Rodolfo M. Nayga, Jr. Professor and Tyson Endowed Chair University of Arkansas and NILF

By Rodolfo M. Nayga, Jr. Professor and Tyson Endowed Chair University of Arkansas and NILF

Outline of Presentation Motivation The Current Literature Endogeneity Issue Instrument Validity and Relevance Data Sources Methodology Results Some Implications Current and Future Research Undertakings

Outline of Presentation Motivation The Current Literature Endogeneity Issue Sources of Endogeniety Addressing Endogeneity Instrument Validity and Relevance Data Sources Methodology Results Some Implications Current and Future Research Undertakings

Childhood Obesity in US Childhood obesity has more than tripled in the past 30 years. The prevalence of obesity among children aged 6 to 11 years increased from 6.5% in 1980 to 20% in 2008. The prevalence of obesity among adolescents aged 12 to 19 years increased from 5% to 18%. Why important obese children tend to also become obese adults

Motivation Fast foods are concentrated in areas in short walking distances of schools (Davis and Carpenter, 2009). Increased labor force participation of women (Anderson, Butcher, and Levine 2003) reduced the time allocated for food preparation and child care (Anderson and Butcher, 2006).

Motivation Fast food marketing messages and childhood obesity (Chou, Rashad and Grossman, 2008). Main goal to determine whether the proximity to fast food restaurants is a significant driver of childhood obesity rates in Arkansas.

Why is Arkansas an Interesting Case to Study One of the least healthy the Delta region in particular is home to a historically disadvantaged population More importantly for our study, Arkansas s childhood obesity rate has doubled in the last couple of decades and is one of the highest in the country at nearly 40 percent.

The Current Literature: Among Children Among 9th grade level school children, presence of a fast food restaurant at the tenth of a mile increases obesity rates by 1.2 percentage points (Currie et. al, 2010). Davis and Carpenter (2009) found that students whose school is near fast food restaurants within half mile were likely to be overweight, relative to students whose school were not near any fastfood restaurant.

The Current Literature: Among Adults Fast food restaurants do not causally impact increases in BMI rates (Anderson and Matsa 2011). 10% increase in the number of fast food restaurant translate to 0.33 increase in BMI percentage points (Dunn 2010).

Our study Similar to Currie et al. use school level data But different in many ways: Covers broader range of ages K 10 th grade Actual count of fast food restaurants within certain distances We use IV approach

Endogeneity Issue omitted variables measurement error reverse causality

Sources of Endogeneity Decisions regarding child health outcomes are made by the parents, and as such the child s food choices and preferences are still largely dependent on parental decisions (Anderson, Butcher and Levine 2003a). Adults may choose to locate near areas where fastfood restaurants proliferate and restaurants may also position themselves based on individual preferences.

Sources of Endogeneity Fast food restaurants could be expected to locate near consumer segments that are generally unconcerned about dietary health and obesity may well be a more prevalent problem among these consumers. On the other hand, fast food restaurants might primarily target consumers with a high opportunity cost of food preparation at home.

Sources of Endogeneity Fast food restaurants may locate near schools where there are many obese children or near schools where many children come from households with higher disposable incomes Given these concerns, directly regressing obesity rates against the number of restaurants will likely produce inconsistent estimates of model coefficients

Addressing Endogeneity Consequently, we utilize the IV regression approach and identify the model: The proportion of individuals within the school district falling into the 15 to 24 yearold age group. Three distance measures representing the nearest distance of a school to a US, State and Interstate Highway.

Instrument Validity Young adult workers are ideal candidates as they are generally better able to tolerate low salaries, shifting hours of work. The constructed distance measures reflect the argument that fast food establishments tend to cluster near highway off ramps.

Instrument Validity A threat to validity it would be possible for some among the 15 to 24 year old age group to be parents of young schoolchildren. Probability of low SES would be high correlated with higher obesity rates We assess this by examining the relationship between younger grade (e.g. kindergarten 2nd grade) enrollments and the proportion of population within the 15 to 24 year old age group. (not statistically significant)

Instrument Validity Another threat locales with a high proportion of younger people may be attractive to additional business formats, such as convenience stores, that provide unhealthy food options and this could affect obesity outcomes among children. We found no statistically significant relationship between convenience stores per capita and percentage of the population aged 15 24 at the county level. This finding was robust to the inclusion/exclusion of controls for other county level population characteristics

Instrument Validity The main challenge to the three distance instruments presence of highways may expand food options during the lunch period for students of driving age (e.g., HS students). We address this challenge by determining whether our distance instruments are related to school enrollments in grade 10 and grade 8 enrollments. We find no statistical evidence that relates HS grade enrollments with our highway proximity variables

Instrument Relevance Hansen J statistic insignificant indicating that the null hypothesis of the instruments being uncorrelated with the error terms is not rejected. Kleibergen Paap rk Wald F statistics for weak identification show the instruments are marginally relevant (Stock and Yogo, 2005).

