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151. Association Between Muscle Strength and Modeling Estimates of Muscle Tissue Heterogeneity in Young and Old Adults.

Author

Gonzales, Tomas I., Woletz, Paula, Harris‐Love, Michael O., Ismail, Catheeja, Blackman, Marc R., Zabal, Johannah, DiPietro, Loretta, and Wei, Qi

Subjects
AGING, MUSCLES, MUSCULOSKELETAL system, ULTRASONIC imaging, STATISTICAL models
Abstract

Objectives: Assessing aging muscle through estimates of muscle heterogeneity may overcome some of the limitations of grayscale analyses. The objectives of this study included determining statistical model parameters that characterize muscle echogenicity and are associated with strength in younger and older participants. Methods: Thirty‐three community‐dwelling participants were assigned to younger and older groups. Quantitative B‐mode ultrasound scanning of the rectus femoris and isometric grip strength testing were completed. Shape or dispersion parameters from negative binomial distribution, Nakagami, gamma, and gamma mixture models were fitted to the grayscale histograms. Results: The mean ages ± SDs of the younger and older groups were 24.0 ± 2.3 and 65.1 ± 6.5 years, respectively. Statistical model shape and dispersion parameters for the grayscale histograms significantly differed between the younger and older participants (P = .002–.006). Among all of the statistical models considered, the gamma mixture model showed the best fit with the grayscale histograms (χ2 goodness of fit = 62), whereas the Nakagami distribution displayed the poorest fit (χ2 goodness of fit = 2595). Grayscale values were significantly associated with peak grip strength force in younger adult participants (R2 = 0.36; P < .008). However, the negative binomial dispersion parameter k (adjusted R2 = 0.70; P < .001) and gamma shape parameter α (adjusted R2 = 0.68; P < .01) showed the highest associations with peak grip strength force in older adult participants. Conclusions: The negative binomial dispersion parameter k and the gamma shape parameter α have clinical relevance for the assessment of age‐related muscle changes. Statistical models of muscle heterogeneity may characterize the association between muscle tissue composition estimates and strength better than grayscale measures in samples of community‐dwelling older adults. [ABSTRACT FROM AUTHOR]

Published
2019
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152. The Impact of Physical Activity and Physical Fitness on Health Indicators Among Older Adults.

Author

Pescatello, Linda S., DiPietro, Loretta, Fargo, Ann E., Ostfeld, Adrian M., and Nadel, Ethan R.

Subjects
PHYSICAL fitness for older people, HEMODYNAMIC monitoring, OBESITY, BLOOD pressure measurement, CALORIC expenditure, BODY mass index
Abstract

The cross-sectional relationship between physical activity, physical fitness, and measures of resting hemodynamic function and adiposity was examined in 11 women and 14 men, all of whom were in good health (M age = 69.3 yrs). Resting diastolic blood pressure (DBP) differed significantly by quartiles of both weekly energy expenditure and estimated VO2max. Subjects whose energy expenditure was above the 50th percentile had significantly lower DBP than Less active subjects, independent of age, gender, and VO2max, whereas those above the 75th percentile of VO2max had lower DBP and mean arterial pressure compared to less fit subjects, independent of age, gender, and weekly energy expenditure. There were no significant differences in the body mass index or percent body fat by quartile of weekly energy expenditure or estimated VO2max in the multivariable analysis. Mean waist- to-hip ratio (WHR) differed by level of weekly energy expenditure, independent of age, gender, and VO2max; individuals who reported a threshold of energy expenditure >&mn;6,099 kcal/wk had less relative abdominal fat than those reporting less activity. There were no significant independent differences in mean WHR or the central-to-peripheral skinfold ratio between quartiles of VO2max. [ABSTRACT FROM AUTHOR]

Published
1994
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157. Proceedings of the Thirteenth International Society of Sports Nutrition (ISSN) Conference and Expo

