1: Se considera que un alto porcentaje de estudiantes tienen acceso a computadores

Self-reported Fruit and Vegetable Consumption:

Outcome measures for Aims 2 and 3 of this study included self-reported fruit and vegetable consumption and objectively measured physical activity. The Dietary Risk Assessment (DRA) was used in WISEWOMAN to measure diet and to provide a basis for counseling for healthful dietary changes. It has been previously validated;88 however, the DRA has been modified over time to reflect new recommendations regarding components of a heart healthy diet. (Appendix F is a manuscript describing validation of the modified DRA.) Baseline self-reported fruit and vegetable consumption was measured by responses to four items on the DRA, which were:

• “How many servings a day do you have of fruit?”

• “How many servings a day do you have of juice?”

• “In an average week, how many servings of tossed salad do you eat?”

• “How many servings a day do you have of vegetables of any kind?”

Responses to these items were summed to create a fruit and vegetable index (higher score indicating less consumption of fruits and vegetables.). This index was found to have significant correlations with an estimate of fruit and vegetable consumption from a longer, previously validated food frequency questionnaire.89 The fruit and vegetable index also had significant associations with biochemical markers of fruit and vegetable intake, even after adjusting for potential confounders. (Tables 4.5. and 4.6)

Table 4.4. Pearson’s Correlation Coefficients (r) between Dietary Risk Assessment (DRA) Fruit and Vegetable Index and Measured Plasma Carotenoids

DRA index Plasma Carotenoid r (n = 200) p-value Fruit/vegetable Carotenoid index (Sum of zeaxanthin, S-

carotene, U-carotene, cryptoxanthin)

-0.30 < 0.0001 Fruit/vegetable Zeaxanthin -0.15 0.03 Fruit/vegetable S-carotene -0.23 0.0009 Fruit/vegetable U-carotene -0.31 < 0.0001 Fruit Cryptoxanthin -0.27 < 0.0001 Vegetable Zeaxanthin -0.10 0.16 Vegetable S-carotene -0.33 < 0.0001 Vegetable U-carotene -0.35 < 0.0001

Table 4.5. Association between the Dietary Risk Assessment (DRA) Fruit and Vegetable Index and Natural Log of Plasma Carotenoid Index

1

Participants with S-tocopherol values W2 mg/dl and/or U-carotene values W50 ug/dl, values consistent with supplement use, were excluded.

Model1 _{Covariates Standardized}

parameter estimate p-value Adjusted R2 1, n = 200 -- -0.25 0.0004 0.06 2, non-smokers, n = 145 -- -0.20 0.01 0.03 smokers, n = 55 -- -0.36 0.006 0.12 3, non-smokers, n = 145 BMI -0.19 0.02 0.03 smokers, n = 54 BMI -0.40 0.003 0.13 4, non-smokers, n = 140 BMI, HDL, LDL, VLDL -0.18 0.04 0.02 smokers, n = 53 BMI, HDL, LDL, VLDL -0.41 0.005 0.15 5, non-smokers, n = 140 BMI, HDL, LDL, VLDL, age -0.22 0.01 0.07 smokers, n = 53 BMI, HDL, LDL, VLDL, age -0.45 0.003 0.15

Objectively Measured Physical Activity:

The dependent variable for Aim 3 of this project was moderate to vigorous physical activity, measured using the ActiGraph model 7164 accelerometer, formerly known as CSA (ActiGraph LLC, Fort Walton Beach, FL). The ActiGraph is a valid and reliable measure of moderate physical activity in the field.90;91 One study found a statistically significant

correlation between accelerometer data and measured VO2for lifestyle activities (mean r = 0.55).92 There was 68.4% agreement between accelerometer and activity diary classifications of subjects into low, moderate, or highly active groups.90 The CSA/MTI had the least

variability and highest reliability in a study of 4 activity monitors.93 Accelerometer data are not influenced by social desirability or other biases inherent to self-report and are thought to be more precise than self-reported activity.94 The accelerometer measures uniaxial

acceleration using a piezoelectric plate; signals (counts) generated from acceleration are summed and stored over a user-specified time interval (epoch).90 In this study, one-minute epochs were used as the time interval, and the instrument collected 22 consecutive days of data.