Instrument Relevance Since our chosen instruments are relatively weak, we use Fuller s modified limited information maximum likelihood (Fuller LIML) estimation procedure. This procedure is robust when weak instruments are present and is less sensitive than the two stage least squares to finite sample bias (Bascle 2008).

Data and Sources Arkansas Act 1220 required all school districts to measure BMI for every public school student annually and report results to parents. Proportion of obese students in Arkansas public schools obtained from the Arkansas Center for Health Improvement (ACHI). Fast food restaurant locations obtained from Acxiom restaurant database for Arkansas. These data are geo coded in terms of longitude and latitude positions.

Data and Sources The instrumental variable representing the proportion of population in the 15 24 year old age group were derived from block level data found in the 2000 Census. The instrumental variables representing the distance measures were measured as the distance of a school to the nearest US highway, State Highway and Interstate Highway using Arc GIS.

Methodology The reduced form baseline specification can be represented as: where P i is the proportion of children that are obese at the school i and the variable F j i is the number of fast food restaurants indexed by different radial distances. X i contains control variables for socio economic and demographic characteristics, school and district level characteristics.

Methodology The first stage relation involving the instrumentation of the number of fast food restaurants. The first stage relation can be represented as: F j i= γx i + Z i + i F j i are the number of fast food restaurants at different j incremental distances from school i, Z i is vector of variables namely the proportion of population in the 15 24 year old age group and the three distance variables measuring the nearest distance of a school to a US, State and Interstate highway. i is the error term.

Results Table 1. Effect of Fast-food Restaurants on School-level Obesity Rates under Alternative Specifications Specification Distance of Fast-Food Restaurants 0-0.25 mile 0-0.5 mile 0-1 mile 0.25-0.5 mile 0.25-1 mile 0.5-1 mile 1A. Entire sample (N=942) 2.019 0.944 0.652 (1.830) (0.897) (0.493) 1B. Entire sample (N=942) 2.149 0.753** (1.833) (0.373) 1C. Entire sample (N=942) 1.206* 0.654 (0.664) (0.503) 1D. Entire sample (N=942) 0.915*** (0.336) Note: Robust standard errors appear in parentheses. *** denotes coefficient is significant at the 1 % level ** denotes coefficient is significant at the 5 % level * denotes coefficient is significant at the 10 % level

Estimated impact of restaurants on school level obesity rates is robust to the differences in model specification. When projected through the sample means, specifications 1A through 1D suggest that the average impact of additional restaurant within a mile radius of schools ranges from a 2.77 to 3.09 percentage point increase in school level obesity rates. There is only about a 0.3 percentage point difference among these four specifications.

Results Table 2. Results Separating Elementary and Higher Grade Schools Variable Elementary Schools Fast-food restaurants within 0.25 mile 1.73 2.84** Fast-food restaurants (0.25 and 0.5 mile) 1.40* 1.13* Fast-food restaurants (0.5 mile and 1.0 mile) 0.69* 0.06 Schools with Higher Grades

Results Table 3. Results by SES Level Variable Low SES Schools Non-Low SES Schools Fast-food restaurants within 0.25 mile 4.59* 3.80* Fast-food restaurants (0.25 and 0.5 mile) 2.73* 0.53 Fast-food restaurants (0.5 mile and 1.0 mile) 0.48 0.31

General Findings Our results suggest that the number of fast food restaurants positivelyaffectsschool level obesity rates. Impact is robust but significance levels depend on specification Effect of number of fast food restaurants is highest when they are within 0.25 mile from the school, especially for upper grades and lower SES schools. Effect diminishes at the incremental ranges of 0.25 mile to 0.5 mile and 0.5 mile to 1 mile from the school.

Why the declining effects? transport costs for students are quite high and distance would matter a great deal in cases where students are able to leave campus during what are usually very short lunch breaks. most school days end in the mid to late afternoon several hours after the child has last had a meal. many children will have developed an appetite by this time of day presence of a fast food restaurant near the school may be an especially important stimulus that motivates the child to request fast food on the ride home or causes him to develop a greater desire for fast food items that manifests itself on other dining occasions. The effects of this type of exposure would be more heterogeneous at longer distances from the school and so would be less likely to show up in a schoollevel obesity measure.

Some Implications Proposed zoning policies that will restrict the availability of fast foods restaurants particularly in upper grade levels and lower SES schools, will likely have a significant impact on school level obesity rates.

Some Implications If fast food restaurants locate further away from schools, then the effects of increasing transport costs can become a major search disincentive.

Current and Future Research Analysis at the individual student level Number of restaurants along the route of student s home to school (different buffer zones along the route) Food access, food desert issues (D&B data) Built environment: geocoded parks, rec centers, sidewalks Student educational achievement scores School lunch program