Scenario-based extrapolation models of aging effects on America’s food consumption

There is always a significant amount of speculation as to how the American diet changes over time. Some of speculation is based on what’s good for people, and others base their speculation on various supply and demand issues and the impact of world social changes. However one approach to forecasting the demand for various food products in the American diet is to extrapolate how America’s eating habits would change based on two different scenarios. The first scenario is an cohort model. In this scenario individuals continue their eating habits as they get older. The second scenario is the aging model, with which it is assumed that as people age they adopt the eating habits of the group that they’re moving into. In this chapter we will evaluate these two scenario-based extrapolation models for projecting food consumption. Data comes from the National Health and Nutrition Examination survey (NHANES), which is conducted regularly by the National Center for Health Statistics (NCHS). It measures levels of consumption with a level accuracy usually not associated with traditional business data services. The specific food items consumed in a 24-hour period are collected for over 30,000 people along with an extensive list of biometric, anthropometric, social, and clinical variables. The models we evaluate assume that new consumers will enter the market based on projected population growth rates and that consumers “exit” the market based on projected death rates. This chapter applies the models to a subset of the total food variables in the database. Food groups that are pertinent to current issues were selected, such as beef, carbonated soft drinks, and snack foods. The models forecast food consumption of the by 5 year increments from age 1 to age 85+ an aging cohort model extrapolate how eating habits could be expected to changeover this time interval. The implications of this exercise are essential to the forecasting and management of food processors. The extrapolations may provide guidance for potential changes in capital investment or entry into other markets.