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How people connect habits with long-term health

Overview

This topic starts with how adults describe their health, then looks at what they believe shapes long-term well-being.


Personal health behaviors lead the list of perceived health drivers, while physical activity and clinician advice show how prevention enters ordinary routines.

Most adults describe their health positively

A 79.1% share rated their physical health as good, very good, or excellent.

Mental health ratings were similar, with 77.1% choosing good, very good, or excellent.

Stacked breakdown

54.7% say personal health behaviors have the greatest impact on well-being.

Which of the following do you believe has the greatest impact on your overall health and well-being?

Personal health behaviors (e.g. diet, exercise, sleep, substance use, stress management)
54.7%
Access to healthcare
10.9%
Financial stability
12.9%
Social relationships and support
10.4%
Physical environment (e.g., housing, neighborhood safety, etc.)
6.3%
Work or job conditions
2.6%
Other
2.2%

2026 · base n 1,000 · +/- 3.2%

Personal behaviors lead the health drivers

A 54.7% majority selected personal health behaviors, including diet, exercise, sleep, substance use, and stress management, as the greatest influence on overall health and well-being.

That response puts habits ahead of financial stability, access to healthcare, social support, physical environment, and work conditions.

Stacked breakdown

60.4% say they already engage in regular physical activity.

Do you do engage in regular physical activity as described above?

No, and I do not intend to start regular physical activity in the next 6 months.
10.5%
No, but I intend to start regular physical activity in the next 6 months.
12.9%
No, but I intend to start regular physical activity in the next 30 days.
16.1%
Yes, I have been, but for less than 6 months.
17.2%
Yes, I have been for more than 6 months.
43.2%

2026 · base n 1,000 · +/- 3.2%

Additional supporting data from this section.

Stacked breakdown

23.7% were told to increase muscle-strengthening exercise.

To lower your risk for certain diseases, during the last 12 months have you ever been told by a doctor or health professional to increase your muscle-strengthening exercise (e.g., resistance training, body weight exercise)?

Yes
23.7%
No
71.2%
I don't know
5.0%

2026 · base n 1,000 · +/- 3.2%

Exercise shows the prevention gap

A 60.4% share said they already engage in regular physical activity, while others said they intend to start or do not plan to start soon.

A 23.7% share said a doctor or health professional told them in the past year to increase muscle-strengthening exercise to lower disease risk.

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

[6]

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-1-1

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.