Biomedical subjects

K C Cain

Publications and source records attributed to K C Cain.

11 recordsLinked to original sources

PubMed1992

Analysing the relationship between change in a risk factor and risk of disease.

There are numerous examples in the epidemiologic literature of analyses that relate the change in a risk factor, such as serum cholesterol, to the risk of an adverse outcome, such as heart disease. Many of these analyses fit some type of regression model (such as logistic regression or the Cox model for survival time data) that includes both the change in the risk factor and the baseline value as covariates. We show that this method of adjusting for the baseline level can produce misleading results. The problem occurs when the true value of the risk factor relates to the outcome, and the measured value differs from the true value due to measurement error. We may find the observed change in the risk factor significantly related to the outcome when there is in fact no relationship between the true change and the outcome. If the question of interest is whether a person who lowers his level of the risk factor by means of drugs or lifestyle changes will thereby reduce his risk of disease, then we should consider an association due solely to measurement error as spurious. We present a method that adjusts for the measurement error in a linear regression analysis and show that an analogous adjustment applies asymptotically to logistic regression. As in other errors-in-variables problems, this analysis depends on knowledge of the relative variances of the random variation, the true baseline value, and the true change. Since the magnitudes of these variances are usually unknown and sometimes unknowable (the distinction between true change and measurement error being ambiguous), we recommend a sensitivity analysis that examines how the analysis results depend on the assumptions concerning the variances. The commonly used analysis method corresponds to the extreme case in which there is no measurement error. We use data from the Framingham Study and simulations to illustrate these points.

Bias↗

PubMed1992

Effect of intensive endurance training on lipoprotein profiles in young and older men.

Although there are considerable data concerning the effects of endurance exercise training (ET) on plasma lipoproteins, the results have been quite inconsistent. The observed variability of response may be related to the age, sex, adiposity, or diet of the subjects tested, or to the type and intensity of the exercise intervention. Furthermore, there is relatively little such data in older individuals. Therefore, in the present study, we investigated the effects of intensive ET on lipoprotein profiles in healthy young (n = 12; 28.2 +/- 2.4 years) and older (n = 15; 67.5 +/- 5.8 years) men. Unlike subjects in most similar studies, our subjects were weight-stabilized on a constant-composition diet for 21 days prior to determination of the lipoprotein profile before and after the ET program. At baseline, the two groups were not significantly different with respect to any individual component of their lipoprotein profiles, relative weight, or percent body fat, but the older men had a more central distribution of fat by both waist to hip ratio (WHR) and computed tomography (CT). Maximal aerobic power, expressed per kilogram of body weight (VO2 max), was 33% lower (P less than .001) in the older men at baseline. Following the 6-month, walk/jog/bike ET program (5 d/wk), both the young (+18%, P less than .001) and the older (+22%, P less than .001) men increased their VO2 max. This was associated with small, but significant, decrements in weight, percent body fat, and WHR only in the older men.(ABSTRACT TRUNCATED AT 250 WORDS)

Adult↗

PubMed1992

Fibrinolytic response during exercise and epinephrine infusion in the same subjects.

To determine whether exercise-induced increases in tissue plasminogen activator (t-PA) were related to plasma epinephrine concentration during exercise, 14 healthy men (aged 24 to 62 years) were studied during epinephrine infusions (10, 25 and 50 ng/kg per min) and graded supine bicycle exercise, beginning at 33 W and increasing in 33-W increments until exhaustion. Plasma epinephrine, active and total t-PA, active plasminogen activator inhibitor type 1 (PAI-1) and t-PA/PAI-1 complex concentrations were measured at each exercise and infusion level. During epinephrine infusion, active and total t-PA levels increased linearly with the plasma epinephrine concentration (respective slopes [+/- SEM] of 0.062 +/- 0.003 and 0.076 +/- 0.003 pmol/ng epinephrine). During exercise, t-PA levels did not increase until plasma epinephrine levels increased, after which both active and total t-PA levels again increased linearly with the plasma epinephrine concentration, but at twice the rate observed with epinephrine infusion (0.131 +/- 0.005 and 0.147 +/- 0.005 pmol/ng, respectively). The t-PA level in blood was directly proportional to the plasma epinephrine concentration during both exercise and epinephrine infusion, suggesting that epinephrine release during exercise stimulates t-PA secretion. In these healthy subjects, active plasminogen activator inhibitor type 1 and t-PA/PAI-1 complex levels were low (41 +/- 11 and 21 +/- 5 pmol/liter, respectively) and did not change significantly during exercise or epinephrine infusion. It is concluded that approximately 50% of the increase in t-PA during exercise is due to stimulated release of t-PA by epinephrine.(ABSTRACT TRUNCATED AT 250 WORDS)

Adult↗

PubMed1992

Can small-area analysis detect variation in surgery rates? The power of small-area variation analysis.

