Documentation
This page provides the following information:
- Survey objectives
- EHM microdata
- EHM data dictionaries and questionnaires
- Module questions
- User’s guide
- Recommended citations
- Selected readings
Survey objectives
The objective of the Eating and Health Module (EHM) of the American Time Use Survey (ATUS) is to collect data on secondary eating—that is, eating while doing another primary activity, and other data to help expand the analysis between food-related time use patterns and obesity, food and nutrition assistance programs, grocery shopping, and meal preparation.
One of the missions of USDA's Economic Research Service (ERS) is to enhance the understanding of economic issues related to the nutrition and health of the U.S. population. Data collection and research on eating patterns, height and weight to calculate the Body Mass Index (BMI), food and nutrition assistance program participation, grocery shopping, and meal preparation all contribute to this goal. Specifically, the economic analysis of decisions made under time constraints provides insight for both policies and programs because the decisions individuals make on how to use their 24 hours in a day have short- and long-run implications for income and earnings, health, and other aspects of well-being.
EHM microdata
Each year of the 2006–08, 2014–16, and 2022 EHM microdata has three files that can be downloaded from the U.S. Department of Labor, Bureau of Labor Statistics’ (BLS) website:
- Respondent file: The respondent file contains information about respondents of the EHM—including self-assessed health status, height, and weight.
- Activity file: The activity file contains information such as the activity number, whether secondary eating occurred during the activity, and the duration of secondary eating.
- Replicate weights file: The replicate weights file contains miscellaneous weights for the EHM.
EHM data dictionaries and questionnaires
Each EHM data dictionary and questionnaire can be downloaded from the BLS website. The data dictionary describes the variable names and descriptions and the questionnaire describes the underlying questions.
Module questions
The 2022–23 Eating and Health Module asks questions on a variety of topics, including:
Eating as a secondary activity
Because many individuals eat while engaged in other main or primary activities, such as driving or watching television, information is needed on eating as both a primary and secondary activity. This question records when and during which primary activities the respondent was eating as a secondary activity.
Grocery shopping in person, online grocery shopping, and food-away-from-home purchases
Information about grocery shopping preferences (in person and online) and food-away-from-home purchases will help to understand household consumer demand for food-at-home and food-away-from home.
Food preparation
Questions on meal preparation will help to understand food-at-home consumption.
Food sufficiency and food assistance
This information will allow time-use-pattern analysis of SNAP (Supplemental Nutrition Assistance Program) and WIC (Special Supplemental Food Program for Women, Infants, and Children) participants versus others—and in particular, low-income persons who are not participating in these food assistance programs.
Household income
This question asks if total household income before taxes was above or below a certain amount. The ATUS Computer Assisted Telephone Interviewing (CATI) software automatically calculates the poverty thresholds of 200 percent, based on the respondent's household composition. This income threshold is slightly higher than the one that determines income eligibility for food assistance programs.
Height, weight, and general health
From self-reported height and weight information, Body Mass Index (BMI) can be calculated. Also, time use patterns and health-related data—such as general health status, physical activity levels, and eating patterns—can be analyzed by BMI category.
See: American Time Use Survey: Eating & Health Module 2022–23 Questionnaire.
The 2014–16 EHM asked ATUS respondents about secondary eating; soft drink consumption; grocery shopping; fast food purchases; meal preparation; food safety practices; USDA food assistance participation; self-assessed health status, height and weight; physical activity; and income.
See: American Time Use Survey: Eating & Health Module 2014–16 Questionnaire.
The 2006–08 EHM asked ATUS respondents about secondary eating; meals obtained at school, day care, or summer camp; grocery shopping; meal preparation; USDA food assistance participation; self-assessed health status; height and weight; and income.
See: American Time Use Survey: Eating & Health Module 2006–08 Questionnaire.
