Effects of psychological stress on blood glucose in diabetes


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Effects of psychological stress on blood glucose in diabetes
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vii, 130 leaves : ill. ; 29 cm.
Samo, Jill Adrienne, 1962-
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Subjects / Keywords:
Research   ( mesh )
Stress, Psychological   ( mesh )
Blood Glucose   ( mesh )
Diabetes Mellitus, Type I   ( mesh )
Diabetes Mellitus, Type II   ( mesh )
Psychophysiology   ( mesh )
Psychosomatic Medicine   ( mesh )
Department of Clinical and Health Psychology thesis Ph.D   ( mesh )
Dissertations, Academic -- College of Health Related Professions -- Department of Clinical and Health Psychology -- UF   ( mesh )
bibliography   ( marcgt )
non-fiction   ( marcgt )


Thesis (Ph.D.)--University of Florida, 1990.
Bibliography: leaves 93-99.
Statement of Responsibility:
by Jill A. Samo.
General Note:
General Note:

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University of Florida
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aleph - 002402947
oclc - 51553565
notis - AMA7877
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I want to take this opportunity to acknowledge those

people whose contributions were so important to the

completion of this project. First and foremost, I wish to

express my deepest appreciation and heartfelt gratitude to

my chairperson, Dr. Suzanne B. Johnson, for her generous

gift of personal time, professional guidance, and patience.

Her excellent insights and suggestions were invaluable.

She provided the best mixture of guidance and freedom for

independence and was quick to step in when needed.

I would also like to thank the other members of my

committee, Drs. Fred Murray, Neil Rowland, Janet

Silverstein, Gary Geffken, Hugh Davis, and Jim Rodrigue, for

their valuable suggestions, thoughts and ideas. I am

particularly grateful to Dr. Fred Murray and Dr. Neil

Rowland for their constructive feedback and reviews. Their

suggestions, physiological expertise, and enthusiastic

encouragement were vital to the completion of the project.

Additionally, I thank Fred for providing the necessary

medical backup and Neil for analyzing the plasma cortisol


I owe special thanks to Lisa Sheeber for running the

show in my absence. Her diligence and persistence are

greatly appreciated. I want to thank the CRC staff for

their assistance in the collection of these data and ongoing

encouragement. Special thanks go to Michael Kelly who

calmly addressed all my naive computer-related questions and

concerns. I am very grateful to Sarah Connelly who stepped

in at the last minute to perform the tedious job of

preparing the final manuscript. Her patience and initiative

are greatly appreciated.

I want to thank my wonderful parents who have always

encouraged my dreams and endeavors and provided the

consistent love, support, and confidence to make it all


I want to thank my great friend Dave Saliwanchik whose

loving support and generosity allowed me to be in a position

to complete this project. I will always cherish his


I want to give very special thanks to Craig Lipman who

has been a constant source of support and inspiration. His

love, laughter, wisdom, and patience are priceless. I

greatly appreciate the time and effort he willingly gave to

this project. Without his programming genius the improved

stress program would not have been available.



ACKNOWLEDGEMENTS......................................... ii

ABSTRACT ........................................... .... vi


1 INTRODUCTION.................................. 1

Mechanisms By Which Stress May Affect
Diabetic Control........................ 5
Methodology for Studying How Stress Affects
Physiology and Metabolic Control....... 9

2 METHODS ....................................... 28

Participants.................... ...............
General Procedure............................ 30
Physiological Measures....................... 36

3 RESULTS.................................... 38

Description of Sample........................ 38
Manipulation Checks.......................... 43
Blood Glucose................................ 49
Experimental Effects .......................... 55

4 DISCUSSION.................................... 68

Comparison to the Wing Study.................
NIDDM....................... .......

Conclusions..... ............................
Implications...................... ..........

REFERENCES.............. ....... ..... ................... 87


A SCREENING QUESTIONNAIRE...................... 94

R-R INTERVAL PROCEDURE....................... 97



D SAM ........................................... 103


BIOGRAPHICAL SKETCH .................................... 124

Abstract of Dissertation Presented to the Graduate School
of the University of Florida in Partial Fulfillment of the
Requirements for the Degree of Doctor of Philosophy



Jill A. Samo

August 1990

Chairperson: Suzanne Bennett Johnson, Ph. D.
Major Department: Clinical and Health Psychology

There is an increasing amount of evidence suggesting

that psychological stress can cause metabolic derangements

in diabetic patients. Laboratory stress-induction methods

evaluating blood glucose reactivity have yielded mixed

results, with blood glucose sometimes showing an increase,

decrease, or no change. The methodological flaws present in

most of these studies may contribute to the variability in

findings. This investigation was designed to evaluate blood

glucose reactivity to a psychological stressor (a

challenging computer "game" that induces monetary losses) in

subjects with insulin-dependent diabetes mellitus (IDDM) N =

9, noninsulin-dependent diabetes mellitus (NIDDM) N = 9, and

nondiabetic controls N= 16. Groups were balanced for age,

sex, and body mass index. Subjects participated in two sep-

arate morning sessions. At each session they arrived fasting.

After a baseline period, they were given 8 oz of a mixed meal

beverage (Sustacal). On nonstress days, subjects watched an

educational video after the Sustacal; on stress days, they

participated in the challenging computer task. Plasma

glucose was measured on 10 occasions over each 120 minute

session. Results of heart rate and self-report data confirmed

that the stressor was arousing. Each group displayed differ-

ent patterns in response to stress. In nondiabetic subjects,

stress delayed the peak in the glucose curve. Subjects with

NIDDM showed a relative increase in blood glucose during the

stressor and a peak shift in the reverse direction from the

nondiabetic subjects. Subjects with IDDM showed yet a

different pattern with an initial decrease in blood glucose

during the stressor followed by an increase. The results

help to reconcile previous conflicting data on this subject.


Diabetes mellitus is characterized either by a defect

in insulin secretion or inefficient use of available insulin

by body tissues. Insulin has many metabolic functions

including making cell membranes permeable to glucose. In

diabetes, because of insufficient insulin production or

inefficient insulin utilization, glucose cannot readily be

used by the cells of the body; it accumulates in the

bloodstream (hyperglycemia) and spills over into the urine

(glycosuria). Because the cells cannot metabolize glucose,

they instead metabolize fat and protein which results in

high levels of fatty acids and ketones in the blood and

urine. This process, if untreated, results in frequent

urination (in an attempt to rid the body of excessive fatty

acids), dehydration, fatigue, weight loss, and ketoacidosis,

hyperosmolar coma, and death. With appropriate medical

treatment, the consequences of severe hyperglycemia can be

avoided and life prolonged. However, even moderately

elevated blood glucose levels over a long period may be

related to the eventual appearance of the long-term

complications of diabetes (e.g., retinopathy, nephropathy,

neuropathy, accelerated cardiovascular disease).

Two forms of diabetes are commonly identified:

insulin-dependent diabetes mellitus (IDDM) and

noninsulin-dependent diabetes mellitus (NIDDM). Insulin-

dependent diabetes mellitus is also labeled juvenile onset

diabetes or Type I diabetes because of its frequent advent

during childhood. In this condition, the beta (or

insulin-producing) cells of the pancreatic islets of

Langerhans secrete little or no insulin. The patient,

therefore, must continuously be treated with daily insulin

injections. In contrast, patients with NIDDM, often labeled

adult-onset diabetes or Type II diabetes, retain some beta

cell function. However, high somatic resistance to insulin

(often exacerbated by obesity) puts increased demands on the

insulin-secretory capacity of these patients, who suffer

from an inability to secrete enough insulin to meet these

demands. Weight reduction, diet modification, or oral

hypoglycemic agents that increase the effectiveness of

endogenous insulin, can be used for treatment, although

exogenous insulin replacement is sometimes needed by a few


The long term complications associated with diabetes

mellitus have been well documented. These complications

include autonomic neuropathy, retinopathy, cardiovascular

disease, kidney disease, blindness, impotence, peripheral

vascular disease, and infection leading to gangrene. Recent

findings, however, suggest that such complications are not

inevitable. Most investigators now agree that improved

diabetic control (defined as the degree to which blood sugar

levels are maintained within the normal range) is effective

in reducing the occurrence and severity of both long and

short term complications (Cahill, Etzwiler, & Freinkel,

1976; Davidson, 1981). Normoglycemia is, in fact, the

principal therapeutic goal for patients with diabetes. To

this end, insulin therapy must be regulated to meet the

metabolic requirements associated with changes of diet,

physical activity, and physical stress from such causes as

infection, trauma, or other disease states.

