BACKGROUND: State-level estimates from the Centers for Disease Control and Prevention (CDC) underestimate the obesity epidemic because they use self-reported height and weight. We describe a novel bias-correction method and produce corrected state-level estimates of obesity and severe obesity.
METHODS: Using non-parametric statistical matching, we adjusted self-reported data from the Behavioral Risk Factor Surveillance System (BRFSS) 2013 (n = 386,795) using measured data from the National Health and Nutrition Examination Survey (NHANES) (n = 16,924). We validated our national estimates against NHANES and estimated bias-corrected state-specific prevalence of obesity (BMI≥30) and severe obesity (BMI≥35). We compared these results with previous adjustment methods.
RESULTS: Compared to NHANES, self-reported BRFSS data underestimated national prevalence of obesity by 16% (28.67% vs 34.01%), and severe obesity by 23% (11.03% vs 14.26%). Our method was not significantly different from NHANES for obesity or severe obesity, while previous methods underestimated both. Only four states had a corrected obesity prevalence below 30%, with four exceeding 40%-in contrast, most states were below 30% in CDC maps.
CONCLUSIONS: Twelve million adults with obesity (including 6.7 million with severe obesity) were misclassified by CDC state-level estimates. Previous bias-correction methods also resulted in underestimates. Accurate state-level estimates are necessary to plan for resources to address the obesity epidemic.
BACKGROUND/OBJECTIVES: State-specific obesity prevalence data are critical to public health efforts to address the childhood obesity epidemic. However, few states administer objectively measured body mass index (BMI) surveillance programs. This study reports state-specific childhood obesity prevalence by age and sex correcting for parent-reported child height and weight bias.
SUBJECTS/METHODS: As part of the Childhood Obesity Intervention Cost Effectiveness Study (CHOICES), we developed childhood obesity prevalence estimates for states for the period 2005-2010 using data from the 2010 US Census and American Community Survey (ACS), 2003-2004 and 2007-2008 National Survey of Children's Health (NSCH) (n=133 213), and 2005-2010 National Health and Nutrition Examination Surveys (NHANES) (n=9377; ages 2-17). Measured height and weight data from NHANES were used to correct parent-report bias in NSCH using a non-parametric statistical matching algorithm. Model estimates were validated against surveillance data from five states (AR, FL, MA, PA and TN) that conduct censuses of children across a range of grades.
RESULTS: Parent-reported height and weight resulted in the largest overestimation of childhood obesity in males ages 2-5 years (NSCH: 42.36% vs NHANES: 11.44%). The CHOICES model estimates for this group (12.81%) and for all age and sex categories were not statistically different from NHANES. Our modeled obesity prevalence aligned closely with measured data from five validation states, with a 0.64 percentage point mean difference (range: 0.23-1.39) and a high correlation coefficient (r=0.96, P=0.009). Estimated state-specific childhood obesity prevalence ranged from 11.0 to 20.4%.
CONCLUSION: Uncorrected estimates of childhood obesity prevalence from NSCH vary widely from measured national data, from a 278% overestimate among males aged 2-5 years to a 44% underestimate among females aged 14-17 years. This study demonstrates the validity of the CHOICES matching methods to correct the bias of parent-reported BMI data and highlights the need for public release of more recent data from the 2011 to 2012 NSCH.
PURPOSE: Best-worst scaling (BWS) is a survey method for assessing individuals' priorities. It identifies the extremes-best and worst items, most and least important factors, biggest and smallest influences-among sets. In this article, we demonstrate an application of BWS in a primary care setting to illustrate its use in identifying patient priorities for services.
METHODS: We conducted a BWS survey in 2014 in Boston, Massachusetts, to assess the relative importance of 10 previously identified attributes of Papanicolaou (Pap) testing services among women experiencing homelessness. Women were asked to evaluate 11 sets of 5 attributes of Pap services, and identify which attribute among each set would have the biggest and smallest influence on promoting uptake. We show how frequency analysis can be used to analyze results.
