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Table 1.  

Characteristic No. Level of activity,b no. (%)
Consistently inactive Inconsistently active Consistently active P valuec
Entire sample of unique patients 8,741 1,578 (18.1) 4,218 (48.3) 2,945 (33.7)
Patients with a single visit 5,745 1,257 (21.9) 2,171 (37.8) 2,317 (40.3)
Patients with ≥2 visits 2,996 321 (10.7) 2,047 (68.3) 628 (21.0)
Female 4,587 927 (20.2) 2,312 (50.4) 1,348 (29.4) <.001
Male 4,154 651 (15.7) 1,906 (45.9) 1,597 (38.4)
Age group at first visit, y
20–34 3,186 463 (14.5) 1,534 (48.1) 1,189 (37.3) <.001
35–44 1,585 260 (16.4) 788 (49.7) 537 (33.9)
45–54 1,325 247 (18.6) 650 (49.1) 428 (32.3)
55–64 1,206 251 (20.8) 577 (47.8) 378 (31.3)
65–74 947 198 (20.9) 455 (48.0) 294 (31.0)
≥75 492 159 (32.3) 214 (43.5) 119 (24.2)
BMI at first visitd
Underweight (<18.5) 146 35 (24.0) 64 (43.8) 47 (32.2) <.001
Normal (18.5–24.9) 3,073 486 (15.8) 1,434 (46.7) 1,153 (37.5)
Overweight (25.0–29.9) 2,784 455 (16.3) 1,312 (47.1) 1,017 (36.5)
Obese (≥30.0) 2,535 555 (21.9) 1,319 (52.0) 661 (26.1)
Asian 1,146 230 (20.1) 588 (51.3) 328 (28.6) <.001
Black or African American 569 156 (27.4) 274 (48.2) 139 (24.4)
Othere 227 54 (23.8) 112 (49.3) 61 (26.9)
Unknown/declined to report 1,560 250 (16.0) 712 (45.6) 598 (38.3)
White 5,239 888 (16.9) 2,532 (48.3) 1,819 (34.7)
Not Hispanic or Latino 6,584 1,220 (18.5) 3,243 (49.3) 2,121 (32.2) <.001
Hispanic or Latino 409 94 (23.0) 192 (46.9) 123 (30.1)
Unknown/declined to report 1,748 264 (15.1) 783 (44.8) 701 (40.1)
Modified Charlson Comorbidity Index scoref
0 6,929 1,137 (16.4) 3,290 (47.5) 2,502 (36.1) <.001
1 902 193 (21.4) 487 (54.0) 222 (24.6)
2 483 115 (23.8) 232 (48.0) 136 (28.2)
3 161 50 (31.1) 76 (47.2) 35 (21.7)
4 83 20 (24.1) 47 (56.6) 16 (19.3)
≥5 183 63 (34.4) 86 (47.0) 34 (18.6)

Table. Distribution of Physical Activity Vital Sign (PAVS) Categories in a Sample of Patients in a Family Medicine Clinic, by Demographic Characteristics and Comorbidities, United States, 2018–2020a

Abbreviations: —, does not apply; BMI, body mass index.


a Percentages across row may not add to 100 because of rounding.

b Patients reporting 0 minutes per week of physical activity consistently in all clinic visits were classified as consistently inactive; patients reporting ≥150 minutes per week of physical activity in all visits were classified as consistently active; patients who reported physical activity rates that did not fit the above 2 categories consistently for all visits were classified as inconsistently active (<150 min/wk).

c χ2 test for independence of variables.

d 203 (2.3%) patients were missing BMI values; percentages are based on the number of patients who had data on BMI. BMI calculated as weight in kg divided by height in meters squared.

e “Other” includes American Indian/Alaska Native, Native Hawaiian/Other Pacific Islander, and multiple races.

f Score was calculated by using the International Classification of Diseases, Tenth Revision, Clinical Modification codes [13] for 17 health conditions from the 3 years before the first clinic visit with PAVS recorded. A higher Charlson Comorbidity Index score is generally associated with increased age, comorbidities, and all-cause mortality [11–13].


