, reach, and sustainability. RESULTS: MA-CORD was adopted in 2 school districts that were facing resource limitations and competing priorities. Although strong leadership support existed in both communities at baseline, one district's staff reported less schoolwide readiness and commitment. Consequently, fewer teachers reported engaging in training, teaching lessons, or planning to sustain the lessons after MA-CORD. Interviews showed that principal and superintendent turnover, statewide testing, and teacher burnout limited implementation; passionate wellness champions in schools appeared to offset implementation barriers. CONCLUSION: Future interventions should assess adoption readiness at both leadership and staff levels, offer curriculum training sessions during school hours, use school nurses or health teachers as wellness champions to support teachers, and offer incentives such as staff stipends or play equipment to encourage school participation and sustained intervention activities.

Child and adolescent obesity: part of a bigger picture.

The prevalence of childhood overweight and obesity has risen substantially worldwide in less than one generation. In the USA, the average weight of a child has risen by more than 5 kg within three decades, to a point where a third of the country's children are overweight or obese. Some low-income and middle-income countries have reported similar or more rapid rises in child obesity, despite continuing high levels of undernutrition. Nutrition policies to tackle child obesity need to promote healthy growth and household nutrition security and protect children from inducements to be inactive or to overconsume foods of poor nutritional quality. The promotion of energy-rich and nutrient-poor products will encourage rapid weight gain in early childhood and exacerbate risk factors for chronic disease in all children, especially those showing poor linear growth. Whereas much public health effort has been expended to restrict the adverse marketing of breastmilk substitutes, similar effort now needs to be expanded and strengthened to protect older children from increasingly sophisticated marketing of sedentary activities and energy-dense, nutrient-poor foods and beverages. To meet this challenge, the governance of food supply and food markets should be improved and commercial activities subordinated to protect and promote children's health.

Changes in water and sugar-containing beverage consumption and body weight outcomes in children.

An intervention study showed that promoting water consumption in schoolchildren prevented overweight, but a mechanism linking water consumption to overweight was not substantiated. We investigated whether increased water consumption replaced sugar-containing beverages and whether changes in water or sugar-containing beverages influenced body weight outcomes. In a secondary analysis of the intervention study in Germany, we analysed combined longitudinal data from the intervention and control groups. Body weight and height were measured and beverage consumption was self-reported by a 24-h recall questionnaire at the beginning and end of the school year 2006/2007. The effect of a change in water consumption on change in sugar-containing beverage (soft drinks and juices) consumption, change in BMI (kg/m2) and prevalence of overweight and obesity at follow-up was analysed using regression analyses. Of 3220 enroled children, 1987 children (mean age 8·3 (sd 0·7) years) from thirty-two schools were analysed. Increased water consumption by 1 glass/d was associated with a reduced consumption of sugar-containing beverages by 0·12 glasses/d (95 % CI -0·16, -0·08) but was not associated with changes in BMI (P=0·63). Increased consumption of sugar-containing beverages by 1 glass/d was associated with an increased BMI by 0·02 (95 % CI 0·00, 0·03) kg/m2 and increased prevalence of obesity (OR 1·22; 95 % CI 1·04, 1·44) but not with overweight (P=0·83). In conclusion, an increase in water consumption can replace sugar-containing beverages. As sugar-containing beverages were associated with weight gain, this replacement might explain the prevention of obesity through the promotion of water consumption.

US States' Childhood Obesity Surveillance Practices and Recommendations for Improving Them, 2014-2015.

INTRODUCTION: Routine collection, analysis, and reporting of data on child height, weight, and body mass index (BMI), particularly at the state and local levels, are needed to monitor the childhood obesity epidemic, plan intervention strategies, and evaluate the impact of interventions. Child BMI surveillance systems operated by the US government do not provide state or local data on children across a range of ages. The objective of this study was to describe the extent to which state governments conduct child BMI surveillance. METHODS: From August through December 2014, we conducted a structured telephone survey with state government administrators to learn about state surveillance of child BMI. We also searched websites of state health and education agencies for information about state surveillance. RESULTS: State agency administrators in 48 states and Washington, DC, completed telephone interviews (96% response rate). Based on our interviews and Internet research, we determined that 14 states collect child BMI data in a manner consistent with standard definitions of public health surveillance. CONCLUSION: The absence of child BMI surveillance systems in most states limits the ability of public health practitioners and policymakers to develop and evaluate responses to the childhood obesity epidemic. Greater investment in surveillance is needed to identify the most effective and cost-effective childhood obesity interventions.

Assessment of a Districtwide Policy on Availability of Competitive Beverages in Boston Public Schools, Massachusetts, 2013.

INTRODUCTION: Competitive beverages are drinks sold outside of the federally reimbursable school meals program and include beverages sold in vending machines, a la carte lines, school stores, and snack bars. Competitive beverages include sugar-sweetened beverages, which are associated with overweight and obesity. We described competitive beverage availability 9 years after the introduction in 2004 of district-wide nutrition standards for competitive beverages sold in Boston Public Schools. METHODS: In 2013, we documented types of competitive beverages sold in 115 schools. We collected nutrient data to determine compliance with the standards. We evaluated the extent to which schools met the competitive-beverage standards and calculated the percentage of students who had access to beverages that met or did not meet the standards. RESULTS: Of 115 schools, 89.6% met the competitive beverage nutrition standards; 88.5% of elementary schools and 61.5% of middle schools did not sell competitive beverages. Nutrition standards were met in 79.2% of high schools; 37.5% did not sell any competitive beverages, and 41.7% sold only beverages meeting the standards. Overall, 85.5% of students attended schools meeting the standards. Only 4.0% of students had access to sugar-sweetened beverages. CONCLUSION: A comprehensive, district-wide competitive beverage policy with implementation support can translate into a sustained healthful environment in public schools.