A variety of statistical methods can be used in small-area analysis to test whether there is more variation than would be expected by chance alone. However, the power of these methods to detect existing variation has never been studied. The authors used data regarding back surgery in Washington State to suggest several types of variation that might exist (alternative hypotheses), and then used computer simulation to determine the power, or the probability of detecting this variation. The chi-square test had the highest power of all methods considered against most alternative hypotheses. Power is higher if there are no multiple admissions, rates are higher, and counties have larger or similar population size. Problems of accounting for multiple admissions, adjustment for age and sex, choosing the optimum size of small areas, and detection of outliers also are discussed.

Age Factors↗

PubMed1992

Exercise training delineates the importance of B-cell dysfunction to the glucose intolerance of human aging.

Aging has been associated with glucose intolerance, insulin resistance, hyperinsulinemia, and diminished islet B-cell function. The relative contribution of these factors to the aging-associated changes in glucose tolerance has been difficult to discern, particularly so for B-cell function, since insulin sensitivity itself is a determinant of B-cell function and, therefore, comparisons of insulin levels and responses between old and young subjects are difficult. To reduce this effect, we compared B-cell function in 14 healthy older men (aged 61-82 yr; body mass index, 21-30 kg/m2), who were exercise trained for 6 months to improve insulin sensitivity, to that of 11 healthy young men (aged 24-31 yr; body mass index, 19-31 kg/m2), who were also trained. Insulin-glucose interactions were assessed by measuring indices of insulin sensitivity (SI) and glucose effectiveness at zero insulin (GEZI) using Bergman's minimal model. B-Cell function was assessed by determining the acute insulin responses (AIR) to glucose (AIRgluc) and arginine at 3 different glucose levels: fasting, approximately 14 mM, and greater than 28 mM (AIRmax). AIRmax provides a measure of B-cell secretory capacity, while the glucose level at which 50% of AIRmax occurs is termed PG50 and is used to estimate B-cell sensitivity to glucose. The insulin sensitivity and glucose effectiveness at zero insulin of the trained older subjects was similar to that of the trained young [SI: old, 5.1 +/- 0.6; young, 6.5 +/- 0.7 x 10(-5) min-1/pM (mean +/- SEM; P = NS); GEZI: old, 1.3 +/- 0.2; young, 1.7 +/- 0.2 x 10(-2) min (P = NS)]. Under these conditions, the fasting glucose levels (old, 5.4 +/- 0.2; young, 5.1 +/- 0.1 mM) and basal insulin levels (old, 49 +/- 6; young, 63 +/- 11 pM) were also similar in the two groups. AIRgluc values were lower in the exercised elderly (old, 253 +/- 50; young, 543 +/- 101 pM; P = 0.01). This decrease in stimulated insulin release was due solely to a reduction in the AIRmax (old, 1277 +/- 179; young, 2321 +/- 225 pM; P less than 0.005); the PG50 was not different (old, 8.9 +/- 0.4; young, 8.8 +/- 0.2 mM; P = NS). These differences in the older subjects were associated with a reduction in iv glucose tolerance (old, 1.49 +/- 0.15; young, 1.95 +/- 0.13%/min; P less than 0.05).(ABSTRACT TRUNCATED AT 400 WORDS)

Adult↗

PubMed1992

Testing the null hypothesis in small area analysis.

