Resource Type: Peer-Reviewed Publications

Systematic Review and Meta-Analysis of the Impact of Restaurant Menu Calorie Labeling

Menu calorie labeling identified as a relatively low-cost education strategy that may lead consumers to purchase slightly fewer calories.

Long MW, Tobias DK, Cradock AL, Batchelder H, Gortmaker SL. Systematic Review and Meta-analysis of the Impact of Restaurant Menu Calorie Labeling. Am J Public Health. 2015 May;105(5):e11-24. doi: 10.2105/AJPH.2015.302570. Epub 2015 Mar 19.

A number of studies have examined the relationship between menu calorie labeling and the calories consumers ordered or purchased in a variety of settings with differing results. To get a combined effect estimate for modeling the cost effectiveness of the federal menu labeling policy, CHOICES researcher Dr. Michael Long conducted a systematic review and meta-analysis. While the meta-analysis evidence does not support a significant impact on calories ordered, menu calorie labeling is a relatively low-cost education strategy that may lead consumers to purchase slightly fewer calories.

← Back to Resources

 

The Cost of a Primary Case-Based Childhood Obesity Prevention Intervention

Wright DR, Taveras EM, Gillman MW, Horan CM, Hohman KH, Gortmaker SL, Prosser LA. The cost of a primary care-based childhood obesity prevention intervention. BMC Health Serv Res. 2014 Jan 29;14:44. doi: 10.1186/1472-6963-14-44.

Abstract

Background

United States pediatric guidelines recommend that childhood obesity counseling be conducted in the primary care setting. Primary care-based interventions can be effective in improving health behaviors, but also costly. The purpose of this study was to evaluate the cost of a primary care-based obesity prevention intervention targeting children between the ages of two and six years who are at elevated risk for obesity, measured against usual care.

Methods

High Five for Kids was a cluster-randomized controlled clinical trial that aimed to modify children’s nutrition and TV viewing habits through a motivational interviewing intervention. We assessed visit-related costs from a societal perspective, including provider-incurred direct medical costs, provider-incurred equipment costs, parent time costs and parent out-of-pocket costs, in 2011 dollars for the intervention (n = 253) and usual care (n =192) groups. We conducted a net cost analysis using both societal and health plan costing perspectives and conducted one-way sensitivity and uncertainty analyses on results.

Results

The total costs for the intervention group and usual care groups in the first year of the intervention were $65,643 (95% CI [$64,522, $66,842]) and $12,192 (95% CI [$11,393, $13,174]). The mean costs for the intervention and usual care groups were $259 (95% CI [$255, $264]) and $63 (95% CI [$59, $69]) per child, respectively, for a incremental difference of $196 (95% CI [$191, $202]) per child. Children in the intervention group attended a mean of 2.4 of a possible 4 in-person visits and received 0.45 of a possible 2 counseling phone calls. Provider-incurred costs were the primary driver of cost estimates in sensitivity analyses.

Conclusions

High Five for Kids was a resource-intensive intervention. Further studies are needed to assess the cost-effectiveness of the intervention relative to other pediatric obesity interventions.

Trial registration: ClinicalTrials.gov NCT00377767.

← Back to Resources

Reaching the Healthy People Goals for Reducing Childhood Obesity: Closing the Energy Gap

Wang YC, Orleans CT, Gortmaker SL. Reaching the healthy people goals for reducing childhood obesity: Closing the energy gap. Am J Prev Med. 2012 May;42(5):437-44. doi: 10.1016/j.amepre.2012.01.018.

Abstract

Background

The federal government has set measurable goals for reducing childhood obesity to 5% by 2010 (Healthy People 2010), and 10% lower than 2005-2008 levels by 2020 (Healthy People 2020). However, population-level estimates of the changes in daily energy balance needed to reach these goals are lacking.

Purpose

To estimate needed per capita reductions in youths’ daily “energy gap” (calories consumed over calories expended) to achieve Healthy People goals by 2020.

Methods

Analyses were conducted in 2010 to fit multivariate models using National Health and Nutrition Examination Surveys 1971-2008 (N=46,164) to extrapolate past trends in obesity prevalence, weight, and BMI among youth aged 2-19 years. Differences in average daily energy requirements between the extrapolated 2020 levels and Healthy People scenarios were estimated.

Results

During 1971-2008, mean BMI and weight among U.S. youth increased by 0.55 kg/m(2) and by 1.54 kg per decade, respectively. Extrapolating from these trends to 2020, the average weight among youth in 2020 would increase by ∼1.8 kg from 2007-2008 levels. Averting this increase will require an average reduction of 41 kcal/day in youth’s daily energy gap. An additional reduction of 120 kcal/day and 23 kcal/day would be needed to reach Healthy People 2010 and Healthy People 2020 goals, respectively. Larger reductions are needed among adolescents and racial/ethnic minority youth.

Conclusions

Aggressive efforts are needed to reverse the positive energy imbalance underlying the childhood obesity epidemic. The energy-gap metric provides a useful tool for goal setting, intervention planning, and charting progress.

