4 resultados para coronary artery disease

em Brock University, Canada


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BACKGROUND: Dyslipidemia is recognized as a major cause of coronary heart disease (CHD). Emerged evidence suggests that the combination of triglycerides (TG) and waist circumference can be used to predict the risk of CHD. However, considering the known limitations of TG, non-high-density lipoprotein (non-HDL = Total cholesterol - HDL cholesterol) cholesterol and waist circumference model may be a better predictor of CHD. PURPOSE: The Framingham Offspring Study data were used to determine if combined non-HDL cholesterol and waist circumference is equivalent to or better than TG and waist circumference (hypertriglyceridemic waist phenotype) in predicting risk of CHD. METHODS: A total of3,196 individuals from Framingham Offspring Study, aged ~ 40 years old, who fasted overnight for ~ 9 hours, and had no missing information on nonHDL cholesterol, TG levels, and waist circumference measurements, were included in the analysis. Receiver Operator Characteristic Curve (ROC) Area Under the Curve (AUC) was used to compare the predictive ability of non-HDL cholesterol and waist circumference and TG and waist circumference. Cox proportional-hazards models were used to examine the association between the joint distributions of non-HDL cholesterol, waist circumference, and non-fatal CHD; TG, waist circumference, and non-fatal CHD; and the joint distribution of non-HDL cholesterol and TG by waist circumference strata, after adjusting for age, gender, smoking, alcohol consumption, diabetes, and hypertension status. RESULTS: The ROC AUC associated with non-HDL cholesterol and waist circumference and TG and waist circumference are 0.6428 (CI: 0.6183, 0.6673) and 0.6299 (CI: 0.6049, 0.6548) respectively. The difference in the ROC AVC is 1.29%. The p-value testing if the difference in the ROC AVCs between the two models is zero is 0.10. There was a strong positive association between non-HDL cholesterol and the risk for non-fatal CHD within each TO levels than that for TO levels within each level of nonHDL cholesterol, especially in individuals with high waist circumference status. CONCLUSION: The results suggest that the model including non-HDL cholesterol and waist circumference may be superior at predicting CHD compared to the model including TO and waist circumference.

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Physical inactivity poses a huge burden on Canada's health care system and is detrimental to the health of Canadians (Katzmarzyk & Janssen, 2004). Walking is a viable option for individuals to become physically active on a daily basis and is in fact the most commonly reported leisure time physical activity. It has been associated with many health benefits including weight loss/weight control, reduced risk of coronary artery disease and diabetes, lowered blood pressure, and improved psychological wellbeing (Brisson & Tudor-Locke, 2004). Specifically, individuals' stage of change, selfefficacy and health related quality of life (HRQL) are three psychological constructs that can be greatly improved with increased physical activity (Dishman, 1991; Penedo & Dahn, 2005; Poag & McAuley, 1992). Public health physical activity recommendations exist but many individuals find these difficult to meet due to overly busy lifestyles (Public Health Agency of Canada, 2003). Pedometers are inexpensive devices that can monitor individual bouts of walking so that the incorporation of physical activity into one's daily life is more plausible. They are also excellent tools for motivation, goalsetting, and immediate feedback (Brisson & Tudor-Locke, 2004). Since many people spend a large proportion of their time at their places of employment, workplaces have begun to be a common site for the development of physical activity interventions. These programs have been growing in popUlarity and have shown numerous benefits for both employees and employers (Voit, 2001). The purpose of the current study was to implement and evaluate the use of a pedometer-based physical activity intervention incorporating goal-setting and physical activity logs in a workplace setting, and to examine the relationship between different types of self-efficacy (task, barrier, and scheduling) and different phases of the intervention. Twenty male participants from a local steel manufacturing plant who exhibited health risk factors (e.g. hypertension, diabetes, etc.) were assigned to one of two groups (group A or group B). All participants were asked to wear pedometers on their waists, record their daily steps, set goals that were outlined on a step-tracking sheet (detennined by their baseline number of steps), and keep track of their work days, wakelbed time, sedentary time, and time spent doing other physical activity. Group A began the intervention immediately following the baseline measures, whereas group B continued with their regular routine for 4 weeks before beginning. Physiological measures (height, weight, blood pressure, relative body fat, waist and hip circumference, and body mass index) were taken and a battery of questionnaires that assessed barrier, task and scheduling self-efficacy, HRQL, and stage of change administered at baseline, week 5 (end of intervention for group A), week 9 (end of intervention for group B; follow-up for group A) and week 13 (follow-up for both groups). Results showed that this workplace physical activity intervention was successful at increasing the participants' daily steps, that task self-efficacy is a significant predictor of participants' exercise adherence during the initial stages of participation (intervention phase), and that the participants felt that this intervention was effective. Finally, further exploratory analyses showed that this intervention was effective for all participants, but most valuable for participants most in need of improvement - that is, those who were most sedentary prior to the intervention. This intervention is an inexpensive use of simple and effective tools (e.g. pedometers), has the potential to attract a wide variety of participants and become a pennanent part of any health promotion initiative.