Author

Ramaswamy, Lalitha, primary, Velraja, Supriya, additional, Escalante, Guillermo, additional, Harvey, Phil, additional, Alencar, Michelle, additional, Haddock, Bryan, additional, Durkalec-Michalski, Krzysztof, additional, Jeszka, Jan, additional, Zawieja, Bogna, additional, Podgórski, Tomasz, additional, Trussardi Fayh, Ana Paula, additional, Okano, Alexandre Hideki, additional, de Jesus Ferreira, Amanda Maria, additional, Jäger, Ralf, additional, Purpura, Martin, additional, Harris, Roger C., additional, Krause, Molly M., additional, Lavanger, Kiley A., additional, Allen, Nina O., additional, Lieb, Allison E., additional, Mullen, Katie A., additional, Eckerson, Joan M., additional, Morales, Elisa, additional, Forsse, Jeffrey, additional, Andre, Thomas, additional, McKinley, Sarah, additional, Hwang, Paul, additional, Tinsley, Grant, additional, Spillane, Mike, additional, Grandjean, Peter, additional, Willoughby, Darryn, additional, Jagim, A., additional, Wright, G., additional, Kisiolek, J., additional, Meinking, M., additional, Ochsenwald, J., additional, Andre, M., additional, Jones, M. T., additional, Oliver, J. M., additional, Ferreira, Victor Araújo, additional, de Souza, Daniel Costa, additional, dos Santos, Victor Oliveira Albuquerque, additional, Browne, Rodrigo Alberto Vieira, additional, Costa, Eduardo Caldas, additional, Fayh, Ana Paula Trussardi, additional, Mathews, Suresh T., additional, Bishop, Haley D., additional, Bowen, Clara R., additional, Liang, Yishan, additional, West, Emily A., additional, Rogers, Rebecca R., additional, Marshall, Mallory R., additional, Petrella, John K., additional, Holland, A. Maleah, additional, Kephart, Wesley C., additional, Mumford, Petey W., additional, Mobley, C. Brooks, additional, Lowery, Ryan P., additional, Wilson, Jacob M., additional, Roberts, Michael D., additional, Trexler, Eric T., additional, Hirsch, Katie R., additional, Campbell, Bill I., additional, Mock, Meredith G., additional, Smith-Ryan, Abbie E., additional, Zemek, Kate, additional, Johnston, Carol, additional, Pascoe, David D., additional, Lockwood, Christopher M., additional, Miller, Michael E., additional, Sanders, Gabriel J., additional, Peveler, Willard, additional, Warning, Brooke, additional, Peacock, Corey A., additional, Sandler, David, additional, Ojalvo, Sara Perez, additional, Komorowski, James, additional, Aguilar, Danielle, additional, Vargas, Andres, additional, Conlin, Laurin, additional, Sanders, Amey, additional, Fink-Irizarry, Paola, additional, Norton, Layne, additional, Perry, Ross, additional, McCallum, Ryley, additional, Wynn, Matthew R., additional, Lenton, Jack, additional, Gai, Chris, additional, Donelson, Seth, additional, Best, Shiva, additional, Bove, Daniel, additional, Couvillion, Kaylee, additional, Dolan, Jeff, additional, Xing, Dante, additional, Chernesky, Kyshia, additional, Pawela, Michael, additional, Toledo, Andres D., additional, Jimenez, Rachel, additional, Rabideau, M., additional, Walker, A., additional, Pellegrino, J., additional, Hofacker, M., additional, McFadden, B., additional, Conway, S., additional, Ordway, C., additional, Sanders, D., additional, Monaco, R., additional, Fragala, M. S., additional, Arent, S. M., additional, Stone, Jason D., additional, Kreutzer, Andreas, additional, Oliver, Jonathan M., additional, Kisiolek, Jacob, additional, Jagim, Andrew R., additional, Tok, Ozlem, additional, Pellegrino, Joseph K., additional, Walker, Alan J., additional, Sanders, David J., additional, McFadden, Bridget A., additional, Rabideau, Meaghan M., additional, Conway, Sean P., additional, Ordway, Chris E., additional, Bello, Marissa, additional, Hofacker, Morgan L., additional, Mackowski, Nick S., additional, Poyssick, Anthony J., additional, Capone, Eddie, additional, Monaco, Robert M., additional, Fragala, Maren S., additional, Arent, Shawn M., additional, Patel, Romil K., additional, Newton, Annie, additional, Beck, Darren T., additional, Young, Kaelin C., additional, Silver, Tobin, additional, Ellerbroek, Anya, additional, Buehn, Richard, additional, Vargas, Leo, additional, Tamayo, Armando, additional, Peacock, Corey, additional, Antonio, Jose, additional, Pollock, Adam, additional, Kreutzer, A., additional, Zavala, P., additional, Fleming, S., additional, Jones, M., additional, Haun, Cody T., additional, Hyde, Parker N., additional, Fairman, Ciaran M., additional, Moon, Jordan R., additional, Kendall, Kristina L., additional, Hudson, Geoffrey M., additional, Hannings, Tara, additional, Sprow, Kyle, additional, DiPietro, Loretta, additional, Kalman, Doug, additional, Oliver, J., additional, Wallace, Brian, additional, Bergstrom, Haley, additional, Wallace, Kelly, additional, Monsalves-Alvarez, Matias, additional, Oyharçabal, Sebastian, additional, Espinoza, Victoria, additional, VanDusseldorp, Trisha A., additional, Escobar, Kurt A., additional, Johnson, Kelly E., additional, Cole, Nathan, additional, Moriarty, Terence, additional, Stratton, Matthew, additional, Endito, Marvin R., additional, Mermier, Christine M., additional, Kerksick, Chad M., additional, Romero, Matthew A., additional, Linden, Melissa, additional, Meers, Grace Margaret-Eleanor, additional, Rector, R. Scott, additional, Gills, Joshua L, additional, Lu, Hocheng, additional, Parker, Kimberly, additional, Dobbins, Chris, additional, Guillory, Joshua N., additional, Romer, Braden, additional, Szymanski, David, additional, Glenn, Jordan, additional, Newmire, Daniel E., additional, Rivas, Eric, additional, Deemer, Sarah E., additional, Wildman, Robert, additional, Ben-Ezra, Victor, additional, Kerksick, C., additional, Gieske, B., additional, Stecker, R., additional, Smith, C., additional, Witherbee, K., additional, Lane, Michael T., additional, Byrd, M. Travis, additional, Bell, Zachary, additional, Frith, Emily, additional, Lane, Lauren M. C., additional, Silver, Tobin A., additional, Colas, Megan, additional, Mena, Mauricio, additional, Rodriguez, Winter, additional, Vansickle, Andrea, additional, DiFiore, Brittany, additional, Stepp, Stephanie, additional, Slack, Grant, additional, Smith, Bridget, additional, Ruffner, Kayla, additional, Mendel, Ronald, additional, Lowery, Lonnie, additional, Blue, Malia M. N., additional, Roelofs, Erica J., additional, Coles, Katie, additional, Martinez, Nic, additional, Joy, Jordan M., additional, Vogel, Roxanne M., additional, Hoover, Thomas H., additional, Broughton, K. Shane, additional, Dalton, R., additional, Sowinski, R., additional, Grubic, T., additional, Collins, P. B., additional, Colletta, A., additional, Reyes, A., additional, Sanchez, B., additional, Kozehchain, M., additional, Jung, Y. P., additional, Rasmussen, C., additional, Murano, P., additional, Earnest, C. P., additional, Greenwood, M., additional, Kreider, R. B., additional, Urbina, Stacie, additional, Santos, Emily, additional, Villa, Katelyn, additional, Olivencia, Alyssa, additional, Bennett, Haley, additional, Lara, Marissa, additional, Foster, Cliffa, additional, Wilborn, Colin, additional, Taylor, Lem, additional, Cholewa, Jason M, additional, Hewins, Amy, additional, Gallo, Samantha, additional, Micensky, Ashley, additional, de Angelis, Christian, additional, Carney, Christopher, additional, Campbell, Bill, additional, Rossi, Fabricio, additional, Koozehchian, M. S., additional, O’Connor, A., additional, Shin, S. Y., additional, Jung, Y. Peter, additional, Sanchez, B. K., additional, Coletta, A., additional, Cho, M., additional, and Murano, P. S., additional

