John D. Sorkin

Time of onset of non-insulin-dependent diabetes mellitus and genetic variation in the β3-adrenergic-receptor gene

BACKGROUND The beta 3-adrenergic receptor is expressed in visceral adipose tissue and is thought to contribute to the regulation of the resting metabolic rate and lipolysis. METHODS To investigate whether mutations in the gene for the beta 3-adrenergic receptor predispose patients to obesity and non-insulin-dependent diabetes mellitus (NIDDM), we studied this gene in 10 Pima Indians by analysis of single-stranded conformational polymorphisms and dideoxy sequence analysis. Association studies were performed in 642 Pima subjects (390 with NIDDM and 252 without NIDDM). RESULTS A missense mutation was identified in the gene for the beta 3-adrenergic receptor that results in the replacement of tryptophan by arginine (Trp64Arg) in the first intracellular loop of the receptor. This mutation was detected with allelic frequencies of 0.31 in Pima Indians, 0.13 in 62 Mexican Americans, 0.12 in 49 blacks, and 0.08 in 48 whites in the United States. Among Pimas, the frequency of the Trp64Arg mutation was similar in nondiabetic and diabetic subjects. However, in subjects homozygous for the mutation the mean (+/- SD) age at the onset of NIDDM was significantly lower (36 +/- 10 years) than in Trp64Arg heterozygotes (40 +/- 10 years) or normal homozygotes (41 +/- 11 years; P = 0.02). Furthermore, subjects with the mutation tended to have a lower adjusted resting metabolic rate (P = 0.14 by analysis of covariance). CONCLUSIONS Pima subjects homozygous for the Trp64Arg beta 3-adrenergic-receptor mutation have an earlier onset of NIDDM and tend to have a lower resting metabolic rate. This mutation may accelerate the onset of NIDDM by altering the balance of energy metabolism in visceral adipose tissue.

Predictors of Progression From Impaired Glucose Tolerance to NIDDM: An Analysis of Six Prospective Studies

Risk factors associated with the progression from impaired glucose tolerance (IGT) to NIDDM were examined in data from six prospective studies. IGT and NIDDM were defined in all studies by World Health Organization (WHO) criteria, and baseline risk factors were measured at the time of first recognition of IGT. The studies varied in size from 177 to 693 participants with IGT, and included men and women followed from 2 to 27 years after the recognition of IGT. Across the six studies, the incidence rate of NIDDM was 57.2/1,000 person-years and ranged from 35.8/1,000 to 87.3/1,000 person-years. Although baseline measures of fasting and 2-h postchallenge glucose levels were both positively associated with NIDDM incidence, incidence rates were sharply higher for those in the top quartile of fasting plasma glucose levels, but increased linearly with increasing 2-h postchallenge glucose quartiles. Incidence rates were higher among the Hispanic, Mexican-American, Pima, and Nauruan populations than among Caucasians. The effect of baseline age on NIDDM incidence rates differed among the studies; the rates did not increase or rose only slightly with increasing baseline age in three of the studies and formed an inverted U in three studies. In all studies, estimates of obesity (including BMI, waist-to-hip ratio, and waist circumference) were positively associated with NIDDM incidence. BMI was associated with NIDDM incidence independently of fasting and 2-h post challenge glucose levels in the combined analysis of all six studies and in three cohorts separately, but not in the three studies with the highest NIDDM incidence rates. Sex and family history of diabetes were generally not related to NIDDM progression. This analysis indicates that persons with IGT are at high risk and that further refinement of risk can be made by other simple measurements. The ability to identify persons at high risk of NIDDM should facilitate clinical trials in diabetes prevention.