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The main objective of the present investigation was to continue the research initiated by Hay and colleagues (2004) in examining the efficacy of the Children's Self-Perceptions of Adequacy in and Predilection for Physical Activity (CSAPPA) scale as a proxy for the short form of the Bruininks-Oseretsky Test of Motor Proficiency (BOTMP-SF) in screening for Developmental Coordination Disorder (DCD) in children. To better appreciate DCD knowledge outside Canada, the measurements of this investigation were expanded in Greece. A translated Greek CSAPP A scale and the BOTMP-SF were administered for the first time in Greek children. A second objective was to investigate the relationship between DCD and various risk factors of coronary artery disease (CAD) in Canadian and Greek children. A sample of 591 (Ms=322; Fs=269) Canadian and 392 (Ms=211; Fs=181) Greek children, aged 9 to 13 years, consented to the BOTMP-SF, CSAPP A Scale, participation in physical activity questionnaire, Leger 20-meter Multistage Shuttle Run test, and body fat using bioelectric impedance. Prevalence of DCD in Canada and Greece was 8% and 19%, respectively. Significant agreement (p

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Introduction: The prevalence of coronary artery disease (CAD) is ever increasing in western industrialized societies. An individuals overall risk for CAD may be quantified by integrating a number of factors including, but not limited to, cardiorespiratory fitness, body composition, blood lipid profile and blood pressure. It might be expected that interventions aimed at improving any or all of these independent factors might improve an individual 's overall risk. To this end, the influence of standard endurance type exercise on cardiorespiratory fitness, body composition, blood lipids and blood pressure, and by extension the reduction of coronary risk factors, is well documented. On the other hand, interval training (IT) has been shown to provide an extremely powerful stimulus for improving indices of cardiorespiratory function but the influence of this training type on coronary risk factors is unknown. Moreover, the vast majority of studies investigating the effects of IT on fitness have used laboratory type training protocols. As a result of this, the influence of participation in interval-type recreational sports on cardiorespiratory fitness and coronary risk factors is unknown. Aims: The aim of the present study was to evaluate the effectiveness of recreational ball hockey, a sport associated with interval-type activity patterns, on indices of aerobic function and coronary risk factors in sedentary men in the approximate age range of 30 - 60 years. Individual risk factors were compiled into an overall coronary risk factor score using the Framingham Point Scale (FPS). Methods: Twenty-four sedentary males (age range 30 - 60) participated in the study. Subject activity level was assessed apriori using questionnaire responses. All subjects (experimental and control) were assessed to have been inactive and sedentary prior to participation in the study. The experimental group (43 ± 3 years; 90 ± 3 kg) (n = 11) participated in one season of recreational ball hockey (our surrogate for IT). Member of this group played a total of 16 games during an 11 week span. During this time, the control group (43 ± 2 years; 89 ± 2 kg) (n = 11) performed no training and continued with their sedentary lifestyle. Prior to and following the ball hockey season, experimental and control subjects were tested for the following variables: 1) cardiorespiratory fitness (as V02 Max) 2) blood lipid profile 3) body composition 5) waist to hip ratio 6) blood glucose levels and 7) blood pressure. Subject V02 Max was assessed using the Rockport submaximal walking test on an indoor track. To assess body composition we determined body mass ratio (BMI), % body fat, % lean body mass and waist to hip ratio. The blood lipid profile included high density lipoprotein, low density lipoprotein and total cholesterol levels; in addition, the ratio of total cholesterol to high density was calculated. Blood triglycerides were also assessed. All data were analyzed using independent t - tests and all data are expressed as mean ± standard error. Statistical significance was accepted at p :S 0.05. Results: Pre-test values for all variables were similar between the experimental and control group. Moreover, although the intervention used in this study was associated with changes in some variables for subjects in the experimental group, subjects in the control group did not exhibit any changes over the same time period. BODY COMPOSITION: The % body fat of experimental subjects decreased by 4.6 ± 0.5%, from 28.1 ± 2.6 to 26.9 ± 2.5 % while that of the control group was unchanged at 22.7 ± 1.4 and 22.2 ± 1.3 %. However, lean body mass of