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Ítalo R. Lemes, Rômulo A. Fernandes, Bruna C. Turi-Lynch, Jamile S. Codogno, Luana C. de Morais, Kelly A.K. Koyama and Henrique L. Monteiro

Metabolic syndrome (MetS) is a cluster of cardiovascular risk factors, including abdominal obesity, dyslipidemia, blood pressure, and elevated fasting glucose (impaired fasting glucose or type 2 diabetes mellitus). MetS is a predictor of cardiovascular disease and type 2 diabetes mellitus. 1

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YoonMyung Kim

Childhood obesity is an epidemic ( 45 ), and it is recognized as a leading health concern due to its strong associations with comorbid conditions, such as impaired glucose tolerance ( 57 ), metabolic syndrome ( 7 ), type 2 diabetes (T2DM) ( 29 , 48 ), and nonalcoholic fatty liver disease (NAFLD

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Kenneth E. Powell, Abby C. King, David M. Buchner, Wayne W. Campbell, Loretta DiPietro, Kirk I. Erickson, Charles H. Hillman, John M. Jakicic, Kathleen F. Janz, Peter T. Katzmarzyk, William E. Kraus, Richard F. Macko, David X. Marquez, Anne McTiernan, Russell R. Pate, Linda S. Pescatello and Melicia C. Whitt-Glover

gain in children, adults, and pregnant women; (4) reduced risk of gestational diabetes and postpartum depression; and (5) reduced risk of fall-related injuries in older people. In addition, there is evidence that physical activity is associated with (1) improved quality of life, (2) improved sleep; (3

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Arya M. Sharma, Donna L. Goodwin and Janice Causgrove Dunn

poor definition of obesity, which is based on BMI. The problem here is that you have two people with the exact same BMI levels, say 35 or what we would say is Stage 2 obesity; one of them can have diabetes, sleep apnea, osteoarthritis, gastroesophageal reflux disease, fatty liver disease, and fertility

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Meghan K. Edwards and Paul D. Loprinzi

heart; (2) malignant neoplasms; (3) chronic lower respiratory diseases; (4) accidents (unintentional injuries); (5) cerebrovascular diseases; (6) Alzheimer’s disease; (7) diabetes mellitus; (8) influenza and pneumonia; (9) nephritis, nephrotic syndrome, and nephrosis; and (10) all other causes (residual

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Xiaomin Sun, Zhen-Bo Cao, Kumpei Tanisawa, Satomi Oshima and Mitsuru Higuchi

et al., 2010 ). These studies suggest that altered vitamin D homeostasis may play a role in the development of insulin resistance and Type 2 diabetes mellitus (T2DM; Afzal et al., 2013 ; Song et al., 2013 ). Prior evidence has shown that circulating 25(OH)D concentrations are not only negatively

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Samuel G. Wittekind, Nicholas M. Edwards, Philip R. Khoury, Connie E. McCoy, Lawrence M. Dolan, Thomas R. Kimball and Elaine M. Urbina

type 2 diabetes mellitus (T2DM) were matched by age, sex, and race to lean [body mass index (BMI) < 85th percentile] and obese (BMI > 95th percentile) control subjects proven nondiabetic by oral glucose tolerance test as part of a study of CV aging. 12 Subjects with valid exposure and outcome data

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Neng Wan, Ming Wen, Jessie X. Fan, O. Fahina Tavake-Pasi, Sara McCormick, Kirsten Elliott and Emily Nicolosi

as obesity, 2 cardiovascular diseases, 3 cancer, 4 – 6 and diabetes. 2 , 7 , 8 For example, PI adults have an 80% higher risk of getting diabetes than the general US population 8 and a 30% higher risk of being diagnosed with cancer than non-Hispanic whites. 9 A recent survey conducted in

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Angelika Wientzek, Anna Floegel, Sven Knüppel, Matthaeus Vigl, Dagmar Drogan, Jerzy Adamski, Tobias Pischon and Heiner Boeing

The aim of our study was to investigate the relationship between objectively measured physical activity (PA) and cardiorespiratory fitness (CRF) and serum metabolites measured by targeted metabolomics in a population- based study. A total of 100 subjects provided 2 fasting blood samples and engaged in a CRF and PA measurement at 2 visits 4 months apart. CRF was estimated from a step test, whereas physical activity energy expenditure (PAEE), time spent sedentary and time spend in vigorous activity were measured by a combined heart rate and movement sensor for a total of 8 days. Serum metabolite concentrations were determined by flow injection analysis tandem mass spectrometry (FIA-MS/MS). Linear mixed models were applied with multivariable adjustment and p-values were corrected for multiple testing. Furthermore, we explored the associations between CRF, PA and two metabolite factors that have previously been linked to risk of Type 2 diabetes. CRF was associated with two phosphatidylcholine clusters independently of all other exposures. Lysophosphatidylcholine C14:0 and methionine were significantly negatively associated with PAEE and sedentary time. CRF was positively associated with the Type 2 diabetes protective factor. Vigorous activity was positively associated with the Type 2 diabetes risk factor in the mutually adjusted model. Our results suggest that CRF and PA are associated with serum metabolites, especially CRF with phosphatidylcholines and with the Type 2 diabetes protective factor. PAEE and sedentary time were associated with methionine. The identified metabolites could be potential mediators of the protective effects of CRF and PA on chronic disease risk.

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Yoshinori Fujiwara, Shoji Shinkai, Shuichiro Watanabe, Shu Kumagai, Takao Suzuki, Hiroshi Shibata, Tanji Hoshi and Toru Kita

This study investigated the effect of chronic medical conditions on changes in functional capacity in Japanese older adults. Participants comprised 1,518 people aged 65-84 living in an urban and a rural community. They were interviewed to determine the presence of chronic medical conditions and assessed for functional capacity using the Tokyo Metropolitan Institute of Gerontology (TMIG) Index of Competence. Follow-up occurred 4 years later. Statistical analysis revealed that self-reported medical conditions at baseline contributed to declines in the TMIG Index over the 4 years, even after participants’ age, sex, educational attainment, and baseline TMIG level were controlled for. In the urban area, chronic obstructive pulmonary disease, diabetes mellitus, and musculoskeletal disease significantly predicted decline in the index, whereas in the rural area, hypertension and diabetes mellitus were significant predictors. These results indicate the importance of controlling chronic medical conditions in order to prevent further declines in functional capacity in older adults.