There is some evidence that psychological stress, in

addition to physical stress, can cause metabolic

derangements. Although the exact role of psychological

stress in diabetes has been rather elusive and

controversial, the literature contains a good deal of

support for the belief that elevated blood glucose can be

directly related to perceived threat or stress (Menninger,

1935; Hinkle & Wolf, 1952; Sackett & Haynes, 1976; Kirkley,

1982). The investigations in this field date back to 1877

when Boehm and Hoffman (Greydanus & Hoffman, 1979) found

that they could produce glycosuria in cats within half an

hour after enraging them and by inflicting pain. Cannon,

Shohl, and Wright (1911) produced the same result by simply

immobilizing the animals, without inflicting pain. They

also discovered that the level of glucose found in the urine

of these animals increased in direct proportion to the rage

of the animal.

"Emotional glycosuria" (Menninger, 1935) in man has

been reported in the literature since the early part of this

century. Folin, Denis, and Smillie (1914) discussed two

experiments involving second-year medical students and

female college students where the stress of an examination

resulted in transient glycosuria in 18% of the students.

Psychological stress has been an important theoretical

construct used to account for both onset and course of

diabetes. Onset theories assume that the individual is

at-risk for diabetes, but that it takes some trauma or

stress to hasten the occurrence of the disease. However,

the research methodology for investigating such

precipitating stressful events has been wholly retrospective

in nature. These types of studies can never satisfactorily

address this topic because the data are slanted by the

interpretation of the patient and family as to why the

disease developed.

While there may be some controversy as to whether

psychological stress is involved in the etiology of

diabetes, there is general agreement that stress may

influence the course (metabolic control) of patients with

the disease.

In one study, adult patients were asked whether or not

psychological stress affected the control of their diabetes;

the majority perceived that stress was very influential

(Cox, Taylor, Nowacek, Holley-Wilcox, Pohl, & Guthrow,


One of the earliest demonstrations of stress effects in

diabetes was a case report by Hinkle and Wolf (1949)

describing a 15 year old girl with a repeated history of

diabetic ketoacidosis. The teenager had a very poor

relationship with her mother, with many violent arguments.

In a diary, the patient recorded these daily stressful

events and her urine ketone test results. The patient's

recording showed a striking relationship between the two.

Mechanisms By Which Stress May Affect Diabetic Control

The mechanisms by which stress influences diabetic

metabolism have not been well elucidated. The following two

mechanisms have been suggested and may coexist:

1. Emotional arousal in response to stress may lead

to changed production of particular hormones

catecholaminess, cortisol, growth hormone) that in turn

influence glucose and fat metabolism.

2. Stressful experiences may lead to changed

adherence behavior including those of diet management,

exercise, and insulin monitoring.

These mechanisms will be discussed in detail.

Physiological Mechanisms

Stress causes the body to react by secreting hormones

which activate the release of stored glucose thereby

ensuring adequate supplies of energy for the central nervous

system and other body tissues, enabling the individual.to

fight or flee. Theoretically, exposure to stress is thought

to have a significant effect on diabetic control through the

effects of increased levels of the stress hormones--e.g.

epinephrine, norepinephrine, cortisol. These hormones, when

released into the blood in sufficient amounts, stimulate a

complex series of events which may induce both hyperglycemia

and excess ketone body production. Catecholamines

antagonize the peripheral metabolic effects of insulin and

stimulate glycogenolysis and gluconeogenesis by the liver,

which should result in increased blood glucose levels in the

patients with diabetes. Catecholamines also encourage

mobilization of free fatty acids which are converted by the

liver to ketone bodies. Ketone body production may lead to

diabetic ketoacidosis in diabetes.

Once the stress terminates, there is typically a

temporary exaggerated increase in insulin production--the

normal function counters the stress hormones and permits the

body to return to a normal metabolic state. Individuals

with insulin dependent diabetes, whose pancreatic islets are

unable to produce normal amounts of insulin in response to

changes of the plasma glucose level, may be impaired in

their ability to counteract the effects of stress hormones.

As a result, IDDM patients may be particularly prone to the

development of marked or prolonged stress hyperglycemia.

Evidence supporting this hypothesis has come from

studies manipulating stress hormones (i.e., assessing the

infusion of stress hormones into patients). For example,

Shamoon, Hendler, and Sherwin (1980) compared the

hyperglycemic effect of epinephrine infusions in normal

subjects and in subjects with IDDM. They provided data

suggesting that IDDM patients exhibit increased sensitivity

to infused cortisol and catecholamines when compared to

normal individuals, so that the hyperglycemic response to

those hormones is more marked. Gerich, Lorenzi, Tsalikian

and Karem (1976) have shown that epinephrine release induces

hyperglycemia in humans, and Baker, Minuchin, Milman,

Leibman, and Todd (1975) have shown that children with

diabetes have a more rapid increase in blood ketones

concentration following epinephrine infusion than do

nondiabetic children. Baker, Kay, and Hague (1967) assert

that in labile adolescent patients, emotional stress leads

to mobilization of free fatty acids and ketoacidosis

mediated by counter-insulin stress hormones, especially by

the catecholamines and cortisol. Hamburg and Inoff (1982)

showed that small increments of plasma epinephrine produced

a marked reduction in glucose tolerance in otherwise healthy

persons by interfering with insulin action.

There is research evidence implicating stress and its

hormonal consequences in precipitating or exacerbating

hyperglycemia in diabetes. For example, Christensen (1983)

reported high levels of plasma catecholemines in poorly

controlled diabetic patients when compared to patients with

good control. Schade and Eaton (1980, 1983) show in their

data that metabolic decompensation may be precipitated by

stress-induced counter-regulatory hormones even in the

presence of insulin.

The above studies demonstrate the importance of

conterregulatory hormone influence on metabolic control.

However, studies actually manipulating stress (i.e.,

stress-induction procedures) have led to mixed results with

blood glucose sometimes showing an increase (Barglow,

Hatcher, & Edidin, 1984), decrease (e.g., Hinkle & Wolf,

1951, 1952), or no significant change (e.g., Kemmer,

Bisping, & Steingruber, 1986). These discrepant results may

be due to methodological problems and will be discussed in

detail later.

Regimen Adherence

Most studies have emphasized psychophysiologic

explanations of the impact of stress on metabolic control.

Stress, however, can also affect adherence to the diabetic

regimen and thus alter diabetic control through disruption

of dietary compliance, activity level, insulin use, or the

self-monitoring of glucose levels. These changes in

behavior may often explain the presence of hyperglycemia.

In a study by Kirkley (1982), the impact of stress on

adherence was manifest in self-reports of 57 diabetics

regarding antecedents of eating too much or eating the wrong

foods. They attributed 19% of such violations to negative

emotions and another 7% to conflict. Cohen, Vance, Runyan,

and Hurwitz (1960) reviewed 72 cases of ketoacidosis and

found that the most common precipitating factor (27%) was

the omission of insulin. In half of these cases insulin

omission was attributed to psychological stress.

Most studies assessing effects of stress on diabetic

control fail to separate adherence to treatment from

hormonal mediation as the major agent relating stress and

diabetic control. Further, their designs are also marred by

the use of only a small number of subjects and a paucity of

metabolic and psychologic quantification.

In summary, if stress does affect diabetes control it

exerts its action by altering either or both the "internal

milieu" (stress hormones), or the "external milieu"

(patient's compliance). Both means of action may be

operating simultaneously since stress reduction affecting

levels of neuroendocrine substances could also increase or

decrease adherence to medical regimen. Stress reduction

could facilitate diabetic control if high levels of stress

could be proven to change compliance behavior or to produce

large, rapid, or prolonged changes in carbohydrate and fat


Methodology for Studying How Stress Affects
Physiology and Metabolic Control

Two approaches have been taken by investigators

studying psychologic stressors. One approach is

correlational and assesses the relationship between

naturally occurring, psychologically stressful events and

blood sugar control. The second is experimental and assesses

the effect of acute laboratory stressors on metabolic

control in diabetic or nondiabetic individuals.


The more common approach is correlational. In these

studies, life stress is defined as the occurrence of events

which require significant change in life patterns. Such

events include losing a close friend, moving to a new home,

parents' divorce, etc. It is commonly assumed that high

levels of change in a short period of time may have a

cumulative impact on the individual and may contribute to

problems of health and adjustment.

Evidence supportive of a relationship between

undesirable life events and changes in a patient's metabolic

condition can be found in investigations of adults with the

disease. For example, Grant, Kyle, Teichman, and Mendels

(1974) using a modification of Holmes and Rahe's Schedule of

Recent Life Events inventory observed a positive correlation

(+.40 or greater) between undesirable life events and the

patients' diabetic condition in a sample of 37 patients with

diabetes. In this study negative events accounted for most

of the variance.

