Nicholas Beyler

Physical Activity in U.S. Adults Compliance with the Physical Activity Guidelines for Americans

BACKGROUND To date, no study has objectively measured physical activity levels among U.S. adults according to the 2008 Physical Activity Guidelines for Americans (PAGA). PURPOSE The purpose of this study was to assess self-reported and objectively measured physical activity among U.S. adults according to the PAGA. METHODS Using data from the NHANES 2005-2006, the PAGA were assessed using three physical activity calculations: moderate plus vigorous physical activity ≥150 minutes/week (MVPA); moderate plus two instances of vigorous physical activity ≥150 minutes/week (M2VPA); and time spent above 3 METs ≥500 MET-minutes/week (METPA). Self-reported physical activity included leisure, transportation, and household activities. Objective activity was measured using Actigraph accelerometers that were worn for 7 consecutive days. Analyses were conducted in 2009-2010. RESULTS U.S. adults reported 324.5 ± 18.6 minutes/week (M ± SE) of moderate physical activity and 73.6 ± 3.9 minutes/week of vigorous physical activity, although accelerometry estimates were 45.1 ± 4.6 minutes/week of moderate physical activity and 18.6 ± 6.6 minutes/week of vigorous physical activity. The proportion of adults meeting the PAGA according to M2VPA was 62.0% for self-report and 9.6% for accelerometry. CONCLUSIONS According to the NHANES 2005-2006, fewer than 10% of U.S. adults met the PAGA according to accelerometry. However, physical activity estimates vary substantially depending on whether self-reported or measured via accelerometer.

Associations between Physical Activity and Metabolic Syndrome: Comparison between Self-Report and Accelerometry

Purpose. To assess the relationship between self-reported and objectively measured physical activity (PA) and metabolic syndrome and its risk factors in U.S. adults. Design. A cross-sectional design was used for this study. Setting. The study was set among a nationally representative sample of U.S. adults. Subjects. Adults, ages 20 years and older, from the National Health and Nutrition Examination Survey (NHANES) 2003–2006 (n = 5580) participated in the study. Measures. PA measures included minutes per week of moderate plus vigorous PA estimated by self-report (MVPAsr), total 7-day accelerometry (MVPAa), and accelerometer-based MVPA performed in 10-minute bouts (MVPAb). Risk factors for metabolic syndrome included blood pressure, high-density lipoprotein cholesterol, triglycerides, glucose, and waist circumference. Analysis. Odds ratios (ORs) for having metabolic syndrome were calculated for men and women who met the Physical Activity Guidelines for Americans compared to those who did not. Results. Women who did not meet the PA guidelines had significantly greater odds of having metabolic syndrome according to MVPAsr (OR = 2.20; 95% confidence interval [CI] = 1.65–2.94), MVPAa (OR = 4.40; 95% CI= 2.65–7.31), and MVPAb (OR= 2.91; 95% CI= 1.42–5.96). Men had significantly higher odds of having metabolic syndrome according to MVPAa (OR = 2.57; 95% CI= 1.91–3.45) and MVPAb (OR = 2.83; 95% CI = 1.55–5.17), but not MVPAsr. These ORs remained significant after adjusting for all potential confounders except body mass index, after which only MVPAsr in women and MVPAb in men remained significant. Conclusion. Individuals who do not meet the PA guidelines exhibited greater odds of having metabolic syndrome. This relationship tended to be stronger for objective PA measures than for self-report.

Calibration of Self-Report Measures of Physical Activity and Sedentary Behavior

Introduction Calibration equations offer potential to improve the accuracy and utility of self-report measures of physical activity (PA) and sedentary behavior (SB) by rescaling potentially biased estimates. The present study evaluates calibration models designed to estimate PA and SB in a representative sample of adults from the Physical Activity Measurement Study. Methods Participants in the Physical Activity Measurement Study project completed replicate single-day trials that involved wearing a Sensewear armband (SWA) monitor for 24 h followed by a telephone administered 24-h PA recall (PAR). Comprehensive statistical model selection and validation procedures were used to develop and test separate calibration models designed to predict objectively measured SB and moderate-to-vigorous PA (MVPA) from self-reported PAR data. Equivalence testing was used to evaluate the equivalence of the model-predicted values with the objective measures in a separate holdout sample. Results The final prediction model for both SB and MVPA included reported time spent in SB and MVPA, as well as terms capturing sex, age, education, and body mass index. Cross-validation analyses on an independent sample exhibited high correlations with observed SB (r = 0.72) and MVPA (r = 0.75). Equivalence testing demonstrated that the model-predicted values were statistically equivalent to the corresponding objective values for both SB and MVPA. Conclusions The results demonstrate that simple regression models can be used to statistically adjust for overestimation or underestimation in self-report measures among different segments of the population. The models produced group estimates from the PAR that were statistically equivalent to the observed time spent in SB and MVPA obtained from the objective SWA monitor; however, additional work is needed to correct for estimates of individual behavior.

Predicting objective physical activity from self-report surveys: a model validation study using estimated generalized least-squares regression

Physical activity measurements derived from self-report surveys are prone to measurement errors. Monitoring devices like accelerometers offer more objective measurements of physical activity, but are impractical for use in large-scale surveys. A model capable of predicting objective measurements of physical activity from self-reports would offer a practical alternative to obtaining measurements directly from monitoring devices. Using data from National Health and Nutrition Examination Survey 2003–2006, we developed and validated models for predicting objective physical activity from self-report variables and other demographic characteristics. The prediction intervals produced by the models were large, suggesting that the ability to predict objective physical activity for individuals from self-reports is limited.

Re-Defining the Who, When, and Where of Mentoring for Professional Statisticians

ABSTRACT Organizations tailor their mentoring strategies to accommodate internal resources and preferences, producing different approaches in academic, government, and corporate environments. Across these settings, three common barriers impede effective mentoring of statisticians: overspecialization, time constraints, and geographic dispersion. The authors share mentoring strategies that have emerged at their organization, Mathematica Policy Research, to overcome these obstacles. Practices include creating a methodology working group to unite researchers with diverse backgrounds, integrating mentoring into existing workflows, and harnessing modern technological infrastructure to facilitate virtual mentoring. Although these strategies emerged within a specific professional context, they suggest opportunities for statisticians to expand the channels through which mentorship can occur.