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4. Digital Tools to Support Family-Based Weight Management for Children: Mixed Methods Pilot and Feasibility Study

Author

Staiano, Amanda E, Shanley, Jenelle R, Kihm, Holly, Hawkins, Keely R, Self-Brown, Shannon, Höchsmann, Christoph, Osborne, Melissa C, LeBlanc, Monique M, Apolzan, John W, and Martin, Corby K

Subjects
Pediatrics, RJ1-570
Abstract

BackgroundFamily-based behavioral therapy is an efficacious approach to deliver weight management counseling to children and their parents. However, most families do not have access to in-person, evidence-based treatment. We previously developed and tested DRIVE (Developing Relationships that Include Values of Eating and Exercise), a home-based parent training program to maintain body weight among children at risk for obesity, with the intent to eventually disseminate it nationally alongside SafeCare, a parent support program that focuses on parent-child interactions. Currently the DRIVE program has only been tested independently of SafeCare. This study created the “mHealth DRIVE” program by further adapting DRIVE to incorporate digital and mobile health tools, including remotely delivered sessions, a wireless scale that enabled a child-tailored weight graph, and a pedometer. Telehealth delivery via mHealth platforms and other digital tools can improve program cost-effectiveness, deliver long-term care, and directly support both families and care providers. ObjectiveThe objective of this study was to examine preliminary acceptability and effectiveness of the mHealth DRIVE program among children and parents who received it and among SafeCare providers who potentially could deliver it. MethodsStudy 1 was a 13-week pilot study of a remotely delivered mHealth family-based weight management program. Satisfaction surveys were administered, and height and weight were measured pre- and post-study. Study 2 was a feasibility/acceptability survey administered to SafeCare providers. ResultsParental and child satisfaction (mean of 4.9/6.0 and 3.8/5.0, respectively) were high, and children’s (N=10) BMI z-scores significantly decreased (mean –0.14, SD 0.17; P=.025). Over 90% of SafeCare providers (N=74) indicated that SafeCare families would benefit from learning how to eat healthily and be more active, and 80% of providers reported that they and the families would benefit from digital tools to support child weight management. ConclusionsPediatric mHealth weight management interventions show promise for effectiveness and acceptability by families and providers. Trial RegistrationClinicaltrials.gov NCT03297541, https://clinicaltrials.gov/ct2/show/NCT03297541.

Published
2021
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5. Calorie restriction reduces biomarkers of cellular senescence in humans.

Author

Aversa, Zaira, White, Thomas, Heeren, Amanda, Hulshizer, Cassondra, Saul, Dominik, Zhang, Xu, Redman, Leanne, Martin, Corby, Racette, Susan, Huffman, Kim, Bhapkar, Manjushri, Khosla, Sundeep, Das, Sai, Fielding, Roger, Atkinson, Elizabeth, LeBrasseur, Nathan, and Molina, Anthony

Subjects
CALERIE™, aging, biomarkers, caloric restriction, inflammation, metabolism, senescence-associated secretory phenotype, Middle Aged, Humans, Caloric Restriction, Aging, Cellular Senescence, Energy Intake, Biomarkers
Abstract

Calorie restriction (CR) with adequate nutrient intake is a potential geroprotective intervention. To advance this concept in humans, we tested the hypothesis that moderate CR in healthy young-to-middle-aged individuals would reduce circulating biomarkers of cellular senescence, a fundamental mechanism of aging and aging-related conditions. Using plasma specimens from the Comprehensive Assessment of Long-term Effects of Reducing Intake of Energy (CALERIE™) phase 2 study, we found that CR significantly reduced the concentrations of several senescence biomarkers at 12 and 24 months compared to an ad libitum diet. Using machine learning, changes in biomarker concentrations emerged as important predictors of the change in HOMA-IR and insulin sensitivity index at 12 and 24 months, and the change in resting metabolic rate residual at 12 months. Finally, using adipose tissue RNA-sequencing data from a subset of participants, we observed a significant reduction in a senescence-focused gene set in response to CR at both 12 and 24 months compared to baseline. Our results advance the understanding of the effects of CR in humans and further support a link between cellular senescence and metabolic health.

Published
2024

6. Associations between daily step count classifications and continuous glucose monitoring metrics in adults with type 1 diabetes: analysis of the Type 1 Diabetes Exercise Initiative (T1DEXI) cohort

Author

Turner, Lauren V., Marak, Martin Chase, Gal, Robin L., Calhoun, Peter, Li, Zoey, Jacobs, Peter G., Clements, Mark A., Martin, Corby K., Doyle, III, Francis J., Patton, Susana R., Castle, Jessica R., Gillingham, Melanie B., Beck, Roy W., Rickels, Michael R., and Riddell, Michael C.

Published
2024
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7. The Remote Food Photography Method and SmartIntake App for the Assessment of Alcohol Use in Young Adults: Feasibility Study and Comparison to Standard Assessment Methodology

Author

Fazzino, Tera L, Martin, Corby K, and Forbush, Kelsie

Subjects
Information technology, T58.5-58.64, Public aspects of medicine, RA1-1270
Abstract

BackgroundHeavy drinking is prevalent among young adults and may contribute to obesity. However, measurement tools for assessing caloric intake from alcohol are limited and rely on self-report, which is prone to bias. ObjectiveThe purpose of our study was to conduct feasibility testing of the Remote Food Photography Method and the SmartIntake app to assess alcohol use in young adults. Aims consisted of (1) quantifying the ability of SmartIntake to capture drinking behavior, (2) assessing app usability with the Computer System Usability Questionnaire (CSUQ), (3) conducting a qualitative interview, and (4) comparing preference, usage, and alcohol use estimates (calories, grams per drinking episode) between SmartIntake and online diet recalls that participants completed for a parent study. MethodsCollege students (N=15) who endorsed a pattern of heavy drinking were recruited from a parent study. Participants used SmartIntake to send photographs of all alcohol and food intake over a 3-day period and then completed a follow-up interview and the CSUQ. CSUQ items range from 1-7, with lower scores indicating greater usability. Total drinking occasions were determined by adding the number of drinking occasions captured by SmartIntake plus the number of drinking occasions participants reported that they missed capturing. Usage was defined by the number of days participants provided food/beverage photos through the app, or the number of diet recalls completed. ResultsSmartIntake captured 87% (13/15) of total reported drinking occasions. Participants rated the app as highly usable in the CSUQ (mean 2.28, SD 1.23). Most participants (14/15, 93%) preferred using SmartIntake versus recalls, and usage was significantly higher with SmartIntake than recalls (42/45, 93% vs 35/45, 78%; P=.04). Triple the number of participants submitted alcohol reports with SmartIntake compared to the recalls (SmartIntake 9/15, 60% vs recalls 3/15, 20%; P=.06), and 60% (9/15) of participants reported drinking during the study. ConclusionsSmartIntake was acceptable to college students who drank heavily and captured most drinking occasions. Participants had higher usage of SmartIntake compared to recalls, suggesting SmartIntake may be well suited to measuring alcohol consumption in young adults. However, 40% (6/15) did not drink during the brief testing period and, although findings are promising, a longer trial is needed.

Published
2018
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8. Greater male variability in daily energy expenditure develops through puberty.