Bradley (1979) examined individual measures of physical

state in relation to retrospective measures of life events

experienced over a 12 month period. She found that the

number of stressful life events was associated with diabetes

control in adults. More specifically, increases in the

incidence of glycosuria, changes in prescriptions and

frequency of clinic attendance were associated with

increases in the reported occurrence of life events.

However, the experience of life events was not reflected in

blood glucose measures.

Another example of this approach is provided by Bedell,

Giordani, Amour, Tavormina, and Boll (1977) who studied the

relationship between life stress and day-to-day health using

a sample of 45 chronically ill children (40% with diabetes)

attending a 3-week residential summer camp. These

investigators found life stress to be correlated with the

frequency of acute symptoms by youngsters during the camp

session, suggesting that life stress may be related to the

day-to-day health status of chronically ill children.

Campers who had a high incidence of pre-camp life stress had

significantly more illness episodes during their camp stay

than campers with low life stress.

Chase and Jackson (1981) in a study of children with

diabetes demonstrated that high stress scores on the

Coddington Life Events Record (Coddington, 1972), which

provided a general measure of life change during the

preceding 3 months, were correlated with decreased short and

long term glucose control as measured by triglyceride

concentrations, percent Hemoglobin Al, cholesterol values,,

and serum glucose concentrations. However, this

relationship between increased stress and decreased

metabolic control could only be found for 15-18 year old


Studying younger patients, Brand, Johnson, and Johnson

(1986) also found a relationship between undesirable life

experiences prior to a summer camp and metabolic control

(only significantly related with urine ketones) during the

camp stay, but only for 10-12 year old male children, with

an internal locus of control.

While there appears to be some evidence that negative

life stress is associated with poorer metabolic control,

findings are not always consistent from study to study and

the strength of the relationship between stress and control

is usually weak. Life event checklists have inherent

problems. The major shortcoming is that they tap major life

events that occur relatively infrequently in the general

population. Additionally, individual patients may

experience various life events differently and a particular

patient's stressful experiences may be missing from the

checklist. Major life events are only one type of stress

and are probably not representative of the daily hassles one

experiences in living. Therefore, day-to-day stress may be

a more important influence on metabolic control than

occasional, albeit undesirable, "life events."

A measure that taps day-to-day hassles and frustrations

has recently been developed (Kanner, Coyne, Schaefer, &

Lazarus, 1981). Scores on the Hassles Scale have been

related to the development of psychological and physical

symptoms and also account for most of the variance

attributable to major life events (DeLongis, Coyne, Dakof,

Folkman, & Lazaraus, 1982). Little research has been

conducted on the relationship between everyday stress and

metabolic control (compared to major life events), even

though recent evidence suggests that minor life events

scales may have more utility than major life events scales

in predicting health outcome (Kanner et al., 1981).

Cox et al. (1984) assessed the relationship between

daily hassles or irritations and diabetic control in a

sample of 59 adult IDDM patients. A significant positive

correlation (r = .25, p<.05) was found between daily hassles

and hemoglobin Al levels. However, once again, the strength

of the relationship was relatively weak.

Another problem with correlation research is that most

field studies have not taken subjects' insulin, diet, and

exercise regimens into account. In an unusual study, Hanson

and Pichert (1986) assessed whether stresses perceived on a

day-to-day basis influenced blood glucose levels in IDDM

patients, statistically controlling for insulin, diet, and

exercise. When stress was broken down into positive and

negative components, negative cumulative stress was

significantly related to blood glucose levels in the

children. These findings suggest that minor stressors can

influence health outcome. However, positive and negative

stress need to be assessed independently, and the influence

of other variables (e.g., food, exercise, insulin) needs to

be controlled.

Although it is typically assumed that stress causes

poor metabolic control, it is possible that poor metabolic

control could be causing the stress. Mazze et al. (1984),

for example, found that changes in glycemic control were

consistently related to changes in reported anxiety,

depression, and quality of life. It is certainly possible

that health status may contribute to patients with diabetes

psychological stress as opposed to stress affecting the

patient's health status. The bidirectionality of the

stress/health status relationships makes the interpretation

of correlational data most difficult.


Studies that have directly manipulated stress in

diabetic patients have used stressors including stress

induction interviews (Baker et al., 1975; Hinkle, Conger, &

Wolf, 1950; Hinkle & Wolf, 1952; Minuchin, Rosman, & Baker,

1978), hypnosis (Vandenbergh, Sussman, & Titus, 1966), and

shock (Vandenbergh, Sussman, & Vaughn, 1967). For example,

Hinkle and Wolf (1952) studied diabetic subjects (IDDM and

NIDDM) and nondiabetic subjects individually during

baseline, stress (interview), and post-stress phases. This

format was used in the fasting state with diabetic subjects

receiving no insulin before the stress. During the stress

phase blood ketones and urinary output increased and blood

glucose levels showed a decrease for most but not all

subjects. Similar results in diabetic subjects were

reported by Vandenbergh and his colleagues (Vandenbergh,

Sussman, & Titus, 1966; Vandenbergh, Sussman, & Vaughn,

1967). Vandenbergh, Sussman, and Vaughn (1967) found that a

task involving an unpredictable shock produced a significant

decrease in glucose concentration and nonsignificant

increases in free fatty acid (FFA) and urine volume in six

diabetic patients and an inconsistent response pattern in

nondiabetic controls. Hypnotically induced emotional stress

also caused a decrease in blood glucose levels in diabetic

patients and nonsignificant increases in FFA and urine

volume (Vandenbergh, Sussman, & Titus, 1966).

In contrast, Baker et al. (1975) reported an increase

in glucose during a stress interview. Two preadolescent

girls with diabetes were studied, both of whom had a history

of multiple hospitalizations for severe diabetic

ketoacidosis. A specific stress interview with one child

caused free fatty acid concentrations associated with

significant increases in plasma corticosteroids and growth

hormone concentrations as well as increased urinary

excretion of epinephrine. Beta-adrenergic blockade prior to

a repeat stress interview blocked the metabolic changes

without interfering with the hormonal response to stress.

The few studies that have investigated the question

systematically have shown that increases in blood ketones,

FFA and urine volumes were the changes most consistently

associated with stress. Interestingly, these studies show

variability or even decreases in blood glucose in response

to stress (Vanderbergh, Sussman, & Titus, 1966; Minuchin et

al., 1978; Lustman, Carney, & Amado, 1981). Urine glucose

measures appeared to be least sensitive to the stress

manipulations (Hinkle et al., 1950; Vandenbergh, Sussman, &

Vaughan, 1967). The results of these initial investigations

demonstrated that although psychologic stressors may elevate

plasma free fatty acid levels, urine ketone levels and urine

volume, the effect on blood glucose levels is less

consistent. While stress appears to be a destabilizing

stimulus, these controlled studies did not support the

conclusion that acute stress is a hyperglycemia-inducing


While these early studies made an important

contribution, they suffer from serious methodological flaws.

Most exerted relatively poor control over conditions, few

made efforts to counterbalance the designs to control for

order effects, and most lacked consistent dependent

measurement. Much of the work is case-study oriented

(although some studies used nondiabetic comparison

subjects), lacks statistical tests of significance, used

highly heterogeneous subjects (e.g., mixed IDDM and NIDDM),

and did not carefully measure the participants experience of

stress by self-report and by psychophysiological indices.

The stress manipulation used may have been experienced as

more or less stressful by different subjects, introducing

substantial variability into what appeared to be a

well-controlled experiment. Another methodological concern

is the lack of control for effects of insulin use and

carbohydrate ingestion before the studies.

For many years following this early work, few studies

were conducted assessing the acute relationship between

psychological stress and blood glucose level in diabetes,

perhaps due to methodological difficulties unique to this

research area. However, in recent years there have been

several more sophisticated, systematic studies conducted

which analyze the effects of stress on IDDM subjects.

Kemmer et al. (1986) assessed the effect of acute

psychological stress (mental arithmetic and public speaking)

on metabolic control and glucoregulatory hormones in normal

subjects and normoglycemic and hyperglycemic IDDM patients.

