Gregory J. Welk

Bio: Gregory J. Welk is an academic researcher from Iowa State University. The author has contributed to research in topics: Physical fitness & Physical activity level. The author has an hindex of 64, co-authored 285 publications receiving 16286 citations. Previous affiliations of Gregory J. Welk include Nationwide Children's Hospital & Mathematica Policy Research.

Physical Activity in US Adults Compliance with the Physical Activity Guidelines for Americans

Abstract: This study assesses self-reported and objectively measured physical activity among U.S. adults according to the 2008 Physical Activity Guidelines for Americans. The National Health and Nutrition Examination Survey of 2005–2006 found that fewer than 10 percent of U.S. adults met the guidelines. However, physical activity estimates vary substantially depending on how they are reported and measured.

Measurement Issues in the Assessment of Physical Activity in Children

Abstract: This paper reviewed the nature of children's physical activity patterns and how the unique nature of children can impact the assessment of physical activity. To accurately assess children's activity patterns, an instrument must be sensitive enough to detect, code, or record sporadic and intermittent activity. Care also must be used to select criterion measures that reflect appropriate physical activity guidelines for children. A number of different measurement approaches have been described for assessing children's activity, but no specific method can be identified as the best option for all studies. Selection of an appropriate instrument depends on the specific research question being addressed as well as the relative importance of accuracy and practicality (Baranowski & Simons-Morton, 1991). For example, accurate measures of energy expenditure using doubly-labeled water, indirect calorimetry, or heart rate calibration equations may be needed for certain clinical studies, but the cost and inconvenience would make them impractical for field-based assessments on larger samples. The "accuracy-practicality" trade-off presents a more challenging predicament with children than for adults. In adults, a number of self-report instruments have been found useful for large epidemiological studies or interventions where less precision is needed. Because of developmental differences, especially in ability to think abstractly and perform detailed recall (Going et al., 1999; Sallis, 1991), children are less likely to make accurate self-report assessment than adults. Though self-report methods are still likely to be a principal source of information for many studies, other approaches (or the use of combined measures) may be needed to better characterize children's activity levels. While objective instruments (e.g., direct observation or activity monitoring) require more time and resources than self-report, there are options available to simplify data collection. One approach may be to focus assessments on key times or places that allow children to be active. The time after school, for example, appears to be a critical period that defines their propensity for physical activity (Hager, 1999). Monitoring of entire groups for discrete periods of time (e.g., recess or physical education) may also be useful to understand variability in activity patterns since children would all be exposed to the same stimulus or opportunity to be active. Proxy measures may also be useful in studying activity in children. For example, several studies (Baranowski, Thompson, DuRant, Baranowski, & Puhl, 1993; Sallis et al., 1993) have demonstrated that time spent outside is strongly predictive of activity in children. Involvement in community sports programs may also be a useful proxy measure as sports programs have been found to account for approximately 55-65% of children's moderate to vigorous activity (Katzmarzyk & Malina, 1999). Another option for improving assessments in children is to employ multiple measures of physical activity. A number of studies (Coleman, Saelens, Wiedrich-Smith, Finn, & Epstein, 1997; McMurray et al., 1998; Sallis et al., 1998; Simons-Morton et al., 1994) have reported differences in levels of activity when activity monitors were compared with self-report data. The method of measurement has also been shown to influence the results of studies on the determinants of physical activity in children (Epstein, Paluch, Coleman, Vito, & Anderson, 1996). While we do not currently know which measure is most accurate, reporting the results with different instruments provides a more complete description of children's activity and permit a triangulation of outcomes. In summary, there remains no single way of obtaining a highly accurate account of physical activity or energy expenditure in children. The nature of children's movement patterns, the various types of activities engaged in, and the inherent limitations of each assessment tool limit the ultima

Physical Activity Assessments for Health-Related Research

Abstract: Methods for assessing physical activity and challenges for research measurement issues for the assessment of physical activity construct validity in physical activity research physical activity data - odd distributions yield strange answers equating and linking of physical activity questionnaires power calculations and the design of behavioural interventions use of self-report instruments to assess physical activity use of accelerometry-based activity monitors to assess physical activity use of heart rate monitors to assess physical activity use of pedometers to assess physical activity use of direct observation to assess physical activity use of doubly labelled water and indirect calorimetry to assess physical activity applying multiple methods to improve the accuracy of activity assessments physical activity assessment issues in population-based interventions - a stage environmental and policy measurement in physial activity research.

Compendium of physical activities: an update of activity codes and MET intensities.