Author

Haisma, Hinke, Hambly, Catherine, Hoffman, Daniel, Hoos, Marije, Hu, Sumei, Joonas, Noorjehan, Joosen, Annemiek, Katzmarzyk, Peter, Kempen, Kitty, Kimura, Misaka, Kraus, William, Kriengsinyos, Wantanee, Kuriyan, Rebecca, Kushner, Robert, Lambert, Estelle, Lanerolle, Pulani, Larsson, Christel, Lessan, Nader, Löf, Marie, Martin, Corby, Matsiko, Eric, Meijer, Gerwin, Morehen, James, Morton, James, Must, Aviva, Neuheuser, Marian, Nicklas, Theresa, Ojiambo, Robert, Pietilainen, Kirsi, Pitsiladis, Yannis, Plange-Rhule, Jacob, Plasqui, Guy, Prentice, Ross, Rabinovich, Roberto, Racette, Susan, Raichen, David, Ravussin, Eric, Redman, Leanne, Reilly, John, Reynolds, Rebecca, Roberts, Susan, Rood, Jennifer, Samaranayake, Dulani, Sardinha, Luís, Scuitt, Albertine, Silva, Analiza, Sinha, Srishti, Sjödin, Anders, Stice, Eric, Stunkard, Albert, Urlacher, Samuel, Valencia, Mauro, Valenti, Giulio, van Etten, Ludo, Van Mil, Edgar, Verbunt, Jeanine, Wells, Jonathan, Wilson, George, Wood, Brian, Yoshida, Tsukasa, Zhang, Xueying, Murphy-Alford, Alexia, Loechl, Cornelia, Luke, Amy, Pontzer, Herman, Sagayama, Hiroyuki, Westerterp, Klaas, Wong, William, Yamada, Yosuke, Speakman, John, Halsey, Lewis, Careau, Vincent, Ainslie, Philip, Alemán-Mateo, Heliodoro, Andersen, Lene, Anderson, Liam, Arab, Leonore, Baddou, Issad, Bandini, Linda, Bedu-Addo, Kweku, Blaak, Ellen, Blanc, Stephane, Bonomi, Alberto, Bouten, Carlijn, Bovet, Pascal, Brage, Soren, Buchowski, Maciej, Butte, Nancy, Camps, Stephan, Casper, Regian, Close, Graeme, Colbert, Lisa, Cooper, Jamie, Cooper, Richard, Dabare, Prasangi, Das, Sai, Davies, Peter, Deb, Sanjoy, and Nyström, Christine

Subjects
age, height, inter-individual variation, morphometry, weight, Adolescent, Young Adult, Female, Humans, Male, Adult, Puberty, Sexual Behavior, Reproduction, Energy Metabolism, Phenotype
Abstract

There is considerably greater variation in metabolic rates between men than between women, in terms of basal, activity and total (daily) energy expenditure (EE). One possible explanation is that EE is associated with male sexual characteristics (which are known to vary more than other traits) such as musculature and athletic capacity. Such traits might be predicted to be most prominent during periods of adolescence and young adulthood, when sexual behaviour develops and peaks. We tested this hypothesis on a large dataset by comparing the amount of male variation and female variation in total EE, activity EE and basal EE, at different life stages, along with several morphological traits: height, fat free mass and fat mass. Total EE, and to some degree also activity EE, exhibit considerable greater male variation (GMV) in young adults, and then a decreasing GMV in progressively older individuals. Arguably, basal EE, and also morphometrics, do not exhibit this pattern. These findings suggest that single male sexual characteristics may not exhibit peak GMV in young adulthood, however total and perhaps also activity EE, associated with many morphological and physiological traits combined, do exhibit GMV most prominently during the reproductive life stages.

Published
2023

11. Effectiveness of SmartMoms, a Novel eHealth Intervention for Management of Gestational Weight Gain: Randomized Controlled Pilot Trial

Author

Redman, Leanne M, Gilmore, L. Anne, Breaux, Jeffrey, Thomas, Diana M, Elkind-Hirsch, Karen, Stewart, Tiffany, Hsia, Daniel S, Burton, Jeffrey, Apolzan, John W, Cain, Loren E, Altazan, Abby D, Ragusa, Shelly, Brady, Heather, Davis, Allison, Tilford, J. Mick, Sutton, Elizabeth F, and Martin, Corby K

Subjects
Information technology, T58.5-58.64, Public aspects of medicine, RA1-1270
Abstract

BackgroundTwo-thirds of pregnant women exceed gestational weight gain (GWG) recommendations. Because excess GWG is associated with adverse outcomes for mother and child, development of scalable and cost-effective approaches to deliver intensive lifestyle programs during pregnancy is urgent. ObjectiveThe aim of this study was to decrease the proportion of women who exceed the Institute of Medicine (IOM) 2009 GWG guidelines. MethodsIn a parallel-arm randomized controlled trial, 54 pregnant women (age 18-40 years) who were overweight (n=25) or obese (n=29) were enrolled to test whether an intensive lifestyle intervention (called SmartMoms) decreased the proportion of women with excess GWG, defined as exceeding the 2009 IOM guidelines, compared to no intervention (usual care group). The SmartMoms intervention was delivered through mobile phone (remote group) or in a traditional in-person, clinic-based setting (in-person group), and included a personalized dietary intake prescription, self-monitoring weight against a personalized weight graph, activity tracking with a pedometer, receipt of health information, and continuous personalized feedback from counselors. ResultsA significantly smaller proportion of women exceeded the IOM 2009 GWG guidelines in the SmartMoms intervention groups (in-person: 56%, 10/18; remote: 58%, 11/19) compared to usual care (85%, 11/13; P=.02). The remote intervention was a lower cost to participants (mean US $97, SD $6 vs mean US $347, SD $40 per participant; P

Published
2017
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12. Smartloss: A Personalized Mobile Health Intervention for Weight Management and Health Promotion

Author

Martin, Corby K, Gilmore, L. Anne, Apolzan, John W, Myers, Candice A, Thomas, Diana M, and Redman, Leanne M

Subjects
Information technology, T58.5-58.64, Public aspects of medicine, RA1-1270
Abstract

BackgroundSynonymous with increased use of mobile phones has been the development of mobile health (mHealth) technology for improving health, including weight management. Behavior change theory (eg, the theory of planned behavior) can be effectively encapsulated into mobile phone-based health improvement programs, which is fostered by the ability of mobile phones and related devices to collect and transmit objective data in near real time and for health care or research professionals and clients to communicate easily. ObjectiveTo describe SmartLoss, a semiautomated mHealth platform for weight loss. MethodsWe developed and validated a dynamic energy balance model that determines the amount of weight an individual will lose over time if they are adherent to an energy intake prescription. This model was incorporated into computer code that enables adherence to a prescribed caloric prescription determined from the change in body weight of the individual. Data from the individual are then used to guide personalized recommendations regarding weight loss and behavior change via a semiautomated mHealth platform called SmartLoss, which consists of 2 elements: (1) a clinician dashboard and (2) a mobile phone app. SmartLoss includes and interfaces with a network-connected bathroom scale and a Bluetooth-connected accelerometer, which enables automated collection of client information (eg, body weight change and physical activity patterns), as well as the systematic delivery of preplanned health materials and automated feedback that is based on client data and is designed to foster prolonged adherence with body weight, diet, and exercise goals. The clinician dashboard allows for efficient remote monitoring of all clients simultaneously, which may further increase adherence, personalization of treatment, treatment fidelity, and efficacy. ResultsEvidence of the efficacy of the SmartLoss approach has been reported previously. The present report provides a thorough description of the SmartLoss Virtual Weight Management Suite, a professionally programmed platform that facilitates treatment fidelity and the ability to customize interventions and disseminate them widely. ConclusionsSmartLoss functions as a virtual weight management clinic that relies upon empirical weight loss research and behavioral theory to promote behavior change and weight loss.