Each subject was studied on three days for 140 minutes,

approximately 1.5 hours after a standard breakfast. The

normoglycemic IDDM group took their usual insulin doses the

evening before and on the morning of the study. The

hyperglycemic group injected only regular insulin the

evening before the study and withheld their usual insulin

injection on the morning of the study to induce an acute

state of poor metabolic control. On the first day the

subjects received no stress. On each of the other two days

after a 10 minute baseline, the subjects experienced a

stress period of either 15 minutes (public speaking) or 45

minutes (mental arithmetic) and a recovery period of 105 or

75 minutes. Blood glucose was analyzed every 5 minutes for

the first 15 minutes (during the stress period) and every 15

minutes for the next 3 measurements (until time 60) then

every 30 minutes for the rest of the study. These

psychological stimuli produced marked cardiovascular

responses and moderate elevations in plasma concentrations

of epinephrine, norepinephrine, and cortisol. However,

concentrations of blood glucose, plasma ketone bodies, and

free fatty acids did not increase in any of the groups

compared to the no stress day.

Similar results were found by Delamater et al. (1988)

in a study assessing the physiologic effects of acute

psychological stress in adolescents with IDDM. Subjects,

divided into good, fair and poor metabolic control groups,

were studied in the morning prior to insulin and breakfast.

Physiologic responses were determined before and after three

10-minute stressors (cognitive quiz, family

interaction-disagree, and family interaction-neutral)

administered over 80 minutes. Although subjective and

cardiovascular responses to stress occurred, significant

metabolic and hormonal changes as a result of the stress

were not observed for any of the groups.

In a similar study, Gilbert, Johnson, Silverstein, and

Malone (1989) reported consistent findings studying two IDDM

adolescents groups (good versus poor metabolic control) and

nondiabetic controls. Patients took their insulin and ate

breakfast the morning of the experiment. Metabolic indices

were measured only at the beginning and the end of the

experiment. Despite increases in anxiety and arousal to the

three stressors (venipuncture and two public speaking tasks)

separated by brief rest periods, there was no evidence that

the stressors produced derangements in metabolic control in

any of the groups studied.

Edwards and Yates (1985) measured blood glucose levels

and subjective estimates of stress levels in 45 minute

baseline sessions on three successive days in IDDM and

nondiabetic groups. Each session began at 2 p.m., 2 hours

after the subject's last meal and 8 hours after the last

insulin injection. On two subsequent days half of each

group performed a high demand and half a low demand task,

blood glucose levels and subjective stress levels being

assessed before, during and after the stress period. Stress

did not appear to induce significant changes in blood

glucose level in any of the groups even though subjective

stress level measures indicated that the task was stressful.

Thus, recent studies of the effects of stress on metabolic

control in IDDM do not reveal altered blood glucose levels

associated with psychological stress.

There has been no recent work which provides empirical

data utilizing laboratory psychological stress-induction

studies in human NIDDM subjects. Researchers have

indirectly studied the effects of stress on diabetes control

by investigating the effects of relaxation techniques.

Since relaxation techniques appear to decrease sympathetic

nervous system activity (Degood & Redgate, 1982), relaxation

therapy may serve to moderate some of the negative effects

of the stress response on metabolic control. In a well

controlled study, Surwit and Feinglos (1983a,b) studied the

acute effects of relaxation training on glucose tolerance in

NIDDM patients. Glucose tolerance improved significantly in

patients who received progressive muscle relaxation training

as compared to a control group. Subjects receiving

relaxation showed a decrease in plasma cortisol, whereas

control subjects showed an increase over the same time

period. Lammers, Naliboff, and Straatmeyer (1984) showed

that progressive muscle relaxation significantly lowered

blood glucose levels in two of four NIDDM subjects. The

researchers noted that this positive response may be

especially likely to occur in those patients with initially

elevated glucose levels and less stable metabolic control.

In contrast, relaxation interventions with IDDM

subjects have provided mixed results (Fowler, Budzynski, &

Vandenbergh, 1976; Landis, Janovic, & Landis, 1985;

Feinglos, Hastedt, & Surwit, 1987). Feinglos et al.

investigated the effect of treatment with

biofeedback-associated progressive muscle relaxation on

poorly controlled IDDM subjects compared with equivalent

untreated patients. In contrast to previous studies of

NIDDM subjects, relaxation had no effect on glucose

tolerance and several indices of metabolic control. These

data are consistent with Landis et al. (1985), who found a

reduction in the daily range of blood glucose levels, but no

significant change in average glucose levels,

glycohemoglobin, or insulin requirements in stable IDDM

patients after 15 weekly sessions of relaxation training and

3 monthly follow-ups. These negative findings contradict

earlier case reports that suggest that relaxation training

lowered insulin requirements and reduced the frequency of

ketoacidosis in IDDM patients (Fowler et al., 1976; Seeburg

& DeBoer, 1980).

Based on the results of animal model studies and

chemical infusion studies indicating altered sympathetic

nervous system (SNS) activity in NIDDM, Surwit and Feinglos

(1988) proposed a model describing the impact of stress in

NIDDM. They suggest that increased alpha-adrenergic

sensitivity in the endocrine pancreas and other tissues in

NIDDM leads to an exaggerated suppression of insulin

secretion and glucose utilization, leading to an

exaggeration of SNS effects upon glucose metabolism. Their

model does not require the presence of unusual psychologic

stress for metabolic dysregulation to occur since the

metabolic effects of even normal SNS activity appear to be


Although the Surwit and Feinglos (1988) model is of

interest, it is clear that, there is a great paucity of

sophisticated studies assessing the direct effects of stress

on diabetes control in NIDDM patients.

The failure to find a direct link between stress and

hyperglycemia might be attributable to methodological

defects as well as other unmeasured mediating factors. For

example, some investigators have emphasized the need to

consider the patient's coping response (Brand et al., 1986;

Delamater, Kurtz, Bubb, White, & Santiago (1987) and Type A

or B behavior patterns (Cox et al., 1984; Stabler, Morris,

Litton, Feinglos, & Surwit, 1986) as a possible moderating

influence on stress/metabolic control relationships.

Additional variables of this type that have been mentioned

in the literature include whether the stress is impersonal

or has personal relevance and importance to the patient, the

difference between anticipation of stress and the stress

itself, and whether the stress is predictable or

unpredictable (or controllable or uncontrollable). This

area of research reveals the importance of standardizing the

stressor and utilizing manipulation checks when studying the

effects of stress on metabolic control.

Autonomic activation is no longer thought of as a

relatively fixed pattern independent of varying

environmental demands and intended goals as originally

inferred by Selye's "nonspecific stress response."

Investigators (e.g., Mason, 1975) now suggest that the

endocrine system, as well as the autonomic system exhibits
"situational stereotypy"--with differing events evoking

distinctive patterns of integrated hormonal response. For

example, Lunberg and Frankenhaeuser (1980) found two

distinct responses to stress by varying experimental

conditions and performing a factor analysis. They

discovered that pituitary-adrenal activation (cortisol

excretion) was associated with negative feelings of

distress, and sympathetic-adrenal activation (epinephrine

excretion) with feelings of alertness and action proneness.

These data are consistent with other studies (Henry &

Stephens, 1977; Levine, Weinberg, & Brett, 1979; Ursin,

Baade, & Levine, 1978; Cox et al., 1984) which conclude that

different endocrine systems are stimulated by different

types and severity of stressors.

There is also evidence to suggest that individuals may

respond idiosyncratically to stress--termed response

specificity. For example, Elwood, Ferguson, and Thakar

(1986) found both increases and decreases in catecholamine

levels in response to a stressor situation (cognitive

tasks), with an increase representing an adaptive response

and a decrease representing a less adaptive response.

This area of research shows that it may be important,

when designing a study involving stress effects, to have

each subject serve as their own control (in addition to

having control groups). The data from this type of design

need to be analyzed between groups and within subjects to

help assess idiosyncratic responses to stress.

Therefore, it appears that it is not just the stimuli

or physical environment per se that determines the

physiological response, but the individual's evaluation of

these stimuli. This point indicates the importance of

subjective appraisal of the stress situation (or perceived


It should be clear from the foregoing discussion of the

existing literature in this research area that the

investigations conducted to date present contradictory

findings in their studies of the relationship between stress

and metabolic control. The two potential mechanisms by

which stress could affect metabolic control (physiological

effects of hormones versus regimen adherence) have not been

clearly distinguished from each other by existing studies.

The discussion of the methodological problems and

potentially influential mediating variables discussed above

emphasizes the importance of a well designed study utilizing

a standardized stressor, subjective self-report data in

addition to physiological indices for measuring stress and

most importantly, using each subject as their own control in

a repeated measures design.

Such a study conducted by Wing, Epstein, Blair, and

Norwalk (1985) provides a starting point for sorting out

some of the discrepancies in the data. Wing et al. (1985)

assessed the effect of a standardized psychological stressor

on blood glucose levels in nondiabetic subjects. All

subjects participated in two sessions (stress/nonstress)

presented in counterbalanced order. After a 20-minute

baseline, fasting subjects consumed a carbohydrate load. On

nonstress days subjects relaxed after the drink; on stress

days, subjects participated in competitive tasks for 30

minutes after the drink. Blood glucose responses were

measured at 0, 30, 60, 90, and 120 minutes after the load.