Implementation of a Physical Activity Vital Sign in Primary Care: Associations Between Physical Activity, Demographic Characteristics, and Chronic Disease Burden

  • Authors: Cindy Y. Lin, MD; Nicole L. Gentile, MD, PhD; Levi Bale, BEd; Melanie Rice, MA; E. Sally Lee, PhD; Lisa S. Ray, BA; Marcia A. Ciol, PhD
  • CME / ABIM MOC Released: 6/23/2022
  • Valid for credit through: 6/23/2023
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  • Credits Available

    Physicians - maximum of 1.00 AMA PRA Category 1 Credit(s)™

    ABIM Diplomates - maximum of 1.00 ABIM MOC points

    You Are Eligible For

    • Letter of Completion
    • ABIM MOC points

Target Audience and Goal Statement

This activity is intended for primary care physicians, endocrinologists, and other physicians who advise patients about physical activity.

The goal of this activity is for learners to be better able to understand the relationship between physical activity and chronic disease burden and how implementation of a physical vital sign can be used for screening.

Upon completion of this activity, participants will:

  • Distinguish the percentage of US adults who are not physically active from the current study by Lin and colleagues
  • Describe limitations of the Physical Activity Vital Sign (PAVS) assessment as a screening tool
  • Analyze variables associated with higher rates of physical inactivity


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  • Cindy Y. Lin, MD

    University of Washington
    Department of Rehabilitation Medicine
    The Sports Institute at the University of Washington
    Seattle, Washington

  • Nicole L. Gentile, MD, PhD

    University of Washington
    Department of Family Medicine
    Seattle, Washington

  • Levi Bale, BEd

    University of Washington School of Medicine
    Seattle, Washington

  • Melanie Rice, MA

    The Sports Institute at the University of Washington
    Seattle, Washington

  • E. Sally Lee, PhD

    opulation Health Analytics
    University of Washington Medicine
    Seattle, Washington

  • Lisa S. Ray, BA

    Information Technology Services
    University of Washington Medicine
    Seattle, Washington

  • Marcia A. Ciol, PhD

    University of Washington
    Department of Rehabilitation Medicine
    Seattle, Washington

CME Author

  • Charles P. Vega, MD

    Health Sciences Clinical Professor of Family Medicine
    University of California, Irvine School of Medicine
    Irvine, California


    Charles P. Vega, MD, has the following relevant financial relationships:
    Advisor or consultant for: GlaxoSmithKline; Johnson & Johnson Pharmaceutical Research & Development, L.L.C.


  • Ellen Taratus, MS

    Senior Editor
    Preventing Chronic Disease
    Atlanta, GA

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    Associate Director, Accreditation and Compliance
    Medscape, LLC


    Leigh A. Schmidt, MSN, RN, CMSRN, CNE, CHCP, has no relevant financial relationships.

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Implementation of a Physical Activity Vital Sign in Primary Care: Associations Between Physical Activity, Demographic Characteristics, and Chronic Disease Burden

Authors: Cindy Y. Lin, MD; Nicole L. Gentile, MD, PhD; Levi Bale, BEd; Melanie Rice, MA; E. Sally Lee, PhD; Lisa S. Ray, BA; Marcia A. Ciol, PhDFaculty and Disclosures

CME / ABIM MOC Released: 6/23/2022

Valid for credit through: 6/23/2023




Physical activity is important to prevent and manage multiple chronic medical conditions. The objective of this study was to describe the implementation of a physical activity vital sign (PAVS) in a primary care setting and examine the association between physical activity with demographic characteristics and chronic disease burden.


We extracted data from the electronic medical records of patients who had visits from July 2018 through January 2020 in a primary care clinic in which PAVS was implemented as part of the intake process. Data collected included self-reported physical activity, age, sex, body mass index, race, ethnicity, and a modified Charlson Comorbidity Index score indicating chronic disease burden. We classified PAVS into 3 categories of time spent in moderate to strenuous intensity physical activity: consistently inactive (0 min/wk), inconsistently active (<150 min/wk), and consistently active (≥150 min/wk). We used χ2 tests of independence to test for association between PAVS categories and all other variables.


During the study period, 13,704 visits, corresponding to 8,741 unique adult patients, had PAVS recorded. Overall, 18.1% of patients reported being consistently inactive, 48.3% inconsistently active, and 33.7% consistently active. All assessed demographic and clinical covariates were associated with PAVS classification (all P < .001). Larger percentages of consistent inactivity were reported for female, older, and underweight or obese patients. Larger percentages of consistent activity were reported for male, younger, and normal weight or overweight patients.


Using PAVS as a screening tool in primary care enables physicians to understand the physical activity status of their patients and can be useful in identifying inactive patients who may benefit from physical activity counseling.