Research article
Obesity and Severe Obesity Forecasts Through 2030

https://doi.org/10.1016/j.amepre.2011.10.026Get rights and content

Background

Previous efforts to forecast future trends in obesity applied linear forecasts assuming that the rise in obesity would continue unabated. However, evidence suggests that obesity prevalence may be leveling off.

Purpose

This study presents estimates of adult obesity and severe obesity prevalence through 2030 based on nonlinear regression models. The forecasted results are then used to simulate the savings that could be achieved through modestly successful obesity prevention efforts.

Methods

The study was conducted in 2009–2010 and used data from the 1990 through 2008 Behavioral Risk Factor Surveillance System (BRFSS). The analysis sample included nonpregnant adults aged ≥18 years. The individual-level BRFSS variables were supplemented with state-level variables from the U.S. Bureau of Labor Statistics, the American Chamber of Commerce Research Association, and the Census of Retail Trade. Future obesity and severe obesity prevalence were estimated through regression modeling by projecting trends in explanatory variables expected to influence obesity prevalence.

Results

Linear time trend forecasts suggest that by 2030, 51% of the population will be obese. The model estimates a much lower obesity prevalence of 42% and severe obesity prevalence of 11%. If obesity were to remain at 2010 levels, the combined savings in medical expenditures over the next 2 decades would be $549.5 billion.

Conclusions

The study estimates a 33% increase in obesity prevalence and a 130% increase in severe obesity prevalence over the next 2 decades. If these forecasts prove accurate, this will further hinder efforts for healthcare cost containment.

Introduction

Obesity prevalence has increased dramatically since the 1970s.1, 2 According to the National Health and Nutrition Examination Survey (NHANES),2 obesity prevalence in 2007–2008 was 33.8%, representing a >100% increase from 1976–1980 and a 50% increase from 1988–1994.1 Since 2003–2004, obesity prevalence might be leveling off for some adult subpopulations.2 Severe obesity was extremely rare before the early 1970s but has since increased faster than obesity, with no evidence of slowing.3

Given the relationship between excess weight, poor health, and high medical expenditures, successful cost-containment efforts will need to address obesity. For example, Thorpe et al.4 report that 27% of the rise in inflation-adjusted medical expenditures between 1987 and 2001 was due to the rising prevalence and costs of obesity. Finkelstein et al.5 estimate that costs of obesity may be as high as $147 billion per year, or roughly 9% of annual medical expenditures.

The current paper forecasts future obesity and severe obesity prevalence over the next 20 years. The forecasted results are then used to simulate the savings that could be achieved through modestly successful obesity prevention efforts. All previous attempts to forecast future trends and costs of obesity6, 7, 8, 9 used past obesity prevalence data to predict linear future trends. For example, using data from the NHANES, Wang et al.6 projected that if historical trends continue linearly, by 2030, 51% of U.S. adults will be obese. However, this and other forecasts likely overstate future obesity prevalence given the recent evidence of slower growth.2

This analysis also uses past trends to predict future obesity prevalence, but incorporates two improvements over prior estimates. First, consistent with the recent data showing slower obesity growth, the assumption of linear trajectories in the future rise of obesity prevalence is relaxed. Second, rather than relying solely on historical obesity levels, the relationship between obesity and exogenous, state-level variables thought to influence obesity, is estimated. Although this approach also necessitates using past data to forecast future trends, it allows for a better model fit than a regression of linear time trends alone and should produce more-accurate predictions of future obesity prevalence and related healthcare costs.

Section snippets

Methods

Analysis was conducted in 2009–2010, and the primary data source was the 1990 through 2008 Behavioral Risk Factor Surveillance System (BRFSS). BRFSS is a state-based, cross-sectional telephone interview survey conducted by the CDC and state health departments. The survey is based on a multistage cluster design that uses random-digit dialing to select samples that represent the civilian, non-institutionalized adult population in each of the 50 states, the District of Columbia, and three U.S.

Results

Descriptive statistics for the analysis sample in years 1990, 2000, and 2008 are presented in Table 1. Self-reported prevalence of obesity and severe obesity more than doubled during this 19-year period, increasing from 11.1% to 26.8% and from 0.9% to 3.5%, respectively. The annual unemployment rate was 5.63% in 1990, decreased to 4.01% in 2000, but then increased to 5.80% in 2008. The price of alcohol increased from 1990 to 2000 (from $2.10 to $2.45 per ounce) and then decreased from 2000 to

Discussion

The current study contributes to the literature on the future prevalence and costs of obesity by moving beyond simple linear predictions and allowing the forecasts to vary based on expected trends in both individual- and state-level variables. With respect to obesity, the present study estimates lower forecasts than those of prior studies. These forecasts are more consistent with recent NHANES data, suggesting a leveling off of obesity for some subpopulations. The projections presented here did

Conclusion

Given the many caveats listed in the preceding paragraph, the current study forecasts a 33% increase in the prevalence of obesity over the next 2 decades based on extrapolating prior available data and assuming these trends continue into the future. If these forecasts prove accurate, this will further hinder efforts for healthcare cost containment. Yet successful interventions that generate even small improvements in obesity prevalence, including those noted in the preceding paragraph, could

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