Child hood obesity programs

The strength of evidence SOE supporting interventions was graded for each study setting e. Meta-analyses were performed on studies judged sufficiently similar and appropriate to pool using random effect models. This paper reported our findings on various adiposity-related outcomes. We identified articles intervention studies of which studies were primarily school based, although other settings could have been involved.

Email Address. What's this? Division of Nutrition, Physical Activity, and Obesity. Related Topics. Links with this icon indicate that you are leaving the CDC website. Linking to a non-federal website does not constitute an endorsement by CDC or any of its employees of the sponsors or the information and products presented on the website. You will be subject to the destination website's privacy policy when you follow the link. The afterschool policy would reduce obesity prevalence in children by 1.

The microsimulation predicted that disparities would decrease for black and Hispanic adolescents, with obesity decreasing by 2. The change would be similar for children. The predicted impact of afterschool PA programs on disparities reflects higher baseline rates of obesity among blacks and Hispanics and the non-linear relationship between behavior change and BMI.

For children, afterschool PA programs would have the largest impact on obesity of the three policies. Obesity would decrease by 1. The tax would also reduce disparities, especially in adolescents. Obesity in blacks and Hispanics would drop by 3. This was due to two factors: compared to blacks and Hispanics, whites had higher income levels and are therefore less affected by a price increase, and had a lower baseline rate of obesity.

The child-directed ban on fast food TV advertising has the greatest predicted behavioral impact, but would reduce obesity prevalence the least. Although its predicted impact on obesity is small, the large behavioral result shows that TV advertising affects what children eat.

Like the other policies, its estimated impact is greater for blacks and Hispanics who watch more TV and are more heavily targeted by food marketers than whites, and thus are more impacted by reduced advertising. The Appendix describes the key univariate results of a sensitivity analysis. This microsimulation analysis suggests that long-term implementation of three federal policies could reduce childhood obesity in the U.

To our knowledge, this study provides the first quantitative estimate of the potential impact of afterschool PA programs on U. The use of microsimulation contributes to the childhood obesity literature because behavior change can be modeled over time in the simulated population.

This approach differs from models that derive estimates from population-level trends, and provides valuable information as to how policies may impact known disparities in health behaviors and obesity in different populations. Smith et al. According to the present study, a ban on child-directed fast food TV advertising would reduce obesity among children and adolescents by nearly 1 percentage point in Chou et al.

The model of Veerman and colleagues 39 predicts that a ban on all TV food advertising would reduce obesity prevalence among U. The bans in both studies are much broader than in this study. All three policies could reduce childhood obesity prevalence, particularly among blacks and Hispanics, who have higher rates of obesity than whites, thus demonstrating that federal policy could alter the childhood obesity epidemic.

It reduces obesity while generating significant revenue for additional obesity prevention activities. Andreyeva et al.

It would also reduce obesity among adults who consume SSBs, does not require substantial federal funding to implement unlike the afterschool policy , and would not face the legal hurdles that new regulations often encounter. Unfortunately, reduced federal spending, industry lobbying, a contentious political environment, and legal protection for commercial speech hinder near-term implementation of any of these policies. However, over the long timeframe included in this analysis, the infeasible may become feasible as the evidence base for these policies grows and changes in public knowledge increase calls for stronger governmental action.

Research showing the harms of consuming SSBs coupled with the need for new revenue sources may spur Congress to consider a national SSB excise tax. In the meantime, the findings support state- and local-level action to enact SSB excise taxes, promote PA in afterschool settings, and reduce marketing and advertising of unhealthy foods and beverages in public schools.

This study has several limitations. Modeling childhood obesity is challenging and others believe attempts should stop at energy balance owing to insufficient data on the association between changes in behaviors and changes in BMI z -scores. These results are only as accurate as the method used for translating short-term study results into multiple-year effects and the reliability of cross-sectional data in determining how changes in PA and diet impact BMI z -scores. Although strong survey surveillance systems allow robust estimation of baseline trends, there are little effectiveness data for the SSB and advertising policies, particularly in children, and existing data often come from observational studies.

