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Zhang D, Spiropoulos KA, Wijayabahu A, Christou DD, Karanth SD, Anton SD, Leeuwenburgh C, Liang M, Wheeler M, Yang D, Livingstone AP, Mankowski RT, Cheng TYD, Zhang H, Siegel EM, Penedo FJ, Licht JD, Braithwaite D. Low muscle mass is associated with a higher risk of all-cause and cardiovascular disease-specific mortality in cancer survivors. Nutrition 2023; 107:111934. [PMID: 36563433 PMCID: PMC10753936 DOI: 10.1016/j.nut.2022.111934] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/01/2022] [Revised: 11/11/2022] [Accepted: 12/06/2022] [Indexed: 12/14/2022]
Abstract
OBJECTIVES Individuals with prior cancer diagnosis are more likely to have low muscle mass (LMM) than their cancer-free counterparts. Understanding the effects of LMM on the prognosis of cancer survivors can be clinically important. The aim of this study was to investigate whether risks for all-cause and cardiovascular disease (CVD)-specific mortality differ by status of LMM in cancer survivors and a matched cohort without cancer history. METHODS We used cohort data from the 1999-2006 and 2011-2014 National Health and Nutrition Examination Survey. Participants included 946 adults surviving for ≥1 since cancer diagnosis and a matched cohort (by age, sex, and race) without cancer history (N = 1857). LMM was defined by appendicular lean mass and body height (men <7.26 kg/m2, women <5.45 kg/m2). Death was ascertained via the National Death Index and cause of death was assessed via International Classification of Diseases, Tenth Revision. Multivariable Cox proportional hazards models were used to estimate adjusted hazard ratio (aHR) and 95% confidence interval (CI) of LMM. RESULTS The mean age of cancer survivors and matched cohort was 60.6 y (SD 15) and 60.2 y (SD 14.9), respectively. The median follow-up was 10.5 y for survivors and 10.9 y for matched cohort. Overall, 22.2% of cancer survivors and 19.7% of the matched cohort had LMM, respectively. In all, 321 survivors (33.9%) and 495 participants (26.7%) in the matched cohort died during follow-up. CVD-specific deaths were identified in 58 survivors (6.1%) and 122 participants in the matched cohort (6.6%). The multivariable Cox model suggested that LMM was positively associated with all-cause (aHR, 1.73; 95% CI, 1.31-2.29) and CVD-specific (aHR, 2.13; 95% CI, 1.14-4.00) mortality in cancer survivors. The associations between LMM and risk for all-cause (aHR, 1.24; 95% CI, 0.98-1.56) and CVD-specific (aHR, 1.21; 95% CI, 0.75-1.93) mortality were not statistically significant in the matched cohort. CONCLUSION Cancer survivors with LMM have an increased risk for all-cause and CVD-specific mortality. This increase appears to be larger than that in counterparts without cancer history.
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Affiliation(s)
- Dongyu Zhang
- Department of Epidemiology, University of Florida College of Public Health and Health Professions, Gainesville, Florida, USA; University of Florida Health Cancer Center, Gainesville, Florida, USA.