RESULTS: In all, 165 women participated, a response rate of 72%. We identified the most and least salient influences on encouraging Pap screening based on their frequency of report among our sample, with possible standardized scores ranging from+1.0 (biggest influence) to -1.0 (smallest influence). Most important was the availability of support for issues beyond health (+0.39), while least important was the availability of accommodations for personal hygiene (-0.27).
CONCLUSIONS: BWS quantifies patient priorities in a manner that is transparent and accessible. It is easily comprehendible by patients and relatively easy to administer. Our application illustrates its use in a vulnerable population, showing that factors beyond those typically provided in health care settings are highly important to women in seeking Pap screening. This approach can be applied to other health care services where prioritization is helpful to guide decisions.
INTRODUCTION: Food and beverage TV advertising contributes to childhood obesity. The current tax treatment of advertising as an ordinary business expense in the U.S. subsidizes marketing of nutritionally poor foods and beverages to children. This study models the effect of a national intervention that eliminates the tax subsidy of advertising nutritionally poor foods and beverages on TV to children aged 2-19 years.
METHODS: We adapted and modified the Assessing Cost Effectiveness framework and methods to create the Childhood Obesity Intervention Cost Effectiveness Study model to simulate the impact of the intervention over the 2015-2025 period for the U.S. population, including short-term effects on BMI and 10-year healthcare expenditures. We simulated uncertainty intervals (UIs) using probabilistic sensitivity analysis and discounted outcomes at 3% annually. Data were analyzed in 2014.
RESULTS: We estimated the intervention would reduce an aggregate 2.13 million (95% UI=0.83 million, 3.52 million) BMI units in the population and would cost $1.16 per BMI unit reduced (95% UI=$0.51, $2.63). From 2015 to 2025, the intervention would result in $352 million (95% UI=$138 million, $581 million) in healthcare cost savings and gain 4,538 (95% UI=1,752, 7,489) quality-adjusted life-years.
CONCLUSIONS: Eliminating the tax subsidy of TV advertising costs for nutritionally poor foods and beverages advertised to children and adolescents would likely be a cost-saving strategy to reduce childhood obesity and related healthcare expenditures.
INTRODUCTION: Reducing sugar-sweetened beverage consumption through taxation is a promising public health response to the obesity epidemic in the U.S. This study quantifies the expected health and economic benefits of a national sugar-sweetened beverage excise tax of $0.01/ounce over 10 years.
METHODS: A cohort model was used to simulate the impact of the tax on BMI. Assuming ongoing implementation and effect maintenance, quality-adjusted life-years gained and disability-adjusted life-years and healthcare costs averted were estimated over the 2015-2025 period for the 2015 U.S.
POPULATION: Costs and health gains were discounted at 3% annually. Data were analyzed in 2014.
RESULTS: Implementing the tax nationally would cost $51 million in the first year. The tax would reduce sugar-sweetened beverage consumption by 20% and mean BMI by 0.16 (95% uncertainty interval [UI]=0.06, 0.37) units among youth and 0.08 (95% UI=0.03, 0.20) units among adults in the second year for a cost of $3.16 (95% UI=$1.24, $8.14) per BMI unit reduced. From 2015 to 2025, the policy would avert 101,000 disability-adjusted life-years (95% UI=34,800, 249,000); gain 871,000 quality-adjusted life-years (95% UI=342,000, 2,030,000); and result in $23.6 billion (95% UI=$9.33 billion, $54.9 billion) in healthcare cost savings. The tax would generate $12.5 billion in annual revenue (95% UI=$8.92, billion, $14.1 billion).
CONCLUSIONS: The proposed tax could substantially reduce BMI and healthcare expenditures and increase healthy life expectancy. Concerns regarding the potentially regressive tax may be addressed by reduced obesity disparities and progressive earmarking of tax revenue for health promotion.
INTRODUCTION: Many American children do not meet recommendations for moderate to vigorous physical activity (MVPA). Although school-based physical education (PE) provides children with opportunities for MVPA, less than half of PE minutes are typically active. The purpose of this study is to estimate the cost effectiveness of a state "active PE" policy implemented nationally requiring that at least 50% of elementary school PE time is spent in MVPA.
