Understanding and Utilizing Physical Activity Data

1. Understanding and Utilizing Physical Activity Data Working Group: Barbara Ainsworth, Alain Bertoni, Hyoju Chung, David Jacobs, Craig Johnson

2. Physical Activity, Exam 1 MESA • Survey asked regarding specific types of activity, such as walking, sports, yard work, etc, leisure activities, and occupational activities • Designed to capture light, moderate, and vigorous activity (to estimate METs) • Allows for total, light, moderate, vigorous Minutes/Wk or MET-Min/wk, OR by type of activity • Additional question asked about typical walking pace

4. Total reported PA Activity averaged 12.6 hours/day

7. Physical Activity by Site

8. Moderate Activity averaged 3.3 hours/day

9. Vigorous Activity was Rare • Averaged 0.3 hours/week; 68.4% reported 0 minutes

10. Which PA Measure to Utilize I? • Early work with summary measures-Total PA, Moderate PA, Vigorous PA- did not yield expected (or consistent) results • Strongly related to age, gender, race • Mostly not related to physiologic variables • General issues with the survey • Validated in Black & White women, English speaking • Not men, or Hispanic or Chinese populations • Specific issues with MESA’s results • Over reporting (totals >18-24 hrs/day) (no sleep!) • Mode of administration influenced reporting

11. Physical Activity Questionnaire Administration Issues • Mode of administration differed across sites • Interviewer admin (31% of exam 1) more common in Chinese, Hispanics, older participants, less educated participants • Interviewer administered on average resulted in fewer reported minutes in nearly all categories • Avg hrs/day self 13.7 vs Int 10.2) • Interviewing increased at 3 sites during exam 3

12. Which PA Measure to Utilize II? • Validity of survey tested with BMI and HDL, as both should be related to vigorous activity and plausible that moderate PA would also have a beneficial impact • Considered each type of activities • Constructed different groupings • Vigorous non occupational activities • Moderate+vigorous activities • TV activities • Intentional exercise (walk for exercise, sports, conditioning) • Walking (2 types) • Evaluated Walking Pace variable • How to deal with mode of administration • Adjust vs stratify • Final: adjust and use interaction term (with site)

13. Analyses • In the next two slides, we estimated the beta-coefficient for 210 MET/Minutes per week for each type of PA in models with either BMI or HDL as dependent variable, and adjusted for age, gender, race, clinic, mode of questionnaire administration, and interaction between interview type and clinic. • In the graphs of groupings of variables, categories were created (somewhat arbitrarily) and same variables as above in models (except for stratification factor)

14. BMI and 30-60 Min/day at 7/3.5 METS

15. HDL and 30-60 Min/day at 7/3.5 METS

16. Vigorous activity and BMI

17. Non-Occupational Vigorous activity and BMI

18. Moderate+Vigorous PA

19. TV watching (Light PA)

20. TV and HDL, BMI

21. Intentional Exercise • Walking for exercise +Sports+ Conditioning • Exclude walking to get places • Created categories based on 500 MET-min/wk (this is 100 min * 5 MET-intensity)

22. Intentional Exercise and BMI

23. Intentional Exercise and HDL

24. Walking Pace Variable • “When you walk outside of your home, what is your usual walking pace? • Graph adjusted for age, gender, race, site, admin type

25. Walking pace and BMI, by gender

26. Walking Pace and BMI, by Race

28. Placed intentional exercise variable and TV watching (both categories) simultaneously in model with BMI as independent variable, plus age, gender, race, clinic, education, interview admin, and interaction term between site and Interview Admin Both sets of variables highly significant (p<0.001); R squared 0.169 (W/O TV/Ex: R squared 0.148) Highest exercise group: -2 kg/m2; highest TV group +1.6 kg/m2 (both p<0.001) Similar results seen for HDL Highest exercise: +2.6 mg/dl; highest TV -2.7 mg/dl PA variables in analyses

29. Age, Gender, Race, Education, Site*self-admin adjusted Body Mass Index by TV and Exercise Category

30. Exam 2

31. Exam3

32. Conclusions I • The MESA PA questionnaire is measuring a variety of activities typically done by the participants and may reflect lifestyle as well as actual physical activity • For analyses, rather than summary measures, consider using component activities • Sedentary: TV watching • Exercise: Mod+vigorous, non-occupational vigorous, Intentional exercise are potentially useful • Ability?: Walking Pace • Still considering how to combine walking pace with walking duration (perhaps adjusting METS)

33. Conclusions II • We have utilized categories with somewhat arbitrary cut points, as most of this data is not normally distributed • Regardless of variable chosen, need to adjust for age, and suggest race, gender, site, PA administration type, and probably admin*site interaction • Expect that similar adjustments will be necessary for exam2/exam3 data, but not yet evaluated • Can now progress to see if PA associated with other measures • Subclinical atherosclerosis • Change in risk factors (BMI, lipids) • Outcomes