Treadmill Exercise Rehabilitation Improves Ambulatory Function and Cardiovascular Fitness in Patients With Chronic Stroke A Randomized, Controlled Trial

Background and Purpose— Physical inactivity propagates disability after stroke through physical deconditioning and learned nonuse. We investigated whether treadmill aerobic training (T-AEX) is more effective than conventional rehabilitation to improve ambulatory function and cardiovascular fitness in patients with chronic stroke. Methods— Sixty-one adults with chronic hemiparetic gait after ischemic stroke (>6 months) were randomized to 6 months (3×/week) progressive T-AEX or a reference rehabilitation program of stretching plus low-intensity walking (R-CONTROL). Peak exercise capacity (Vo2 peak), o2 consumption during submaximal effort walking (economy of gait), timed walks, Walking Impairment Questionnaire (WIQ), and Rivermead Mobility Index (RMI) were measured before and after 3 and 6 months of training. Results— Twenty-five patients completed T-AEX and 20 completed R-CONTROL. Only T-AEX increased cardiovascular fitness (17% versus 3%, &dgr;% T-AEX versus R-CONTROL, P<0.005). Group-by-time analyses revealed T-AEX improved ambulatory performance on 6-minute walks (30% versus 11%, P<0.02) and mobility function indexed by WIQ distance scores (56% versus 12%, P<0.05). In the T-AEX group, increasing training velocity predicted improved Vo2 peak (r=0.43, P<0.05), but not walking function. In contrast, increasing training session duration predicted improved 6-minute walk (r=0.41, P<0.05), but not fitness gains. Conclusions— T-AEX improves both functional mobility and cardiovascular fitness in patients with chronic stroke and is more effective than reference rehabilitation common to conventional care. Specific characteristics of training may determine the nature of exercise-mediated adaptations.

