Andrew S. Jackson

Bio: Andrew S. Jackson is an academic researcher from University of Houston. The author has contributed to research in topics: Cardiorespiratory fitness & Physical fitness. The author has an hindex of 39, co-authored 108 publications receiving 12728 citations. Previous affiliations of Andrew S. Jackson include Wake Forest University & Edinburgh Napier University.

Generalized equations for predicting body density of men

Abstract: 1. Skinfold thickness, body circumferences and body density were measured in samples of 308 and ninety-five adult men ranging in age from 18 to 61 years. 2. Using the sample of 308 men, multiple regression equations were calculated to estimate body density using either the quadratic or log form of the sum of skinfolds, in combination with age, waist and forearm circumference. 3. The multiple correlations for the equations exceeded 0.90 with standard errors of approximately +/- 0.0073 g/ml. 4. The regression equations were cross validated on the second sample of ninety-five men. The correlations between predicted and laboratory-determined body density exceeded 0.90 with standard errors of approximately 0.0077 g/ml. 5. The regression equations were shown to be valid for adult men varying in age and fatness.

Generalized equations for predicting body density of women

Abstract: Previous research with women has shown that body composition regression equations derived from anthropometric variables were population specific. This study sought to derive generalized equations for women differing in age and body composition. The hydrostatic method was used to determine body density (BD) and percent fat (%F) on 249 women in 18 to 55 years (X = 31.4 +/- 10.8 yrs) and 4 to 44 %F (X = 24.1 +/-7.2 %F). Skinfold fat (S), gluteal circumference (C) and age were independent variables. The quadratic form of the sum of three, four and seven S in combination with age and gluteal C produced multiple correlations that ranged from 0.842 to 0.867 with standard errors of 3.6 to 3.8 %F. The equations were cross-validated on a different sample of 82 women with similar age and %F characteristics. The correlations between predicted and hydrostatically determined %F ranged from 0.815 to 0.820 with standard errors of 3.7 to 4.0 %F. This study showed that valid generalized body composition equations could be derived for women varying in age and body composition, but care need to be exercised with women over an age of forty.

Practical Assessment of Body Composition

Abstract: In brief: The assessment of body composition has become an important method for determining a desirable body weight of adults and athletes. Hydrostatic weighing is a popular and valid method, but it is often not feasible for the clinical setting or for mass testing; thus, anthropometry has become the preferred method. This article reviews the scientific basis for generalized body composition prediction equations and provides methods for evaluating body composition. The authors recommend using a sum of three skinfolds (triceps, chest, and subscapula for men and triceps, abdomen, and suprailium for women) and give detailed instructions for securing accurate measurements of body fat.

Prediction of functional aerobic capacity without exercise testing.

Abstract: The purpose of this study was to develop functional aerobic capacity prediction models without using exercise tests (N-Ex) and to compare the accuracy with Astrand single-stage submaximal prediction methods. The data of 2,009 subjects (9.7% female) were randomly divided into validation (N = 1,543) and cross-validation (N = 466) samples. The validation sample was used to develop two N-Ex models to estimate VO2peak. Gender, age, body composition, and self-report activity were used to develop two N-Ex prediction models. One model estimated percent fat from skinfolds (N-Ex %fat) and the other used body mass index (N-Ex BMI) to represent body composition. The multiple correlations for the developed models were R = 0.81 (SE = 5.3 ml.kg-1.min-1) and R = 0.78 (SE = 5.6 ml.kg-1.min-1). This accuracy was confirmed when applied to the cross-validation sample. The N-Ex models were more accurate than what was obtained from VO2peak estimated from the Astrand prediction models. The SEs of the Astrand models ranged from 5.5-9.7 ml.kg-1.min-1. The N-Ex models were cross-validated on 59 men on hypertensive medication and 71 men who were found to have a positive exercise ECG. The SEs of the N-Ex models ranged from 4.6-5.4 ml.kg-1.min-1 with these subjects.(ABSTRACT TRUNCATED AT 250 WORDS).

Health benefits of physical activity: the evidence

Abstract: The primary purpose of this narrative review was to evaluate the current literature and to provide further insight into the role physical inactivity plays in the development of chronic disease and premature death. We confirm that there is irrefutable evidence of the effectiveness of regular physical activity in the primary and secondary prevention of several chronic diseases (e.g., cardiovascular disease, diabetes, cancer, hypertension, obesity, depression and osteoporosis) and premature death. We also reveal that the current Health Canada physical activity guidelines are sufficient to elicit health benefits, especially in previously sedentary people. There appears to be a linear relation between physical activity and health status, such that a further increase in physical activity and fitness will lead to additional improvements in health status.