The goal of small area analysis is often to demonstrate that hospital admission rates or procedure rates vary greatly among regions, suggesting the occurrence of unnecessary admissions or procedures in some regions. Recent articles have shown that such variation may be largely due to chance, even if no underlying differences exist among the small areas; thus, it is important to test if the observed variation is larger than expected by chance. In this article we discuss how the appropriate method for testing the null hypothesis depends on the distribution of the number of admissions at the person level. If it is not possible for an individual to have more than one admission for a given procedure, the appropriate test is a simple chi-square test. If multiple admissions are possible, a modified chi-square test can be used to account for the excess variability due to multiple admissions. Failure to make the correct modification to the chi-square test in this latter case can result in spurious results. This underscores the importance of collecting data on multiple admissions in order to estimate the distribution of the number of admissions at the individual-patient level.

Analysis of Variance↗

PubMed1991

The effect of intensive endurance exercise training on body fat distribution in young and older men.

Little is known about the effects of exercise interventions on the distribution of central and/or intra-abdominal (IA) fat, and until now there were no studies in the elderly. Therefore, in this study we investigated the effects of an intensive 6-month endurance training program on overall body composition (hydrostatic weighing), fat distribution (body circumferences), and specific fat depots (computed tomography [CT]), in healthy young (n = 13; age, 28.2 +/- 2.4 years) and older (n = 15; age, 67.5 +/- 5.8 years) men. At baseline, overall body composition was similar in the two groups, except for a 9% smaller fat free mass in the older men (P less than .05). The thigh and arm circumferences were smaller (P = .001 and P less than .05, respectively), while the waist to hip ratio (WHR) was slightly greater in the older men (0.92 +/- 0.04 v 0.97 +/- 0.04, P less than .01). Compared with the relatively small baseline differences in body composition and circumferences, CT showed the older men to have a twofold greater IA fat depot (P less than .001), 48% less thigh subcutaneous (SC) fat (P less than .01), and 21% less thigh muscle mass (P less than .001). Following endurance (jog/bike) training, both the young (+18%, P less than .001) and the older men (+22%, P less than .001) significantly increased their maximal aerobic power (VO2max). This was associated with small but significant decrements in weight, percent body fat, and fat mass (all P less than .001) only in the older men.(ABSTRACT TRUNCATED AT 250 WORDS)

Abdomen↗

PubMed1991

Effects of physical conditioning on fibrinolytic variables and fibrinogen in young and old healthy adults.

BACKGROUND: The effects of 6 months of intensive endurance exercise training on resting tissue-type plasminogen activator (t-PA) activity, plasminogen activator inhibitor type 1 (PAI-1) activity, t-PA antigen, and fibrinogen were studied in 10 young (24-30 years) and in 13 old male subjects (60-82 years). METHODS AND RESULTS: After training, maximum oxygen consumption was increased in the young group by 18% (44.9 +/- 5.0 to 52.9 +/- 6.6 ml/kg/min, p less than 0.001), whereas it was increased in the old group by 22% (29.0 +/- 4.2 to 35.5 +/- 3.6 ml/kg/min, p less than 0.001). The young group had no significant changes in any of the measured variables, whereas the old group had a 39% increase in t-PA activity (0.82 +/- 0.47 to 1.14 +/- 0.42 IU/ml, p less than 0.03), a 141% increase in the percentage of t-PA in the active form (11.1 +/- 7.7 to 26.8 +/- 15.1%, p less than 0.01), a 58% decrease in PAI-1 activity (8.4 +/- 4.9 to 3.5 +/- 1.7 AU/ml, p less than 0.01), and a 13% decrease in fibrinogen (3.57 +/- 0.79 to 3.11 +/- 0.52 g/l, p less than 0.01). CONCLUSIONS: We conclude that intensive exercise training enhances resting t-PA activity and reduces fibrinogen and PAI-1 activity in older men. These effects are potential mechanisms by which habitual physical activity might reduce the risk of cardiovascular disease.

Adult↗

PubMed1990

Body fat distribution in healthy young and older men.