Category of questions | 2006–08 | 2014–16 | 2022–23 |
---|---|---|---|
Secondary eating | |||
Were there any [fill: other] times you were eating any meals or snacks yesterday, for example while you were doing something else? | X | X | X |
Prompt: When thinking about meals or snacks also consider any fruits, veggies, sweets, or salty snacks you ate. | X | ||
During which activities? | X | X | X |
Were you eating the entire time you were [fill: ACTIVITY]? | X | X | X |
About how long would you say you were eating while you were [fill: ACTIVITY]? *Enter HOURS and MINUTES | X | X | X |
Secondary drinking | |||
Not including plain water, were there any other times yesterday when you were drinking any beverages? | X | X | |
During which activities? | X | ||
Were you drinking the entire time you were [fill: ACTIVITY]? | X | ||
About how long would you say you were drinking while you were [fill: ACTIVITY]? *Enter HOURS | X | ||
About how long would you say you were drinking while you were [fill: ACTIVITY]? *Enter MINUTES | X | ||
Were any of the beverages soft drinks such as cola, root beer, or ginger ale? | X | ||
Was the soft drink diet, regular or did you have both kinds? | X | ||
Grocery shopping | |||
Are you the person who usually does the grocery shopping in your household? | X | X | |
How much of the grocery shopping in the household do you usually do? | X | ||
How much do you enjoy doing the grocery shopping for your household? | X | ||
Where do you get the majority of your groceries (in person)? Do you get them at the grocery store, supercenter, warehouse club, drugstore or convenience store, or some other place? | X | X | |
What is the main reason you shop there? Is it because of price, location, quality of products, variety of products, customer service, or other? | X | X | |
Thinking back over the last 30 days, how many times did you purchase groceries online for pick up or delivery for your household? | X | ||
Did you usually pick up your online grocery order or did you have it delivered? | X | ||
What is the main reason you chose to purchase groceries online instead of in person? | X | ||
What is the main reason you did not buy groceries online? | X | ||
Food-away-from-home-purchases | |||
Thinking back over the last 7 days, did you purchase any prepared food from a deli, carry-out, delivery food, or fast food? | X | ||
In the last 7 days, excluding frozen foods, how many times did you purchase prepared, ready-to-eat food from a deli, carryout, delivery food, fast food place, or restaurant, for your household or yourself? | X | ||
Yesterday, did you eat food prepared by any food service provider, such as a deli, restaurant, fast food place, cafeteria, or any other type of eatery? | X | ||
How many times in the last 7 days did you purchase prepared food from a deli, carry-out, delivery food, or fast food? | X | ||
Did you purchase any prepared food from a deli, carry-out, delivery food, or fast food yesterday? | X | ||
Food preparation | |||
Are you the person who usually prepares the meals in your household? | X | X | |
How much of the meal preparation in the household are you usually responsible for? | X | ||
How much do you enjoy doing the food preparation for your household? | X | ||
In the last 7 days, did you prepare any meals with meat, poultry or seafood? | X | ||
Did you use a food or meat thermometer when preparing any of those meals? | X | ||
In the last 7 days, did you drink or serve unpasteurized or raw milk? | X | ||
Food security, SNAP/Food Stamp, and WIC program participation | |||
Which of the following statements best describes the amount of food eaten in your household in the last 30 days—enough food to eat, sometimes not enough to eat, or often not enough to eat? Note: In 2022-23, the question was the same, but the possible responses were as follows: enough of the kinds of food we want to eat, enough but not always the kinds of food we want to eat, sometimes not enough to eat, or often not enough to eat. | X | X | |
In the past 30 days, did you or any member of this household receive [fill State SNAPNAME], SNAP, or food stamp benefits? | X | X | X |
In the last 30 days, did {you/you or any member of your household} receive benefits from the WIC program, that is, the Women, Infants and Children program? | X | X | |
Breakfast and lunch obtained at school | |||
In the past week, did [fill: you / names of household children under the age of 19/you or names of household children under the age of 19] eat a BREAKFAST that was prepared and served at a school, [fill: a paid day care], [fill: a Head Start center], [fill: or] [fill: a summer day program]? This question refers ONLY to BREAKFASTS prepared at the school or center—not meals brought from home. | X | ||
Which children? | X | ||
What about LUNCH? In the past week, did [you / names of household children under the age of 19 / you or names of household children under the age of 19] eat a LUNCH that was prepared and served at a school, [a paid day care], [a Head Start center], [or] [a summer day program]? This question refers ONLY to LUNCHES prepared at the school or center—not meals brought from home. | X | ||