| | - Kori A Spiropoulos
- Department of Epidemiology, University of Florida College of Public Health and Health Professions, Gainesville, Florida, USA
| | - Akemi Wijayabahu
- Department of Epidemiology, University of Florida College of Public Health and Health Professions, Gainesville, Florida, USA
| | - Demetra D Christou
- Department of Applied Physiology and Kinesiology, University of Florida College of Health & Human Performance, Gainesville, Florida, USA
| | - Shama D Karanth
- University of Florida Health Cancer Center, Gainesville, Florida, USA; Department of Aging and Geriatric Research, University of Florida College of Medicine, Gainesville, Florida, USA
| | - Stephen D Anton
- Department of Aging and Geriatric Research, University of Florida College of Medicine, Gainesville, Florida, USA
| | - Christiaan Leeuwenburgh
- Department of Aging and Geriatric Research, University of Florida College of Medicine, Gainesville, Florida, USA
| | - Muxuan Liang
- Department of Biostatistics, University of Florida College of Public Health and Health Professions, Gainesville, Florida, USA
| | - Meghann Wheeler
- Department of Epidemiology, University of Florida College of Public Health and Health Professions, Gainesville, Florida, USA
| | - Danting Yang
- Department of Epidemiology, University of Florida College of Public Health and Health Professions, Gainesville, Florida, USA
| | - Aduse-Poku Livingstone
- Department of Epidemiology, University of Florida College of Public Health and Health Professions, Gainesville, Florida, USA
| | - Robert T Mankowski
- Department of Aging and Geriatric Research, University of Florida College of Medicine, Gainesville, Florida, USA
| | - Ting-Yuan David Cheng
- Division of Cancer Prevention and Control, The Ohio State University College of Medicine, Columbus, Ohio, USA
| | - Hanchao Zhang
- Division of Biostatistics, Department of Population Health, New York University School of Medicine, New York, New York, USA
| | - Erin M Siegel
- Department of Cancer Epidemology, H. Lee Moffitt Cancer Center & Research Institute, Tampa, Florida, USA
| | - Frank J Penedo
- Department of Psychology, University of Miami, Miami, Florida, USA; Sylvester Comprehensive Cancer Center, University of Miami, Miami, Florida, USA
| | - Jonathan D Licht
- University of Florida Health Cancer Center, Gainesville, Florida, USA; Division of Hematology and Oncology, University of Florida Health Cancer Center, Gainesville, Florida, USA
| | - Dejana Braithwaite
- Department of Epidemiology, University of Florida College of Public Health and Health Professions, Gainesville, Florida, USA; University of Florida Health Cancer Center, Gainesville, Florida, USA; Department of Surgery, University of Florida College of Medicine, Gainesville, Florida, USA
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Perry RJ, Lyu K, Rabin-Court A, Dong J, Li X, Yang Y, Qing H, Wang A, Yang X, Shulman GI. Leptin mediates postprandial increases in body temperature through hypothalamus-adrenal medulla-adipose tissue crosstalk. J Clin Invest 2020; 130:2001-2016. [PMID: 32149734 DOI: 10.1172/jci134699] [Citation(s) in RCA: 25] [Impact Index Per Article: 6.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/31/2019] [Accepted: 01/14/2020] [Indexed: 02/03/2023] Open
Abstract
Meal ingestion increases body temperature in multiple species, an effect that is blunted by obesity. However, the mechanisms responsible for these phenomena remain incompletely understood. Here we show that refeeding increases plasma leptin concentrations approximately 8-fold in 48-hour-fasted lean rats, and this normalization of plasma leptin concentrations stimulates adrenomedullary catecholamine secretion. Increased adrenal medulla-derived plasma catecholamines were necessary and sufficient to increase body temperature postprandially, a process that required both fatty acids generated from adipose tissue lipolysis and β-adrenergic activation of brown adipose tissue (BAT). Diet-induced obese rats, which remained relatively hyperleptinemic while fasting, did not exhibit fasting-induced reductions in temperature. To examine the impact of feeding-induced increases in body temperature on energy balance, we compared rats fed chronically by either 2 carbohydrate-rich boluses daily or a continuous isocaloric intragastric infusion. Bolus feeding increased body temperature and reduced weight gain compared with continuous feeding, an effect abrogated by treatment with atenolol. In summary, these data demonstrate that leptin stimulates a hypothalamus-adrenal medulla-BAT axis, which is necessary and sufficient to induce lipolysis and, as a result, increase body temperature after refeeding.
