Reubin Andres

The effect of insulin on renal handling of sodium, potassium, calcium, and phosphate in man.

The effects of insulin on the renal handling of sodium, potassium, calcium, and phosphate were studied in man while maintaining the blood glucose concentration at the fasting level by negative feedback servocontrol of a variable glucose infusion. In studies on six water-loaded normal subjects in a steady state of water diuresis, insulin was administered i.v. to raise the plasma insulin concentration to between 98 and 193 muU/ml and infused at a constant rate of 2 mU/kg body weight per min over a total period of 120 min. The blood glucose concentration was not significantly altered, and there was no change in the filtered load of glucose; glomerular filtration rate (CIN) and renal plasma flow (CPAH) were unchanged. Urinary sodium excretion (UNaV) decreased from 401 plus or minus 46 (SEM) to 213 plus or minus 18 mueq/min during insulin administration, the change becoming significant (P smaller than 0.02) within the 30-60 min collection period. Free water clearance (CH2O) increased from 10.6 plus or minus 0.6 to 13 plus or minus 0.5 ml/min (P smaller than 0.025); osmolar clearance decreased and urine flow was unchanged. There was no change in plasma aldosterone concentration, which was low throughout the studies, and a slight reduction was observed in plasma glucagon concentration. Urinary potassium (UKV) and phosphate (UPV) excretion were also both decreased during insulin administration; UKV decreased from 66 plus or minus 9 to 21 plus or minus 1 mueq/min (P smaller than 0.005), and tupv decreased from 504 plus or minus 93 to 230 plus or minus 43 mug/min (P smaller than 0.01). The change in UKV was associated with a significant reduction in plasma potassium concentration. There was also a statistically significant but small reduction in plasma phosphate concentration which was not considered sufficient alone to account for the large reduction in UPV. Urinary calcium excretion (UCaV) increased from 126 plus or minus 24 to 200 plus or minus 17 mug/min (P smaller than 0.01). These studies demonstrate a reduction in UNaV associated with insulin administration that occurs in the absence of changes in the filtered load of glucose, glomerular filtration rate, renal blood flow, and plasma aldosterone concentration. The effect of insulin on CH2O suggests that insulins effect on sodium excretion is due to enhancement of sodium reabsorption in the diluting segment of the distal nephron.

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.

A Model of the Kinetics of Insulin in Man

The design of the present study of the kinetics of insulin in man combines experimental features which obviate two of the major problems in previous insulin studies. (a) The use of radioiodinated insulin as a tracer has been shown to be inappropriate since its metabolism differs markedly from that of the native hormone. Therefore porcine insulin was administered by procedures which raised insulin levels in arterial plasma into the upper physiologic range. Hypoglycemia was prevented by adjusting the rate of an intravenous infusion of glucose in order to control the blood glucose concentration (the glucose-clamp technique). (b) Estimation of a single biological half-time of insulin after pulse injection of the hormone has been shown to be inappropriate since plasma insulin disappearance curves are multiexponential. Therefore the SAAM 25 computer program was used in order to define the parameters of a three compartment insulin model. The combined insulin mass of the three compartments (expressed as plasma equivalent volume) is equal to inulin space (15.7% body wt). Compartment 1 is apparently the plasma space (4.5%). The other two compartments are extra-vascular; compartment 2 is small (1.7%) and equilibrates rapidly with plasma, and compartment 3 is large (9.5%) and equilibrates slowly with plasma. The SAAM 25 program can simulate the buildup and decay of insulin in compartments 2 and 3 which cannot be assayed directly. Insulin in compartment 3 was found to correlate remarkably with the time-course of the servo-controlled glucose infusion. Under conditions of a steady-state arterial glucose level, glucose infusion is a measure of glucose utilization. We conclude that compartment 3 insulin (rather than plasma insulin) is a more direct determinant of glucose utilization. We suggest that the combined use of glucose-clamp and kinetic-modeling techniques should aid in the delineation of pathophysiologic states affecting glucose and insulin metabolism.

The quantitatively minor role of carbohydrate in oxidative metabolism by skeletal muscle in intact man in the basal state. Measurements of oxygen and glucose uptake and carbon dioxide and lactate production in the forearm.