Results show that stress impaired nondiabetic subjects'

ability to handle a carbohydrate load. Stress did not raise

or lower blood glucose levels but rather caused a temporal

shift (30 minutes) in the glucose curve. These results

demonstrate that direction of blood glucose may hinge on

when blood samples are obtained and when the stress is

administered with respect to the last meal.

Most stress-induction studies measure blood glucose

before, and at one time after, the stressor. In the Wing

study, if only one blood sample had been obtained at 30

minutes, stress would have appeared to lower blood glucose.

If the sample had been taken at 60 minutes, stress would

have appeared to raise blood glucose. This important study

may point out a prime explanation for why previous data

assessing the effect of psychological stress on glycemic

control in diabetes are so variable. The next obvious step

is to replicate this study using diabetic subjects. As

emphasized above, IDDM and NIDDM patients should be

evaluated separately.

In conclusion, many of the existing studies on the

effects of stress on metabolic control have methodological

defects such as poorly controlled conditions, few efforts to

counterbalance the designs to control for order effects,

inappropriate subject groups, lack of consistent dependent

measurement, and failure to measure the participants'

experience of stress by self-report and psychophysiological

indices. In addition to methodological defects, it appears

that stress effects may be modified or mediated by a number

of different factors including the type of stressor

employed, the availability of endogenous insulin, presence

of Type A/B behavior pattern and coping mechanisms. There

is also evidence to suggest that individuals respond

idiosyncratically to stress. Although the recent work by

Wing et al. (1985) overcomes many of the defects

characteristic of earlier work, the present study goes

beyond the Wing et al. (1985) research by taking more

frequent blood samples and by using IDDM and NIDDM subjects.

The present study attempted to minimize the effects of

differences in diet, exercise, and insulin dose, and

utilized appropriate subject groups, a standardized

stressor, a repeated measures design with consistent,

frequent measurement of the dependent variables using each

subject as their own control (in counterbalanced order), as

well as self-report and psychophysiological measures.

This study was designed to test the following


1. Because the present study is a modified

replication of the Wing et al. (1985) study, it is

hypothesized that the response of the nondiabetic group will

be reproduced: stress will not raise or lower blood glucose

levels but will cause a temporal shift in the glucose curve.

2. As described in the introduction, the pancreatic

islets of IDDM patients are unable to respond normally to

changes in plasma glucose level. Therefore, it may be

difficult for them to counteract the effects of stress

hormones. As a result, IDDM patients may be particularly

prone to the development of stress hyperglycemia (as

compared to nondiabetic controls).

3. As has recently been hypothesized (Surwit &

Feinglos, 1988), NIDDM may be related to abnormalities in

the sympathetic nervous system. In particular, enhanced

sensitivity of the alpha2-receptors in the pancreas and

elsewhere can lead to exaggeration of sympathetic nervous

system effects and the impairment of both insulin secretion

and glucose utilization. This metabolic malfunctioning may

occur even in the absence of unusual psychological stress.

Because psychological stress stimulates sympathetic nervous

system activity, NIDDM patients may be extremely sensitive

to the effects of psychological stress.

It is hypothesized that NIDDM patients will exhibit

greater stress hyperglycemia than normal controls.

4. Patients with IDDM and NIDDM may have different

responsiveness to stress since stress reduction studies

evidence disparate consequences of relaxation therapy on

these two patient populations (Feinglos et al., 1987). The

results of the Feinglos et al. series of studies showed that

NIDDM patients responded positively to relaxation training

whereas IDDM patients do not, suggesting that the direct

physiologic effects of stress may possibly be more important

in patients with NIDDM. Therefore, it is hypothesized that

NIDDM patients may show greater stress hyperglycemia than


The present investigation differed from past attempts

to study the effects of stress in persons with diabetes in a

number of important respects. This study used appropriate

subject groups (e.g., separated IDDM and NIDDM groups);

tightly controlled conditions that minimized the effects of

differences in diet, exercise, and insulin dose; used a

standardized stressor; used each subject as his/her own

control (in counterbalanced order); used self-report and

psychophysiological measures; and used consistent, frequent

measurement of relevant dependent measures. The study

assessed whether the standardized stressor was "perceived"

as stressful subjectively (via self-report measures),

psychophysiologically (via heart rate), and physiologically

(via plasma cortisol) and whether the stressor had an effect

on glycemic control (via blood glucose) of IDDM, NIDDM, and

nondiabetic controls.

Participants consisted of IDDM, NIDDM, and nondiabetic

control subjects. These subjects were studied in the

Clinical Research Center (CRC) at the J. Hillis Miller

Health Center, University of Florida, Gainesville. Subjects

were recruited from the following: lists of diabetic

patients provided by the Diabetes Clinic at the J. Hillis

Miller Health Center and local physicians, advertisements

placed on bulletin boards or in newspapers, and word of

mouth. The age range was from 18 to 65 years.

Criteria for inclusion in the diabetic groups included

diagnosed IDDM for at least three years or NIDDM of one

year. Noninsulin-dependent diabetes mellitus subjects with

a current or past history of exogenous insulin use were

excluded. All subjects were free from major medical

problems (e.g., no diagnosed cardiovascular or neurological

abnormalities), and except for insulin and hypoglycemic oral

agents, were not taking any medications which would affect

heart rate or carbohydrate metabolism. They were not taking

antihypertensive medications (fludrocortisone or

beta-adrenergic antagonists, or diuretics) and they were not

on salt restricted diets. Subjects with autonomic diabetic

neuropathy were screened out.

Nondiabetic subjects were healthy, with no immediate

family history of diabetes and normal fasting blood glucose

and Hemoglobin Alc (HbAlc) levels. The HbAlc is a measure

of the amount of glucose adhering to hemoglobin in the blood

and reflects average blood glucose over 2 4 months (Tarnow

& Silverman, 1981-1982). Diabetic and nondiabetic subjects

were matched on sex, age, and Body Mass Index (BMI)

[BMI = weight(kg)/height (m)]1 (Garrow, 1981).

General Procedure

Subject screening was conducted via a generalized

screening questionnaire (Appendix A) designed to exclude

subjects who were clearly unacceptable for the study.

Acceptable subjects were scheduled for an appointment on the

CRC for further screening. During this appointment, the

subjects were formally tested for diabetic autonomic

neuropathy via an assessment of the R-R interval: a test

measuring immediate heart rate increase after rising from a

supine position (Ewing, Campbell, Murray, Neilson, & Clarke,

1978) (refer to Appendix B for procedure). If the patients'

test ratio (length of the R-R interval at beat 30 following

standing divided by the length of the R-R interval at beat

15) was less than 1.0, they were excluded from the study.

Otherwise the patient was asked to complete the Social

Readjustment Rating Scale (Holmes & Rahe, 1967) (Appendix C)

for life events occurring during the past month--significant

items were clarified by the subject. If the subject was

IBody Mass Index is a way of incorporating height and weight
into one measurement in order to more easily match subjects and
assess the degree of overweight. A BMI of 27 is considered 20%

experiencing major life stress or an unusual life event,

scheduling was postponed or the subject was excluded.

Procedures of the study were explained in detail to

acceptable participants both verbally and in writing and

consent was obtained in writing.

Study Protocol

Subjects were scheduled to attend two sessions,

separated by 1-7 days. These two sessions included a stress

and a nonstress or control condition, presented in random

order. Subjects were instructed to fast (including coffee

and cigarettes) from midnight and arrive at the laboratory

at approximately 8:15 a.m.

Height and weight were recorded and a Sears Digital

Electronic Heart Rate Monitor was attached to the subjects'

ear for continuous monitoring of heart rate (recorded every

60 seconds from a digital display readout). A heparin lock

was placed in the nondominant arm for pain-free monitoring

of blood glucose throughout the experiment. At this time, a

blood sample was taken, centrifuged, and analyzed for plasma

glucose concentration (via a Beckman Analyzer in the

CRC--enzyme hexokinase technique), Hemoglobin Alc (via a

column chromatography method--Bio-Rad's by Column Test), and

cortisol (by Dr. Neil Rowland via a commercial

radioimmunoassay kit by Diagnostic Products). All

subsequent blood draws were managed and analyzed in this

manner (except the HbAlc analysis which was performed once

per diabetic subject).