← Back to Resources

Changing the Future of Obesity: Science, Policy, and Action

Gortmaker SL, Swinburn BA, Levy D, Carter R, Mabry PL, Finegood DT, Huang T, Marsh T, Moodie ML. Changing the future of obesity: Science, policy, and action. Lancet. 2011 Aug 27;378(9793):838-47. doi: 10.1016/S0140-6736(11)60815-5.

Abstract

The global obesity epidemic has been escalating for four decades, yet sustained prevention efforts have barely begun. An emerging science that uses quantitative models has provided key insights into the dynamics of this epidemic, and enabled researchers to combine evidence and to calculate the effect of behaviours, interventions, and policies at several levels–from individual to population. Forecasts suggest that high rates of obesity will affect future population health and economics. Energy gap models have quantified the association of changes in energy intake and expenditure with weight change, and have documented the effect of higher intake on obesity prevalence. Empirical evidence that shows interventions are effective is limited but expanding. We identify several cost-effective policies that governments should prioritise for implementation. Systems science provides a framework for organising the complexity of forces driving the obesity epidemic and has important implications for policy makers. Many parties (such as governments, international organisations, the private sector, and civil society) need to contribute complementary actions in a coordinated approach. Priority actions include policies to improve the food and built environments, cross-cutting actions (such as leadership, healthy public policies, and monitoring), and much greater funding for prevention programmes. Increased investment in population obesity monitoring would improve the accuracy of forecasts and evaluations. The integration of actions within existing systems into both health and non-health sectors (trade, agriculture, transport, urban planning, and development) can greatly increase the influence and sustainability of policies. We call for a sustained worldwide effort to monitor, prevent, and control obesity.

← Back to Resources

Quantification of the Effect of Energy Imbalance on Body Weight

Hall KD, Sacks G, Chandramohan D, Chow CC, Wang YC, Gortmaker SL, Swinburn BA. Quantification of the effect of energy imbalance on body weight. Lancet. 2011 Aug 27;378(9793):826-37. doi: 10.1016/S0140-6736(11)60812-X.

Abstract

Obesity interventions can result in weight loss, but accurate prediction of the bodyweight time course requires properly accounting for dynamic energy imbalances. In this report, we describe a mathematical modelling approach to adult human metabolism that simulates energy expenditure adaptations during weight loss. We also present a web-based simulator for prediction of weight change dynamics. We show that the bodyweight response to a change of energy intake is slow, with half times of about 1 year. Furthermore, adults with greater adiposity have a larger expected weight loss for the same change of energy intake, and to reach their steady-state weight will take longer than it would for those with less initial body fat. Using a population-averaged model, we calculated the energy-balance dynamics corresponding to the development of the US adult obesity epidemic. A small persistent average daily energy imbalance gap between intake and expenditure of about 30 kJ per day underlies the observed average weight gain. However, energy intake must have risen to keep pace with increased expenditure associated with increased weight. The average increase of energy intake needed to sustain the increased weight (the maintenance energy gap) has amounted to about 0·9 MJ per day and quantifies the public health challenge to reverse the obesity epidemic.

← Back to Resources

Health and Economic Burden of the Projected Obesity Trends in the USA and the UK

Wang YC, McPherson K, Marsh T, Gortmaker SL, Brown M. Health and economic burden of the projected obesity trends in the USA and the UK. Lancet. 2011 Aug 27;378(9793):815-25. doi: 10.1016/S0140-6736(11)60814-3.

Erratum in:
  • Lancet. 2011 Nov 19;378(9805):1778

Abstract

Rising prevalence of obesity is a worldwide health concern because excess weight gain within populations forecasts an increased burden from several diseases, most notably cardiovascular diseases, diabetes, and cancers. In this report, we used a simulation model to project the probable health and economic consequences in the next two decades from a continued rise in obesity in two ageing populations–the USA and the UK. These trends project 65 million more obese adults in the USA and 11 million more obese adults in the UK by 2030, consequently accruing an additional 6-8·5 million cases of diabetes, 5·7-7·3 million cases of heart disease and stroke, 492,000-669,000 additional cases of cancer, and 26-55 million quality-adjusted life years forgone for USA and UK combined. The combined medical costs associated with treatment of these preventable diseases are estimated to increase by $48-66 billion/year in the USA and by £1·9-2 billion/year in the UK by 2030. Hence, effective policies to promote healthier weight also have economic benefits.

← Back to Resources

The Global Obesity Pandemic: Shaped by Global Drivers and Local Environments

Swinburn BA, Sacks G, Hall KD, McPherson K, Finegood DT, Moodie ML, Gortmaker SL. The global obesity pandemic: shaped by global drivers and local environments. Lancet. 2011 Aug 27;378(9793):804-14. doi: 10.1016/S0140-6736(11)60813-1.