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Affiliation(s)
- Rachel J Perry
- Departments of Internal Medicine.,Cellular & Molecular Physiology
| | - Kun Lyu
- Departments of Internal Medicine.,Cellular & Molecular Physiology
| | | | | | - Xiruo Li
- Departments of Internal Medicine.,Cellular & Molecular Physiology
| | | | - Hua Qing
- Departments of Internal Medicine.,Immunobiology, Yale School of Medicine, New Haven, Connecticut, USA
| | - Andrew Wang
- Departments of Internal Medicine.,Immunobiology, Yale School of Medicine, New Haven, Connecticut, USA
| | - Xiaoyong Yang
- Cellular & Molecular Physiology.,Comparative Medicine, and
| | - Gerald I Shulman
- Departments of Internal Medicine.,Cellular & Molecular Physiology
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Molnár PK, Klanjscek T, Derocher AE, Obbard ME, Lewis MA. A body composition model to estimate mammalian energy stores and metabolic rates from body mass and body length, with application to polar bears. J Exp Biol 2009; 212:2313-23. [DOI: 10.1242/jeb.026146] [Citation(s) in RCA: 48] [Impact Index Per Article: 3.2] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/20/2022]
Abstract
SUMMARY
Many species experience large fluctuations in food availability and depend on energy from fat and protein stores for survival, reproduction and growth. Body condition and, more specifically, energy stores thus constitute key variables in the life history of many species. Several indices exist to quantify body condition but none can provide the amount of stored energy. To estimate energy stores in mammals, we propose a body composition model that differentiates between structure and storage of an animal. We develop and parameterize the model specifically for polar bears (Ursus maritimus Phipps)but all concepts are general and the model could be easily adapted to other mammals. The model provides predictive equations to estimate structural mass,storage mass and storage energy from an appropriately chosen measure of body length and total body mass. The model also provides a means to estimate basal metabolic rates from body length and consecutive measurements of total body mass. Model estimates of body composition, structural mass, storage mass and energy density of 970 polar bears from Hudson Bay were consistent with the life history and physiology of polar bears. Metabolic rate estimates of fasting adult males derived from the body composition model corresponded closely to theoretically expected and experimentally measured metabolic rates. Our method is simple, non-invasive and provides considerably more information on the energetic status of individuals than currently available methods.
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Affiliation(s)
- Péter K. Molnár
- Centre for Mathematical Biology, Department of Mathematical and Statistical Sciences, University of Alberta, Edmonton, AB, Canada T6G 2G1
- Department of Biological Sciences, University of Alberta, Edmonton, AB, Canada T6G 2E9
| | - Tin Klanjscek
- Department for Marine and Environmental Research, Ruder BoškovićInstitute, POB. 180, Bijenička 54, HR-10002 Zagreb, Croatia
| | - Andrew E. Derocher
- Department of Biological Sciences, University of Alberta, Edmonton, AB, Canada T6G 2E9
| | - Martyn E. Obbard
- Wildlife Research and Development Section, Ontario Ministry of Natural Resources, DNA Building, Trent University, 2140 East Bank Drive, Peterborough,ON, Canada K9J 7B8
| | - Mark A. Lewis
- Centre for Mathematical Biology, Department of Mathematical and Statistical Sciences, University of Alberta, Edmonton, AB, Canada T6G 2G1
- Department of Biological Sciences, University of Alberta, Edmonton, AB, Canada T6G 2E9
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Jakicic JM. The role of physical activity in prevention and treatment of body weight gain in adults. J Nutr 2002; 132:3826S-3829S. [PMID: 12468633 DOI: 10.1093/jn/132.12.3826s] [Citation(s) in RCA: 68] [Impact Index Per Article: 3.1] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/12/2022] Open
Abstract
Overweight and obesity are increasing in prevalence, and this has resulted in a significant public health burden. Therefore, it is important to identify interventions that prevent weight gain and prevent weight regain after weight loss. Energy expended in physical activity has the potential to affect energy balance, and this can potentially affect body weight regulation. There is some evidence that physical activity can minimize weight gain, and it appears that needs to be moderate to vigorous in intensity to significantly affect body weight. Moreover, it appears that improvements in fitness are associated with reductions in risk of weight gain. Physical activity also is associated with improved maintenance of weight loss. Although it appears that interventions targeting physical activity are necessary to affect weight gain and improve long-term weight loss, the impact of these interventions on other components of energy balance should be examined. In addition, although minimal public health recommendations can significantly affect health outcomes, additional research is needed to identify the optimal dose of physical activity to prevent weight gain and improve long-term weight loss.