Long-Term Effects of Change in Body Weight on All-Cause Mortality: A Review

Many studies have described body weight as a risk factor for or a predictor of subsequent death. The clear consensus of these population studies is that a quadratic or U-shaped relation exists between weight and death. Furthermore, the nadir of the U, that is, the body weight associated with lowest mortality rate, is generally considerably lower in young adults than in middle-aged or older adults. Many theoretic complexities exist in the interpretation of this finding, including two major potential confounders: 1) because cigarette smoking is associated with low body weight and high mortality rate, decreases in smoking with advancing age could variably distort the association between weight and death at different ages; and 2) serious illness influences weight and death and is more prevalent with age. Results of studies that attempted to control for these complicating factors support the basic finding that body weight associated with minimal mortality rate increases with age. The implication of this result is unexpected and disturbing: If body weight for optimal survival increases with age, then some weight gain over time is not only permissible but can even be recommended for persons who are not overweight in early adult life. A test of this controversial conclusion is to examine persons on two occasions, to compute their changes in body weight, to follow these persons for specific outcomes, and to relate the observed weight changes to outcome. Such studies have the same potential confounders as those noted previously. Why was weight gained or lost? Although most potentially lethal illnesses lead to weight loss, weight gain is also possible (for example, edema in heart failure and inactivity due to illness). Weight may also be lost, however, in a purposeful program of health promotion that includes increased activity and a healthful diet. Unexplained weight loss in older persons is known to be an ominous symptom just as weight loss in elderly rodents is a harbinger of death. Despite these complexities, results of studies that quantify weight change must be examined. This review examines only the effects of weight change on all-cause mortality. Studies of the effects of long-term weight change on diabetes, coronary heart disease, cancer, and cause-specific death will not be reported in detail. Methods Change in weight is sometimes reported in kilograms, sometimes in body mass index (BMI, kg/m2), and sometimes as a percentage. For ease of comparison, data were converted, when feasible, to metric BMI units. It was assumed that the average height of men was 1.75 m (69 in) and of women was 1.63 m [64 in]. This report is limited to all published population studies that 1) assessed change in weight as the independent variable, 2) determined overall mortality rate as the dependent variable, and 3) had not been reported elsewhere in these proceedings. Studies were identified through a comprehensive bibliographic search of the literature. Williamson and Pamuk [1] critically summarized the results of six published studies that specifically purported to show increased longevity in association with long-term weight loss. We report results from 13 other published studies [214]. Their salient characteristics are summarized in Table 1. Publications [214] should be referred to for more detailed descriptions. The order of presentation was determined alphabetically by author. Descriptors included in the tables are not repeated in the brief summaries that follow. Table 1. Studies Reporting Change in Weight and All-Cause Mortality* Each study examined participants at two distinct periods in life. In the first, changes in body weight were determined; in the second, mortality rates were determined. In addition, 7 of the 13 studies included a period of temporal separation in the analytic scheme (Table 1). Although monitoring for death started at the end of the weight change period, data from participants who died in the early years of the mortality follow-up period were excluded from the analysis. Thus in the seven studies that included a temporal separation period, persons who had an illness that had caused weight loss and subsequent death were omitted to minimize the effects of serious illness on weight change and death. Results The Paris Prospective Study [2] of civil servants working in the Paris Police Administration computed BMI at 20 years of age from weight at the age of military service and height measured in middle-age at study entry. Participants were divided into quintiles of change in BMI between 20 and 43 to 53 years of age. Minimal mortality (6.7 deaths per 1000 person-years) occurred in the third quintile of BMI change (gains of 2.5 to 4.4 kg/m2). Highest mortality rates (10.8 and 9.3) occurred in the lowest quintile of weight change (a gain of 0.5 kg/m2 and in those who gained the most weight [> 6.5 kg/m2]). The Dutch Longitudinal Study among the Elderly [3], conducted between 1955 and 1957, examined a probability sample of elderly men and women. They were re-examined between 1960 and 1962, and five categories of weight change were then computed. Vital status was ascertained in 1983. Longevity was expressed as the realized probability of dying [3]. Additional analyses were limited to only those participants surviving 2 or more years after the end of the weight-change period. Data were analyzed separately for persons 65 to 74 years old and for those 75 years or older. Separate analyses were done for men and women. Both age groups and sexes showed a quadratic relation between weight change and death, but none of these patterns was statistically significant. The Western Electric Study by Hamm and colleagues [4] was directed primarily at fluctuations in weight and therefore used rather selective and unusual weight-change categories (see Table 1). Of 1959 employees studied, only 178 met the no weight change definition, and 133 met the gain only criteria. Only these groups provided data pertinent to this report. The weight-gain group had a relative mortality risk of 1.4 compared with the no-change group [95% CI, 1.0 to 2.1]. Weight gains averaged 37% and thus represented a serious degree of increase. No data on weight loss or on lesser degrees of weight gain were described in the report. The Framingham Heart Study [5] examined residents of Framingham, Massachusetts, and excluded persons who reported smoking cigarettes at any visit. Participants were placed in one of four BMI change groups. Lowest mortality rates occurred in men and women who gained from 0% to 9% in BMI. Men and women who lost 10% or more and men who lost 0% to 9% had significantly increased mortality rates. An analysis of weight change in this population at an earlier age is presented later in this report. In the Harvard Alumni Study by Lee and Paffenbarger [6], change in weight was monitored after participants had reached ages 35 to 74 years. Weight changes during an earlier phase of the life cycle were reported in a separate report. Participants were divided into five weight-change categories (loss of > 5 kg, loss of 1 to 5 kg, no change [ 1 kg], gain of 1 to 5 kg, and gain of > 5 kg). Relative risks for death (with the no change group set at 1.0) were 1.6, 1.25, 1.0, 1.0, and 1.3 for the five groups, respectively. They further showed similar patterns when analyses were stratified for initial BMI (more and less than 25 kg/m2). When participants were stratified by smoking pattern, nonsmokers showed significantly increased mortality rates in the two weight-loss groups and among those who gained more than 5 kg. Smokers showed the lowest mortality rate with 1 to 5 kg weight gain, and only those who lost more than 5 kg had a significant increase in mortality rate. In the Baltimore Longitudinal Study of Aging [7], change in BMI among community-dwelling volunteers was computed as a slope for each participant from four consecutive measurements made during a period that averaged 3.9 years. A significant (P = 0.05) negative association was noted between weight change and mortality rate; that is, weight loss was associated with increased mortality rate. To test for a quadratic (U-shaped) association, we used further analyses to show that, when participants were divided by quintiles of BMI change (from a loss of > 1.1 kg/m2 to a gain of > 0.8 kg/m2), a corresponding decrease was seen in relative risk for death. The values were 1.00 (referent), 0.94, 0.90, 0.78, and 0.75 for the five groups, respectively. A test for linear trend (orthogonal polynomials) showed the results analyzed by quintiles to be of borderline significance (P = 0.058). The Gothenburg prospective studies [8] combined two separate population studies. In women, a multiple logistic regression analysis showed that change in BMI was negatively associated with death (weight loss predicted death) (P < 0.03); in men, results were similar (P < 0.001). Addition of smoking to the model did not change either result. In addition to the weight-change analysis of persons 55 to 65 years old presented by Harris and colleagues [5], an analysis of the Framingham data based on weight changes occurring between 25 and 44-76 years of age has been published [9]. Highly significant effects of the slope of BMI change with time on total mortality rate were present in men and in women (P < 0.001 for both groups). These findings persisted despite the inclusion of five other risk factors for cardiovascular disease: smoking, serum cholesterol level, systolic blood pressure, glucose tolerance, and physical activity. Results remained statistically significant with temporal separation periods of either 4 or 6 years. The Harvard Alumni Study by Paffenbarger and coworkers [10] measured the height and weight of incoming Harvard freshmen during the years 1916 to 1959. Participants were enrolled in a follow-up study at ages 35 to 74 years, when weight was obtained by questionnaire. They were then placed into quintiles according to chan