Which children? | X | ||
General health, physical activity, height, and weight | |||
In general, would you say that the quality of your diet is excellent, very good, good, fair, or poor? | X | ||
In general, would you say that your health is excellent, very good, good, fair, or poor? | X | X | X |
During the past 7 days, other than your regular job, did you participate in any leisure-time physical activities or exercises for fitness and health such as running, bicycling, working out in a gym, walking for exercise, or playing sports? | X | X | |
How many times over the past 7 days did you take part in these activities? | X | X | |
How much of this leisure-time physical activity and exercise was vigorous enough to cause a large increase in breathing or heart rate? | X | ||
How tall are you without shoes? | X | X | X |
How much do you weigh without shoes? | X | X | X |
Household income | |||
Last month, was your total household income before taxes more or less than [fill 185 percent of poverty threshold] per month? Note: In 2022-23, the question was the same, but 200 percent of the poverty threshold was used. | X | X | X |
Was it more or less than [fill 130 percent of poverty threshold] per month? | X | X | |
Note: For a detailed list of the questions and responses appearing in each survey module, please see the corresponding questionnaire. Source: USDA, Economic Research Service using information from U.S. Department of Labor, Bureau of Labor Statistics' American Time Use Survey and Eating and Health Module for 2006-08, 2014-16, and 2022-23. |
User's guide
For general information about using data from the American Time Use Survey, please see the American Time Use Survey User’s Guide: Understanding ATUS 2003 to 2022. For specific information on the EHM, please see the 2014–16 Eating and Health Module User’s Guide or the 2006–08 Eating and Health Module User’s Guide.
Relevant information when using the EHM:
The three EHM files can be merged to the ATUS files using the following linking variables:
- Respondent file: TUCASEID and TULINENO (always equal to 1 in the EHM)
- Activity file: TUCASEID and TUACTIVITY_N
- Replicate weights: TUCASEID
The ATUS Respondent file has a variable indicating whether EHM data are available for each respondent: TREMODR = 1 for completed EHM interviews, and TREMODR = 0 for incomplete interviews, and TREMODR= -1 for years when the EHM was not conducted. Researchers can use this variable to select only the ATUS cases with completed EHM interviews. Respondents with incomplete EHM interviews (TREMODR=0) are not included in the EHM microdata files.
In 2022, 97 percent of the ATUS respondents completed the EHM questionnaire. Because incomplete interviews for the EHM (but complete for the ATUS) were excluded, a separate set of sample weights accounts for the difference in completed responses, and therefore EHM weights should be used when using the EHM data.
- The EHM final weight variable is EUFINLWGT, which weights the sample so that weighted total days for selected population groups correspond to the number of person-days spent by those groups for each calendar quarter. Weighted total person-days correspond to population person-days both for weekdays and for weekends.
- See the ATUS User’s Guide for details on calculating standard errors (SE).
The Current Population Survey has both a stratified and clustered sampling procedure and thus is nonrandom; the ATUS follows the same sampling procedure. The replicate weights method is a treatment for stratified and/or clustered sampling. Both SAS and Stata now have procedures for calculating estimates using replicate weights and the procedures for calculating SE. Note that calculating an estimate without using replicate weights and without using a Fay coefficient will generate the correct estimate, but an incorrect SE.
- The EHM replicate weights are EUFINLWGT001—EUFINLWGT160.
- The method chosen is BRR (balanced repeated replication).
- If FAY=0.5, then the correct SE will be generated.
Finally, the ERS standard for cell suppression, following BLS’s recommendations, is as follows:
Case 1: No one reported doing the activity
- If no one reported doing the activity and there are fewer than 77 respondents in the population (n < 77), then suppress all estimates for the activity.
- If no one reported doing the activity, but there are 77 or more observations in the population (n ≥ 77) then:
- The mean time participants spent in the activity must be suppressed.
- The participation rate for the activity is "approximately zero" (~0).
- The mean time the population spent in the activity is "approximately zero" (~0).
- The mean time participants spent in the activity must be suppressed.
Case 2: Only a few (at least 1 but fewer than 10) people reported doing the activity
- The mean time participants spent in the activity must be suppressed.
- The participation rate for the activity is publishable, as long as there are 77 or more respondents in the population of interest and the estimated SE ≤ 5 percent.
- The mean time the population spent in the activity may or may not be publishable.