To broaden the evidence base, international studies were included in this analysis, which may limit applicability in the U. In addition, the estimated policy impact is sensitive to the model assumptions. In the absence of data on substitution effects in food consumption resulting from an advertising ban, it was assumed that a lower-calorie meal would be available and consumed instead.

Another limitation is the inability to assess interaction effects among the three policies or with existing policies, such as state-level physical education policies. In this analysis, policies were assessed independently, but to reverse the childhood obesity epidemic, a comprehensive set of national policies would need to be implemented.

The three federal policies in this analysis could each reduce childhood obesity prevalence by This analysis used a microsimulation model originally developed to estimate the health impact of physical activity interventions recommended by the Community Preventive Services Task Force. The model is designed to examine how the policies affect obesity-related behaviors physical activity and diet , and in turn, how changes in these behaviors affect BMI and obesity prevalence.

The model was developed with TreeAge to track the state age, diet, physical activity, body mass index BMI , and health status of simulated individuals over time.

TreeAge Pro R2. Within the model, each agent is uniquely defined by a set of heterogeneous characteristics. All simulated agents are independent, in that the actions of one individual do not impact those of another. The distribution of demographic characteristic across individuals is determined by data abstracted from the literature and the population being modeled. Demographic characteristics sex, race and ethnicity were assigned proportional to those of the U.

Appendix Figure 1 summarizes the flow of the microsimulation. There are two discreet processes within the model: Initiation and Progression. The following section describes how agents are initialized and then aged. At initiation, or baseline, demographics and health behaviors are set in a sequential manner as illustrated in Appendix Figure 1. Appendix Table 1 lists the agent-level parameters tracked within the model, their conditioning factors, assumed distribution across the population, and the timing of their initialization in the model.

For each agent, these are determined by a random draw from a multinomial distribution set proportional to the population being modeled. Note: Other was omitted from the results because it is impossible to draw policy conclusions when race is unknown. Time varying agent-level behavioral factors are initialized by random draws from joint probability distributions.

The time-varying factors that are initialized and tracked are: body mass index BMI , physical activity level expressed in metabolic equivalents of task or METs , and diet total kilocalories and grams of protein, carbohydrates, dietary fiber, fat, and sugar.

This begins with initialization of BMI whose conditioning factors are sex, ethnicity, and initial age. The other behavioral factors physical activity and dietary factors , which are the target of the modeled policy interventions, are further conditioned upon initial BMI. Youth obesity is a relative concept. Considerable changes in BMI are anticipated as a normal part of growth and development. A BMI of 20 is considered high for a 6-year-old, but normal for a year-old.

The Centers for Disease Control and Prevention define childhood obesity as a BMI at or above the 95th percentile for age and sex, and overweight as a BMI that is at or above the 85th percentile and below the 95th percentile for age and sex. The microsimulation reflects this growth pattern by modeling the change in BMI over time in terms of percentiles of the standardized BMI distribution conditioned upon agent age, sex, ethnicity, physical activity, and diet.

Similarly, the time-variant behaviors of physical activity and diet are determined from a random draw from a distribution conditioned on age, sex, ethnicity, and BMI. Each cycle, BMI, or more precisely BMI percentile, is adjusted according to age-, sex-, and ethnicity-based trends, as well as changes in diet and physical activity attributable to the policy intervention.

For instance, an individual initialized into the model at the 60th percentile of the BMI distribution will stay at that percentile unless there is a significant change in their behavior. This chart pertains to the life of a simulated non-Hispanic white male from ages and illustrates how baseline BMI and the impact of interventions are modeled. The individual is introduced into the model at age 2 with a BMI of At age 3, his BMI decreases to This process is repeated until age 18 and, assuming no significant behavioral changes, results in the BMI path shown by the black, triangled line.

The dotted line reflects the impact of a modeled policy intervention. In this instance, the intervention was an afterschool physical activity program initiated at age 9 and continuing until age Thus, this individual has 10 years of exposure to the intervention, and the intervention resulted in a sustained, elevated level of physical activity. At age 11, there is an additional decrease in BMI and the pattern continues until age 14 where a BMI path consistent with the increased level of physical activity is reached.

