Obesity is an epidemic that threatens the health of millions of people worldwide and is a major risk factor for cardiovascular diseases, hypertension, diabetes, and dyslipidemia. There are multiple and complex mechanisms to explain how obesity can cause cardiovascular disease. In recent years, studies have shown some limitations in the way we currently define obesity and assess adiposity. This review focuses on the mechanisms involved in the cardiometabolic consequences of obesity and on the relationship between obesity and cardiovascular comorbidities, and provides a brief review of the latest studies focused on normal weight obesity and the obesity paradox.
BackgroundParticipation in cardiac rehabilitation (CR) is an essential component of care for patients with coronary artery disease. However, little is known about its benefit on cardiovascular outcomes in patients with diabetes mellitus (DM) who have undergone percutaneous coronary intervention. The aim of our study was to evaluate the impact of CR in this high‐risk group of patients.Methods and ResultsWe performed a retrospective analysis of all patients with DM who underwent percutaneous coronary intervention in Olmsted County (Minnesota) between 1994 and 2010, assessing the impact of CR participation on clinical outcomes. CR participation was significantly lower in patients with DM (38%, 263/700) compared with those who did not have DM (45%, 1071/2379; P=0.004). Using propensity score adjustment, we found that in patients with DM, CR participation was associated with significantly reduced all‐cause mortality (hazard ratio, 0.56; 95% confidence interval, 0.39–0.80; P=0.002) and composite end point of mortality, myocardial infarction, or revascularization (hazard ratio, 0.77; 95% confidence interval, 0.60–0.98; P=0.037), during a median follow‐up of 8.1 years. In patients without DM, CR participation was associated with a significant reduction in all‐cause mortality (hazard ratio, 0.67; 95% confidence interval, 0.55–0.82; P<0.001) and cardiac mortality (hazard ratio, 0.67; 95% confidence interval, 0.47–0.95; P=0.024).Conclusions CR participation after percutaneous coronary intervention is associated with lower all‐cause mortality rates in patients with DM, to a similar degree as for those without DM. However, CR participation was lower in patients with DM, suggesting the need to identify and correct the barriers to CR participation for this higher‐risk group of patients.
Background: Regular exercise is considered a key element to maintain weight loss, but its role to induce weight loss has been controversial. Methods: In this retrospective study of 7237 individuals attending a worksite wellness center from September 2008 to October 2011 to assess predictors of weight loss at 12 months after joining. Upon joining the wellness center, participants completed a survey that assessed for the presence of cardiovascular risk factors, height, weight, self-perceived health behaviors and psychosocial factors using validated 11-point scale items. We limited the sample to 1927 overweight (25 < BMI ≤ 30) and obese (BMI > 30) participants who completed the survey in full at baseline and at 12 months (+/- 90 days). The outcome variable was weight change at 12 months after enrollment. Weight loss was defined as a loss of > 1kg. Results: Of 1927 participants, 998 (52%) were either overweight (n=573; 57%) or obese (n=425; 43%), and 60% were women. Mean (SD) age was 41 (11.5) yr, BMI 30.7 (5.5) kg/m 2 and they visited the wellness center 49 (90) times/year. At 12 months, 416 (42%) of the participants had lost >1 kg and 19% had lost > 5kg. The predictors of weight loss were: baseline BMI, [Odds Ratio (OR)= 1.56 (1.15-2.13); p < .0044] and [OR= 1.75 (1.26-2.44); p < .0010] for BMI between 30-35 and BMI ≥35, vs BMI between 25-29, respectively. In addition, visits/year [OR= 1.60 (1.19-2.16); p < .0010] and [OR= 1.85 (1.37-2.61); p < .0001] for those attending 13-52 sessions and > 52 visits/year, vs ≤ 12 visits/year, respectively. The association persisted after controlling for all covariates (ie, cardiovascular risk factors, self-perceived health behavior and psychosocial factors). The Table shows the results of the multivariate analysis assessing predictors for >1kg weight loss. Neither age, gender, perceived stress, self-perception of being overweight, following a healthy diet, nor history of hypertension, high blood cholesterol or diabetes predicted weight loss. Conclusions: A significant percentage of overweight or obese individuals lose weight after enrolling in a worksite wellness center. Frequency of attendance, baseline BMI, and support for maintaining a healthy living are associated with weight loss. These results suggest interventions to promote usage of wellness centers maybe be beneficial for the obese adult.
Background: Physical activity (PA) prevents cardiovascular (CV) disease and maintains health. It is unclear which factors predict the adoption or maintenance of PA at a worksite wellness center. Methods: To assess the predictors of increase in PA we conducted a retrospective study on 7237 adults attending a worksite wellness center between September 2008 and October 2011. Upon joining the wellness center, participants completed an electronic or paper survey that assessed for the presence of CV risk factors, height, weight, self-perceived health behaviors and psychosocial factors using eleven validated 0-10 point scale. We included 1927 participants who completed the standard survey at the time of enrollment and at 12 months (+/- 90 days). For logistic regression analysis PA increase at 12 months was defined as an increase of ≥2 points of self-reported PA, on a 0 to 10 point scale, or maintenance of a high level of PA at follow up (FU). Results: Mean (SD) age was 38 (11) yr., BMI was 26.93 (6.06) kg/m 2 and 32% were men. From the study sample, 717 (37%) participants increased their PA level or maintained a high level of PA at FU. When comparing people who increased or maintained a high level of PA with the group without improvement or a decline in PA, there were differences in age and BMI: age [39 (11) vs. 38 (11) yr.; p=0.04] and BMI [27.37 (5.92) vs. 26.68 (5.92) kg/m 2 ; p=0.024]. The Table reports the results of the multivariate logistic regression model. While CV risk factors (tobacco use, hyperglycemia/diabetes mellitus, and high blood cholesterol), perceived stress level and self-perception of being overweight were not significant predictors of increase PA, low muscular strength and flexibility and interactions with close friends were significantly associated with PA. Conclusion: A significant proportion of people, over one-third, enrolled in a wellness center increase their PA level or maintain high levels of PA at 12 months after enrollment. Increasing age and BMI, and a measure of social support; interaction with close friends, and perceived muscular strength and flexibility, predict increase in PA. Presence of CV risk factors do not predict increase in PA. Tailoring programs to address these domains may help younger, less fit, and those with less social support improve their PA level.
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