- If there are fewer than 77 respondents in the population of interest, the mean must be suppressed.
- If there are 77 or more respondents in the population of interest, then calculate a conservative upper bound for the mean to determine whether it meets publication standards. If this calculated upper bound is less than 5 minutes, then the mean for the population is published as "approximately zero" (~0); if the calculated upper bound is greater than or equal to 5 minutes, then the estimated mean for the population is suppressed.
- An upper bound for the mean for participants is determined by calculating a 90-percent confidence interval around the mean. The Kott-Liu formula can be used to calculate an upper bound for the participation rate.
- If there are fewer than 77 respondents in the population of interest, the mean must be suppressed.
Case 3: 10 or more people reported doing the activity
- The participation rate for the activity is publishable, as long as there are 77 or more respondents in the population of interest and the estimated SE ≤ 5 percent.
- The mean time participants spent in the activity and the mean time the population spent in the activity are publishable if one of the following criterion is met:
- The estimated SE is less than 5 minutes.
- The estimated coefficient of variation is less than 0.3.
- The estimated SE is less than 5 minutes.
Recommended citations
Publications and research reports based on the Eating & Health Module data should include the following suggested citation:
U.S. Department of Agriculture (USDA), Economic Research Service (ERS). [year] Eating and Health Module, supplement to the U.S. Department of Labor, Bureau of Labor Statistics (BLS) [year] American Time Use Survey, [current date].
Selected readings
ERS publications
Food-Related Time Use: Changes and Demographic DifferencesThis report uses data from the 2004–17 American Time Use Survey to present an overview of food-related time-use patterns over time. The data is for both the U.S. population aged 15 and older— and for U.S. subgroups defined by educational attainment, household type, and other demographic factors (November 2019).
Frequency and Time of Day That Americans Eat: A Comparison of Data From the American Time Use Survey and the National Health and Nutrition Examination SurveyThis study compares the time-of-day and the number of eating occasions of U.S. adults as reported in the American Time Use Survey and the Eating & Health Module to those in the dietary intake data in the National Health and Nutrition Examination Survey, which are currently the best available data for estimating average daily dietary intake among U.S. adults (July 2019).
Adult Eating and Health Patterns: Evidence From the 2014-16 Eating & Health Module of the American Time Use SurveyWith data from the 2014–16 Eating & Health Module (EHM) of the American Time Use Survey (ATUS), this report presents national statistics on eating and health patterns for the U.S. adult population as a whole, and for a wide variety of important demographic subgroups. This report also examines whether and how certain behaviors have changed over time, using data from the 2006–08 EHM (October 2018).
Americans Spend an Average of 37 Minutes a Day Preparing and Serving Food and Cleaning Up
This article examines the time spent on meal preparation by various groups, and includes a comparison between those who purchased fast food and those who did not (Amber Waves, November 2016).
Americans' Eating Patterns and Time Spent on Food: The 2014 Eating & Health Module DataThis report uses data from the 2014 USDA Economic Research Service (ERS) Eating & Health Module of the American Time Use Survey to describe Americans’ eating and other food-related time-use patterns, including grocery shopping and meal preparation (July 2016).
The Role of Time in Fast-Food Purchasing Behavior in the United StatesThis study examines the effects of time-use behaviors on fast-food purchases in the United States. Findings reveal that those who purchase fast food do so to save time, and the share of the population that purchased fast food on a given day stayed fairly constant during and after the 2007–09 recession (November 2014).
Nonresponse Bias Analysis of Body Mass Index Data in the Eating and Health ModuleFindings showed that any nonresponse bias associated with height and weight data appears small and would not affect future analyses of correlations between Body Mass Index (BMI) and time use (August 2012).
Investigating the Time Use Patterns of Obese Americans
This article examines time spent on various activities by individuals in different body mass index (BMI) groups. Across all BMI groups, those who were obese over the 2006-08 period spent the longest amount of time watching TV, and the shortest amount of time engaged in sports and exercise (Amber Waves, June 2012).
How Much Time Do Americans Spend on Food?This report uses data from the 2006–08 USDA Economic Research Service (ERS) Eating & Health Module of the American Time Use Survey to present an overview of Americans' eating and other food-related time use patterns (November 2011).
Shopping for, Preparing, and Eating Food: Where Does the Time Go?