Insulin-dependent diabetes mellitus subjects were

instructed to take their insulin, and NIDDM subjects on oral

hypoglycemic agents took their medication. After ten

minutes the baseline period began. Nondiabetics and

diet-only NIDDM subjects began the session with the baseline


Each session began with a 20-minute baseline period,

during which the subject sat quietly, reading or watching

T.V. At the end of the baseline period, a blood glucose

sample was obtained. Subjects then completed two short

self-report inventories: the A-State portion of the

State/Trait Anxiety Inventory (STAI) (Speilberger, Gorsuch,

& Lushene, 1970) and a paper and pencil version of the

"Self-Assessment Manikin" (SAM) (Hodes, Cook, & Lang, 1985)

(Appendix D). The subject then consumed an 8-oz can of

Sustacal (Mead Johnson Nutritionals) within 1-2 minutes.

This mixed meal beverage contains 240 kcal (1 Calorie/ml),

33.1 grams (55%) of carbohydrate, 14.5 grams (24%) of

protein, and 5.5 grams (21%) of fat per 8-oz can. The time

at which the subject finished the last sip of the beverage

was recorded as t = 0. Blood samples were drawn

(approximately 4 ml) for glucose and cortisol analysis taken

via the heparin lock at t = 10, 20, 30, 45, 60, 75, 90, 105,

and 120 minutes. At t = 30 subjects completed the same

self-report inventories. Exactly the same schedule of blood

samples and self-report measures were used on stress and

nonstress (control) days. Stress and control sessions were

performed at the same time of the day in order to avoid

errors introduced by duration of fasting.

On control days, subjects sat quietly and watched a

videotaped documentary during the 120 minute period

following the Sustacal load.On stress days, subjects

participated in a psychologic stressor for the 30 minutes

period immediately following the drink (t = 0-30) and then

watched a similar videotape for the remaining 90 minutes

(t = 30-120).

Standardized Psychological Stress Manipulation Task

The stressor involved a variety of tasks (3) presented

via an (IBM compatible) laptop computer (NEC Multispeed).

Subjects were told that they have the opportunity to win

more money (in addition to their $20.00 subject

participation money) by partaking in these tasks. The tasks

changed every 10 minutes and included mental arithmetic,

falling numbers and matching. For each correct answer the

subject won 20 cents, for each incorrect answer they lost 20

cents. Subjects were informed that although it has not

occurred with other subjects so far, there is a chance that

they could actually lose money.

The computer program (developed by Craig S. Lipman and

the candidate) is designed (in Clipper--compiled dBase

language) so that the level of difficulty of the task

adjusts to the skill level of the participant forcing the

participant to achieve and maintain a 40 percent accuracy

--so that it will not be too easy or too hard for them; the

better they do the harder it gets, the worse they do the

easier it gets. The program accomplishes this by tracking

the participants performance. The logic for adjusting the

difficulty is as follows: The difficulty level will increase

if all of the following are true: 1) The total percent

correct is greater than 40.5 percent; 2) at least two of the

last four attempts were correct, and 3) the difficulty level

was not previously adjusted within the last four attempts.

The level of difficulty will decrease if the following

are true: 1) The total percent correct is less than 39.5; 2)

at least two of the last four attempts were incorrect, and

3) the difficulty level was not previously adjusted within

the last four attempts.

Additionally, the program was designed so that all

subjects lost the same amount of money and they were aware

of how much as the tasks continued because it was displayed

on the computer screen. Subjects were debriefed immediately

after completing the post self-report questionnaires and

received the full $20.00 at the end of the study.

Self-Report Measures

Subjects completed the State portion of the State-Trait

Anxiety Inventory ("Self-Evaluation Questionnaire"), and the

SAM (Self-Assessment Manikin) at the beginning of each

session and at t = 30 (just after the psychologic

stressor--on stress days).

The State portion of the STAI consists of 20 statements

that ask the individual to indicate how they feel at a

particular moment in time. The Scale is designed to be

self-administering--the subject merely has to indicate one

of four possible responses for each statement: not at all,

somewhat, moderately so, or very much so. The manual

specifically states that "researchers can use the A-State

scale to determine the actual levels of A-State intensity

induced by stressful experimental procedures." The manual

notes that it has been shown that scores on the A-State

scale increase in response to various kinds of stress and

decrease as a result of relaxation training (Speilberger et

al., 1970).

SAM Administration. The SAM is an instrument designed

to obtain ratings from subjects on three independent

affective dimensions: pleasure (valance), arousal, and

dominance (control). This instrument presents analogue

representations for each dimension (e.g., for pleasure, a

human-like figure with a series of facial expressions

ranging from smiling to frowning). The SAM is available as

a computer program or a paper-and-pencil measure, which is

the form used in this study. Subjects were instructed to

place an X on one of the five pictures or in between them,

allowing for a 9-point rating scale.

The following instructions, adapted from Hodes, Cook,

and Lang (1985) were verbally communicated to the subject:

In addition to your physiological responses, we
are interested in your emotional feelings. In
order for us to obtain information about emotions
in a standard way, you will use a "self-assessment
manikin" or SAM. SAM can be used to represent the
way you feel. You will use SAM to report three
separate dimensions of feeling: happy-unhappy,
excited-calm, in control-controlled. These
feelings are experienced along a scale from
maximum to minimum. At one extreme of the
happy-unhappy scale your are: happy, pleased,
satisfied, contented, hopeful. These words
describe a similar feeling. When you feel
completely contented, SAM should look like this.
(Point to SAM with maximum pleasure). Now let's
look at the opposite feeling from pleasure--at the
other end of the scale. This is the way SAM
should look when you feel completely: unhappy,
annoyed, unsatisfied, melancholic, despairing,
bored. (Point to SAM with minimum pleasure).
This is what SAM will look like when you feel
completely neutral, neither happy nor really
unhappy. (Point to SAM with neutral pleasure).
By picking pictures of SAM between the minimum and
neutral and maximum you can make SAM show just how
you feel, not just completely satisfied or
completely unsatisfied, but in between. (pp. 558-

Instructions were explained in a similar way for the

"excited-calm" dimension and the "in control-controlled"

dimension. Time was taken to make sure the subject

understood each dimension and examples were used to assess


Physiological Measures
Heart Rate

One sympathetic response to psychological stress is an

increase in heart rate.

Heart rate data was collected using the Sears Digital

Electronic Heart Rate Monitor, accurate to approximately 2

BPM, at 60 second intervals throughout each session.

Blood Glucose

The major dependent measure in this study was bloody

glucose. After the baseline blood sample, additional

samples were collected, centrifuged, and analyzed (via the

Beckman Analyzer, accurate to within 2-4 mg/dl) at 10, 20,

30, 45, 60, 75, 90, 105, and 120 minutes after the Sustacal



Plasma cortisol levels were measured to assess they

role of stress in cortisol release and its relationship to

glucose fluctuation. Plasma (0.2 0.4 ml) from each blood

draw was transferred into a small plastic vial, labeled,

frozen and delivered to Dr. Neil Rowland's Psychobiology Lab

for analysis via a commercial radioimmunoassay kit by

Diagnostic Products.

Data Analysis

All statistical analyses were conducted using the

statistical package--PC SAS on a IBM compatible PC. The

main analysis used was a repeated measures analysis of

variance, with Group (IDDM/NIDDM/Nondiabetics) as a between

subject factor and Condition (Stress/Control) and Time (each

measurement period) as repeated measures. All analyses were

2-tailed with a p value of .05.


Description of Sample

Thirty-four subjects participated in the study

including 9 IDDM, 9 NIDDM and 16 nondiabetic control

subjects. Diabetic subjects were matched with nondiabetic

control subjects according to age, sex, and Body Mass Index

(BMI). All subjects were Caucasian.

Six subjects from the original selected sample size of

10 IDDM, 10 NIDDM, and 20 nondiabetic controls had to be

dropped from the study for a variety of reasons. One IDDM

subject fainted after the second blood draw (diagnosed as a

vago-vagal response) on day two of the study and was

subsequently dismissed after receiving medical attention and

fully recovering from the incident. One NIDDM subject was

dropped due to the lack of any "stress effect" during the

stressor. He essentially "gave up" after realizing during

the first few minutes of the stressor that he "could not

win." Self-report, heart rate, blood glucose data, and

behavioral observations all confirmed the absence of a

stress effect. Four nondiabetic control subjects were

dropped from the data set. All four were set up to be

matched with NIDDM subjects and tended to be older and

heavier. Two of the subjects were untestable due to great

difficulty locating a suitable vein for adequate blood

draws. Acceptable veins were located for the other two

subjects, but proved to be deficient for properly timed

blood draws for the duration of the study. Therefore, due

to clotting, difficulty drawing blood and a need for

reinsertion of the heplock, missing data, and off time blood

draws ensued. A total of 16 complete matches remained, with

one extra nondiabetic control subject for the IDDM group and

a deficiency of three nondiabetics for the NIDDM group.