Published
2016
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14. Total daily energy expenditure has declined over the past three decades due to declining basal expenditure, not reduced activity expenditure.

Author

Speakman, John, de Jong, Jasper, Sinha, Srishti, Westerterp, Klaas, Yamada, Yosuke, Sagayama, Hiroyuki, Ainslie, Philip, Anderson, Liam, Arab, Lenore, Bedu-Addo, Kweku, Blanc, Stephane, Bonomi, Alberto, Bovet, Pascal, Brage, Soren, Buchowski, Maciej, Butte, Nancy, Camps, Stefan, Cooper, Jamie, Cooper, Richard, Das, Sai, Davies, Peter, Dugas, Lara, Ekelund, Ulf, Entringer, Sonja, Forrester, Terrence, Fudge, Barry, Gillingham, Melanie, Ghosh, Santu, Goris, Annelies, Halsey, Lewis, Hambly, Catherine, Haisma, Hinke, Hoffman, Daniel, Hu, Sumei, Joosen, Annemiek, Kaplan, Jennifer, Katzmarzyk, Peter, Kraus, William, Kushner, Robert, Leonard, William, Löf, Marie, Martin, Corby, Matsiko, Eric, Medin, Anine, Meijer, Erwin, Neuhouser, Marian, Nicklas, Theresa, Ojiambo, Robert, Pietiläinen, Kirsi, Plange-Rhule, Jacob, Plasqui, Guy, Prentice, Ross, Racette, Susan, Raichlen, David, Ravussin, Eric, Redman, Leanne, Roberts, Susan, Rudolph, Michael, Sardinha, Luis, Schuit, Albertine, Silva, Analiza, Stice, Eric, Urlacher, Samuel, Valenti, Giulio, Van Etten, Ludo, Van Mil, Edgar, Wood, Brian, Yanovski, Jack, Yoshida, Tsukasa, Zhang, Xueying, Murphy-Alford, Alexia, Loechl, Cornelia, Kurpad, Anura, Luke, Amy, Pontzer, Herman, Rodeheffer, Matthew, Rood, Jennifer, Schoeller, Dale, Wong, William, and Gurven, Michael

Subjects
Male, Female, United States, Humans, Health Expenditures, Exercise, Basal Metabolism, Energy Metabolism, Obesity
Abstract

Obesity is caused by a prolonged positive energy balance1,2. Whether reduced energy expenditure stemming from reduced activity levels contributes is debated3,4. Here we show that in both sexes, total energy expenditure (TEE) adjusted for body composition and age declined since the late 1980s, while adjusted activity energy expenditure increased over time. We use the International Atomic Energy Agency Doubly Labelled Water database on energy expenditure of adults in the United States and Europe (n = 4,799) to explore patterns in total (TEE: n = 4,799), basal (BEE: n = 1,432) and physical activity energy expenditure (n = 1,432) over time. In males, adjusted BEE decreased significantly, but in females this did not reach significance. A larger dataset of basal metabolic rate (equivalent to BEE) measurements of 9,912 adults across 163 studies spanning 100 years replicates the decline in BEE in both sexes. We conclude that increasing obesity in the United States/Europe has probably not been fuelled by reduced physical activity leading to lowered TEE. We identify here a decline in adjusted BEE as a previously unrecognized factor.

Published
2023

15. Human Activity Recognition on Time Series Accelerometer Sensor Data using LSTM Recurrent Neural Networks

Author

Odhiambo, Chrisogonas O., Saha, Sanjoy, Martin, Corby K., and Valafar, Homayoun

Subjects
Electrical Engineering and Systems Science - Signal Processing, Computer Science - Human-Computer Interaction, Computer Science - Machine Learning
Abstract

The use of sensors available through smart devices has pervaded everyday life in several applications including human activity monitoring, healthcare, and social networks. In this study, we focus on the use of smartwatch accelerometer sensors to recognize eating activity. More specifically, we collected sensor data from 10 participants while consuming pizza. Using this information, and other comparable data available for similar events such as smoking and medication-taking, and dissimilar activities of jogging, we developed a LSTM-ANN architecture that has demonstrated 90% success in identifying individual bites compared to a puff, medication-taking or jogging activities., Comment: 8 pages, Accepted for publication at 2022 CSCE Conference (SPRINGER NATURE - Research Book Series)

Published
2022

16. Eating disorders in weight-related therapy (EDIT): Protocol for a systematic review with individual participant data meta-analysis of eating disorder risk in behavioural weight management

Author

Jebeile, Hiba, Lister, Natalie B, Libesman, Sol, Hunter, Kylie E, McMaster, Caitlin M, Johnson, Brittany J, Baur, Louise A, Paxton, Susan J, Garnett, Sarah P, Ahern, Amy L, Wilfley, Denise E, Maguire, Sarah, Sainsbury, Amanda, Steinbeck, Katharine, Askie, Lisa, Braet, Caroline, Hill, Andrew J, Nicholls, Dasha, Jones, Rebecca A, Dammery, Genevieve, Grunseit, Alicia M, Cooper, Kelly, Kyle, Theodore K, Heeren, Faith A, Quigley, Fiona, Barnes, Rachel D, Bean, Melanie K, Beaulieu, Kristine, Bonham, Maxine, Boutelle, Kerri N, Branco, Braulio Henrique Magnani, Calugi, Simona, Cardel, Michelle I, Carpenter, Kelly, Cheng, Hoi Lun, Grave, Riccardo Dalle, Danielsen, Yngvild S, Demarzo, Marcelo, Dordevic, Aimee, Eichen, Dawn M, Goldschmidt, Andrea B, Hilbert, Anja, Houben, Katrijn, do Prado, Mara Lofrano, Martin, Corby K, McTiernan, Anne, Mensinger, Janell L, Pacanowski, Carly, do Prado, Wagner Luiz, Ramalho, Sofia M, Raynor, Hollie A, Rieger, Elizabeth, Robinson, Eric, Salvo, Vera, Sherwood, Nancy E, Simpson, Sharon A, Skjakodegard, Hanna F, Smith, Evelyn, Partridge, Stephanie, Tanofsky-Kraff, Marian, Taylor, Rachael W, Van Eyck, Annelies, Varady, Krista A, Vidmar, Alaina P, Whitelock, Victoria, Yanovski, Jack, Seidler, Anna L, and Collaboration, on behalf of the Eating Disorders In weight-related Therapy

Subjects
Biomedical and Clinical Sciences, Nutrition and Dietetics, Health Sciences, Brain Disorders, Obesity, Clinical Research, Mental Illness, Behavioral and Social Science, Eating Disorders, Nutrition, Mental Health, Clinical Trials and Supportive Activities, Prevention, 3.1 Primary prevention interventions to modify behaviours or promote wellbeing, 6.6 Psychological and behavioural, Mental health, Metabolic and endocrine, Stroke, Oral and gastrointestinal, Adult, Adolescent, Humans, Overweight, Feeding and Eating Disorders, Behavior Therapy, Systematic Reviews as Topic, Meta-Analysis as Topic, Eating Disorders In weight-related Therapy (EDIT) Collaboration, General Science & Technology
Abstract