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Affiliation(s)
- John M Jakicic
- Physical Activity and Weight Management Research Center, University of Pittsburgh, PA 15261, USA.
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Abstract
Marked abnormalities in cardiovascular structure and hemodynamic function are present both in normotensive and hypertensive obese individuals. Cardiac abnormalities include excentric left ventricular hypertrophy and left atrial dilatation, a finding compatible with the presence of cardiac volume overload. In contrast, hypertension, often associated with abdominal obesity, is characterized by increased peripheral resistance and concentric hypertrophy. Weight reduction can result in marked improvement of ventricular dimensions and cardiac function in patients undergoing massive weight reduction following bariatric surgery. In this paper we review recent findings that have broadened our understanding of cardiovascular hemodynamic function in obesity.
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Affiliation(s)
- R Koch
- Medizinische Klinik, Klinkum Benjamin Franklin, Free University of Berlin, Hindenburgdamm 30, D-12200, Berlin, Germany
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Segal KR, Albu J, Chun A, Edano A, Legaspi B, Pi-Sunyer FX. Independent effects of obesity and insulin resistance on postprandial thermogenesis in men. J Clin Invest 1992; 89:824-33. [PMID: 1541675 PMCID: PMC442927 DOI: 10.1172/jci115661] [Citation(s) in RCA: 47] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/27/2022] Open
Abstract
The putative blunted thermogenesis in obesity may be related to insulin resistance, but insulin sensitivity and obesity are potentially confounding factors. To determine the independent effects of obesity and insulin resistance on the thermic effect of food, at rest and after exercise, lean and obese men were matched at two levels of insulin sensitivity determined by insulin-stimulated glucose disposal (milligrams per kilogram fat-free mass [FFM] per minute) during the euglycemic, hyperinsulinemic (40 mU/m2.min) clamp: 5.4 mg/kg FFM for the lean and obese groups with low insulin sensitivity, and 8.1 mg/kg FFM for the groups with high insulin sensitivity. The two lean groups were matched for percent fat (approximately 15 +/- 1% fat), as were the two obese groups (approximately 33 +/- 2% fat). Energy expenditure was measured for 3 h in the fasting state and for 3 h after a 720-kcal mixed meal, each at rest and immediately after 1 h of cycling at 100 W. The thermic effect of food (TEF) was calculated as the postprandial minus fasting energy expenditure (kcal/3 h) during rest and after exercise. During rest, TEF was blunted by both obesity (24 +/- 5 and 34 +/- 6 kcal/3 h for obese groups with low and high insulin sensitivity vs. 56 +/- 6 and 74 +/- 6 kcal/3 h for the lean groups with low and high insulin sensitivity; P less than 0.01 lean vs. obese) and insulin resistance (insulin-resistant less than insulin-sensitive, at both levels of obesity; P less than 0.01). After exercise, TEF was also impaired in the obese (47 +/- 6 and 44 +/- 5 kcal/3 h for the insulin-resistant and -sensitive groups) and in the lean insulin-resistant (55 +/- 5 kcal/3 h), compared with the lean insulin-sensitive men (71 +/- 3 kcal/3 h), P less than 0.01. Compared with rest, TEF after exercise was improved, but not normalized, in both obese groups (P less than 0.05), but unchanged in the lean groups. These results suggest that both insulin resistance and obesity are independently associated with impaired TEF at rest, but the responsiveness of thermogenesis to exercise before a meal is related to the obese state and not independently to insulin resistance per se.
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Affiliation(s)
- K R Segal
- Department of Pediatrics, Mount Sinai School of Medicine, New York 10029
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