This article describes time use patterns of SNAP participants and low-income nonparticipants (Amber Waves, December 2009).
Working Parents Outsource Children's Meals
This article describes time use patterns of employed persons and whether children in the household obtain meals at school (Amber Waves, March 2009).
How Much Time Do Americans Spend Eating?
This article describes time Americans spent on eating and drinking beverages in 2006 (Amber Waves, June 2008).
Who Has Time To Cook? How Family Resources Influence Food PreparationAnalysis of how family resources affect food preparation time (May 2007).
How Much Time Do Americans Spend Preparing and Eating Food?
This article describes time Americans spent on grocery shopping, food preparation, and eating in 2003 (Amber Waves, November 2005).
Resource links
Bureau of Labor Statistics American Time Use Survey (ATUS)—Provides access to the ATUS data, survey methodology, and estimates of Americans' time spent on various activities.
Metabolic Equivalents for Activities in the American Time Use Survey—Bridge between the Compendium of Physical Activities and the ATUS Activity Lexicon.
American Time Use Survey Extract Builder—Data extractor that can make the ATUS microdata easier to use.
University of Maryland Population Research Center Time Use Events—The Center sponsors and hosts numerous events to support researchers working in population science.
University of Oxford Centre for Time Use Research—Provides access to harmonized multinational time use data. The Centre for Time Use Research also provides access to the American Heritage Time Use Study, a database of five decades of time use/diary samples.
International Association for Time Use Research—International organization devoted to time-use data collection and research. The organization publishes the electronic International Journal of Time Use Research.
Agricultural Resource Management Survey (ARMS)—USDA’s Economic Research Service (ERS) has collected time use data of farm operators.
Journal articles
Disclaimer: Many of the authors of the following studies were not affiliated with ERS at the time of publication; this information is provided for your convenience and does not constitute an endorsement.
Lee, J.Y., Nayga, R.M. Jr., Jo, Y., & Restrepo, B.J. (2022). Time use and eating patterns of SNAP participants over the benefit month. Food Policy 106:102186.
Rhodes, M., & Kuchler, F. (2021). Determinants of weekly raw milk use by at-home meal preparers in the USA: Evidence from the 2014–16 American Time Use Survey – Eating and Health Module. Public Health Nutrition 24(3):487–498.
Gough, M., et al. (2019). The role of time use behaviors in the risk of obesity among low-income mothers. Women's Health Issues 29(1): 23–30.
Sharif, M.Z., Alcalá, H.E., Albert, S.L., & Fischer, H. (2017). Deconstructing family meals: Do family structure, gender and employment status influence the odds of having a family meal? Appetite 114: 187–93.
Tajeu, G.S. & Sen, B. (2017). "New pathways from short sleep to obesity? Associations between short sleep and "secondary" eating and drinking behavior. American Journal of Health Promotion 31(3): 181–88.
Hamrick, K. S. & Andrews, M. (2016). SNAP participants' eating patterns over the benefit month: A time use perspective," PLoS One 11(7): e0158422.
Jarosz, E. (2016). Food for thought: A comparative analysis of eating behavior in the United States, Poland, and Armenia. Food, Culture & Society 19(4): 655–79.
Patel, V. C., Spaeth, A.M., & Basner, M. (2016). Relationships between time use and obesity in a representative sample of Americans. Obesity (Silver Spring) 24(10): 2164–75.
Wojan, T. R. & Hamrick, K.S. (2015). Can walking or biking to work really make a difference? Compact development, observed commuter choice and body mass index. PLoS One 10(7): e0130903.
Shinall, J. B. (2015). Occupational characteristics and the obesity wage penalty. Vanderbilt Law and Economics Research Paper (16–12): 16–23.
Mazumder, B. & Seeskin, Z. (2015). "Breakfast skipping, extreme commutes, and the sex composition at birth. Biodemography Social Biology 61(2): 187–208, 2015.
Courtemanche, C., Pinkston J.C., & Stewart, J. (2015). Adjusting body mass for measurement error with invalid validation data. Economics & Human Biology 19: 275–93.
Sliwa, S. A., Must, A., Perea, F., & Economos, C. (2014). Maternal employment, acculturation, and time spent in food-related behaviors among Hispanic mothers in the United States: Evidence from the American Time Use Survey. Appetite, 87(1): 10–19, 2014.