The Eating Disorders In weight-related Therapy (EDIT) Collaboration brings together data from randomised controlled trials of behavioural weight management interventions to identify individual participant risk factors and intervention strategies that contribute to eating disorder risk. We present a protocol for a systematic review and individual participant data (IPD) meta-analysis which aims to identify participants at risk of developing eating disorders, or related symptoms, during or after weight management interventions conducted in adolescents or adults with overweight or obesity. We systematically searched four databases up to March 2022 and clinical trials registries to May 2022 to identify randomised controlled trials of weight management interventions conducted in adolescents or adults with overweight or obesity that measured eating disorder risk at pre- and post-intervention or follow-up. Authors from eligible trials have been invited to share their deidentified IPD. Two IPD meta-analyses will be conducted. The first IPD meta-analysis aims to examine participant level factors associated with a change in eating disorder scores during and following a weight management intervention. To do this we will examine baseline variables that predict change in eating disorder risk within intervention arms. The second IPD meta-analysis aims to assess whether there are participant level factors that predict whether participation in an intervention is more or less likely than no intervention to lead to a change in eating disorder risk. To do this, we will examine if there are differences in predictors of eating disorder risk between intervention and no-treatment control arms. The primary outcome will be a standardised mean difference in global eating disorder score from baseline to immediately post-intervention and at 6- and 12- months follow-up. Identifying participant level risk factors predicting eating disorder risk will inform screening and monitoring protocols to allow early identification and intervention for those at risk.

Published
2023

17. Variation in human water turnover associated with environmental and lifestyle factors

Author

Yamada, Yosuke, Zhang, Xueying, Henderson, Mary ET, Sagayama, Hiroyuki, Pontzer, Herman, Watanabe, Daiki, Yoshida, Tsukasa, Kimura, Misaka, Ainslie, Philip N, Andersen, Lene F, Anderson, Liam J, Arab, Lenore, Baddou, Issad, Bedu-Addo, Kweku, Blaak, Ellen E, Blanc, Stephane, Bonomi, Alberto G, Bouten, Carlijn VC, Bovet, Pascal, Buchowski, Maciej S, Butte, Nancy F, Camps, Stefan G, Close, Graeme L, Cooper, Jamie A, Cooper, Richard, Das, Sai Krupa, Dugas, Lara R, Eaton, Simon, Ekelund, Ulf, Entringer, Sonja, Forrester, Terrence, Fudge, Barry W, Goris, Annelies H, Gurven, Michael, Halsey, Lewis G, Hambly, Catherine, Hamdouchi, Asmaa El, Hoos, Marije B, Hu, Sumei, Joonas, Noorjehan, Joosen, Annemiek M, Katzmarzyk, Peter, Kempen, Kitty P, Kraus, William E, Kriengsinyos, Wantanee, Kushner, Robert F, Lambert, Estelle V, Leonard, William R, Lessan, Nader, Martin, Corby K, Medin, Anine C, Meijer, Erwin P, Morehen, James C, Morton, James P, Neuhouser, Marian L, Nicklas, Theresa A, Ojiambo, Robert M, Pietiläinen, Kirsi H, Pitsiladis, Yannis P, Plange-Rhule, Jacob, Plasqui, Guy, Prentice, Ross L, Rabinovich, Roberto A, Racette, Susan B, Raichlen, David A, Ravussin, Eric, Redman, Leanne M, Reilly, John J, Reynolds, Rebecca M, Roberts, Susan B, Schuit, Albertine J, Sardinha, Luis B, Silva, Analiza M, Sjödin, Anders M, Stice, Eric, Urlacher, Samuel S, Valenti, Giulio, Van Etten, Ludo M, Van Mil, Edgar A, Wells, Jonathan CK, Wilson, George, Wood, Brian M, Yanovski, Jack A, Murphy-Alford, Alexia J, Loechl, Cornelia U, Luke, Amy H, Rood, Jennifer, Westerterp, Klaas R, Wong, William W, Miyachi, Motohiko, Schoeller, Dale A, Speakman, John R, and Consortium§, International Atomic Energy Agency Doubly Labeled Water Database

Subjects
Prevention, Clean Water and Sanitation, Female, Humans, Pregnancy, Exercise, Humidity, Life Style, Social Class, Water, Infant, Newborn, Infant, Child, Preschool, Child, Adolescent, Young Adult, Adult, Middle Aged, Aged, Aged, 80 and over, Drinking, International Atomic Energy Agency (IAEA) Doubly Labeled Water (DLW) Database Consortium§, General Science & Technology
Abstract

Water is essential for survival, but one in three individuals worldwide (2.2 billion people) lacks access to safe drinking water. Water intake requirements largely reflect water turnover (WT), the water used by the body each day. We investigated the determinants of human WT in 5604 people from the ages of 8 days to 96 years from 23 countries using isotope-tracking (2H) methods. Age, body size, and composition were significantly associated with WT, as were physical activity, athletic status, pregnancy, socioeconomic status, and environmental characteristics (latitude, altitude, air temperature, and humidity). People who lived in countries with a low human development index (HDI) had higher WT than people in high-HDI countries. On the basis of this extensive dataset, we provide equations to predict human WT in relation to anthropometric, economic, and environmental factors.

Published
2022

18. Variability in energy expenditure is much greater in males than females

Author

Halsey, Lewis G, Careau, Vincent, Pontzer, Herman, Ainslie, Philip N, Andersen, Lene F, Anderson, Liam J, Arab, Lenore, Baddou, Issad, Bedu-Addo, Kweku, Blaak, Ellen E, Blanc, Stephane, Bonomi, Alberto G, Bouten, Carlijn VC, Bovet, Pascal, Buchowski, Maciej S, Butte, Nancy F, Camps, Stefan GJA, Close, Graeme L, Cooper, Jamie A, Das, Sai Krupa, Cooper, Richard, Dugas, Lara R, Ekelund, Ulf, Entringer, Sonja, Forrester, Terrence, Fudge, Barry W, Goris, Annelies H, Gurven, Michael, Hambly, Catherine, Hamdouchi, Asmaa El, Hoos, Marije B, Hu, Sumei, Joonas, Noorjehan, Joosen, Annemiek M, Katzmarzyk, Peter, Kempen, Kitty P, Kimura, Misaka, Kraus, William E, Kushner, Robert F, Lambert, Estelle V, Leonard, William R, Lessan, Nader, Martin, Corby K, Medin, Anine C, Meijer, Erwin P, Morehen, James C, Morton, James P, Neuhouser, Marian L, Nicklas, Theresa A, Ojiambo, Robert M, Pietiläinen, Kirsi H, Pitsiladis, Yannis P, Plange-Rhule, Jacob, Plasqui, Guy, Prentice, Ross L, Rabinovich, Roberto A, Racette, Susan B, Raichlen, David A, Ravussin, Eric, Reynolds, Rebecca M, Roberts, Susan B, Schuit, Albertine J, Sjödin, Anders M, Stice, Eric, Urlacher, Samuel S, Valenti, Giulio, Van Etten, Ludo M, Van Mil, Edgar A, Wilson, George, Wood, Brian M, Yanovski, Jack, Yoshida, Tsukasa, Zhang, Xueying, Murphy-Alford, Alexia J, Loechl, Cornelia U, Luke, Amy H, Rood, Jennifer, Sagayama, Hiroyuki, Schoeller, Dale A, Westerterp, Klaas R, Wong, William W, Yamada, Yosuke, and Speakman, John R

Subjects
Obesity, Behavioral and Social Science, Affordable and Clean Energy, Adult, Aged, Aging, Animals, Body Composition, Energy Metabolism, Female, Humans, Male, Mammals, Reproduction, Sex Characteristics, DLW, Energetics, Activity, Trait variability, Biological sex, Evolutionary Biology, Anthropology, Archaeology
Abstract

