This study examines whether discounts on nutritionally more desirable foods predict dietary behaviors and weight status. The HealthyFood program started in February 2009 and has since enrolled about 260,000 households who are eligible for up to 25% discount on healthier food choices in about 800 supermarkets across South Africa. The data were collected through repeated online health risk assessments. HealthyFood Program participation is associated with more consumption of fruit/vegetables and wholegrain foods, and less consumption of high sugar/salt foods, fried foods, processed meats, and fast-food. There is no strong evidence that participation is associated with lower BMI or obesity prevention.
Poor diet quality and physical inactivity are among the most pressing health challenges in the U.S., and are associated with major causes of morbidity and mortality, including cardiovascular disease, hypertension, type 2 diabetes, and some types of cancer (USDA and HHS, 2010
). Since 1980, to increase consumption of nutrient-dense foods and reduce consumption of energy-dense foods has been a major theme of Federal dietary guidelines (USDA and HHS, 2010
). However, using National Health and Nutrition Examination Survey 2001–2004 data, it was found that a large majority of the U.S. population fails to meet those guidelines, with insufficient consumption of nutrient-rich foods and excessive discretionary calorie intake (Smith et al., 2010
). There is much interest in the role of prices and financial incentives to encourage healthier diets, but little data is available and none come from interventions in a large population. This paper provides some initial results from a promising intervention, although we need to take the findings with some reservation due to the limitations of the study.
The first set of limitations concerns the measures. HRA surveys do not comprehensively capture diet, but only have some general questions on eating behaviors. Items are not specific in relation to type of food, unit of measurement, and frequency of intake, and respondents are provided with limited instructions on how to frame their responses. For example, the survey did not tell people how to assess a serving size for fruits/vegetables and wholegrain foods. Both diets and height/weight were self-reported and thus subject to measurement errors.
For an online survey, the response rate of the HRA (35%) is very good, and actually not very different from telephone household surveys in the U.S., including the California Health Interview Surveys (CHIS) and the Behavioral Risk Factor Surveillance System (BRFSS) whose response rates have been falling (CHIS, 2011; BRFSS, 2011). Nevertheless, our results are based on a minority of individuals eligible for the HealthyFood benefit.
Arguably, the biggest limitation of the study stems from potential selection biases into the HealthyFood benefit. While all Vitality members were eligible to participate, 74% of families did not activate the benefit, and among the participants, 56% did not complete the HRA to become eligible for the full 25% discount. If the enrollees were those who could potentially gain the most from the program in healthier diet and weight loss, our estimates would overstate the true effects in the population and thus should be interpreted as an upper bound of what can be achieved with a price intervention.
While the HealthyFood program addresses a hot policy question worldwide, its generalizability to other populations remains uncertain. Employers or health insurers in other countries may not be as committed to improving diets and reducing obesity through food subsidies. In the U.S., food subsidy programs funded by the federal government are considered an entitlement program that often carries negative political implications, but the U.S. is the only place where a similar discount program will be piloted soon.
While not conclusive, this study serves as a preliminary analysis of an ongoing effort to quantify the role of prices on dietary behaviors by evaluating the HealthyFood program. So far, subsidizing healthy food purchases among health plan members appears to be a promising intervention. As a next step, we will obtain scanner data from participating supermarkets that can be matched to plan participants and conduct a longitudinal analysis. This may provide a better understanding of how prices affect food purchases.