experimental and control subjects did not change at 64.3 ± 1.3 versus 66.1 ± 1.3 kg and 65.5 ± 0.8 versus 64.7 ± 0.8 kg, respectively. In terms of body mass index and waist to hip ratio, neither the experimental nor the control group showed any significant change. Respective values for the waist to hip ratio and body mass index (pre and post) were as follows: 1 ± 0.1 vs 0.9 ± 0.1 (experimental) and 0.9 ± 0.1 versus 0.9 ± 0.1 (controls) while for BMI they were 29 ± 1.4 versus 29 ± 1.2 (experimental) and 26 ± 0.7 vs. 26 ± 0.7 (controls). CARDIORESPIRATORY FITNESS: In the experimental group, predicted values for absolute V02 Max increased by 10 ± 3% (i.e. 3.3 ± 0.1 to 3.6 ± 0.1 liters min -1 while that of control subjects did not change (3.4 ± 0.2 and 3.4 ± 0.2 liters min-I). In terms of relative values for V02 Max, the experimental group increased by 11 ± 2% (37 ± 1.4 to 41 ± 1.4 ml kg-l min-I) while that of control subjects did not change (41 ± 1.4 and 40 ± 1.4 ml kg-l min-I). BLOOD LIPIDS: Compared to pre-test values, post-test values for HDL were decreased by 14 ± 5 % in the experiment group (from 52.4 ± 4.4 to 45.2 ± 4.3 mg dl-l) while HDL data for the control group was unchanged (49.7 ± 3.6 and 48.3 ± 4.1 mg dl-l, respectively. On the other hand, LDL levels did not change for either the experimental or control group (110.2 ± 10.4 versus 112.3 ± 7.1 mg dl-1 and 106.1 ± 11.3 versus 127 ± 15.1 mg dl-1, respectively). Further, total cholesterol did not change in either the experimental or control group (181.3 ± 8.7 mg dl-1 versus 178.7± 4.9 mg dl-l) and 190.7 ± 12.2 versus 197.1 ± 16.1 mg dl-1, respectively). Similarly, the ratio of TC/HDL did not change for either the experimental or control group (3.8 ± 0.4 versus 4.5 ± 0.5 and 4 ± 0.4 versus 4.2 ± 0.4, respectively). Blood triglyceride levels were also not altered in either the experimental or control group (100.3 ± 19.6 versus 114.8 ± 15.3 mg dl-1 and 140 ± 23.5 versus 137.3 ± 17.9 mg dl-l, respectively). BLOOD GLUCOSE: Fasted blood glucose levels did not change in either the experimental or control group. Pre- and post-values for experimental and control groups were 92.5 ± 4.8 versus 93.3 ± 4.3 mg dl-l and 92.3 ± 11.3 versus 93.2 ± 2.6 mg dl-1 , respectively. BLOOD PRESSURE: No aspect of blood pressure was altered in either the experimental or control group. For example, pre- and post-test systolic blood pressures were 131 ± 2 versus 129 ± 2 mmHg (experimental) and 123 ± 2 and 125 ± 2 mmHg (controls), respectively. Pre- and post-test diastolic blood pressures were 84 ± 2 and 83 ± 2 mmHg (experimental) and 81 ± 1 versus 82 ± 1 mmHg, respectively. Similarly, calculated pulse pressure was not altered in the experimental or control as pre- and post-test values were 47 ± 1 versus 47 ± 2 mmlHg and 42 ± 2 versus 43 ± 2 mmHg, respectively. FRAMINGHAM POINT SCORE: The concerted changes reported above produced an increased risk in the Framingham Point Score for the subjects in the experimental group. For example, the pre- and post-test FPS increased from 1.4 ± 0.9 to 2.7 ± 0.7. On the other hand, pre- and post-test scores for the control group were 1.8 ± 1 versus 1.8 ± 0.9. Conclusions: Our data confirms previous studies showing that interval-type exercise is a useful intervention for increasing aerobic fitness. Moreover, the increase in V02 Max we found in response to limited participation in ball hockey (i.e. 16 games) suggests that recreational sport may help reduce this aspect of coronary risk in previously sedentary individual. On the other hand, our results showing little or no positive change in body composition, blood lipids or blood pressures suggest that one season of recreational sport in not in of itself a powerful enough stimulus to reduce the overall risk of coronary artery disease. In light of this, it is recommended that, in addition to participation in recreational sport, the performance of regular physical activity is used as an adjunct to provide a more powerful overall stimulus for decreasing coronary risk factors. LIMITATIONS: The increase in the FPS we found for the experimental group, indicative of an increased risk for coronary disease, was largely due to the large decrease in HDL we observed after compared to above one season of ball hockey. In light of the fact that cardiorespiratory fitness was increased and % body fat was decreased, as well as the fact that other parameters such as blood pressure showed positive (but non statistically significant) trends, the possibility that the decrease in HDL showed by our data was anomalous should be considered. FUTURE DIRECTIONS: The results of this study suggesting that recreational sport may be a potentially useful intervention in the reduction of CAD require to be corroborated by future studies specifically employing 1) more rigorous assessment of fitness and fitness change and 2) more prolonged or frequent participants.