In mammals, trait variation is often reported to be greater among males than females. However, to date, mainly only morphological traits have been studied. Energy expenditure represents the metabolic costs of multiple physical, physiological, and behavioral traits. Energy expenditure could exhibit particularly high greater male variation through a cumulative effect if those traits mostly exhibit greater male variation, or a lack of greater male variation if many of them do not. Sex differences in energy expenditure variation have been little explored. We analyzed a large database on energy expenditure in adult humans (1494 males and 3108 females) to investigate whether humans have evolved sex differences in the degree of interindividual variation in energy expenditure. We found that, even when statistically comparing males and females of the same age, height, and body composition, there is much more variation in total, activity, and basal energy expenditure among males. However, with aging, variation in total energy expenditure decreases, and because this happens more rapidly in males, the magnitude of greater male variation, though still large, is attenuated in older age groups. Considerably greater male variation in both total and activity energy expenditure could be explained by greater male variation in levels of daily activity. The considerably greater male variation in basal energy expenditure is remarkable and may be explained, at least in part, by greater male variation in the size of energy-demanding organs. If energy expenditure is a trait that is of indirect interest to females when choosing a sexual partner, this would suggest that energy expenditure is under sexual selection. However, we present a novel energetics model demonstrating that it is also possible that females have been under stabilizing selection pressure for an intermediate basal energy expenditure to maximize energy available for reproduction.

Published
2022

19. Human total, basal and activity energy expenditures are independent of ambient environmental temperature

Author

Zhang, Xueying, Yamada, Yosuke, Sagayama, Hiroyuki, Ainslie, Philip N, Blaak, Ellen E, Buchowski, Maciej S, Close, Graeme L, Cooper, Jamie A, Das, Sai Krupa, Dugas, Lara R, Gurven, Michael, Hamdouchi, Asmaa El, Hu, Sumei, Joonas, Noorjehan, Katzmarzyk, Peter, Kraus, William E, Kushner, Robert F, Leonard, William R, Martin, Corby K, Meijer, Erwin P, Neuhouser, Marian L, Ojiambo, Robert M, Pitsiladis, Yannis P, Plasqui, Guy, Prentice, Ross L, Racette, Susan B, Ravussin, Eric, Redman, Leanne M, Reynolds, Rebecca M, Roberts, Susan B, Sardinha, Luis B, Silva, Analiza M, Stice, Eric, Urlacher, Samuel S, Van Mil, Edgar A, Wood, Brian M, Murphy-Alford, Alexia J, Loechl, Cornelia, Luke, Amy H, Rood, Jennifer, Schoeller, Dale A, Westerterp, Klaas R, Wong, William W, Pontzer, Herman, Speakman, John R, consortium, the IAEA DLW database, Andersen, Lene F, Anderson, Liam J, Arab, Lenore, Baddou, Issad, Addo, Bedu, Blanc, Stephane, Bonomi, Alberto, Bouten, Carlijn VC, Bovet, Pascal, Branth, Stefan, De Bruin, Niels C, Butte, Nancy F, Colbert, Lisa H, Camps, Stephan G, Dutman, Alice E, Eaton, Simon D, Ekelund, Ulf, Entringer, Sonja, Ebbeling, Cara, Elmståhl, Sölve, Fogelholm, Mikael, Forrester, Terrence, Fudge, Barry W, Harris, Tamara, Heijligenberg, Rik, Goris, Annelies H, Hambly, Catherine, Hoos, Marije B, Jorgensen, Hans U, Joosen, Annemiek M, Kempen, Kitty P, Kimura, Misaka, Kriengsinyos, Watanee, Lambert, Estelle V, Larsson, Christel L, Lessan, Nader, Ludwig, David S, McCloskey, Margaret, Medin, Anine C, Meijer, Gerwin A, Matsiko, Eric, Melse-Boonstra, Alida, Morehen, James C, Morton, James P, Nicklas, Theresa A, Pannemans, Daphne L, Pietiläinen, Kirsi H, Philippaerts, Renaat M, Rabinovich, Roberto A, Reilly, John J, Rothenberg, Elisabet M, Schuit, Albertine J, Schulz, Sabine, and Sjödin, Anders M

Subjects
Nutrition, IAEA DLW database consortium, Human Physiology, Human activity in medical context, Human metabolism
Abstract

Lower ambient temperature (Ta) requires greater energy expenditure to sustain body temperature. However, effects of Ta on human energetics may be buffered by environmental modification and behavioral compensation. We used the IAEA DLW database for adults in the USA (n = 3213) to determine the effect of Ta (-10 to +30°C) on TEE, basal (BEE) and activity energy expenditure (AEE) and physical activity level (PAL). There were no significant relationships (p > 0.05) between maximum, minimum and average Ta and TEE, BEE, AEE and PAL. After adjustment for fat-free mass, fat mass and age, statistically significant (p

Published
2022

22. Protocol to evaluate the effectiveness and cost-effectiveness of an environmental nutrition and physical activity intervention in nurseries (Nutrition and Physical Activity Self Assessment for Child Care - NAP SACC UK): a multicentre cluster randomised controlled trial

Author

Kipping, Ruth, Pallan, Miranda, Hannam, Kim, Willis, Kate, Dobell, Alex, Metcalfe, Chris, Jago, Russell, Johnson, Laura, Langford, Rebecca, Martin, Corby K., Hollingworth, William, Cochrane, Madeleine, White, James, Blair, Pete, Toumpakari, Zoi, Taylor, Jodi, Ward, Dianne, Moore, Laurence, Reid, Tom, Pardoe, Megan, Wen, Liping, Murphy, Marie, Martin, Anne, Chambers, Stephanie, and Simpson, Sharon Anne

Published
2023
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29. Social influences on physical activity for establishing criteria leading to exercise persistence

Author

Mema, Ensela, Spain, Everett S, Martin, Corby K, Hill, James O, Sayer, R Drew, McInvale, Howard D, Evans, Lee A, Gist, Nicholas H, Borowsky, Alexander D, and Thomas, Diana M

Subjects
Prevention, Basic Behavioral and Social Science, Cardiovascular, Behavioral and Social Science, Cancer, Humans, Exercise, Sedentary Behavior, Peer Influence, General Science & Technology
Abstract

Despite well-documented health benefits from exercise, a study on national trends in achieving the recommended minutes of physical activity guidelines has not improved since the guidelines were published in 2008. Peer interactions have been identified as a critical factor for increasing a population's physical activity. The objective of this study is for establishing criteria for social influences on physical activity for establishing criteria that lead to exercise persistence. A system of differential equations was developed that projects exercise trends over time. The system includes both social and non-social influences that impact changes in physical activity habits and establishes quantitative conditions that delineate population-wide persistence habits from domination of sedentary behavior. The model was generally designed with parameter values that can be estimated to data. Complete absence of social or peer influences resulted in long-term dominance of sedentary behavior and a decline of physically active populations. Social interactions between sedentary and moderately active populations were the most important social parameter that influenced low active populations to become and remain physically active. On the other hand, social interactions encouraging moderately active individuals to become sedentary drove exercise persistence to extinction. Communities should focus on increasing social interactions between sedentary and moderately active individuals to draw sedentary populations to become more active. Additionally, reducing opportunities for moderately active individuals to engage with sedentary individuals through sedentary social activities should be addressed.

