Fighting Youth Body Fatness

Childhood obesity is a major health concern whose effects persist into adulthood. Targeted taxation of unhealthy foods has been shown to reduce body mass index (BMI), but this is an imperfect measure of obesity. This column provides evidence that taxation affects percentage body fat (PBF), a more direct measure. This evidence strengthens the argument in favour of tax-based incentives as a policy tool.

According to the World Health Organization, childhood obesity is one of the most serious public-health problems of the 21st century. The prevalence of obesity among children has been on the rise globally over the last several decades and is now an epidemic in the US.

• Since the mid-1970s, the proportion of children aged 12 to 19 who are obese has more than tripled from 5.0% to 18.1% in the US (Ogden et al. 2010).

These trends are extremely alarming.

• Childhood obesity has been associated with a host of chronic health problems, such as high blood pressure, hypertension, gallbladder disease, and Type 2 diabetes as early as adolescence (Serdula et al. 1993; Freedman et al. 1999; 2007; Hill, Catenacci, and Wyatt 2006).

Children who are obese during early childhood are likely to be obese during adulthood. This not only exacerbates the aforementioned health problems, but also leads to negative long-term psychological and labour market outcomes ranging from poor self-esteem and depression to discrimination and lower wages (Daniels 2006; Mocan and Tekin 2011; Dietz 1998; Strauss 2000).

Why the extra weight?

There is a long list of explanations offered for the rapid rise in childhood obesity and overweightness. These include:

• Falling food prices.
• Increased demand for sugary drinks.
• Advertising of unhealthy foods targeted at children.
• Increased time spent in sedentary activities, such as watching TV or videos, using a computer, or playing computer games.
• Lack of vigorous physical activity.
• Increased food-portion sizes.

Just as there is no single explanation for the obesity epidemic, there is no single or simple solution. Most public interventions aimed at improving child and adolescent health generally take the form of policies that limit access and provide price incentives or disincentives.

The latest policy proposals for reducing childhood obesity rates involve raising the prices of unhealthy, nutrient-dense food items such as sugar-sweetened beverages and fast-foods through taxations. Such policy proposals are based on findings that selective applications of taxation and subsidies are effective in shifting food consumption away from unhealthy food towards healthier alternatives (Cawley 2010; Powell and Chaloupka 2009).

• In general, empirical studies that examined the effects of prices on obesity found stronger effects than studies that examined the effects of food taxes (Powell, Chriqui, and Chaloupka 2009; Fletcher, Frisvold, and Tefft 2010).¹
• There is also reasonably consistent evidence demonstrating that fruit and vegetable prices, particularly of the non-starch variety, are associated with lower weight outcomes while fast-food prices are associated with higher weight outcomes for the adolescent population (Powell et al. 2013).

Moreover, these effects tend to be larger for minorities, children in lower-income families, and children whose mothers have less than a high school education.

Problems with the BMI as an indicator of obesity

The existing evidence almost exclusively comes from studies that rely solely on body mass index (BMI) as the measure of obesity. This is not surprising since BMI is easy to calculate and readily available from many social science datasets, but its reliability for use in epidemiological studies has come into question recently.

• It is argued that some of the weak or mixed results documented by studies using BMI may be due to its limited ability to correctly distinguish body fat from lean body mass (e.g., Yusuf et al. 2004, 2005; Romero-Corral et al. 2006, 2007).

Since it is body fat (and not fat-free mass) that is responsible for the detrimental health effects of obesity, several studies caution against a sole reliance on BMI and point to a need for using direct measures of body composition in obesity studies (e.g. Smalley et al. 1990; Romero-Corral et al. 2006).

Our contribution

In a recent paper, we use clinically obtained body composition measures to conduct a comprehensive and comparative analysis of the effects of various food prices on body fatness among youths ages 12 through 18 and compare the sensitivity of our findings to results using BMI (Grossman, Tekin, and Wada 2013). Ours is the first study to consider clinically measured levels of body composition to examine the effects of food prices on body fatness among youths. It is important to assess the extent to which alternative body fat measurements are reliable and precise in the identification of the degree of obesity among youths in order to better understand the risk factors associated with obesity and develop policies to counter these risk factors.