Published
2016
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159. The Joint Associations of Sedentary Time and Physical Activity With Mobility Disability in Older People: The NIH-AARP Diet and Health Study.

Author

DiPietro, Loretta, Yichen Jin, Talegawkar, Sameera, Matthews, Charles E., and Jin, Yichen

Subjects
*PHYSICAL activity, *HEALTH of older people, *LOGISTIC regression analysis, *SEDENTARY lifestyles, *FUNCTIONAL assessment, *EXERCISE, *LONGITUDINAL method, *SURVEYS, *SYMPTOMS
Abstract

Background: The purpose of this study was to determine the joint associations of sedentary time and physical activity with mobility disability in older age.Methods: We analyzed prospective data from 134,269 participants in the National Institutes of Health (NIH)-American Association of Retired Persons (NIH-AARP) Diet and Health Study between 1995-1996 and 2004-2005. Total sitting time (h/d), TV viewing time (h/d) and light- and moderate-to-vigorous-intensity physical activity (h/wk) were self-reported at baseline, and mobility disability at follow-up was defined as being "unable to walk" or having an "easy usual walking pace (<2 mph)." Multivariable logistic regression determined the independent and joint associations of sedentary time and total physical activity with the odds of disability.Results: Among the most active participants (>7 h/wk), sitting <6 h/d was not related to excess disability at follow-up, and those in the most active group reporting the highest level of sitting time (≥7 h/d) still had a significantly lower odds (odds ratios = 1.11; 95% confidence interval = 1.02, 1.20) compared with those reporting the lowest level of sitting (<3 h/d) in the least active group (≤3 h/wk; odds ratios = 2.07; 95% confidence interval = 1.92, 2.23). Greater TV time was significantly related to increased disability within all levels of physical activity.Conclusions: Reduction of sedentary time, combined with increased physical activity may be necessary to maintain function in older age. [ABSTRACT FROM AUTHOR]

Published
2018
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160. Association Between Muscle Strength and Modeling Estimates of Muscle Tissue Heterogeneity in Young and Old Adults

Author

Harris‐Love, Michael O., Gonzales, Tomas I., Wei, Qi, Ismail, Catheeja, Zabal, Johannah, Woletz, Paula, DiPietro, Loretta, and Blackman, Marc R.