Abstract: We provide an updated version of the Compendium of Physical Activities, a coding scheme that classifies specific physical activity (PA) by rate of energy expenditure. It was developed to enhance the comparability of results across studies using self-reports of PA. The Compendium coding scheme links a five-digit code that describes physical activities by major headings (e.g., occupation, transportation, etc.) and specific activities within each major heading with its intensity, defined as the ratio of work metabolic rate to a standard resting metabolic rate (MET). Energy expenditure in MET-minutes, MET-hours, kcal, or kcal per kilogram body weight can be estimated for specific activities by type or MET intensity. Additions to the Compendium were obtained from studies describing daily PA patterns of adults and studies measuring the energy cost of specific physical activities in field settings. The updated version includes two new major headings of volunteer and religious activities, extends the number of specific activities from 477 to 605, and provides updated MET intensity levels for selected activities.

Heart Disease and Stroke Statistics—2017 Update: A Report From the American Heart Association

Abstract: WRITING GROUP MEMBERS Emelia J. Benjamin, MD, SCM, FAHA Michael J. Blaha, MD, MPH Stephanie E. Chiuve, ScD Mary Cushman, MD, MSc, FAHA Sandeep R. Das, MD, MPH, FAHA Rajat Deo, MD, MTR Sarah D. de Ferranti, MD, MPH James Floyd, MD, MS Myriam Fornage, PhD, FAHA Cathleen Gillespie, MS Carmen R. Isasi, MD, PhD, FAHA Monik C. Jiménez, ScD, SM Lori Chaffin Jordan, MD, PhD Suzanne E. Judd, PhD Daniel Lackland, DrPH, FAHA Judith H. Lichtman, PhD, MPH, FAHA Lynda Lisabeth, PhD, MPH, FAHA Simin Liu, MD, ScD, FAHA Chris T. Longenecker, MD Rachel H. Mackey, PhD, MPH, FAHA Kunihiro Matsushita, MD, PhD, FAHA Dariush Mozaffarian, MD, DrPH, FAHA Michael E. Mussolino, PhD, FAHA Khurram Nasir, MD, MPH, FAHA Robert W. Neumar, MD, PhD, FAHA Latha Palaniappan, MD, MS, FAHA Dilip K. Pandey, MBBS, MS, PhD, FAHA Ravi R. Thiagarajan, MD, MPH Mathew J. Reeves, PhD Matthew Ritchey, PT, DPT, OCS, MPH Carlos J. Rodriguez, MD, MPH, FAHA Gregory A. Roth, MD, MPH Wayne D. Rosamond, PhD, FAHA Comilla Sasson, MD, PhD, FAHA Amytis Towfighi, MD Connie W. Tsao, MD, MPH Melanie B. Turner, MPH Salim S. Virani, MD, PhD, FAHA Jenifer H. Voeks, PhD Joshua Z. Willey, MD, MS John T. Wilkins, MD Jason HY. Wu, MSc, PhD, FAHA Heather M. Alger, PhD Sally S. Wong, PhD, RD, CDN, FAHA Paul Muntner, PhD, MHSc On behalf of the American Heart Association Statistics Committee and Stroke Statistics Subcommittee Heart Disease and Stroke Statistics—2017 Update

Physical activity in the United States measured by accelerometer.

Abstract: Purpose:To describe physical activity levels of children (6-11 yr), adolescents (12-19 yr), and adults (20+ yr), using objective data obtained with accelerometers from a representative sample of the U.S. population.Methods:These results were obtained from the 2003-2004 National Health and Nu

Heart Disease and Stroke Statistics—2016 Update: A Report From the American Heart Association

Abstract: Author(s): Writing Group Members; Mozaffarian, Dariush; Benjamin, Emelia J; Go, Alan S; Arnett, Donna K; Blaha, Michael J; Cushman, Mary; Das, Sandeep R; de Ferranti, Sarah; Despres, Jean-Pierre; Fullerton, Heather J; Howard, Virginia J; Huffman, Mark D; Isasi, Carmen R; Jimenez, Monik C; Judd, Suzanne E; Kissela, Brett M; Lichtman, Judith H; Lisabeth, Lynda D; Liu, Simin; Mackey, Rachel H; Magid, David J; McGuire, Darren K; Mohler, Emile R; Moy, Claudia S; Muntner, Paul; Mussolino, Michael E; Nasir, Khurram; Neumar, Robert W; Nichol, Graham; Palaniappan, Latha; Pandey, Dilip K; Reeves, Mathew J; Rodriguez, Carlos J; Rosamond, Wayne; Sorlie, Paul D; Stein, Joel; Towfighi, Amytis; Turan, Tanya N; Virani, Salim S; Woo, Daniel; Yeh, Robert W; Turner, Melanie B; American Heart Association Statistics Committee; Stroke Statistics Subcommittee