What Americans Spend on Food: A Full Breakdown
Food is the third-largest household expense. How much goes to groceries vs. restaurants? How does income change food choices? Here's the full picture from 2024 BLS data.
Food Spending Breakdown (2024)
| Food Category | Annual | Monthly |
|---|---|---|
| Food at home | $6,224 | $519 |
| Food away from home | $3,945 | $329 |
Food Spending by Income Level (2024)
| Income Group | Annual Food |
|---|---|
| Lowest 20% | $5,498 |
| Second 20% | $7,400 |
| Middle 20% | $9,097 |
| Fourth 20% | $11,845 |
| Highest 20% | $16,989 |
Key Findings
- Food away from home (dining out) has grown steadily. Post-pandemic, restaurant and delivery spending has increased for all income groups, especially higher-income households.
- Food consumes a higher share of lower-income budgets. Even though lower-income households spend less in dollars, food represents a larger portion of their total expenditures.
- Regional differences are notable. The Northeast has higher food costs than the South, reflecting both grocery prices and restaurant costs.
Explore more: Full Food Category Data · By Income Level · By Region
Source: U.S. Bureau of Labor Statistics, Consumer Expenditure Survey 2024.
Compiled by the " research team.
Understanding the Data
The information presented throughout this guide is informed by publicly available public records published by federal and state government agencies. Our database aggregates and standardizes these records to make them more accessible and easier to interpret for general audiences. When we reference specific statistics or trends, they are drawn directly from these authoritative sources unless explicitly noted otherwise.
It is important to understand the limitations of any large-scale data dataset. Records may contain errors from the original data collection process, some fields may be incomplete for older entries, and classification systems may have changed over time. Our analysis accounts for these factors by clearly labeling data vintage, flagging records with missing critical fields, and noting when temporal comparisons span methodology changes in the source data.
For readers who want to conduct their own research, we recommend going directly to the source whenever possible. federal and state government agencies provides detailed documentation on collection methodology, sampling frames, and known data quality issues. Our goal is not to replace primary sources but to make them more approachable and to highlight patterns that may not be immediately obvious when browsing raw records.
How We Analyze Data Records
Our analytical approach involves several steps designed to surface meaningful insights from large datasets. First, we clean and standardize the raw data, handling variations in naming conventions, date formats, and categorical labels. Then we compute summary statistics, distributions, and comparative benchmarks across relevant dimensions such as geography, time period, and category type.
Key metrics we examine include statistical records, geographic distributions, temporal trends. These indicators provide a multi-dimensional view of each entity in our database, allowing users to understand not just individual records but how they compare to peers, regional averages, and national benchmarks. We believe this contextual approach is far more valuable than presenting raw numbers in isolation.
Food-at-home vs. food-away-from-home: the long-run shift
One of the most-cited findings in BLS Consumer Expenditure Survey commentary is the gradual reallocation of household food dollars from groceries (food at home, "FAH") to restaurants, takeout, and delivery (food away from home, "FAFH"). The pandemic temporarily inverted this trend in 2020-2021, but subsequent years restored the long-run trajectory and pushed FAFH share to historical highs in the upper quartile of income.
| Income quintile | Total food $ (annual, 2024) | Food-at-home share | Food-away share |
|---|---|---|---|
| Lowest 20% | ~$5,250 | ~71% | ~29% |
| Second 20% | ~$6,820 | ~66% | ~34% |
| Middle 20% | ~$8,310 | ~62% | ~38% |
| Fourth 20% | ~$10,440 | ~58% | ~42% |
| Highest 20% | ~$15,300 | ~50% | ~50% |
Approximated from BLS Consumer Expenditure Survey 2024 Table 1101 (quintiles of income before taxes). Exact composition varies by reporting period.
Why food-share matters for budget vulnerability
The food share of total spending is one of the oldest indicators of household economic stress used by economists (originally formalized by Engel's Law in the 19th century). When food consumes more than 15% of total household expenditure, relatively small price shocks — a 10% grocery inflation print, a job loss, an unexpected medical bill — can cascade rapidly into delinquencies elsewhere in the budget. Lower-quintile households in the table above sit close to or above that 15% threshold, which is why food inflation reads in the Consumer Price Index tend to dominate cost-of-living narratives even when overall inflation is moderate.
Limitations and Caveats
Several constraints warrant emphasis when drawing inferences from these figures. Sampling error, nonresponse bias, and imputation procedures each introduce quantifiable uncertainty that propagates through derived statistics. Confidence intervals, where published by the collecting agency, should be consulted before attributing significance to small differences between observations.
The taxonomy used to classify entities, expenditures, or incidents evolves periodically. A category redefinition between consecutive releases can produce apparent discontinuities that reflect classification changes rather than genuine behavioral shifts. longitudinal analyses must verify category stability across the studied interval.
Suppression rules applied to protect confidentiality may eliminate observations from sparsely populated strata. This differential suppression disproportionately affects rural counties, small institutions, and minority subgroups, systematically biasing the observable distribution toward larger, more urbanized populations. Researchers should note that absence of a data point may signify suppression rather than a true zero.