Abstract

Assessing aging muscle through estimates of muscle heterogeneity may overcome some of the limitations of grayscale analyses. The objectives of this study included determining statistical model parameters that characterize muscle echogenicity and are associated with strength in younger and older participants. Thirty‐three community‐dwelling participants were assigned to younger and older groups. Quantitative B‐mode ultrasound scanning of the rectus femoris and isometric grip strength testing were completed. Shape or dispersion parameters from negative binomial distribution, Nakagami, gamma, and gamma mixture models were fitted to the grayscale histograms. The mean ages ± SDs of the younger and older groups were 24.0 ± 2.3 and 65.1 ± 6.5 years, respectively. Statistical model shape and dispersion parameters for the grayscale histograms significantly differed between the younger and older participants (P= .002–.006). Among all of the statistical models considered, the gamma mixture model showed the best fit with the grayscale histograms (χ2goodness of fit = 62), whereas the Nakagami distribution displayed the poorest fit (χ2goodness of fit = 2595). Grayscale values were significantly associated with peak grip strength force in younger adult participants (R2= 0.36; P< .008). However, the negative binomial dispersion parameter k(adjusted R2= 0.70; P< .001) and gamma shape parameter α(adjusted R2= 0.68; P< .01) showed the highest associations with peak grip strength force in older adult participants. The negative binomial dispersion parameter kand the gamma shape parameter αhave clinical relevance for the assessment of age‐related muscle changes. Statistical models of muscle heterogeneity may characterize the association between muscle tissue composition estimates and strength better than grayscale measures in samples of community‐dwelling older adults.

Published
2019
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174. Commentaries on Viewpoint: A time for exercise: the exercise window.

Author

Boulé, Normand G., Terada, Tasuku, Francois, Monique E., Hawley, John A., Cotter, James D., Kruse, Nicholas T., McDonald, Matthew W., Olver, T. Dylan, Paoli, Antonio, Sacchetti, Massimo, Di Luigi, Luigi, van Dijk, Jan-Willem, van Loon, Luc J. C., Yardley, Jane, DiPietro, Loretta, Gribok, Andrei, and Rumpler, William

Published
2017
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175. Using the Inverse Maximum Ratio- Λ as a Technique to Quantify Surface Uniformity.

Author

Chandran, Avinash, Brown, Derek, Danoff, Jerome, and DiPietro, Loretta

Subjects
PREDICATE calculus, SURFACE texture, DATA analysis, CURVES, DISTRIBUTION (Probability theory), IMPACT (Mechanics), MATHEMATICAL models
Abstract

Techniques used in variability assessment are subsequently used to draw conclusions regarding the “spread”/uniformity of data curves. Due to the limitations of these techniques, they are not adequate for circumstances where data manifest with multiple peaks. Examples of these manifestations (in three-dimensional space) include under-foot pressure distributions recorded for different types of footwear (Becerro-de-Bengoa-Vallejo et al., 2014; Cibulka et al., 1994; Davies et al., 2003), surface textures and interfaces designed to impact friction, and and and molecular surface structures such as viral epitopes (Torras and Garcia-Valls, 2004; Pacejka, 1997; Fustaffson, 1997). This article proposes a technique for generating a single variable –Λthat will quantify the uniformity of such surfaces. We define and validate this technique using several mathematical and graphical models. [ABSTRACT FROM AUTHOR]

Published
2016
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177. Successful Aging

Author

DiPietro, Loretta, primary, Fiatarone Singh, Maria, additional, Fielding, Roger, additional, and Nose, Hiroshi, additional

Published
2012
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195. The Value of Athletic Trainers in Ambulatory Settings.

Author

Frogner, Bianca K., Westerman, Beverly, and DiPietro, Loretta

Abstract

Athletic trainers (ATs) are increasingly used in ambulatory care settings. This study piloted a new survey instrument to assess the value that ATs add to these settings. The survey collected data on six domains: 1) general facility characteristics, 2) AT staffing characteristics, 3) other staffing characteristics, 4) patient characteristics. 5) billing practices, and 6) participation in innovations. A national sample of physician practices using ATs was recruited to participate in a web-based survey. The study found that ATs were among the most common clinical occupations in the practice. Practices were almost all "very satisfied" with the services provided by ATs with equal expectations to either maintain or increase the number of ATs. While most practices invested in training and continuing education units, the larger practices were more likely to do so. Practices were more likely to bill for AT services if ATs had a national provider identifier. The mean number of clinical visits, rate of billing, patient scheduling, wait times, and participation in innovations did not vary significantly by the number of ATs employed. Overall, the study found evidence that ambulatory care practices see value in hiring ATs. [ABSTRACT FROM AUTHOR]

Published
2015

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