UNITED STATES DIETARY RECOMMENDATIONS AND 

GROCERY SPENDING : A COHORT ANALYSIS

LACEY WILSON, UNIVERSITY OF SOUTH CAROLINA

DIRECTOR: DR. ORGUL OZTURK

CE Microdata User’s Workshop

July 19, 2018
INTRODUCTION

 Grocery shopping patterns with regards to changing dietary recommendations

 Generational approach
BACKGROUND
USDA DIETARY 

RECOMMENDATIONS

 1943 

 US National Archives and Records/USDA
USDA DIETARY 

RECOMMENDATIONS

 1958

 USDA
USDA DIETARY 

RECOMMENDATIONS

 1980

 USDA
USDA DIETARY 

RECOMMENDATIONS

 1990

 USDA
USDA DIETARY 

RECOMMENDATIONS

 1995

 USDA
USDA DIETARY 

RECOMMENDATIONS

 2005

 USDA
COHORT STUDIES OF EATING HABITS

 Individuals grouped according to birth year to study impact of historical conditions

 Learning and habit formation theory  eating habits may be retained throughout 

lifetime
METHODOLOGY
COHORT STUDY

FIVE-YEAR GROUPINGS OF BIRTH YEARS
DATA USAGE

 Consumer Expenditure Survey : 1996-2014

 Diary Survey : FMLD, EXPD

 Primary variables

 Age_ref, age2, strtyear, [to construct cohorts]; cost [to calculate budget shares]; beef, 

poultry, milkprod, etc. from FMLD or UCC from EXPD

 Educ_ref, fam_size, fincaftx used as controls in regression
ANALYSIS
EGGS

 Late 1970’s – 1990 : Strong 

recommendations against eggs

 1990 onward : Some 

recommendations against eggs

 Early – late 1970’s : Some 

recommendations against eggs
REGRESSION ESTIMATION

 Run on egg expenditures ; patterns demonstrate most correlation with recommendations

 Tobit model 

 Y

∗

= βiXi + β2X2 ... . + βiXi + εi

 Y = Y

∗

if Y

∗ > 0

 Y = 0 otherwise

Percentage = β0 + β1EggPrice + β2 SubstitutePrice + β3 ComplementPrice + β4 IncomePerCap

+ β5Educ + β6Over40 + β7RecAgst + ε
TOBIT 

REGRESSION 

RESULTS
ISSUES/QUESTIONS WITH DATA
TARGETING INFLUENCE OF RECOMMENDATIONS

 Reference person’s age used, but other HH members could be influencing purchasing 

decisions

 This study limits the data to single person HH’s or HH’s that include only members of the 

same cohort

 Assumes childhood exposure to dietary recommendations

 Respondents who moved to US during adulthood not denoted
FOOD GROUPINGS V NUTRITIONAL INFORMATION

 Food group variables large, but UCC’s can further narrow

 Ex. Butter, margarine, and oils can be distinguished from MILKPROD & 

OILS

 Some product groupings do not lend themselves to our nutritional 

analysis; “Fresh Milk” doesn’t distinguish whole v skim
COMPLETENESS OF OBSERVATION OF DIFFERENT AGE GROUPS

 Stage in life affects food consumption choices (ie preferences for drinking 

milk)

 Although data spans 18 years, cohorts are still observed at different ages

 Age variable in regression

 Better results as more years of data become available
TIME ISSUES

 Relative prices between goods may be different over time (eg butter v 

margarine)

 Oldest cohorts are observed in earlier time period than youngest 

cohorts

 Because data doesn’t contain quantity or price, information must be 

pulled from elsewhere to account for price 
CONCLUSIONS

 Some evidence that some individuals remain influenced by childhood 

dietary recommendations

 Limits of the data in terms of nutritional information disallow thorough 

investigation of some food groups
THANK YOU

LACEYWILSON95@GMAIL.COM
COHORT 

STUDY

GROCERY BASKET ANALYSIS



COHORT 

COMPOSITION
HOUSEHOLD TYPES

MEAT

 Types of meat analyzed 

as a percentage of total 

expenditures on meat
COOKING FATS 

AND OILS

 Types of cooking oils as a 

percentage of total spent 

on all fats and oils

CHEESE
MILK

 Milk as a percentage of 

spending on all nonwater, non-alcoholic 

beverages

 Consideration : milk 

consumption declines 

with age