A more detailed example is provided in Appendix Table 2. There, a six-year-old experiences a dietary intervention that entails fewer calories, increased protein, and reduced sugar and fat. As the data in the table illustrates, the impact of the dietary change occurs across several dimensions, but there is a net decrease in BMI z-score.

The results of this analysis were incorporated into the microsimulation. This analysis used a log specification in order to estimate BMI z-score sensitivity to a percentage change in caloric consumption and physical activity, respectively. In addition, it estimated BMI z-score sensitivity to discreet changes to the following macronutrients whose daily consumption is measured in grams: protein, carbohydrates, fiber, sugar, and fat. The following general specification was used:. All of these are included in Appendix Table 3.

Two of the covariates, METs and kilocalories, were heavily skewed and of several orders of magnitude larger than the other covariates. To protect against outlying values and put all covariates in the equation on a similar scale, both of these were log transformed.

The log transformations, applied to both physical activity measured in metabolic equivalents or METs and kilocalories, allows their corresponding coefficient estimates to be interpreted as the change in BMI z-score that corresponds to a given percentage change in either physical activity or total energy consumption.

Appendix Table 4 contains estimates that are incorporated into the microsimulation model. Separate intercepts were included for each survey in order to filter mean level shifts due to variation attributable to question rewording or measurement change. For instance, in , a two-day food frequency questionnaire replaced a one-day questionnaire. Similarly, questions regarding types of physical activity varied slightly from year to year.

Similarly, an indicator, or dummy, variable for ages less than 12 was incorporated to adjust for known differences in how NHANES collects data regarding physical activity and diet. Prior to age 12, physical activity and diet were measured through parental interview and certain questions, such as the detailed daily activity questionnaire, were not used. No significant interactions with either physical activity or energy consumption kilocalories were found. Once the microsimulation model had been adapted for this study, a comprehensive list of obesity prevention policies was developed and then narrowed in a two-stage process to the final three policies.

First, policy recommendations to improve nutrition, increase physical activity, or promote breastfeeding were collected. These policies were found by researching recommendations issued by health organizations e.

The policies were categorized by approach, as seen in the childhood obesity literature e. Next, criteria were used to narrow the list to 7 policies to consider further. For each of the 26 policies, the literature was briefly reviewed to better understand the policy, identify possible federal policy mechanisms, and provide a rating for each criterion to be used in the selection process.

The criteria used to select the 7 policies were: extent of the evidence base, effectiveness, reach into the general population , reach into high risk populations , feasibility political , and feasibility of implementation. Tables were created that included the information gathered from the brief literature review, plus a rating for each criterion. The selections were then tallied and discussed. The 7 policies were determined by consensus from those receiving either the most or next-to-most number of votes:.

Provide funding for communities to build or make improvements to public parks, playgrounds, and other safe spaces for youth to be physically active. Strengthen and expand federally-funded afterschool programs to promote physical activity. Enact a 1-cent-per-ounce excise tax on sugar-sweetened beverages, and earmark revenue for obesity prevention strategies in high risk communities.

Assessment of a school-based intervention in eating habits and physical activity in school children: the AVall study. J Epidemiol Community Health. A controlled, class-based multicomponent intervention to promote healthy lifestyle and to reduce the burden of childhood obesity. A participatory and capacity-building approach to healthy eating and physical activity- SCIP-school: a 2-year controlled trial. Using routinely collected growth data to assess a school-based obesity prevention strategy.

Int J Obes Lond ; 37 — A school-based program of physical activity may prevent obesity. Prevention of obesity in elementary and nursery school children. Public Health. Effect of school based physical activity programme KISS on fitness and adiposity in primary schoolchildren: cluster randomised controlled trial.

Effect of a two-year obesity prevention intervention on percentile changes in body mass index and academic performance in low-income elementary school children. Am J Public Health. Child and Adolescent Trial for Cardiovascular Health. The effects of a health education intervention program among Cretan adolescents. A coordinated school health approach to obesity prevention among Appalachian youth: the Winning with Wellness Pilot Project. Fam Community Health. Int J Obes Lond ; 33 — Overweight prevention implemented by primary school teachers: a randomised controlled trial.