Age as independent determinant of glucose tolerance.

It has been proposed that the decline in glucose tolerance with age is not a primary aging effect but is secondary to a combination of other age-associated characteristics, i.e., disease, medication, obesity, central and upper-body fat deposition, and inactivity. To test this hypothesis, we first eliminated from analysis the Baltimore Longitudinal Study of Aging participants with identifiable diseases or medications known to influence glucose tolerance. Seven hundred forty-three men and women, aged 17–92 yr, remained for analysis. As indices of fatness, body mass index and percent body fat were determined. As indices of body fat distribution, waist-hip ratio and subscapular triceps skin-fold ratio were calculated. As indices of fitness, physical activity level, determined by detailed questionnaire, and maximum 02 consumption were calculated. We tested whether the effect of age on glucose tolerance remains when data were adjusted for fatness, fitness, and fat distribution; 2-h glucose values were 6.61, 6.78, and 7.83 mM for young (17–39 yr), middle-aged (40–59 yr), and old (60–92 yr) men and 6.22, 6.22, and 7.28 mM for the three groups of women, respectively. The differences between the young and middle-aged groups were not significant, but the old groups had significantly higher values than young or middle-aged groups. Fatness, fitness, and fat distribution can account for the decline in glucose tolerance from the young adult to the middle-aged years. However, age remains a significant determinant of the further decline in glucose tolerance of healthy old subjects.

Exercise rehabilitation improves functional outcomes and peripheral circulation in patients with intermittent claudication: a randomized controlled trial.

OBJECTIVE: To determine the effects of a 6‐month exercise program on ambulatory function, free‐living daily physical activity, peripheral circulation, and health‐related quality of life (QOL) in disabled older patients with intermittent claudication.