Published
2022

30. Total energy expenditure is repeatable in adults but not associated with short-term changes in body composition

Author

Rimbach, Rebecca, Yamada, Yosuke, Sagayama, Hiroyuki, Ainslie, Philip N, Anderson, Lene F, Anderson, Liam J, Arab, Lenore, Baddou, Issaad, Bedu-Addo, Kweku, Blaak, Ellen E, Blanc, Stephane, Bonomi, Alberto G, Bouten, Carlijn VC, Bovet, Pascal, Buchowski, Maciej S, Butte, Nancy F, Camps, Stefan GJA, Close, Graeme L, Cooper, Jamie A, Das, Sai Krupa, Dugas, Lara R, Ekelund, Ulf, Entringer, Sonja, Forrester, Terrence, Fudge, Barry W, Goris, Annelies H, Gurven, Michael, Hambly, Catherine, El Hamdouchi, Asmaa, Hoos, Marije B, Hu, Sumei, Joonas, Noorjehan, Joosen, Annemiek M, Katzmarzyk, Peter, Kempen, Kitty P, Kimura, Misaka, Kraus, William E, Kushner, Robert F, Lambert, Estelle V, Leonard, William R, Lessan, Nader, Martin, Corby K, Medin, Anine C, Meijer, Erwin P, Morehen, James C, Morton, James P, Neuhouser, Marian L, Nicklas, Theresa A, Ojiambo, Robert M, Pietiläinen, Kirsi H, Pitsiladis, Yannis P, Plange-Rhule, Jacob, Plasqui, Guy, Prentice, Ross L, Rabinovich, Roberto A, Racette, Susan B, Raichlen, David A, Ravussin, Eric, Reynolds, Rebecca M, Roberts, Susan B, Schuit, Albertine J, Sjödin, Anders M, Stice, Eric, Urlacher, Samuel S, Valenti, Giulio, Van Etten, Ludo M, Van Mil, Edgar A, Wells, Jonathan CK, Wilson, George, Wood, Brian M, Yanovski, Jack, Yoshida, Tsukasa, Zhang, Xueying, Murphy-Alford, Alexia J, Loechl, Cornelia U, Luke, Amy H, Rood, Jennifer, Schoeller, Dale A, Westerterp, Klaas R, Wong, William W, Speakman, John R, and Pontzer, Herman

Subjects
Nutrition, Pediatric, Clinical Research, Obesity, Aetiology, 2.1 Biological and endogenous factors, Metabolic and endocrine, Adipose Tissue, Adult, Bayes Theorem, Body Composition, Child, Databases, Factual, Energy Metabolism, Female, Humans, Isotope Labeling, Longitudinal Studies, Male, Middle Aged, Water, Weight Gain, IAEA DLW Database Consortium
Abstract

Low total energy expenditure (TEE, MJ/d) has been a hypothesized risk factor for weight gain, but repeatability of TEE, a critical variable in longitudinal studies of energy balance, is understudied. We examine repeated doubly labeled water (DLW) measurements of TEE in 348 adults and 47 children from the IAEA DLW Database (mean ± SD time interval: 1.9 ± 2.9 y) to assess repeatability of TEE, and to examine if TEE adjusted for age, sex, fat-free mass, and fat mass is associated with changes in weight or body composition. Here, we report that repeatability of TEE is high for adults, but not children. Bivariate Bayesian mixed models show no among or within-individual correlation between body composition (fat mass or percentage) and unadjusted TEE in adults. For adults aged 20-60 y (N = 267; time interval: 7.4 ± 12.2 weeks), increases in adjusted TEE are associated with weight gain but not with changes in body composition; results are similar for subjects with intervals >4 weeks (N = 53; 29.1 ± 12.8 weeks). This suggests low TEE is not a risk factor for, and high TEE is not protective against, weight or body fat gain over the time intervals tested.

Published
2022

31. Physical activity and fat-free mass during growth and in later life

Author

Westerterp, Klaas R, Yamada, Yosuke, Sagayama, Hiroyuki, Ainslie, Philip N, Andersen, Lene F, Anderson, Liam J, Arab, Lenore, Baddou, Issaad, Bedu-Addo, Kweku, Blaak, Ellen E, Blanc, Stephane, Bonomi, Alberto G, Bouten, Carlijn VC, Bovet, Pascal, Buchowski, Maciej S, Butte, Nancy F, Camps, Stefan GJA, Close, Graeme L, Cooper, Jamie A, Das, Sai K, Cooper, Richard, Dugas, Lara R, Ekelund, Ulf, Entringer, Sonja, Forrester, Terrence, Fudge, Barry W, Goris, Annelies H, Gurven, Michael, Hambly, Catherine, Hamdouchi, Asmaa El, Hoos, Marije B, Hu, Sumei, Joonas, Noorjehan, Joosen, Annemiek M, Katzmarzyk, Peter, Kempen, Kitty P, Kimura, Misaka, Kraus, William E, Kushner, Robert F, Lambert, Estelle V, Leonard, William R, Lessan, Nader, Martin, Corby K, Medin, Anine C, Meijer, Erwin P, Morehen, James C, Morton, James P, Neuhouser, Marian L, Nicklas, Theresa A, Ojiambo, Robert M, Pietiläinen, Kirsi H, Pitsiladis, Yannis P, Plange-Rhule, Jacob, Plasqui, Guy, Prentice, Ross L, Rabinovich, Roberto A, Racette, Susan B, Raichlen, David A, Ravussin, Eric, Reynolds, Rebecca M, Roberts, Susan B, Schuit, Albertine J, Sjödin, Anders M, Stice, Eric, Urlacher, Samuel S, Valenti, Giulio, Van Etten, Ludo M, Van Mil, Edgar A, Wells, Jonathan CK, Wilson, George, Wood, Brian M, Yanovski, Jack, Yoshida, Tsukasa, Zhang, Xueying, Murphy-Alford, Alexia J, Loechl, Cornelia U, Luke, Amy H, Pontzer, Herman, Rood, Jennifer, Schoeller, Dale A, Wong, William W, Speakman, John R, Branth, Stefan, Colbert, Lisa H, De Bruin, Niels C, Dutman, Alice E, Elmståhl, Sölve, Fogelholm, Mikael, Harris, Tamara, Heijligenberg, Rik, Jorgensen, Hans U, Larsson, Christel L, Rothenberg, Elisabet M, McCloskey, Margaret, Meijer, Gerwin A, Pannemans, Daphne L, Schulz, Sabine, Van den Berg-Emons, Rita, Van Gemert, Wim G, and Wilhelmine, W

Subjects
Prevention, Aging, Clinical Research, Nutrition, Adipose Tissue, Adolescent, Adult, Aged, Aged, 80 and over, Body Composition, Child, Child, Preschool, Cross-Sectional Studies, Energy Metabolism, Exercise, Female, Humans, Male, Middle Aged, Young Adult, physical activity level, age, energy expenditure, body composition, doubly labeled water, International Atomic Energy Agency Doubly Labeled Water database group, Engineering, Medical and Health Sciences, Nutrition & Dietetics
Abstract

BackgroundPhysical activity may be a way to increase and maintain fat-free mass (FFM) in later life, similar to the prevention of fractures by increasing peak bone mass.ObjectivesA study is presented of the association between FFM and physical activity in relation to age.MethodsIn a cross-sectional study, FFM was analyzed in relation to physical activity in a large participant group as compiled in the International Atomic Energy Agency Doubly Labeled Water database. The database included 2000 participants, age 3-96 y, with measurements of total energy expenditure (TEE) and resting energy expenditure (REE) to allow calculation of physical activity level (PAL = TEE/REE), and calculation of FFM from isotope dilution.ResultsPAL was a main determinant of body composition at all ages. Models with age, fat mass (FM), and PAL explained 76% and 85% of the variation in FFM in females and males

