Comparison of Four "Time in Intensity“ Physical Activity Indices as Predictors of Cardiometabolic Health David A. Rowe1 Minsoo Kang2 Youngdeok Kim2 1University of Strathclyde, Glasgow, Scotland 2Middle Tennessee State University, Murfreesboro, TN Background Recent physical activity (PA) guidelines recognize the greater health benefits of higher intensity PA, but still dichotomize intensity into moderate or vigorous categories[1,2].It is possible using modern technology to measure PA intensity along the continuum from moderate intensity upwards so the need to dichotomize PA intensity is not evident. For PA promotion and research, more sensitive measures of “time in intensity” may provide greater motivation to improve, and increased accuracy in determining the PA-health relationship. Results On average, participants engaged in 28.9 min of PA that was of at least moderate intensity, and 1.4 min of PA that was of vigorous intensity. All PA indices were highly interrelated (r = .94 - .99). The baseline model explained between 1% (BMI) and 13% (HDL-C) of the six health outcomes. As expected in this large sample, all PA variables added significantly (p < .05) to the baseline model in explaining each of the six health outcomes. However, variance explained additional to the baseline model was generally low, ranging from R2 = .004 for mean arterial pressure to R2 = .041 for waist circumference. Adjusted correlations with several of the cardiometabolic health measures were higher for the MET-min points systems, especially MET-MinsNet, in comparison to MinsMVPA. This pattern was evident for R2 and F-change, as well as other indices of fit ( RMSE,  AIC, and  BIC). Similar patterns were evident for the logistic regression, with several indices of fit ( AIC,  BIC,  AUC and Wald 2) showing improved sensitivity for a protective effect from metabolic syndrome for MET-MinsGross and MET-MinsNet compared to MinsMVPA. However, diagnostic accuracy was unimpressive for all four PA indices, with the area under the curve being only 0.67. Table 1 Multiple regression results Health measure  R2adj F-value* BMI: Baseline model 0.0084 MinsMVPA 0.0310 76.37 W-MinsMVPA 0.0335 81.77 MET-MinsGross 0.0356 85.82 MET-MinsNet 0.0364 87.22 HDL-C: 0.1273 0.0164 27.58 0.0175 28.26 0.0182 29.27 0.0185 29.54 Fasting glucose: 0.0776 0.0065 22.33 0.0069 26.79 0.0068 29.00 31.02 Waist circumference 0.0961 0.0363 56.16 0.0388 60.04 0.0403 61.65 0.0408 62.66 Purpose To compare two versions of a MET-min points system to two interpretations of recent guidelines, in relation to cardiometabolic health. Methods NHANES 2003-2004 and 2005-2006 accelerometry data were screened according to previous NHANES protocols[3], and converted into four PA indices: a) minutes in moderate intensity or above (3+ METs; MinsMVPA); b) weighted minutes, where vigorous (6+ METs) minutes were scored double (W-MinsMVPA); c) a MET-min points system (3+ METs) based on gross MET-min (MET-MinsGross); and d) a similar points system based on net MET-min (MET-MinsNet). Participants with at least 1 day, of at least 13 hours of data were included[4,5]. These data processing criteria produced a final sample of N = 2,943. The PA indices were adjusted for age, gender, income and race/ethnicity using multiple regression (Baseline model). They were then regressed in six separate analyses, on six measures of cardiometabolic health: BMI; HDL-C; triglycerides; fasting glucose; mean arterial pressure; and waist circumference. Logistic regression was also used to compare the associations between the four PA indices and the metabolic syndrome[6]. * All p < .001 [triglycerides and mean arterial pressure are not presented] Conclusions It appears that a W-MinsMVPA index incorporating the new PA guidelines (giving double-credit for time in VPA) is more strongly related to cardiometabolic health than measures based on the previous MinsMVPA guideline. Two novel MET-min outcomes also were more strongly related to cardiometabolic health. Although all four measures were weakly related to cardiometabolic health, the MET-min indices could be converted to an activity points system and may hold promise for converting PA guidelines into a simple metric for popular use, incorporating ubiquitous technology such as mobile phones. Table 2 Results of logistic regression models for predicting metabolic syndrome PA index Comparison Odds Ratio (95% CI) MinsMVPA Q1 vs. Q2 0.78 (0.58-1.11) Q1 vs. Q3 0.52 (0.35-0.76)* Q1 vs. Q4 0.25 (0.16-0.38)* W-MinsMVPA 0.73 (0.53-1.01) 0.50 (0.33-0.74)* 0.23 (0.15-0.36)* MET-MinsGross 0.71 (0.52-0.98)* 0.51 (0.34-0.75)* 0.23 (0.15-0.34)* MET-MinsNet 0.72 (0.52-0.98)* 0.51 (0.34-0.76)* 0.22 (0.15-0.33)* Fig 1 Illustration of the four “time in intensity” indices Bout 1 Bout 2 Bout 3 Intensity (METs) 10-minute PA bout Bout MinsMVPA W-MinsMVPA MET-MinsGross MET-MinsNet 1 10 30 20 2 50 40 3 70 60 * p < .05 References Physical Activity Guidelines Advisory Committee. (2008). Physical Activity Guidelines Report, 2008. Washington, DC: U.S. Department of Health and Human Services. O’Donovan G, et al. (2010). The ABC of physical activity for health: A consensus statement from the British Association of Sport and Exercise Sciences. Journal of Sports Science, 28, 573-91. Troiano, R.P., et al. (2008). Physical activity in the United States measured by accelerometer. Medicine & Science in Sports & Exercise, 40, 181-188. Herrmann, S.D., et al. (2012). Impact of accelerometer wear time on physical activity data: a NHANES semisimulation data approach. British Journal of Sports Medicine, Epub ahead of print. Tudor-Locke, C., et al. (2010). Accelerometer profiles of physical activity and inactivity in normal weight, overweight, and obese U.S. men and women. International Journal of Behavioral Nutrition and Physical Activity, 7, 60. Grundy, S. M., et al. (2004). Definition of metabolic syndrome: Report of the National Heart, Lung, and Blood Institute/American Heart Association conference on scientific issues related to definition. Circulation, 109, 433-438. Contact details: david.rowe@strath.ac.uk