Treadmill Exercise Activates Subcortical Neural Networks and Improves Walking After Stroke A Randomized Controlled Trial

Background and Purpose— Stroke often impairs gait thereby reducing mobility and fitness and promoting chronic disability. Gait is a complex sensorimotor function controlled by integrated cortical, subcortical, and spinal networks. The mechanisms of gait recovery after stroke are not well understood. This study examines the hypothesis that progressive task-repetitive treadmill exercise (T-EX) improves fitness and gait function in subjects with chronic hemiparetic stroke by inducing adaptations in the brain (plasticity). Methods— A randomized controlled trial determined the effects of 6-month T-EX (n=37) versus comparable duration stretching (CON, n=34) on walking, aerobic fitness and in a subset (n=15/17) on brain activation measured by functional MRI. Results— T-EX significantly improved treadmill-walking velocity by 51% and cardiovascular fitness by 18% (11% and −3% for CON, respectively; P<0.05). T-EX but not CON affected brain activation during paretic, but not during nonparetic limb movement, showing 72% increased activation in posterior cerebellar lobe and 18% in midbrain (P<0.005). Exercise-mediated improvements in walking velocity correlated with increased activation in cerebellum and midbrain. Conclusions— T-EX improves walking, fitness and recruits cerebellum-midbrain circuits, likely reflecting neural network plasticity. This neural recruitment is associated with better walking. These findings demonstrate the effectiveness of T-EX rehabilitation in promoting gait recovery of stroke survivors with long-term mobility impairment and provide evidence of neuroplastic mechanisms that could lead to further refinements in these paradigms to improve functional outcomes.

Effects of long-term exercise rehabilitation on claudication distances in patients with peripheral arterial disease: a randomized controlled trial.

PURPOSE To determine if improvements in physical function and peripheral circulation after 6 months of exercise rehabilitation could be sustained over a subsequent 12-month maintenance exercise program in older patients with intermittent claudication. METHODS Seventeen patients randomized to exercise rehabilitation and 14 patients randomized to usual care control completed this 18-month study. Patients exercised three times per week during the first 6 months of a progressive exercise program, followed by two times per week during the final 12 months of a maintenance program. Patients were studied at baseline, 6 months, and 18 months during the study. RESULTS Eighteen months of exercise rehabilitation increased the initial claudication distance by 373 meters (189%) (P <.001), the absolute claudication distance by 358 meters (80%) (P <.001), walking economy by 11% (P <.001), 6-minute walk distance by 10% (P <.001), daily physical activity by 31%, and maximal calf blood flow by 18% (P <.001). These changes were similar to those found after 6 months of exercise rehabilitation (P = NS), and were significantly greater than the changes in the control group throughout the study (P <.05). CONCLUSION Improvements in claudication distances, walking economy, 6-minute walk distance, physical activity level, and peripheral circulation after 6 months of exercise rehabilitation are sustained for an additional 12 months in older patients with intermittent claudication using a less frequent exercise maintenance program.

Randomized Clinical Trial of 3 Types of Physical Exercise for Patients With Parkinson Disease

OBJECTIVE To compare the efficacy of treadmill exercises and stretching and resistance exercises in improving gait speed, strength, and fitness for patients with Parkinson disease. DESIGN A comparative, prospective, randomized, single-blinded clinical trial of 3 types of physical exercise. SETTING The Parkinsons Disease and Movement Disorders Center at the University of Maryland and the Baltimore Veterans Affairs Medical Center, Geriatric Research Education and Clinical Center. PATIENTS A total of 67 patients with Parkinson disease who had gait impairment were randomly assigned to 1 of 3 arms of the trial. INTERVENTIONS; (1) A higher-intensity treadmill exercise (30 minutes at 70%-80% of heart rate reserve), (2) a lower-intensity treadmill exercise (50 minutes at 40%-50% of heart rate reserve), and (3) stretching and resistance exercises (2 sets of 10 repetitions on each leg on 3 resistance machines [leg press, leg extension, and curl]). These exercises were performed 3 times a week for 3 months. MAIN OUTCOME MEASURES The primary outcome measures were gait speed (6-minute walk), cardiovascular fitness (peak oxygen consumption per unit time [