Insulin-Dependent Diabetic Subjects (IDDM)

The IDDM group included 5 male and 4 female subjects

with a mean age of 26.2 years (range: 20 37) and an

average BMI of 22.3. The mean number of years for duration

of illness was 15.2 years. As indicated by their HbAlc

levels, most subjects were in adequate control (mean = 7.7,

indicating mild hyperglycemia) during the few months before

their participation in the study. In our laboratory, normal

HbAlc levels range from 3.5 to 6.1. Mild hyperglycemia is

evidenced by a range from 6.2 to 8.3; moderate: 8.4 11.2;

and severe: 11.3 and up. All subjects were undergoing

treatment with conventional insulin therapy. Refer to Table

1 for individual subject data including exact insulin types

and dosages.

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Noninsulin-Dependent Diabetic Subjects (NIDDM)

Three male and 6 female NIDDM subjects participated in

the study with a mean age of 51.9 years (range: 32 64) and

an average BMI of 29.5. Mean duration of diabetes at

diagnosis was 5.3 years. As indicated by their HbAlc

levels, M = 6.5 (range: 5.1 8.5), subjects displayed a

varied range of diabetic control with most subjects

evidencing normal to mild hyperglycemia for the month prior

to participating in the study. Although most of these

subjects used oral hypoglycemic agents (third generation

glyburides), 3 of the 9 NIDDM subjects relied solely on diet

to control their diabetes. See Table 1 for detailed

individual data on these subjects.

Nondiabetic Control Subjects (NC)

A total of 16 nondiabetic control subjects (9 female

and 7 male) participated in the study. A subset of these

subjects (n = 10) closely matched the IDDM group (mean age:

25.9 years; mean BMI: 21.8) while the remainder of the

subjects (n = 6) matched the NIDDM subjects (mean age: 48

years, mean BMI: 30.6). Refer to Table 1 for individual


Manipulation Checks
Self Report Mood Measures

Before examining the effect of the stressor condition

on blood glucose, pre- to post-stress mood data were

examined to determine if subjects in fact reported mood

changes consistent with the stress manipulation. Pre-post

change scores for the State portion of the STAI and each of

the dimensions of the SAM for each of the two experimental

days were analyzed using a repeated measures ANOVA with one

between subjects' factor (Group: IDDM/NIDDM/Nondiabetics),

and one within subjects' factor (Condition: Stress/Control)

to test the effect of the stressor on mood.

No significant differences were found between the three

groups on any of the self-report measures. Mood changes

were associated with significantly less pleasure, greater

anxiety and less feeling of control on the SAM and greater

state anxiety on the STATE for the stress condition. See

Figures 1 and 2 for groups means by condition on each

measure. The greater the negative change score the more

unhappiness, anxiety, and less feeling of control indicated

compared to baseline.

These observations are supported by the following

statistics. A main effect for condition on each of the

dimensions of the SAM was found. Pleasure: F(1,31) = 16.00,

p < .0004; Anxiety: F(1,31) = 35.91, p < .0001; and Control:

F(1,31) = 24.25), p < .0001. Consistent with these



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findings, a significant main effect for condition on the

STATE was evident F(1,31) = 39.23, p < .0001.

Heart Rate

Figure 3 presents the changes in heart rate that

occurred during the study. As expected, heart rate

increased significantly during the stressor for all groups.

In the stress condition, heart rate increased from an

average of 70 beats per minute (BPM) during the baseline to

an average of 78 BPM during the stressor and remained

elevated for the full 30 minutes of the stressor before

returning to an average post stress mean of 72. In the

Control condition, heart rate was low throughout: 69 BPM

during baseline, 70 during the stress phase and 72 during

the post stress phase.

To permit data analyses, heart rate was averaged over

10 minute intervals throughout the study. The two 10 minute

baseline intervals were then combined for each subject on

each experimental day to form a mean baseline heart rate.

Similarly, the three intervals during the stress phase were

combined to establish a mean stress heart rate. The

remainder of the intervals after the stress phase were

incorporated to form a mean post stress heart rate.

A repeated measures ANOVA with one between subjects'

factor (Group: IDDM/NIDDM/Nondiabetics) and two within

subjects' factors (Condition: Stress/Control and Phase:

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effects of the stressor on heart rate. As expected, the

heart rate data showed a highly significant main effect for

Condition, F(1,31) = 24.02, p < .0001, Phase, F(2,

62) = 19.44, p < .0001 and a significant interaction of

Condition and Phase, F(2,62) = 44.13, p < .0001, confirming

the effect of the stressor. There was no main effect found

for group, suggesting that all groups had similar

cardiovascular responses to the stressor. Subsequent

analyses by phase reveal a significant main effect for

Condition during the Stress phase (with heart rate being

greater on the stress day compared to the control day),

F(1,31) = 44.87, p < .0001, but not during Baseline or

Poststress phases.

Blood Cortisol

Figure 4 presents the changes in cortisol levels that

occurred during the study. As expected, plasma cortisol

levels were relatively higher during the stressor and

gradually returned to levels similar to post stress levels

on the control day. A repeated measures ANOVA was computed

for blood cortisol with one between subjects' factor: Group

(IDDM/NIDDM/Nondiabetics) and two within subjects' factors:

Condition (Stress/Control), and Time (measurement periods:

1-10). As expected, there was a significant main effect for

Condition, F(1,28) = 9.00, p < .0027, Time, F(9,252) = 7.06,


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F(9,252) = 2.80, p < .0068. No group differences were


Subsequent analyses revealed significant differences at

times 0: F(1,33) = 5.04, p < .0316, 10: F(1,33) = 7.49,

p < .0099, 20: F(1,32) = 12.49, p < .0013, 30:

F(1,32) = 15.88, p < .0004, 45: F(1,32) = 8.35, p < .0069,

60: F(1,33) = 4.23, p < .0477.

Blood Glucose
As expected, subject groups entered the study with

significantly different baseline levels of blood glucose,

F(2,31) = 16.14, p < .0001 on the stress day, and

F(2,31) = 31.52, p < .0001 on the control day, with the IDDM

subjects showing the highest levels. The following baseline

blood glucose levels (mg/dl) by group and condition were

found: IDDM: stress day = 245, control day = 220; NIDDM:

stress day = 161, control day = 160; Nondiabetics: stress

day = 94, control day = 93. In order to control for these

differences and to permit a fair comparison, the blood

glucose levels were analyzed using difference scores; each

data point was subtracted from the subject's baseline blood

glucose level. Additionally, in order to look at the data

from another perspective, percent change scores were used to

analyze the blood glucose data; each data point was

subtracted from the subject's baseline blood glucose level,

and then divided by the baseline blood glucose level. The

results of these analyses were essentially identical to the

results when using difference scores and, therefore, will

not be reported in this text. Table 2 displays actual data

for IDDM and NIDDM blood glucose. Individual subject graphs

are presented in Appendix E.


Between-group tests of differences in blood glucose

variability were performed. Relevant analyses involved

assessing the standard deviation and range of blood glucose


The standard deviation of blood glucose difference

scores for each subject was calculated for each condition

(stress and control). A repeated measures ANOVA of the

standard deviation data was performed with one between

subjects' factor: Group (IDDM/NIDDM/Nondiabetic) and one

within subjects' factor (Condition: Stress/Control). A

significant main effect for Group was revealed,

F(2,31) = 8.78, p < .001, with IDDM showing the greatest

variability. The following mean standard deviations by

group were found: IDDM = 28.8, NIDDM = 20.4,

Nondiabetics = 13.6. There were no significant differences

between the Stress and Control conditions.




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Range. Range was calculated by subtracting the minimum

blood glucose level attained from the maximum blood glucose

level attained per subject for each condition. A repeated

measures ANOVA of range with one between subjects' factor

(Group: IDDM/NIDDM/Nondiabetic) and one within subjects'

factor (Condition: Stress/Control) was performed on the

blood glucose range data. A significant main effect for

group F(2,31) = 11.70, p < .0002 was found with IDDM again

showing the greatest range. The following mean ranges by

group were found: IDDM = 88, NIDDM = 66.5,

Nondiabetics = 38.8. No significant differences between

conditions (stress vs control) occurred.

Despite evidence of heterogeneity of variance, the F

test statistic is expected to be robust given the small

sample size. Only minimal inflation of the probability of

rejecting the null hypothesis (Type 1 error) is expected.