Abstract

The simultaneous increases in obesity in almost all countries seem to be driven mainly by changes in the global food system, which is producing more processed, affordable, and effectively marketed food than ever before. This passive overconsumption of energy leading to obesity is a predictable outcome of market economies predicated on consumption-based growth. The global food system drivers interact with local environmental factors to create a wide variation in obesity prevalence between populations. Within populations, the interactions between environmental and individual factors, including genetic makeup, explain variability in body size between individuals. However, even with this individual variation, the epidemic has predictable patterns in subpopulations. In low-income countries, obesity mostly affects middle-aged adults (especially women) from wealthy, urban environments; whereas in high-income countries it affects both sexes and all ages, but is disproportionately greater in disadvantaged groups. Unlike other major causes of preventable death and disability, such as tobacco use, injuries, and infectious diseases, there are no exemplar populations in which the obesity epidemic has been reversed by public health measures. This absence increases the urgency for evidence-creating policy action, with a priority on reduction of the supply-side drivers.

← Back to Resources

Simulation Models of Obesity: A Review of the Literature and Implications for Research and Policy

Levy DT, Mabry PL, Wang YC, Gortmaker S, Huang TT, Marsh T, Moodie M, Swinburn B. Simulation models of obesity: A review of the literature and implications for research and policy. Obes Rev. 2011 May;12(5):378-94. doi: 10.1111/j.1467-789X.2010.00804.x. Epub 2010 Oct 26.

Abstract

Simulation models (SMs) combine information from a variety of sources to provide a useful tool for examining how the effects of obesity unfold over time and impact population health. SMs can aid in the understanding of the complex interaction of the drivers of diet and activity and their relation to health outcomes. As emphasized in a recently released report of the Institute or Medicine, SMs can be especially useful for considering the potential impact of an array of policies that will be required to tackle the obesity problem. The purpose of this paper is to present an overview of existing SMs for obesity. First, a background section introduces the different types of models, explains how models are constructed, shows the utility of SMs and discusses their strengths and weaknesses. Using these typologies, we then briefly review extant obesity SMs. We categorize these models according to their focus: health and economic outcomes, trends in obesity as a function of past trends, physiologically based behavioural models, environmental contributors to obesity and policy interventions. Finally, we suggest directions for future research.

← Back to Resources

Estimating the Energy Gap Among U.S. Children: A Counterfactual Approach

Wang YC, Gortmaker SL, Sobol AM, Kuntz KM. Estimating the energy gap among U.S. children: A counterfactual approach. Pediatrics. 2006 Dec;118(6):e1721-33.

Abstract

Objective

Our goal was to quantify the magnitude of energy imbalance responsible for the increase in body weight among US children during the periods 1988-1994 and 1999-2002.

Methods

We adopted a counterfactual approach to estimate weight gains in excess of normal growth and the implicit “energy gap”–the daily imbalance between energy intake and expenditure. On the basis of Centers for Disease Control and Prevention growth charts, we constructed weight, height, and BMI percentile distributions for cohorts 2 to 4 and 5 to 7 years of age in the 1988-1994 National Health and Nutrition Examination Survey (N = 5000). Under the counterfactual “normal-growth-only” scenario, we assumed that these percentile distributions remained the same as the cohort aged 10 years. Under this assumption, we projected the weight and height distributions for this cohort at 12 to 14 and 15 to 17 years of age on the basis of their baseline weight-for-age and stature-for-age percentiles. We compared these distributions with those for corresponding age groups in the 1999-2002 National Health and Nutrition Examination Survey (N = 3091) approximately 10 years after the 1988-1994 National Health and Nutrition Examination Survey. We calculated differences between the counterfactual and observed weight distributions and translated this difference into the estimated average energy gap, adjusting for increased total energy expenditure attributable to weight gain. In addition, we estimated the average excess weight accumulated among overweight adolescents in the 1999-2002 National Health and Nutrition Examination Survey, validating our counterfactual assumptions by analyzing longitudinal data from the National Longitudinal Survey of Youth and Bogalusa Heart Study.

Results

Compared with the counterfactual scenario, boys and girls who were aged 2 to 7 in the 1988-1994 National Health and Nutrition Examination Survey gained, on average, an excess of 0.43 kg/year over the 10-year period. Assuming that 3500 kcal leads to an average of 1-lb weight gain as fat, our results suggest that a reduction in the energy gap of 110-165 kcal/day could have prevented this increase. Among overweight adolescents aged 12 to 17 in 1999-2002, results indicate an average energy imbalance ranging from 678 to 1017 kcal/day because of an excess of 26.5 kg accumulated over 10 years.

Conclusions

Quantifying the energy imbalance responsible for recent changes in weight distribution among children can provide salient targets for population intervention. Consistent behavioral changes averaging 110 to 165 kcal/day may be sufficient to counterbalance the energy gap. Changes in excess dietary intake (eg, eliminating one sugar-sweetened beverage at 150 kcal per can) may be easier to attain than increases in physical activity levels (eg, a 30-kg boy replacing sitting for 1.9 hours with 1.9 hours walking for an extra 150 kcal). Youth at higher levels of weight gain will likely need changes in multiple behaviors and environments to close the energy gap.

← Back to Resources