The body composition measure that we employ is percentage body fat (PBF). We derive our PBF measure from three separate sources, two of which rely upon bioelectrical impedance analysis (BIA) and one of which relies upon dual energy x-ray absorptiometry (DXA). We also employ clinically measured height and weight to estimate the effects of prices on BMI. We draw on data from the restricted-use versions of National Health and Nutrition Examination Survey (NHANES) to merge various county-level time-varying price variables.

Results

Our findings suggest that:

• Increases in the real price of one calorie of food for home consumption and the real price of fast-food restaurant food result in significant reductions in the in PBF among youths.
• An increase in the real price of fruits and vegetables has negative consequences for these outcomes.
• Measures of PBF derived from BIA and DXA are no less sensitive and in some cases more sensitive to the food prices just mentioned than BMI, and serve an important role in demonstrating that rising food prices (except for those of fruits and vegetables) are associated with reductions in obesity rather than in body-size proportions alone.

Policy implications

These findings have important implications for the optimal targeting of public policies designed to reverse the epidemic of childhood obesity. In particular, they have implications for how changes in agricultural, tax, and subsidy policies might affect food and beverage consumption patterns.

• We show that selective taxes or subsidies may be able to accomplish part of this goal through changes in food prices.

We also document that uniform increases or decreases in the price of food have the expected impacts on body fatness.

• It should be kept in mind that taxes are blunt instruments that impose significant welfare costs on individuals who consume food in moderation.

There is also the question as to whether parents may more easily and immediately affect the choices made by their children than the government policies.

Some of our results point to higher rates of time preference and lower expected future wage rates among non-white parents and youths as explanations of why minorities are more sensitive to fast-food prices and less sensitive to fruits and vegetables prices than whites. These interpretations add to the existing evidence on the wide range of benefits to early childhood intervention programs emphasised by Heckman and colleagues (e.g., Conti and Heckman 2012). We view our contribution as an important input into the policy debate concerning the most effective ways to reverse the upward trend in obesity.