Skeletal muscle accounts for some 40 per cent of body weight. Presumably, by virtue of its bulk as the largest mass of tissue, its metabolism may be a major factor in total body economy and yet surprisingly little is known of the quantitative characteristics of metabolism of skeletal muscle. Studies of excised muscle and its extracts have provided a rich background relating to the metabolic capabilities of muscle. They have shown a great deal about the apparatus with which muscle is equipped to perform its functions in dissimilating metabolites but they fail to reveal the quantitative importance of particular pathways of dissimilation in the total scheme.

Aging and ethanol metabolism

The effect of aging on the distribution and elimination of ethanol was studied in a group of 50 healthy subjects ranging in age from 21 to 81 yr (mean, 53.3). Ethanol was administered in a continuous 1‐hr infusion at a mean rate of 375 mg/m2 body surface area/min (equivalent to a mean dose of 0.57 gm/kg body weight). Serial blood samples for the determination of ethanol concentration were obtained at 15‐ to 30‐min intervals for up to 4 hr post irifusion. Ethanol elimination and distribution were evaluated with the aid of a two‐compartment model. Rates of ethanol elimination were not affected by age. Peak ethanol concentration in blood water at the end of the infusion period was correlated with age (r = 0.55, p ‐ 0.001). Lean body mass and total volume of distribution of the ethanol were negatively correlated with age. The smaller volume of distribution, in association with the decreased lean body mass, most likely explains the higher peak ethanol concentration found in the blood after administration of an ethanol dose on the basis of surface area in the old as compared with the young subjects. This study demonstrates that age‐related changes in body composition are important factors in the study of ethanol metabolism and its pharmacologic effects.

Glucose Intolerance in Uremia: QUANTIFICATION OF PANCREATIC BETA CELL SENSITIVITY TO GLUCOSE AND TISSUE SENSITIVITY TO INSULIN

The relative contributions of impaired insulin secretion and of tissue insensitivity to insulin to the carbohydrate intolerance of uremia were investigated in 10 chronically uremic subjects. Two types of glucose-clamp experiments were performed in each patient before and after 10 wk of thrice weekly hemodialysis. In both types the blood glucose concentration was maintained at a constant level by the periodic adjustment of a variable glucose infusion with a negative feedback formula.Hyperglycemic clamp. The blood glucose concentration was acutely raised and maintained 125 mg/dl above basal levels for 2 h. Since the glucose concentration was held constant, the glucose infusion rate is an index of glucose metabolism (M). After dialysis M increased in all patients from an average of 4.23 to 6.30 mg/kg body wt per min (P < 0.001). The plasma insulin responses (I) both pre- and postdialysis were biphasic with an early burst within the first 2-5 min, followed by a phase of gradually increasing insulin concentration. After dialysis the plasma insulin response diminished slightly. Consequently, the M/I ratio, an index of tissue sensitivity to endogenous insulin, increased postdialysis in all subjects by an average of 92% (P < 0.01). Euglycemic clamp. The plasma insulin concentration was acutely raised and maintained by a primecontinuous insulin infusion. The blood glucose concentration was held constant at the basal level by a variable glucose infusion as above. M/I again is a measure of tissue sensitivity to insulin (exogenous) and increased in all patients postdialysis by an average of 57% (P < 0.01). In two patients hepatic glucose production was measured with tritiated glucose during the euglycemic clamp and declined by 84% predialysis. A similar decrease (82%) was observed postdialysis. Thus, both the hyperglycemic and euglycemic clamp techniques demonstrated tissue insensitivity to insulin to be the dominant carbohydrate defect in uremia. The surprising apparent lack of consistency in the change in beta cell response postdialysis is explained by the strong inverse correlation between beta cell sensitivity to glucose and tissue sensitivity to insulin (r = -0.920; P < 0.001). Those individuals who showed the most striking improvement in tissue sensitivity to insulin actually decreased their serum insulin response to hyperglycemia; those whose improvement in tissue sensitivity was more modest showed increases in beta cell responses.

Impact of Age on Weight Goals

Although the health hazards due to excessive obesity and excessive leanness are multiple and diverse, weight recommendations for over 40 years have been based solely on the risk of dying. The weight recommendation tables in nearly universal usage have been derived from the experience of the life insurance industry. Those tables have not recommended any weight adjustments for age. An analysis of the actuarial data on which the most recent tables are based shows that minimal mortality occurs at progressively increasing body weight as age advances (20 to 29, through 60 to 69 years). There is, furthermore, no systematic sex difference in those weights. We have prepared height-weight tables that are age-specific and delete sex and body frame type as variables. These weight standards are lower for young adults and higher for older adults than those previously recommended. A review of 23 other reported populations confirms the need to adjust weight standards for age.