Central and/or intraabdominal (IA) fat is an independent predictor of obesity-related metabolic abnormalities in young and middle-aged subjects. The elderly are "fatter" at any given relative weight and often have similar metabolic abnormalities. In this study we compare body composition, circumferences, and specific fat depots areas in a population of healthy young and older men. Although the two groups were similar in body mass index and percent body fat, their distribution of adiposity was different. The young subjects had 16% and 10% larger thigh (p = .0001) and arm (p less than .01) circumferences respectively, while the ratio of waist-to-hip circumference was greater in the older subjects (0.93 +/- 0.04 vs 0.97 +/- 0.04, p = less than .01). The most striking differences between the groups were noted on computed tomography, with a twofold greater IA fat area (72.6 +/- 38.2 vs 143.6 +/- 56.2 cm2, p less than .0001), and a twofold lesser thigh subcutaneous fat area (156.3 +/- 69.3 vs 82.4 +/- 29.7 cm2, p less than .001) in the older subjects. We conclude there is an age-related central and intraabdominal redistribution of adipose mass, even in healthy older subjects. Since these changes occur in the absence of clinical disease, the associations between metabolic abnormalities and a central and or IA distribution of adiposity in the elderly must be investigated further.

Adipose Tissue↗

PubMed1990

Effect of exercise on insulin action, glucose tolerance, and insulin secretion in aging.

To assess the effect of exercise training on the insulin resistance and impaired pancreatic B-cell function of aging, we studied 13 healthy older men (ages 61-82 yr) before and after 6 mo intensive endurance exercise. An index of insulin sensitivity (SI) was measured using Bergman's minimal model. Intravenous glucose tolerance was quantified using the glucose disappearance constant (KGlc) while oral glucose tolerance was assessed after a 100-g glucose load. B-cell function was evaluated by measuring the acute insulin response (AIR) to glucose injection at fasting glucose (AIRGlc) and the AIR to arginine at multiple clamped glucose levels. Exercise produced an endurance training effect as demonstrated by an 18% increase in maximum O2 consumption (VO2max) [38.2 +/- 1.4 to 45.0 +/- 1.1 (SE) ml.kg fat-free mass-1.min-1, P less than 0.001]. An unchanged fasting glucose (5.3 +/- 0.2 to 5.4 +/- 0.2 mM) despite a reduced fasting insulin (61 +/- 6 to 48 +/- 6 pM, P less than 0.01) suggested exercise training improved insulin sensitivity. This was confirmed by a 36% increase in SI from 3.47 +/- 0.41 to 4.71 +/- 0.42 x 10(-5) min-1/pM (P = 0.01). Intravenous glucose tolerance did not change as measured by KGlc, which was 1.46 +/- 0.09 before and 1.48 +/- 0.16%/min after exercise training. Likewise, the incremental glucose response to oral glucose (633 +/- 49-618 +/- 45 mM.min) was unchanged. B-cell function was decreased as reflected by AIRGlc (351 +/- 73-245 +/- 53 pM, P less than 0.01) and the AIRArg at maximal glycemic potentiation (AIRmax, 1,718 +/- 260-1,228 +/- 191 pM, P less than 0.005).(ABSTRACT TRUNCATED AT 250 WORDS)

Aged↗

PubMedDate not supplied

Physicians' attitudes toward tube feeding chronically ill nursing home patients.

OBJECTIVE: To determine attitudes of physicians toward the limitation of tube feeding in chronically ill nursing home patients and the influences of patient preferences and other patient and physician variables on these decisions. DESIGN: Questionnaire-based, mailed survey. Hypothetical case scenarios derived by fractional factorial design to determine the influences of patient and family preferences, age, life expectancy, physical and cognitive functioning; direct scaling to determine the influences of legal and cost considerations. PARTICIPANTS: Randomly selected national samples of American Geriatrics Society and American Medical Association members (n = 141, participation rate 41%). MAIN RESULTS: Nearly all physicians indicated they would withhold (95%) or withdraw (92%) tube feeding in at least one of the 16 scenarios studied. Physician decisions were most highly associated with patient preferences, followed by family preferences, life expectancy, and cognitive status (p less than 0.02 to less than 0.001). When patients and families agreed, physicians concurred in 87% to 95% of the decisions. However, when patients and families disagreed, physicians concurred with patients in only 48% to 55% of the decisions. Increasing physician concern regarding legal and cost considerations was significantly associated with significantly higher and lower likelihoods of tube feeding, respectively (p less than 0.05). CONCLUSIONS: These results suggest that the majority of study physicians are willing to limit tube feeding in nursing home patients under some circumstances. Patient preferences appear to be the most important factor in these decisions, but may not be honored, especially if the wishes of patients and their families are not in concurrence.

Attitude of Health Personnel↗