Published
2021

32. Energy compensation and adiposity in humans

Author

Careau, Vincent, Halsey, Lewis G, Pontzer, Herman, Ainslie, Philip N, Andersen, Lene F, Anderson, Liam J, Arab, Lenore, Baddou, Issad, Bedu-Addo, Kweku, Blaak, Ellen E, Blanc, Stephane, Bonomi, Alberto G, Bouten, Carlijn VC, Buchowski, Maciej S, Butte, Nancy F, Camps, Stefan GJA, Close, Graeme L, Cooper, Jamie A, Das, Sai Krupa, Cooper, Richard, Dugas, Lara R, Eaton, Simon D, Ekelund, Ulf, Entringer, Sonja, Forrester, Terrence, Fudge, Barry W, Goris, Annelies H, Gurven, Michael, Hambly, Catherine, Hamdouchi, Asmaa El, Hoos, Marije B, Hu, Sumei, Joonas, Noorjehan, Joosen, Annemiek M, Katzmarzyk, Peter, Kempen, Kitty P, Kimura, Misaka, Kraus, William E, Kushner, Robert F, Lambert, Estelle V, Leonard, William R, Lessan, Nader, Martin, Corby K, Medin, Anine C, Meijer, Erwin P, Morehen, James C, Morton, James P, Neuhouser, Marian L, Nicklas, Theresa A, Ojiambo, Robert M, Pietiläinen, Kirsi H, Pitsiladis, Yannis P, Plange-Rhule, Jacob, Plasqui, Guy, Prentice, Ross L, Rabinovich, Roberto A, Racette, Susan B, Raichlen, David A, Ravussin, Eric, Reilly, John J, Reynolds, Rebecca M, Roberts, Susan B, Schuit, Albertine J, Sjödin, Anders M, Stice, Eric, Urlacher, Samuel S, Valenti, Giulio, Van Etten, Ludo M, Van Mil, Edgar A, Wells, Jonathan CK, Wilson, George, Wood, Brian M, Yanovski, Jack, Yoshida, Tsukasa, Zhang, Xueying, Murphy-Alford, Alexia J, Loechl, Cornelia U, Luke, Amy H, Rood, Jennifer, Sagayama, Hiroyuki, Schoeller, Dale A, Wong, William W, Yamada, Yosuke, Speakman, John R, and group, the IAEA DLW database

Subjects
Nutrition, Obesity, Clinical Research, Oral and gastrointestinal, Stroke, Metabolic and endocrine, Cancer, Cardiovascular, Affordable and Clean Energy, Adiposity, Energy Intake, Energy Metabolism, Humans, IAEA DLW database group, Homo sapiens, activity, basal metabolic rate, daily energy expenditure, energy compensation, energy management models, exercise, trade-offs, weight loss, Biological Sciences, Medical and Health Sciences, Psychology and Cognitive Sciences, Developmental Biology
Abstract

Understanding the impacts of activity on energy balance is crucial. Increasing levels of activity may bring diminishing returns in energy expenditure because of compensatory responses in non-activity energy expenditures.1-3 This suggestion has profound implications for both the evolution of metabolism and human health. It implies that a long-term increase in activity does not directly translate into an increase in total energy expenditure (TEE) because other components of TEE may decrease in response-energy compensation. We used the largest dataset compiled on adult TEE and basal energy expenditure (BEE) (n = 1,754) of people living normal lives to find that energy compensation by a typical human averages 28% due to reduced BEE; this suggests that only 72% of the extra calories we burn from additional activity translates into extra calories burned that day. Moreover, the degree of energy compensation varied considerably between people of different body compositions. This association between compensation and adiposity could be due to among-individual differences in compensation: people who compensate more may be more likely to accumulate body fat. Alternatively, the process might occur within individuals: as we get fatter, our body might compensate more strongly for the calories burned during activity, making losing fat progressively more difficult. Determining the causality of the relationship between energy compensation and adiposity will be key to improving public health strategies regarding obesity.

Published
2021

33. Daily energy expenditure through the human life course

Author

Pontzer, Herman, Yamada, Yosuke, Sagayama, Hiroyuki, Ainslie, Philip N, Andersen, Lene F, Anderson, Liam J, Arab, Lenore, Baddou, Issaad, Bedu-Addo, Kweku, Blaak, Ellen E, Blanc, Stephane, Bonomi, Alberto G, Bouten, Carlijn VC, Bovet, Pascal, Buchowski, Maciej S, Butte, Nancy F, Camps, Stefan G, Close, Graeme L, Cooper, Jamie A, Cooper, Richard, Das, Sai Krupa, Dugas, Lara R, Ekelund, Ulf, Entringer, Sonja, Forrester, Terrence, Fudge, Barry W, Goris, Annelies H, Gurven, Michael, Hambly, Catherine, Hamdouchi, Asmaa El, Hoos, Marjije B, Hu, Sumei, Joonas, Noorjehan, Joosen, Annemiek M, Katzmarzyk, Peter, Kempen, Kitty P, Kimura, Misaka, Kraus, William E, Kushner, Robert F, Lambert, Estelle V, Leonard, William R, Lessan, Nader, Martin, Corby, Medin, Anine C, Meijer, Erwin P, Morehen, James C, Morton, James P, Neuhouser, Marian L, Nicklas, Teresa A, Ojiambo, Robert M, Pietiläinen, Kirsi H, Pitsiladis, Yannis P, Plange-Rhule, Jacob, Plasqui, Guy, Prentice, Ross L, Rabinovich, Roberto A, Racette, Susan B, Raichlen, David A, Ravussin, Eric, Reynolds, Rebecca M, Roberts, Susan B, Schuit, Albertine J, Sjödin, Anders M, Stice, Eric, Urlacher, Samuel S, Valenti, Giulio, Van Etten, Ludo M, Van Mil, Edgar A, Wells, Jonathan CK, Wilson, George, Wood, Brian M, Yanovski, Jack, Yoshida, Tsukasa, Zhang, Xueying, Murphy-Alford, Alexia J, Loechl, Cornelia, Luke, Amy H, Rood, Jennifer, Schoeller, Dale A, Westerterp, Klaas R, Wong, William W, Speakman, John R, and Consortium§, IAEA DLW Database

Subjects
Aging, Nutrition, Adolescent, Adult, Aged, Aged, 80 and over, Basal Metabolism, Body Composition, Body Weight, Child, Child, Preschool, Energy Metabolism, Exercise, Female, Humans, Infant, Infant, Newborn, Male, Middle Aged, Pregnancy, Young Adult, IAEA DLW Database Consortium, General Science & Technology
Abstract

Total daily energy expenditure ("total expenditure") reflects daily energy needs and is a critical variable in human health and physiology, but its trajectory over the life course is poorly studied. We analyzed a large, diverse database of total expenditure measured by the doubly labeled water method for males and females aged 8 days to 95 years. Total expenditure increased with fat-free mass in a power-law manner, with four distinct life stages. Fat-free mass-adjusted expenditure accelerates rapidly in neonates to ~50% above adult values at ~1 year; declines slowly to adult levels by ~20 years; remains stable in adulthood (20 to 60 years), even during pregnancy; then declines in older adults. These changes shed light on human development and aging and should help shape nutrition and health strategies across the life span.

