Food prices, access to food outlets and child weight
Introduction
Obesity (age- and gender-specific body mass index (BMI) ≥95th percentile) rates reached 12.4%, 17.0% and 17.6% among children aged 2–5, 6–11, and 12–19 years, respectively, in 2003–2006 and are up roughly three-fold from the early 1970s (Ogden et al., 2002, Ogden et al., 2008). Obese children are at an increased risk for developing type 2 diabetes mellitus (Hannon et al., 2005) and cardiovascular disease risk factors (Freedman et al., 1999). Studies have shown that cardiovascular risk factors present in children are likely to persist into adulthood (Mahoney et al., 1996, Dietz, 1998, Li et al., 2003, Raitakari et al., 2003) and obesity itself tracks from childhood to adulthood (Whitaker et al., 1997, Freedman et al., 2005). The long-term negative health risks associated with obesity are extensive and have been well-documented (USDHHS, 2001). In addition to adverse physical health outcomes, long-term consequences related to obesity may include poorer psychological health (Mustillo et al., 2003, Stunkard et al., 2003), lower earnings outcomes, particularly for women (Averett and Korenman, 1996, Pagán and Dávila, 1997, Cawley, 2004, Baum and Ford, 2004), and lower wealth (Zagorsky, 2005).
Recently, researchers have sought to assess the importance of contextual economic factors such as food prices, restaurant availability and food store availability on individuals’ weight outcomes. The low cost and high convenience of energy-dense food are hypothesized as key contributors to obesity (Drewnowski and Darmon, 2005). Several economists have argued that technological change has contributed to the U.S. obesity epidemic by altering incentives such that the relative price of consuming a calorie has fallen over time while production efficiency has raised the cost of physical activity and work has become more sedentary (Lakdawalla and Philipson, 2002, Philipson and Posner, 2003, Cutler et al., 2003, Lakdawalla et al., 2005). Chou et al. (2004) showed that increases in the per capita number of restaurants, lower real food prices, and higher cigarette prices significantly contributed to the upward trend in adult obesity with the largest effect stemming from greater restaurant availability. In terms of food store access, several studies from the public health literature have found that greater availability of supermarkets is associated with more fruit and vegetable intake, more healthful diets, and lower rates of obesity among American adults (Morland et al., 2002, Morland et al., 2006, Laraia et al., 2004).
A limited number of studies have empirically examined the importance of food prices and access to food among children and most of these have been based on cross-sectional data. Examining the importance of food prices and restaurant outlet density on BMI, obesity, and the consumption of fruit and vegetables among adolescents using repeated cross-sections from the Monitoring the Future Surveys (1997–2003), Powell et al. (2007) found BMI and the probability of obesity to be significantly lower when fast food was more expensive. Fruit and vegetable consumption was found to be lower when fruit and vegetable prices were higher, or when the price of fast food was lower, or when full-service restaurants (versus fast food restaurants) were less readily available. Lower BMI among adolescents has also been associated with higher fast food prices based on analyses using the 1997–1999 cross-sections of the National Longitudinal Survey of Youth 97 (Chou et al., 2005, Chou et al., 2008) and the 2001–2003 cross-sections of the Medical Expenditure Panel Survey (Monheit et al., 2007). Auld and Powell (in press) found that supermarket availability and fruit and vegetable and fast food prices were significantly related to adolescents’ weight and that almost all of the changes in body weight in response to changes in prices occurred in the top quintile of the conditional distribution of BMI. Sturm and Datar (2005) examined the importance of contextual economic factors in a longitudinal framework analyzing weight changes in children in kindergarten through the third grade and found that lower fruit and vegetable prices, but not generally prices of other food items or outlet density, predicted decreases in body weight. Sturm and Datar (2008) found that these results were robust in a follow up study of the same children through fifth grade. Hence, overall, the previous literature has found evidence that younger children's weight is sensitive to the prices of healthy foods (such as fruits and vegetables) and adolescents’ weight is sensitive to fruit and vegetable as well as fast food prices, whereas there is limited evidence that food outlet densities are important predictors of children's weight outcomes.
This study examines the importance of food prices and food outlet availability for child BMI. Specifically, we examine the extent to which child weight is related to the real price of energy-dense foods such as fast food and the real price of healthy foods such as fruits and vegetables. We also assess the importance of fast food and full-service restaurant availability and access to food store outlets such as supermarkets, grocery stores and convenience stores. We draw on individual-level panel data on children 6 through 17 years of age from the 1998, 2000, and 2002 waves of the mother-child merged files from the 1979 cohort of the National Longitudinal Survey of Youth (NLSY79). Using county-level geocode identifiers, we match the individual-level data with fast food and fruit and vegetable price data obtained from the American Chamber of Commerce Researchers Association (ACCRA) and outlet density data on fast food and full-service restaurants and food stores obtained from Dun & Bradstreet (D&B). We examine a continuous BMI outcome measure of weight using a random effects model. We also estimate separate models by children's socioeconomic status (SES) according to family income and mother's education level.
Section snippets
Individual-level data
We use merged child–mother files from the NLSY79 data set for the empirical analysis. The NLSY79 is a nationally representative sample of 12,686 young adults, among whom 6283 were women, who were between 14 and 21 years at their first interviews in 1979. Starting in 1986, children born to the women of the NLSY79 were given separate questionnaires and they were interviewed every 2 years in conjunction with the main adult surveys. Linking children to their mothers, we are able to obtain rich
Empirical model
Economic theory suggests that contextual economic factors such as food prices and access to food outlets may be related to BMI through food consumption. Higher prices of healthy foods (i.e., fruits and vegetables) are expected to decrease healthy food consumption while lower prices for energy-dense unhealthy foods (i.e., fast food) are expected to increase consumption of such foods resulting in higher energy intake levels and a higher energy balance leading to higher weight (Lakdawalla and
Descriptive statistics
Descriptive statistics of the estimation sample are reported in Table 1. The average child has a BMI of 20.3 and over the 1998–2002 sampling period used in this study, children's BMI trended upwards from 19.8 to 20.6 units (not shown in tables). Almost 80% of all children in our sample are non-Hispanic white, 13% are non-Hispanic black and 8% are Hispanic. On average, a child weighed seven and a half pounds at birth and 58% of all children were breastfed. At the time of interview, 5% of
Conclusions
This study drew on individual-level child–mother data from the 1998, 2000 and 2002 waves of the NLSY79 merged with county-level contextual economic data to examine the importance of food prices and food outlet availability on child BMI. Previous studies have examined the importance of food prices and outlet availability on BMI for adolecents using only cross-sectional data and those studies that have used panel data have done so only for younger children (kindergarten through 5th grade). This
Acknowledgements
This research was supported by the National Research Initiative of the U.S. Department of Agriculture Cooperative State Research, Education and Extension Service, grant number 2005-35215-15372. We are also grateful to the Robert Wood Johnson Foundation Bridging the Gap ImpacTeen study for making the price and outlet density data available to us.
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