Our study revealed a wide variation in obesity and physical activity levels among counties in the US. To our knowledge, this is the first study to combine data from NHANES and BRFSS in order to adjust for self-reporting bias of weight and height to measure obesity at the county level. The data showed that although levels of physical activity likely increased during the 2000s, the level of obesity kept increasing in nearly all counties. The US Burden of Diseases, Injuries, and Risk Factors Study [17
] suggests that in 2010 physical inactivity and low physical activity accounted for 234,000 deaths and 5.2% of disability-adjusted life years independent of BMI. Our results call for focusing on a message of the health benefits of physical activity instead of a means for weight reduction.
Elevated BMI is associated with multiple outcomes including higher rates of ischemic heart disease, stroke, cardiomyopathies, hypertensive heart disease, atrial fibrillation, diabetes, osteoarthritis, low back pain, chronic kidney disease, colorectal cancer, breast cancer, esophageal cancer, kidney cancer, gallbladder cancer, pancreatic cancer, and uterine cancer [17
]. A substantial component of the cardiovascular effects of elevated BMI operate through blood cholesterol and blood pressure [13
]. Because of the increase in obesity over the last two decades, the US Burden of Disease shows that high BMI is now the third-leading risk factor in terms of attributable disability-adjusted life years [17
]. The public attention and awareness of the adverse consequences of obesity may have led the population to modify the composition of their diets and increase physical activity. However, these efforts at this time have not made an impact on the epidemic of obesity. Indeed, to address the epidemic of obesity in the US a comprehensive approach may be needed. Although the evidence on successful programs is very limited, reducing caloric intake will likely require community changes as well as individual behavioral response.
During the past decade, there has been no overall improvement in the percentage of adults reporting any physical activity in the BRFSS: for men, the rate was 22.5% in 2001 and 22.4% in 2011; for women, the rate was 28.1% in 2001 and 25.9% in 2011. New strategies to target this segment of the population must be proposed and tested if continued progress in increasing physical activity is to be sustained across the country.
The success of improving levels of sufficient physical activity by a large margin in selected communities stands out in marked contrast to the failure to observe any statistically significant reductions in obesity in any county. Of the 10 counties with the largest improvements, six for men and seven for women were in Kentucky. Other areas with substantial improvements in sufficient physical activity include the metropolitan areas around Atlanta, Los Angeles, San Francisco, San Diego, Houston, and Denver. Although overall there is no correlation between improvements and county size, some large urban areas have been successful. This analysis does not identify why efforts to promote physical activity in these communities have been so much more successful than elsewhere in the country. Further in-depth analyses of these local experiences may be helpful in identifying program insights that can be transferred to other communities, although in-migration to some urban areas may also be a factor. The success in increasing physical activity in some urban and rural communities suggests that more progress in increasing physical activity can be made across the country. This progress, however, will not on its own reverse increases in obesity.
Our findings on increasing obesity levels and improved levels of physical activity are puzzling when put in context with reported declines of mean adult caloric intake in NHANES, from 2,269 kcal/day in 2003–2004 to 2,195 kcal/day in 2009-2010 [18
]. These self-reported figures for caloric consumption are markedly lower than average caloric availability in the US, which exceeds 3,750 kcal/day [19
]. The increases in obesity, decreases in caloric intake, and increases in physical activity seen here require some explanation. First, reported caloric intake in NHANES is known to be biased downwards [12
]. When the data from 24-hour diet recall were validated, obese individuals were more likely to underestimate their caloric intake [20
]. It is possible that as obesity has increased, caloric reporting may have been further underestimated. Alternatively, reporting bias may have increased over time due to social attention on obesity and total caloric intake. Second, if caloric intake was substantially more than the level required for energy balance, the reported 74 kcal/day reduction in intake would indicate the population was not in energy balance, despite higher levels of physical activity. Third, the increase in self-reported physical activity could also be due to increased positivity bias. Given increased public awareness campaigns for physical activity, it is possible that individuals have become more likely to report positive behaviors even if they have not increased their physical activity. Our sensitivity analyses of different ways of constructing sufficient physical activity show that the national trend may be leveling rather than increasing. Finally, it is possible that the behaviors of residents in urban settings are different from those in rural areas. Thus, since NHANES is mainly conducted in about 15 large urban areas in 2011, it is possible that NHANES data are more reflective of urban areas rather than rural areas.
Our findings have some limitations. First, NHANES does not release county identifiers, and we were not able to use such a variable in our adjustment. We assumed that the same correlation between self-reported weight and true weight from a national sample applies to all counties. Our correction model assumes that misreporting of height and weight do not vary over time or by location. However, even if the changes varied by time, our results on the variation in obesity prevalence across counties would not be affected. Second, BRFSS introduced a change in its methodology for weighting in 2011 and included cellular telephones for the first time. Additionally, BRFSS revised the questions used to assess a respondent’s physical activity levels and also changed the standard for recommended physical activity to which respondents were compared. To deal with these changes to how sufficient physical activity was measured and defined we have recalculated this variable for all years to apply the definition used in the 2011 BRFSS. Further, we consider trends over from 2001 to 2009 rather than 2001 to 2011 so that the reported trends will not be influenced by the changes in survey methodology in the 2011 survey. We reported the 2011 prevalence to provide a baseline for the future using the new definition and to account for BRFFS methodology change. Our sensitivity analysis (Additional file 1
), however, shows that our finding that some communities have achieved major increases in prevalence of sufficient physical activity is robust to the definition of sufficient physical activity employed. Third, BRFSS response rates decreased over our study period. However, BRFSS has always been reliable and valid when compared to other household surveys [9
]. Fourth, our physical activity estimates are based on self-reports; direct measures of energy expenditure at the national level are not available to validate self-report. Finally, this study is an area-level analysis; we are not testing hypotheses about the determinants of individual behavior or outcomes. Rather, we are examining the relationships between community characteristics and community outcomes. Further, while we report the association between changes in physical activity and obesity prevalence, controlling for a number of key variables, there may still be other variables that confound the relationship between change in physical activity and change in obesity. Residual measurement error in physical activity levels could also attenuate the estimated relationship between change in physical activity and change in obesity.
Despite these limitations, our study has several advantages. Our study is based on a large sample size. Moreover, our small area estimation method has an advantage compared to other approaches, because it allows us to validate its performance in simulation studies using counties with large sample sizes. Despite these improved small area methods, estimates for some counties with small numbers of responses have wide uncertainty intervals, thereby making detection of statistically significant change over time difficult. Finally, we adjusted for self-reported bias in obesity levels.
Our findings call for searching for more aggressive strategies to prevent and control obesity. Similar to tobacco prevention and control, multisectorial coordinated actions involving our health care and public health systems, along with other government departments such as agriculture, education, and transportation, and non-governmental organizations including consumer groups, service associations, professional bodies, and laws may be needed. Consideration should be given to the role of food labeling, taxation, and incentives both for individuals and for communities [22
]. A balance between caloric intake (consumption) and physical activity levels (expenditure) is needed so that increasing physical activity is not negated by increasing caloric intake. The NHANES analysis of caloric trends gives hope that caloric intake may have stopped increasing; the challenge will be to reduce caloric intake and simultaneously continue increasing physical activity.
The geographic distribution of obesity and physical inactivity are of great importance to public health policy at the local level. Indeed, public health is local and our data will empower counties to design, implement, and evaluate public health programs to address these risk factors. Moreover, county-level information can empower the public to act. Ultimately, our data will allow us to learn from successful programs and improve the efficiency of others dealing with physical inactivity and obesity.