Plasma selenium level before diagnosis and the risk of prostate cancer development.

PURPOSE Epidemiological studies and a randomized intervention trial suggest that the risk of prostate cancer may be reduced by selenium intake. We investigated whether plasma selenium level before diagnosis correlated with the risk of later developing prostate cancer. MATERIALS AND METHODS A case control study was performed on men from the Baltimore Longitudinal Study of Aging registry, including 52 with known prostate cancer and 96 age matched controls with no detectable prostatic disease. Plasma selenium was measured at an average time plus or minus standard deviation of 3.83 +/- 1.85 years before the diagnosis of prostate cancer by graphite furnace atomic absorption spectrophotometry. Adjusted odds ratio and 95% confidence interval were computed with logistic regression. RESULTS After correcting for years before diagnosis, body mass index, and smoking and alcohol use history, higher selenium was associated with a lower risk of prostate cancer. Compared with the lowest quartile of selenium (range 8.2 to 10.7 microg./dl.), the odds ratios of the second (10.8 to 11.8), third (11.9 to 13.2) and fourth (13.3 to 18.2) quartiles were 0.15 (95% confidence interval 0.05 to 0.50), 0.21 (0.07 to 0.68) and 0.24 (0.08 to 0.77, respectively, p =0.01). Furthermore, plasma selenium decreased significantly with patient age (p <0.001). CONCLUSIONS Low plasma selenium is associated with a 4 to 5-fold increased risk of prostate cancer. These results support the hypothesis that supplemental selenium may reduce the risk of prostate cancer. Because plasma selenium decreases with patient age, supplementation may be particularly beneficial to older men.

Insulin Control of Glucose Metabolism in Man: A New Kinetic Analysis

Analyses of the control of glucose metabolism by insulin have been hampered by changes in bloog glucose concentration induced by insulin administration with resultant activation of hypoglycemic counterregulatory mechanisms. To eliminate such mechanisms, we have employed the glucose clamp technique which allows maintenance of fasting blood glucose concentration during and after the administration of insulin. Analyses of six studies performed in young healthy men in the postabsorptive state utilizing the concurrent administration of [14C]glucose and 1 mU/kg per min (40 mU/m2 per min) porcine insulin led to the development of kinetic models for insulin and for glucose. These models account quantitatively for the control of insulin on glucose utilization and on endogenous glucose production during nonsteady states. The glucose model, a parallel three-compartment model, has a central compartment (mass = 68 +/- 7 mg/kg; space of distribution = blood water volume) in rapid equilibrium with a smaller compartment (50 +/- 17 mg/kg) and in slow equilibrium with a larger compartment (96 +/-21 mg/kg). The total plasma equivalent space for the glucose system averaged 15.8 liters or 20.3% body weight. Two modes of glucose loss are introduced in the model. One is a zero-order loss (insulin and glucose independent) from blood to the central nervous system; its magnitude was estimated from published data. The other is an insulin-dependent loss, occurring from the rapidly equilibrating compartment and, in the basal period, is smaller than the insulin-independent loss. Endogenous glucose production averaged 1.74 mg/kg per min in the basal state and enters the central compartment directly. During the glucose clamp experiments plasma insulin levels reached a plateau of 95 +/-8 microU/ml. Over the entire range of insulin levels studied, glucose losses were best correlated with levels of insulin in a slowly equilibrating insulin compartment of a three-compartment insulin model. A proportional control by this compartment on glucose utilization was adequate to satisfy the observed data. Insulin also rapidly decreased the endogenous glucose production to 33% of its basal level (0.58 mg/kg per min), this suppression being maintained for at least 40 min after exogenous insulin infusion was terminated and after plasma insulin concentrations had returned to basal levels. The change in glucose utilization per unit change in insulin in the slowly equilibrating insulin compartment is proposed as a new measure for insulin sensitivity. This defines insulin effects more precisely than previously used measures, such as plasma glucose/plasma insulin concentration ratios. Glucose clamp studies and the modeling of the coupled kinetics of glucose and insulin offers a new and potentially valuable tool to the study of altered states of carbohydrate metabolism.

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