METHODS: A cohort model was used to simulate the impact of an active PE policy on physical activity, BMI, and healthcare costs over 10 years for a simulated cohort of the 2015 U.S. population aged 6-11 years. Data were analyzed in 2014.
RESULTS: An elementary school active PE policy would increase MVPA per 30-minute PE class by 1.87 minutes (95% uncertainty interval [UI]=1.23, 2.51) and cost $70.7 million (95% UI=$51.1, $95.9 million) in the first year to implement nationally. Physical activity gains would cost $0.34 per MET-hour/day (95% UI=$0.15, $2.15), and BMI could be reduced after 2 years at a cost of $401 per BMI unit (95% UI=$148, $3,100). From 2015 to 2025, the policy would cost $235 million (95% UI=$170 million, $319 million) and reduce healthcare costs by $60.5 million (95% UI=$7.93 million, $153 million).
CONCLUSIONS: Implementing an active PE policy at the elementary school level could have a small impact on physical activity levels in the population and potentially lead to reductions in BMI and obesity-related healthcare expenditures over 10 years.
INTRODUCTION: The childhood obesity epidemic continues in the U.S., and fiscal crises are leading policymakers to ask not only whether an intervention works but also whether it offers value for money. However, cost-effectiveness analyses have been limited. This paper discusses methods and outcomes of four childhood obesity interventions: (1) sugar-sweetened beverage excise tax (SSB); (2) eliminating tax subsidy of TV advertising to children (TV AD); (3) early care and education policy change (ECE); and (4) active physical education (Active PE).
METHODS: Cost-effectiveness models of nationwide implementation of interventions were estimated for a simulated cohort representative of the 2015 U.S. population over 10 years (2015-2025). A societal perspective was used; future outcomes were discounted at 3%. Data were analyzed in 2014. Effectiveness, implementation, and equity issues were reviewed.
RESULTS: Population reach varied widely, and cost per BMI change ranged from $1.16 (TV AD) to $401 (Active PE). At 10 years, assuming maintenance of the intervention effect, three interventions would save net costs, with SSB and TV AD saving $55 and $38 for every dollar spent. The SSB intervention would avert disability-adjusted life years, and both SSB and TV AD would increase quality-adjusted life years. Both SSB ($12.5 billion) and TV AD ($80 million) would produce yearly tax revenue.
CONCLUSIONS: The cost effectiveness of these preventive interventions is greater than that seen for published clinical interventions to treat obesity. Cost-effectiveness evaluations of childhood obesity interventions can provide decision makers with information demonstrating best value for the money.
INTRODUCTION: Child care facilities influence diet and physical activity, making them ideal obesity prevention settings. The purpose of this study is to quantify the health and economic impacts of a multi-component regulatory obesity policy intervention in licensed U.S. child care facilities.
METHODS: Two-year costs and BMI changes resulting from changes in beverage, physical activity, and screen time regulations affecting a cohort of up to 6.5 million preschool-aged children attending child care facilities were estimated in 2014 using published data. A Markov cohort model simulated the intervention's impact on changes in the U.S. population from 2015 to 2025, including short-term BMI effects and 10-year healthcare expenditures. Future outcomes were discounted at 3% annually. Probabilistic sensitivity analyses simulated 95% uncertainty intervals (UIs) around outcomes.
RESULTS: Regulatory changes would lead children to watch less TV, get more minutes of moderate and vigorous physical activity, and consume fewer sugar-sweetened beverages. Within the 6.5 million eligible population, national implementation could reach 3.69 million children, cost $4.82 million in the first year, and result in 0.0186 fewer BMI units (95% UI=0.00592 kg/m(2), 0.0434 kg/m(2)) per eligible child at a cost of $57.80 per BMI unit avoided. Over 10 years, these effects would result in net healthcare cost savings of $51.6 (95% UI=$14.2, $134) million. The intervention is 94.7% likely to be cost saving by 2025.
