scholarly journals Physical Activity, Cardiorespiratory Fitness and Body Mass Index as Predictors of Substantial Weight Gain and Obesity

2007 ◽  
Vol 98 (2) ◽  
pp. 121-124 ◽  
Author(s):  
Susan E. Brien ◽  
Peter T. Katzmarzyk ◽  
Cora L. Craig ◽  
Lise Gauvin
Author(s):  
Maria do Socorro Simoes ◽  
Fernando Wehrmeister ◽  
Marcello Romiti ◽  
Antonio de Toledo Gagliardi ◽  
Rodolfo Arantes ◽  
...  

We investigated if cardiorespiratory fitness modifies the association between obesity and the level of physical activity. In this cross-sectional study, we analyzed data from 746 adults, free of diagnosed cardiorespiratory or locomotor diseases. We analyzed sociodemographic and clinical information, cardiovascular risk factors, cardiorespiratory fitness, anthropometry, and level of physical activity (time spent in moderate-to-vigorous physical activity). Those that spent more time in moderate-to-vigorous physical activity were younger, male, with lower body mass index, without self-reported arterial blood hypertension, diabetes and dyslipidemia, non-smokers, and presented with better cardiorespiratory fitness. The linear regression coefficients showed that cardiorespiratory fitness changes according to the level of physical activity and body mass index (obesity in low cardiorespiratory fitness: β 6.0, p = 0.213, 95%CI -3.5 to 15.6; in intermediate cardiorespiratory fitness: β 6.3, p = 0.114, 95%CI -1.5 to 14.2; in high cardiorespiratory fitness: β -6.3, p = 0.304, 95%CI -18.4 to 5.8). This effect modification trend was present after adjusting the model by covariates. Cardiorespiratory fitness potentially modifies the association between body mass index and the level of physical activity. It should be routinely assessed to identify persons with overweight/ obesity with low/ intermediate cardiorespiratory fitness to prescribe individualized training.


2010 ◽  
Vol 68 (2) ◽  
pp. 277-281 ◽  
Author(s):  
Camilla N. De Gaspari ◽  
Carlos A.M. Guerreiro

Antiepileptic drugs (AED) may cause body weight changes. OBJECTIVE: To evaluate the dietary habits and body weight associated with AED in epileptic patients. METHOD: Sixty-six patients were subjected to two interviews, and had their weight and body mass index calculated and compared at both times, interval between six to eight months. RESULTS: It was observed that 59.1% showed weight gain. The patients who had no weight gain had a greater proportion of individuals who engaged in some form of physical activity. However, of the 45 patients who maintained their initial dietary and medication pattern, 75.6% recorded a weight gain. Weight gain was seen in 66.7% of patients on carbamazepine (n=18), 60% on valproate (n=5), 50% on carbamazepine+clobazam treatment (n=14), and 58.3% of patients on other(s) polytherapy (n=12). CONCLUSION: The patient should be alerted to possible weight gain, and should be advised about dieting and participating in regular physical activity.


2009 ◽  
Vol 36 (4) ◽  
pp. 379-387 ◽  
Author(s):  
Anelise Reis Gaya ◽  
Alberto Alves ◽  
Luisa Aires ◽  
Clarice Lucena Martins ◽  
José Carlos Ribeiro ◽  
...  

2015 ◽  
Author(s):  
Huakang Tu ◽  
Xia Pu ◽  
Carrie Daniel-MacDougall ◽  
Stephanie C. Melkonian ◽  
Yuanqing Ye ◽  
...  

2019 ◽  
Vol 189 (4) ◽  
pp. 305-313 ◽  
Author(s):  
Maude Wagner ◽  
Francine Grodstein ◽  
Cécile Proust-Lima ◽  
Cécilia Samieri

Abstract Healthy lifestyles are promising targets for prevention of cognitive aging, yet the optimal time windows for interventions remain unclear. We selected a case-control sample nested within the Nurses’ Health Study (starting year 1976, mean age = 51 years), including 14,956 women aged ≥70 years who were free of both stroke and cognitive impairment at enrollment in a cognitive substudy (1995–2001). Cases (n = 1,496) were women with the 10% worst slopes of cognitive decline, and controls (n = 7,478) were those with slopes better than the median. We compared the trajectories of body mass index (weight (kg)/height (m)2), alternate Mediterranean diet (A-MeDi) score, and physical activity between groups, from midlife through 1 year preceding the cognitive substudy. In midlife, cases had higher body mass index than controls (mean difference (MD) = 0.59 units, 95% confidence interval (CI): 0.39, 0.80), lower physical activity (MD = –1.41 metabolic equivalent of task–hours/week, 95% CI: –2.07, –0.71), and worse A-MeDi scores (MD = –0.16 points, 95% CI: –0.26, –0.06). From midlife through later life, compared with controls, cases had consistently lower A-MeDi scores but a deceleration of weight gain and a faster decrease in physical activity. In conclusion, maintaining a healthy lifestyle since midlife may help reduce cognitive decline in aging. At older ages, both deceleration of weight gain and a decrease in physical activity may reflect early signs of cognitive impairment.


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