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What food and weight reveal about daily health

Source reportMethodology

Overview

Food and weight questions show a practical daily-health story rather than a single diet or body-weight readout.

Adults place themselves around the middle and positive end of healthy eating, while food noise, weight goals, GLP-1 use, food insecurity, and tracking tools add context.

Stacked breakdown

45.0% rate their healthy eating at the midpoint of the scale.

How would you rate your healthy eating behaviors on a scale of 1 - 5, with 1 being poor and 5 being great?

1- Poor
4.6%
2
12.7%
3
45.0%
4
30.3%
5- Great
7.4%

2026 · base n 1,000 · +/- 3.2%

1

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Healthy eating ratings cluster in the middle

Healthy eating ratings clustered around the middle and positive end of the scale, with 45.0% choosing the midpoint and 30.3% choosing the next-highest rating.

Support from others also appears in the food-change context, with 50.7% agreeing or strongly agreeing that support plays an important role.

Stacked breakdown

50.9% experience food noise at least sometimes.

“Food Noise” is a term popularized in media and social media to describe things like “constantly thinking about food, even when not hungry,” or feeling like one’s life “revolves around food.” How often do you experience “Food Noise”?

Never
17.0%
Rarely
32.1%
Sometimes
32.9%
Often
11.9%
Always
6.1%

2026 · base n 1,000 · +/- 3.2%

1

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Food noise and weight goals broaden the picture

A 50.9% share reported experiencing food noise at least sometimes.

Weight goals and beliefs about genetic influence add a broader body-weight context, while 82.8% said they had not taken a GLP-1 medication in the past 12 months.

Stacked breakdown

31.7% say image-based food tracking is not acceptable at all.

How many times per day would it be acceptable to track your food and drink through images?

Zero, not acceptable at all
31.7%
Once per day
15.9%
2 to 3 times a day
31.1%
4 to 5 times a day
5.2%
Every time I eat or drink
16.1%

2026 · base n 1,000 · +/- 3.3%

2

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Tools and food pressure add context

Food insecurity, embarrassment about food, interest in a mobile app for food choices, and image-based tracking preferences all add context around daily food decisions.

Methodology

Full methodology
Mode
Verasight panel recruited via random address-based sampling, random person-to-person text messaging, and dynamic online targeting
Population
US adults age 18+
Field dates
2026-05-01 → 2026-05-04
Base (unweighted)
1,000
Margin of error
+/- 3.2%
Module
1
Sponsor
Verasight
Weight variable
weight
Weighting targets
age, race/ethnicity, sex, income, education, region, metropolitan status

Sources

[9]

Citation

SBM Omnibus Survey #2026-049, fielded May 1-4, 2026, N=1,000 US adults age 18+, +/- 3.2%.

https://reports.verasight.io/reports/sbm-2026#q-1-14

Verasight survey methodology

How Verasight conducts surveys.

This page describes the Verasight general survey contract, separate from how the Data Library packages it. Each wave's specific field dates, sample sizes, and module breakdown are listed in that wave's report.

Mode
Verasight panel recruited via random address-based sampling, random person-to-person text messaging, and dynamic online targeting.
Population
US adults age 18+.
Sample design
Surveys are run as omnibus or single-topic waves. Omnibus waves are split into modules with their own respondent set, typically around one thousand respondents per module.
Field window
Each wave specifies its own field dates. Most omnibus waves field across roughly two weeks.
Weighting
Per-module weighting to CPS targets including age, race and ethnicity, sex, income, education, region, and metropolitan status.
Partisanship benchmark
Pew Research Center's NPORS benchmarking surveys, three-year running average.
Vote benchmark
2024 presidential vote population benchmarks.
Margin of error
Typically about plus or minus 3.4 to 3.6 percent per module at standard module sizes. Question-level MoE is recomputed when a base shrinks materially below the module baseline.
Reporting
Every wave is published as a standalone report at verasight.io/reports with full instrument and methodology.
Transparency
Verasight is a member of the American Association for Public Opinion Research Transparency Initiative.

Wave-specific methodology, full weighting variable lists, and verbatim instrument text live in each report at verasight.io/reports.