Tudor-Locke, C., Schuna Jr, J. M., Katzmarzyk, P.T., Liu, W., Hamrick, K.S., & Johnson, W.D. (2014). Body mass index: Accounting for full time sedentary occupation and 24-Hour self-reported time use," PLOS One 9(10): e109051.
Senia, M., Jensen, H., & Zhylyevskyy, O. (2014). Time in eating and food preparation among single adults. Review of Economics of the Household: 1–34.
Abramowitz, J. (2014). The connection between working hours and body mass index in the United States: a time use analysis. Review of Economics of the Household.
Oh, A., Erinosho, T., Dunton, G., Perna, F. M., & Berrigan, D. (2014). Cross-sectional examination of physical and social contexts of episodes of eating and drinking in a national sample of U.S. adults," Public Health Nutrition: 1–9.
Yang, J. & French, S. (2013). The travel–obesity connection: Discerning the impacts of commuting trips with the perspective of individual energy expenditure and time use. Environment and Planning B: Planning and Design 40(4): 617–629.
Kang, H. (2013). Social integration: How is it related to self-rated health? Advances in Aging Research 02(01): 10–20.
Hamermesh, D. S. (2012). Tall or taller, pretty or prettier: is discrimination absolute or relative? IZA Journal of Labor Economics 1(2).
Kalenkoski, C. M. & Hamrick, K.S. (2012). How does time poverty affect behavior? A look at eating and physical activity. Applied Economic Perspectives and Policy 35(1): 89–105.
Podor, M. & Halliday, T.J. (2012). Health status and the allocation of time. Health Economics 21(5): 514–527, 2012.
Zick, C. D., Stevens, R.B., and & Bryant, W.K. (2011). Time use choices and healthy body weight: A multivariate analysis of data from the American Time Use Survey. International Journal of Behavioral Nutrition and Physical Activity 8(84).
Davis, G. C. & W. You, W. (2011). Not enough money or not enough time to satisfy the Thrifty Food Plan? A cost difference approach for estimating a money–time threshold. Food Policy 36(2): 101–107.
Spears, D. (2011). Economic decision-making in poverty depletes behavioral control. The B.E. Journal of Economic Analysis & Policy 11(1): Article 72.
Roy, M., Millimet, D.L., & Tchernis, R. (2011). Federal nutrition programs and childhood obesity: Inside the black box. Review of Economics of the Household 10(1): 1–38.
Jonas, D. E., Ibuka, Y., & Russell, L.B. (2011). How much time do adults spend on health-related self-care? Results from the American Time Use Survey. The Journal of the American Board of Family Medicine 24(4): 380–390.
Kolodinsky, J. M. & Goldstein, A.B. (2011). Time use and food pattern influences on obesity. Obesity:1–9.
Zick, C. D. & Stevens, R.B. (2011). Time spent eating and its implications for Americans' energy balance. Social Indicators Research 101(2): 267–273.
Reifschneider, M., Hamrick, K., & Lacey, J. (2011). Exercise, eating patterns, and obesity: Evidence from the ATUS and its eating & health module. Social Indicators Research 101(2):215–219.
Hamermesh, D. S. (2010). Incentives, time use and BMI: The roles of eating, grazing and goods. Economics & Human Biology 8(1):2–15, 2010.
Davis, G. C. & You, W. (2010). The time cost of food at home: general and food stamp participant profiles.” Applied Economics 42(20): 2537–2552.
Dunton, G. F., & Berrigan, D., et al. (2009). Joint associations of physical activity and sedentary behaviors with body mass index: Results from a time use survey of U.S. adults.” International Journal of Obesity 33(12):1427–1436.
Zick, C. D. & Stevens, R.B. (2009) Trends in Americans’ food-related time use: 1975–2006. Public Health Nutrition 13(07):1064–1072.
Russell, L.B., Ibuka, Y. & Carr, D. (2008). How much time do patients spend on outpatient visits? The Patient: Patient-Centered Outcome Research 1, 211–222.
Hamermesh, D. S. (2007). Time to eat: Household production under increasing income inequality. American Journal of Agricultural Economics 89(4): 852–863.