Behavioural and weight status outcomes from an exploratory trial of the Healthy Lifestyles Programme HeLP : a novel school-based obesity prevention programme. BMJ Open. Effect of an environmental school-based obesity prevention program on changes in body fat and body weight: a randomized trial. Successful overweight prevention in adolescents by increasing physical activity: a 4-year randomized controlled intervention. A policy-based school intervention to prevent overweight and obesity.

Evaluating the effectiveness of the Kids Living Fit program: a comparative study. The effects of a family fitness program on the physical activity and nutrition behaviors of third-grade children.

Res Q Exerc Sport. Prevention of the epidemic increase in child risk of overweight in low-income schools: the El Paso coordinated approach to child health. Appendix A4 School-based interventions with home and community components Eur J Public Health. Efficacy of a school-based childhood obesity intervention program in a rural southern community: TEAM Mississippi Project. Obesity Silver Spring ; 19 — Effectiveness of a primary school-based intervention to reduce overweight.

Effects of a 2-year healthy eating and physical activity intervention for 3—6-year-olds in communities of high and low socio-economic status: the POP Prevention of Overweight among Pre-school and school children project.

Impact of a nurse-directed, coordinated school health program to enhance physical activity behaviors and reduce body mass index among minority children: a parallel-group, randomized control trial. Int J Nurs Stud. Effectiveness of JUMP-in, a Dutch primary school-based community intervention aimed at the promotion of physical activity.

Br J Sports Med. Reducing unhealthy weight gain in children through community capacity-building: results of a quasi-experimental intervention program, Be Active Eat Well. Fam Pract. The impact of Action Schools! BC on the health of Aboriginal children and youth living in rural and remote communities in British Columbia. Int J Circumpolar Health. Appendix A5 School-based interventions with a community component A simple dietary intervention in the school setting decreased incidence of overweight in children.

Promoting physical activity in middle school girls: Trial of Activity for Adolescent Girls. Results of a multi-level intervention to prevent and control childhood obesity among Latino children: the Aventuras Para Ninos Study.

Ann Behav Med. The Kahnawake Schools Diabetes Prevention Project: intervention, evaluation, and baseline results of a diabetes primary prevention program with a native community in Canada. After-school program to reduce obesity in minority children: a pilot study.

J Child Health Care. Evaluation of the Living 4 Life project: a youth-led, school-based obesity prevention study. Appendix A6 School-based interventions with a consumer health informatics component Spiegel SA, Foulk D. Reducing overweight through a multi-disciplinary school-based intervention.

Evaluation of the web-based computer-tailored FATaintPHAT intervention to promote energy balance among adolescents: results from a school cluster randomized trial.

Impact of a school-based physical activity intervention on fitness and bone in adolescent females. Effectiveness of YouRAction, an intervention to promote adolescent physical activity using personal and environmental feedback: a cluster RCT. PLoS One. An internet obesity prevention program for adolescents. Appendix A7 Home only-based interventions Increasing fruit and vegetable intake and decreasing fat and sugar intake in families at risk for childhood obesity.

Obes Res. Girls on a high-calcium diet gain weight at the same rate as girls on a normal diet: a pilot study. J Am Diet Assoc. Household obesity prevention: Take Action — a group-randomized trial. Family-based hip-hop to health: outcome results. Obesity Silver Spring ; 21 — Appendix A8 Community-based or environmental-level interventions High-intensity training increases spontaneous physical activity in children: a randomized controlled study.

Dutch obesity intervention in teenagers: effectiveness of a school-based program on body composition and behavior. Environmental interventions for eating and physical activity: a randomized controlled trial in middle schools. Healthy Living Cambridge Kids: a community-based participatory effort to promote healthy weight and fitness.

A randomized controlled trial of culturally tailored dance and reducing screen time to prevent weight gain in low-income African American girls: Stanford GEMS. A statewide strategy to battle child obesity in Delaware. Health Aff Millwood ; 29 — Improving weight status in childhood: results from the eat well be active community programs. Int J Public Health. Footnotes Conflict of interest statement No conflict of interest was declared. RFW is the project manager. Yang Wu is the project coordinator.

All authors and some other research team members were responsible for acquisition of data. All authors participated in the analysis and interpretation of data. All authors were responsible for the critical revision of the manuscript for important intellectual content.

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