Published
2021

38. A standard calculation methodology for human doubly labeled water studies.

Author

Speakman, John R, Yamada, Yosuke, Sagayama, Hiroyuki, Berman, Elena SF, Ainslie, Philip N, Andersen, Lene F, Anderson, Liam J, Arab, Lenore, Baddou, Issaad, Bedu-Addo, Kweku, Blaak, Ellen E, Blanc, Stephane, Bonomi, Alberto G, Bouten, Carlijn VC, Bovet, Pascal, Buchowski, Maciej S, Butte, Nancy F, Camps, Stefan GJA, Close, Graeme L, Cooper, Jamie A, Creasy, Seth A, Das, Sai Krupa, Cooper, Richard, Dugas, Lara R, Ebbeling, Cara B, Ekelund, Ulf, Entringer, Sonja, Forrester, Terrence, Fudge, Barry W, Goris, Annelies H, Gurven, Michael, Hambly, Catherine, El Hamdouchi, Asmaa, Hoos, Marije B, Hu, Sumei, Joonas, Noorjehan, Joosen, Annemiek M, Katzmarzyk, Peter, Kempen, Kitty P, Kimura, Misaka, Kraus, William E, Kushner, Robert F, Lambert, Estelle V, Leonard, William R, Lessan, Nader, Ludwig, David S, Martin, Corby K, Medin, Anine C, Meijer, Erwin P, Morehen, James C, Morton, James P, Neuhouser, Marian L, Nicklas, Theresa A, Ojiambo, Robert M, Pietiläinen, Kirsi H, Pitsiladis, Yannis P, Plange-Rhule, Jacob, Plasqui, Guy, Prentice, Ross L, Rabinovich, Roberto A, Racette, Susan B, Raichlen, David A, Ravussin, Eric, Reynolds, Rebecca M, Roberts, Susan B, Schuit, Albertine J, Sjödin, Anders M, Stice, Eric, Urlacher, Samuel S, Valenti, Giulio, Van Etten, Ludo M, Van Mil, Edgar A, Wells, Jonathan CK, Wilson, George, Wood, Brian M, Yanovski, Jack, Yoshida, Tsukasa, Zhang, Xueying, Murphy-Alford, Alexia J, Loechl, Cornelia U, Melanson, Edward L, Luke, Amy H, Pontzer, Herman, Rood, Jennifer, Schoeller, Dale A, Westerterp, Klaas R, Wong, William W, and IAEA DLW database group

Subjects
IAEA DLW database group, doubly labeled water, free-living, total energy expenditure, validation
Abstract

The doubly labeled water (DLW) method measures total energy expenditure (TEE) in free-living subjects. Several equations are used to convert isotopic data into TEE. Using the International Atomic Energy Agency (IAEA) DLW database (5,756 measurements of adults and children), we show considerable variability is introduced by different equations. The estimated rCO2 is sensitive to the dilution space ratio (DSR) of the two isotopes. Based on performance in validation studies, we propose a new equation based on a new estimate of the mean DSR. The DSR is lower at low body masses (

Published
2021

39. Interindividual Differences in Trainability and Moderators of Cardiorespiratory Fitness, Waist Circumference, and Body Mass Responses: A Large-Scale Individual Participant Data Meta-analysis

Author

Bonafiglia, Jacob T., Swinton, Paul A., Ross, Robert, Johannsen, Neil M., Martin, Corby K., Church, Timothy S., Slentz, Cris A., Ross, Leanna M., Kraus, William E., Walsh, Jeremy J., Kenny, Glen P., Goldfield, Gary S., Prud’homme, Denis, Sigal, Ronald J., Earnest, Conrad P., and Gurd, Brendon J.

Published
2022
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45. Human total, basal and activity energy expenditures are independent of ambient environmental temperature

Author

Andersen, Lene F., Anderson, Liam J., Arab, Lenore, Baddou, Issad, Addo, Bedu, Blanc, Stephane, Bonomi, Alberto, Bouten, Carlijn V.C., Bovet, Pascal, Branth, Stefan, De Bruin, Niels C., Butte, Nancy F., Colbert, Lisa H., Camps, Stephan G., Dutman, Alice E., Eaton, Simon D., Ekelund, Ulf, Entringer, Sonja, Ebbeling, Cara, Elmståhl, Sölve, Fogelholm, Mikael, Forrester, Terrence, Fudge, Barry W., Harris, Tamara, Heijligenberg, Rik, Goris, Annelies H., Hambly, Catherine, Hoos, Marije B., Jorgensen, Hans U., Joosen, Annemiek M., Kempen, Kitty P., Kimura, Misaka, Kriengsinyos, Watanee, Lambert, Estelle V., Larsson, Christel L., Lessan, Nader, Ludwig, David S., McCloskey, Margaret, Medin, Anine C., Meijer, Gerwin A., Matsiko, Eric, Melse-Boonstra, Alida, Morehen, James C., Morton, James P., Nicklas, Theresa A., Pannemans, Daphne L., Pietiläinen, Kirsi H., Philippaerts, Renaat M., Rabinovich, Roberto A., Reilly, John J., Rothenberg, Elisabet M., Schuit, Albertine J., Schulz, Sabine, Sjödin, Anders M., Subar, Amy, Tanskanen, Minna, Uauy, Ricardo, Valenti, Giulio, Van Etten, Ludo M., Berg-Emons, Rita Van den, Van Gemert, Wim G., Velthuis-te Wierik, Erica J., Verboeket-van de Venne, Wilhelmine W., Verbunt, Jeanine A., Wells, Jonathan C.K., Wilson, George, Zhang, Xueying, Yamada, Yosuke, Sagayama, Hiroyuki, Ainslie, Philip N., Blaak, Ellen E., Buchowski, Maciej S., Close, Graeme L., Cooper, Jamie A., Das, Sai Krupa, Dugas, Lara R., Gurven, Michael, El Hamdouchi, Asmaa, Hu, Sumei, Joonas, Noorjehan, Katzmarzyk, Peter, Kraus, William E., Kushner, Robert F., Leonard, William R., Martin, Corby K., Meijer, Erwin P., Neuhouser, Marian L., Ojiambo, Robert M., Pitsiladis, Yannis P., Plasqui, Guy, Prentice, Ross L., Racette, Susan B., Ravussin, Eric, Redman, Leanne M., Reynolds, Rebecca M., Roberts, Susan B., Sardinha, Luis B., Silva, Analiza M., Stice, Eric, Urlacher, Samuel S., Van Mil, Edgar A., Wood, Brian M., Murphy-Alford, Alexia J., Loechl, Cornelia, Luke, Amy H., Rood, Jennifer, Schoeller, Dale A., Westerterp, Klaas R., Wong, William W., Pontzer, Herman, and Speakman, John R.

Published
2022
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46. Supporting family meal frequency: Screening Phase results from the Simply Dinner Study

Author

Kerver, Jean M., Brophy-Herb, Holly E., Sturza, Julie, Horodynski, Mildred A., Contreras, Dawn A., Stein, Mara, Garner, Erika, Hebert, Sheilah, Williams, Jessica M., Kaciroti, Niko, Martoccio, Tiffany, Van Egeren, Laurie A., Choi, Hailey, Martin, Corby K., Mitchell, Koi, Dalimonte-Merckling, Danielle, Jeanpierre, L. Alexandra, Robinson, Chelsea A., and Lumeng, Julie C.

Published
2022
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