References

•Auld, M C and L M Powell (2009), “Economics of Food Energy Density and Adolescent Body Weight,” Economica 76(304):719-740.
•Cawley, J (2010), “The Economics of Childhood Obesity,” Health Affairs 29(3): 364-371.
•Chou S Y, M Grossman and H Saffer (2004), “An Economic Analysis of Adult Obesity: Results from the Behavioral Risk Factor Surveillance System,” Journal of Health Economics 23(3):565-587.
•Chou S Y, I Rashad, and M Grossman (2008), “Fast-Food Restaurant Advertising on Television and Its Influence on Childhood Obesity,” Journal of Law & Economics 51(4):599-618.
•Conti, G and J J Heckman (2012), “The Economics of Child Well-Being,” National Bureau of Economic Research Working Paper No. 18466, October.
•Daniels, S R (2006), “The Consequences of Childhood Overweight and Obesity,” The Future of Children 16(1):47-67.
•Dietz, W H (1998), “Health Consequences of Obesity in Youth: Childhood Predictors of Adult Disease,” Pediatrics 101(3 Pt 2):518-525.
•Fletcher J M, D E Frisvold, and N Tefft (2010), “The Effects of Soft Drink Taxes on Child and Adolescent Consumption and Weight Outcomes,” Journal of Public Economics 94(11-12):967-974.
•Freedman D S, W H Dietz, S R Srinivasan and G S Berenson (1999), “The Relation of Overweight to Cardiovascular Risk Factors among Children and Adolescents: The Bogalusa Heart Study,” Pediatrics 103(6 Pt 1):1175–82.
•Freedman D, Z Mei, S Srinivasan, G Berenson and W Dietz (2007), “Cardiovascular Risk Factors and Excess Adiposity among Overweight Children and Adolescents: The Bogalusa Heart Study,” Journal of Pediatrics 150(1):12–17.e2.
•Grossman M, E Tekin and R Wada (2013), “Food Prices and Body Fatness among Youths,” National Bureau of Economic Research Working Paper No. 19143, June.
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•Mocan, N H and E Tekin (2011), “Obesity, Self-esteem and Wages,” In M Grossman and N Mocan (eds.) Economic Aspects of Obesity, University of Chicago Press, pp. 349-380.
•Ogden C L, M D Carroll, L R Curtin, M M Lamb and K M Flegal (2010), “Prevalence of High Body Mass Index in US Children and Adolescents”, 2007-2008. JAMA: The Journal of the American Medical Association 303(3), 242-249.
•Powell, L M (2009), “Fast Food Costs and Adolescent Body Mass Index: Evidence from Panel Data,” Journal of Health Economics 28(5):963-70.
•Powell, L M and F J Chaloupka (2009), “Food prices and obesity: evidence and policy implications for taxes and subsidies,” Milbank Q 87(1):229–257.
•Powell, L M, Chaloupka, F.J. and Bao, Y. (2007), “The Availability of Fast-food and Full-service Restaurants in the US: Associations with Neighborhood Characteristics,” American Journal of Preventative Medicine 33(4 Suppl):S240-S245.
•Powell, L M, J Chriqui and F J Chaloupka (2009), “Associations between State-level Soda Taxes and Adolescent Body Mass Index,” Journal of Adolescent Health 45(3):S57-S63.
•Powell L M, J Chriqui, T Khan, R Wada and F Chaloupka (2013),“Assessing the Potential Effectiveness of Food and Beverage Taxes and Subsidies for Improving Public Health: A Systematic Review of Prices, Demand and Weight Outcomes,” Obesity Reviews 14(2): 110-28.
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•Romero-Corral A, V K Somers, J Sierra-Johnson, M D Jensen, R J Thomas, R W Squires, T J Allison, J Korinek and F Lopez-Jimenez (2007), “Diagnostic Performance of Body Mass Index to Detect Obesity with Coronary Artery Disease,” European Heart Journal 28(17):2087-2093.
•Serdula, M K, D Ivery, R Coates, D S Freedman, D F Williamson and T Byers (1993), “Do Obese Children Become Obese Adults? A Review of the Literature,” Preventive Medicine 22(2):167-77.
•Smalley K J, A N Knerr, Z V Kendrick, J A Colliver and O E Owen (1990), “Reassessment of Body Mass Indices,” American Journal of Clinical Nutrition 52(3):405-408.
•Strauss, R S (2000), “Childhood Obesity and Self-Esteem,” Pediatrics 105(1):e15.
•Yusuf S, S Hawken, S Ounpuu, L Bautista, M G Franzosi, P Commerford, C C Lang, Z Rumboldt, C L Onen, L Lisheng, S Tanomsup, P Wangai Jr, F Razak, A M Sharma and S S Anand (2004), “Effect of Potentially Modifiable Risk Factors Associated with Myocardial Infarction in 52 Countries (the INTERHEART Study): Case-Control Study,” The Lancet 364(9438):937-952.
•Yusuf S, S Hawken, S Ounpuu, L Bautista, M G Franzosi, P Commerford, C C Lang, Z Rumboldt, C L Onen, L Lisheng, S Tanomsup, P Wangai Jr, F Razak, A M Sharma, S S Anand; INTERHEART Study Investigators (2005), “Obesity and the Risk of Myocardial Infarction in 27,000 Participants from 52 Countries: A Case-control Study,” The Lancet 366(9497):1640-1649.
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1 For studies on prices and obesity see, e.g., Chou, Grossman, and Saffer 2004; Rashad, Chou, and Grossman 2006; Chou, Rashad, and Grossman 2008; Powell and Yanjun 2007; Powell 2009; Powell, Chaloupka and Bao 2007; Auld and Powell 2009.

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