Several accelerometer calibration studies have established cutpoints for accelerometer counts to determine levels of activity (Table 4.7).94 The general method for these studies is to compare activity counts recorded using the accelerometer and measured oxygen consumption during specific activities, such as walking or running.94 The population studied and the choice of activities used in these studies accounts for a substantial amount of variability in the cutpoints generated to distinguish activity intensity levels. For instance, Freedson et al.95 found moderate-intensity activity (metabolic equivalents between 3 and 6) fell between 1952

represented moderate-intensity activity. Therefore, it is important to choose cutpoints derived based on activities of interest conducted in a similar population to the one under study.

Table 4.6. Cutpoint Calibration Studies

Reference Population Activity Cutpoints

Freedson et al. 199895

25 males, 25 females; Females’ average age was 22.9 years; average BMI = 22.8

Walking and jogging on a treadmill Light: 706 -1951 Moderate: 1952 – 5724 Vigorous: 5725 – 9498 Very Vigorous: >/= 9498 Yngve et al. 200397 18 men, 16 women; Females’ average age was 43 years; average BMI was 22.6

Field study of walking and jogging on a track

Accelerometer placed on the hip, activity done on a track Moderate: 2743 – 6403 Vigorous: 6403 + Swartz et al.

200096

31 men, 39 women; Females’ average age was 42 years; average BMI was 26

28 self-selected activities (yard work, walking carrying items, housework, family care, conditioning, tennis, golf)

Moderate: 574 – 4944 Vigorous: >/= 4945 Very Vigorous: 9317 + Hendelman et al. 200098 10 males, 15 females; Average age = 40.8 years; average BMI of all participants was 24.4

10 activities, self-selected (washing, dusting, lawn mowing, planting shrubs) Walking, self-selected Self-selected activities Moderate: 191 – 7524 Vigorous: 7525 + Walking Moderate: 2191 – 6892 Vigorous: 6893 + Nichols et al. 200091

30 adults Self-selected walking and running on a track

Moderate: (4 – 6.9 MET): 3285-5676

Vigorous: (>/= 7 MET): 5677 +

WISEWOMAN participants were instructed to wear the accelerometer for 7 days and then mailed it to the research office in postage paid box, at baseline, 6-, and 12-months. The accelerometer data (counts per epoch) were uploaded from the device and data were reduced using the ActiProcess program (Catellier, 2004). Valid days of data were determined by examining and eliminating epochs that were contained within strings of 20 or more consecutive zeros, then summing the remaining epochs and dividing by 60. The ad hoc minimum wearing criteria was 6 valid hours to be defined as a day. Data were considered valid only if the accelerometer was worn a minimum of 4 days. At 12-months, 184/236 (78%) women had valid accelerometer data, with averages of 11.2 hours per day worn and 5.7 days worn. Average minutes of moderate to vigorous physical activity were calculated by dividing the sum of total minutes of activity above 574 counts (using Swartz et al.96 count cutpoints) by the days worn. Swartz et al.96 cutpoints were used was used because

participants in that study were the most similar to the participants in the current study in terms of BMI and age. Additionally, the Swartz cutpoints were established using activities that are likely to be done by WISEWOMAN participants.

While accelerometers are valid and reliable measure of physical activity, there are several limitations to the use of accelerometers and the data collected. Accelerometers do not provide data on physical activities that do not generate vertical acceleration, such as

bicycling. They may induce activity in participants for the first few days of wearing due to heightened sensitivity to monitoring; thus, multiple days of wearing are recommended. Obtaining valid accelerometer data depends on participants complying with accelerometer wearing instructions; individual characteristics may make some participants more likely to

activity-specific cutpoints for translating the magnitude of counts into minutes of moderate and vigorous-intensity physical activity.

Participant adherence is another limitation of accelerometer-based data collection. It is recommended that the accelerometer is worn between 3 and 5 days to reliably estimate physical activity.99 Differential wearing time (e.g., between overweight and normal weight individuals) could introduce bias. To improve adherence, WISEWOMAN participants were given one-on-one instructions about wearing the accelerometer, a log sheet to record days and times the accelerometer was worn, and a postage paid box to mail the accelerometer back to the research office. Women were called approximately 8 days after the enrollment visit, to find out how many days the accelerometer was worn, any problems they had, and were given a reminder to mail the device back to the research office.

IV.H. Aim 3 Measures