CONCLUSIONS: Changing child care regulations could have a small but meaningful impact on short-term BMI at low cost. If effects are maintained for 10 years, obesity-related healthcare cost savings are likely.
Efforts to expand Medicaid while controlling spending must be informed by a deeper understanding of the extent to which the high medical costs associated with severe obesity (having a body mass index of [Formula: see text] or higher) determine spending at the state level. Our analysis of population-representative data indicates that in 2013, severe obesity cost the nation approximately $69 billion, which accounted for 60 percent of total obesity-related costs. Approximately 11 percent of the cost of severe obesity was paid for by Medicaid, 30 percent by Medicare and other federal health programs, 27 percent by private health plans, and 30 percent out of pocket. Overall, severe obesity cost state Medicaid programs almost $8 billion a year, ranging from $5 million in Wyoming to $1.3 billion in California. These costs are likely to increase following Medicaid expansion and enhanced coverage of weight loss therapies in the form of nutrition consultation, drug therapy, and bariatric surgery. Ensuring and expanding Medicaid-eligible populations' access to cost-effective treatment for severe obesity should be part of each state's strategy to mitigate rising obesity-related health care costs.
Policy makers seeking to reduce childhood obesity must prioritize investment in treatment and primary prevention. We estimated the cost-effectiveness of seven interventions high on the obesity policy agenda: a sugar-sweetened beverage excise tax; elimination of the tax subsidy for advertising unhealthy food to children; restaurant menu calorie labeling; nutrition standards for school meals; nutrition standards for all other food and beverages sold in schools; improved early care and education; and increased access to adolescent bariatric surgery. We used systematic reviews and a microsimulation model of national implementation of the interventions over the period 2015-25 to estimate their impact on obesity prevalence and their cost-effectiveness for reducing the body mass index of individuals. In our model, three of the seven interventions--excise tax, elimination of the tax deduction, and nutrition standards for food and beverages sold in schools outside of meals--saved more in health care costs than they cost to implement. Each of the three interventions prevented 129,000-576,000 cases of childhood obesity in 2025. Adolescent bariatric surgery had a negligible impact on obesity prevalence. Our results highlight the importance of primary prevention for policy makers aiming to reduce childhood obesity.
BACKGROUND: Although gastric cancer has declined dramatically in the US, the disease remains the second leading cause of cancer mortality worldwide. A better understanding of reasons for the decline can provide important insights into effective preventive strategies. We sought to estimate the contribution of risk factor trends on past and future intestinal-type noncardia gastric adenocarcinoma (NCGA) incidence.
METHODS AND FINDINGS: We developed a population-based microsimulation model of intestinal-type NCGA and calibrated it to US epidemiologic data on precancerous lesions and cancer. The model explicitly incorporated the impact of Helicobacter pylori and smoking on disease natural history, for which birth cohort-specific trends were derived from the National Health and Nutrition Examination Survey (NHANES) and National Health Interview Survey (NHIS). Between 1978 and 2008, the model estimated that intestinal-type NCGA incidence declined 60% from 11.0 to 4.4 per 100,000 men, <3% discrepancy from national statistics. H. pylori and smoking trends combined accounted for 47% (range = 30%-58%) of the observed decline. With no tobacco control, incidence would have declined only 56%, suggesting that lower smoking initiation and higher cessation rates observed after the 1960s accelerated the relative decline in cancer incidence by 7% (range = 0%-21%). With continued risk factor trends, incidence is projected to decline an additional 47% between 2008 and 2040, the majority of which will be attributable to H. pylori and smoking (81%; range = 61%-100%). Limitations include assuming all other risk factors influenced gastric carcinogenesis as one factor and restricting the analysis to men.
CONCLUSIONS: Trends in modifiable risk factors explain a significant proportion of the decline of intestinal-type NCGA incidence in the US, and are projected to continue. Although past tobacco control efforts have hastened the decline, full benefits will take decades to be realized, and further discouragement of smoking and reduction of H. pylori should be priorities for gastric cancer control efforts.