Progression Models in Resistance Training for Healthy Adults

Abstract: In order to stimulate further adaptation toward specific training goals, progressive resistance training (RT) protocols are necessary The optimal characteristics of strength-specific programs include the use of concentric (CON), eccentric (ECC), and isometric muscle actions and the performance of bilateral and unilateral single- and multiple-joint exercises In addition, it is recommended that strength programs sequence exercises to optimize the preservation of exercise intensity (large before small muscle group exercises, multiple-joint exercises before single-joint exercises, and higher-intensity before lower-intensity exercises) For novice (untrained individuals with no RT experience or who have not trained for several years) training, it is recommended that loads correspond to a repetition range of an 8-12 repetition maximum (RM) For intermediate (individuals with approximately 6 months of consistent RT experience) to advanced (individuals with years of RT experience) training, it is recommended that individuals use a wider loading range from 1 to 12 RM in a periodized fashion with eventual emphasis on heavy loading (1-6 RM) using 3- to 5-min rest periods between sets performed at a moderate contraction velocity (1-2 s CON; 1-2 s ECC) When training at a specific RM load, it is recommended that 2-10% increase in load be applied when the individual can perform the current workload for one to two repetitions over the desired number The recommendation for training frequency is 2-3 d·wk -1 for novice training, 3-4 d·wk -1 for intermediate training, and 4-5 d·wk -1 for advanced training Similar program designs are recommended for hypertrophy training with respect to exercise selection and frequency For loading, it is recommended that loads corresponding to 1-12 RM be used in periodized fashion with emphasis on the 6-12 RM zone using 1- to 2-min rest periods between sets at a moderate velocity Higher volume, multiple-set programs are recommended for maximizing hypertrophy Progression in power training entails two general loading strategies: 1) strength training and 2) use of light loads (0-60% of 1 RM for lower body exercises; 30-60% of 1 RM for upper body exercises) performed at a fast contraction velocity with 3-5 min of rest between sets for multiple sets per exercise (three to five sets) It is also recommended that emphasis be placed on multiple-joint exercises especially those involving the total body For local muscular endurance training, it is recommended that light to moderate loads (40-60% of 1 RM) be performed for high repetitions (>15) using short rest periods (<90 s) In the interpretation of this position stand as with prior ones, recommendations should be applied in context and should be contingent upon an individual's target goals, physical capacity, and training status

ACSM Position Stand: The Recommended Quantity and Quality of Exercise for Developing and Maintaining Cardiorespiratory and Muscular Fitness, and Flexibility in Healthy Adults

Abstract: SUMMARYACSM Position Stand on The Recommended Quantity and Quality of Exercise for Developing and Maintaining Cardiorespiratory and Muscular Fitness, and Flexibility in Adults. Med. Sci. Sports Exerc., Vol. 30, No. 6, pp. 975-991, 1998. The combination of frequency, intensity, and duration of chr

Generalized equations for predicting body density of men

Abstract: 1. Skinfold thickness, body circumferences and body density were measured in samples of 308 and ninety-five adult men ranging in age from 18 to 61 years. 2. Using the sample of 308 men, multiple regression equations were calculated to estimate body density using either the quadratic or log form of the sum of skinfolds, in combination with age, waist and forearm circumference. 3. The multiple correlations for the equations exceeded 0.90 with standard errors of approximately +/- 0.0073 g/ml. 4. The regression equations were cross validated on the second sample of ninety-five men. The correlations between predicted and laboratory-determined body density exceeded 0.90 with standard errors of approximately 0.0077 g/ml. 5. The regression equations were shown to be valid for adult men varying in age and fatness.

Obesity and Cardiovascular Disease: Pathophysiology, Evaluation, and Effect of Weight Loss

Abstract: Obesity is becoming a global epidemic in both children and adults. It is associated with numerous comorbidities such as cardiovascular diseases (CVD), type 2 diabetes, hypertension, certain cancers, and sleep apnea/sleep-disordered breathing. In fact, obesity is an independent risk factor for CVD, and CVD risks have also been documented in obese children. Obesity is associated with an increased risk of morbidity and mortality as well as reduced life expectancy. Health service use and medical costs associated with obesity and related diseases have risen dramatically and are expected to continue to rise. Besides an altered metabolic profile, a variety of adaptations/alterations in cardiac structure and function occur in the individual as adipose tissue accumulates in excess amounts, even in the absence of comorbidities. Hence, obesity may affect the heart through its influence on known risk factors such as dyslipidemia, hypertension, glucose intolerance, inflammatory markers, obstructive sleep apnea/hypoventilation, and the prothrombotic state, in addition to as-yet-unrecognized mechanisms. On the whole, overweight and obesity predispose to or are associated with numerous cardiac complications such as coronary heart disease, heart failure, and sudden death because of their impact on the cardiovascular system. The pathophysiology of these entities that are linked to obesity will be discussed. However, the cardiovascular clinical evaluation of obese patients may be limited because of the morphology of the individual. In this statement, we review the available evidence of the impact of obesity on CVD with emphasis on the evaluation of cardiac structure and function in obese patients and the effect of weight loss on the cardiovascular system.