Experimental Effects
Within-Subject Comparisons

In order to determine the effects of the experimental

manipulation on blood glucose reactivity, a repeated

measures ANOVA with 2 within subjects' factors: Condition

(Stress/Control) and Time (measurement periods: 1 9) was

computed using blood glucose difference scores.


As seen in Figure 5, unstressed nondiabetic subjects

showed an expected peak and recovery of blood glucose

following the Sustacal load. Relative to this baseline, on

the stress day a similar peak was seen but delayed for 25

minutes. Thus, a significant main effect for Time was

noted, F(8,120) = 8.70, p < .0001 and a significant Time by

Condition interaction F(8,120) = 6.92, p < .0001.

Subsequent analyses examined the differences between the

Stress versus Control condition at each point in time.

Results indicate differences in blood glucose at 5 of the 9

points in time, at time 10: F(1,15) = 2.77, p < .12, 20:

F(1,15) = 10.26, p < .006, 45: F(1,15) = 6.83, p < .02, 60:

F(1,15) = 8.46, p < .011, 75: F(1,15) = 3.64, p < .076, and

90: F(1,15) = 4.21, p < .058 minutes after the Sustacal

load. On stress days, blood glucose peaked at 20 minutes

after the Sustacal, while on control days the blood glucose

peaked at 45 minutes. This denotes a 25 minute delay in the

blood glucose peak on stress days compared to nonstress

days. This pattern was exhibited by 11 of 16 subjects (see

Table 1 for individual data).

These results are very similar to the Wing et al.

(1985) data (Figure 6) which shows a glucose peak at 30

minutes after the carbohydrate load on the stress day, with

a 30 minute shift on the control day with glucose peaking at

60 minutes.



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A repeated measures ANOVA, comparing the two subgroups

of the nondiabetics, was computed. In addition to the two

within subjects factors (Condition and Time), Subgroup

(ND1/ND2) was added as a between subjects factor: the

subjects matched with the IDDM subjects (ND1) and the

subjects matched with the NIDDM subjects (ND2) (who tended

to be older and heavier). As seen in Figure 7, the pattern

of stress effects was similar for each subgroup but ND2

subjects had higher blood glucose levels throughout the

study than did ND1 subjects. This is confirmed by the

statistical results which show that in addition to a main

effect for Time, F(8,112) = 11.11, and the expected Time by

Condition interaction, F(8,112) = 6.21, p < .0003, there was

a significant main effect for Subgroup F(1,14) = 10.45,

p < .006.


Figure 8 clearly shows that blood glucose dropped

significantly during the first 30 minutes (Stress Phase) on

the stress day before peaking abruptly at time 60. There

were no main effects for Condition or for Time but the Time

by Condition interaction was highly significant,

F(8,64) = 6.09, p < .0016. Subsequent analyses indicate

that differences in blood glucose levels were evident at

times 10: F(1,8) = 9.86, p < .012, 20: F(1,8) = 7.40,

p < .03, 30: F(1,8) = 6.10, p < .04, and 105: F(1,8) = 3.45,

p < .10.


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Eight of the nine IDDM subjects showed this general

pattern of decreased blood glucose during the stressor,

followed by an increase. One evidenced a decrease in blood

glucose during the stressor that continued to decline

throughout the study. See Table 2 for actual data and

Appendix E for individual subject graphs.


As seen in Figure 9, blood glucose tended to rise

sooner on stress days and peaked at time 45, while on

control days, the peak shifted approximately 30 minutes, to

time 75.

In addition to a main effect for Time, F(8,64) = 15.21,

p < 0001, there was a significant Time by Condition

interaction, F(8,64) = 3.99, p < .015. Subsequent analyses

show blood glucose differences at times 10: F(1,8 ) = 5.34,

p < .05, 20: F = (1,8) =4.58, p < .065 and 105:

F(1,8) = 3.31, p < .10.

Two of the nine NIDDM subjects did not exhibit the

general pattern described above. Close inspection of these

two subjects (#17 and # 42) reveals interesting findings.

As seen in Table 3, subject #17, who showed an opposite

pattern, was the only subject to report more positive mood

changes post stress compared to the control day. Subject

#42 who did not show much of an effect at all was the only

subject on heart medication (50 mg Cardizam).

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Diff Scores

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Between Group Comparisons

A repeated measures ANOVA was computed for blood

glucose difference scores with one between subjects' factor:

Group (IDDM/NIDDM/Nondiabetics) and two within subjects'

factors: Condition (Stress/Control), and Time (measurement

periods 1 9). Results show a significant Group by

Condition by Time interaction, F(16,248) = 7.91, p < .001,

with a main effect for Group F(2,31) = 3.78, p < .034, and a

significant Group by Time interaction, F(16,248) = 3.11,

p < .02. Further analyses by condition were warranted to

analyze the location of the differences.

Control condition

As seen in Figure 10, blood glucose for the NIDDM rose

slower than the Nondiabetic group, but ultimately achieved a

much higher level (greater difference score). The IDDM

blood glucose curve actually dipped slightly (time = 10)

before rising by time = 20.

Groups differed within the control condition at times

10: F(2,31) = 3.06, p < .06, 20: F(2,31) = 3.09, p < .06,

45: F(2,31) = 3.79, p < .034, 60: F(2,31)= 5.85, p < .007,

75: F(2,31) = 5.58, p < .0085, 90: F(2,31)= 2.62, p < .09,

and 105: F(2,31) = 2.45, p < .10.



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There appeared to be greater group differences during

the stressor period. As seen in Figure 11, the relative

blood glucose rises during the initial (stress) phase for

the Nondiabetics and NIDDMs are opposite in the Stress as

compared to the Control condition. In other words, the

NIDDM curve rose more quickly compared to the Nondiabetic

controls during the stress condition, whereas this pattern

was reversed on the control day. The IDDM curve dropped

even lower than the other two groups during the stress phase

on the stress day and rose higher than the nondiabetic

controls during the post-stress phase.

Groups differed within the stress condition at times

10: F(2,31) = 27.19, p < .0001, 20: F(2,31) = 22.63,

p < .0001, 30: F(2,31) = 15.20, p < .0001, 45:

F(2,31) = 6.24, p < .005, 60: F(2,31)= 3.21, p < .054, 75:

F(2,31) = 3.51, p < .042.

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This study provides insight into the effects of

psychological stress on blood glucose levels of IDDM and

NIDDM subjects. The results help to reconcile previous

conflicting data on this subject and build upon the recent

work of Wing et al. (1985) with nondiabetics. The results

obtained here are believed to be of particular value and

interest because of the methodology utilized. Specifically,

this study utilized a standardized psychological stressor,

provided multiple measurements of dependent variables, and

used a repeated measures design in which each subject was

studied twice, serving as their own control. The stressor

effectively induced emotional arousal in all groups as

evidenced by significant increases in cardiovascular

arousal, stress hormone production, and subjective ratings

of emotional arousal.

The findings suggest that, for both diabetic and

nondiabetic subjects, performance of the 30 minute stressor

during the stress day resulted in a significant change in

blood glucose compared to the control day, demonstrating

that even a relatively short exposure to a moderately

stressful event can cause metabolic disruption. However,

the nondiabetic, IDDM, and NIDDM groups studied displayed a

different pattern in response to the experimental

manipulation. In nondiabetics, stress affected glucose

metabolism by delaying the peak of the glucose curve about

25 minutes compared to the control day. Subjects with NIDDM

showed a shift of the glucose peak in the opposite direction

from the nondiabetics. Subjects with IDDM showed yet a

different pattern with an initial decrease in blood glucose

during the stressor followed by an abrupt increase following

termination of the stressor.

The current study reveals that inconsistencies in the

results of previous studies may be attributable to an

insufficient number of blood glucose measurements over time.

The results obtained here clearly demonstrate that blood

glucose level is a very dynamic variable and that the

direction of blood glucose change depends on when the blood

samples are taken and when the psychologic stressor is

administered in relationship to the last meal. For example,

if in the present study, blood had been taken only at

baseline and at 20 minutes for the IDDM and nondiabetic

subjects, the investigator would have concluded that blood

glucose levels were lower during stress than nonstress.

However, if only a 60 minute sample had been taken, blood

glucose levels would have appeared higher in response to

stress. At time 30 for nondiabetic subjects or time 45 for

IDDM subjects there would have appeared to be no change.

These conclusions would have misrepresented the actual

effect of the stressor on glucose levels. Similar spurious

results would have been obtained for the NIDDM group. The

variability of blood glucose over time necessitates frequent

measurement in order to get an accurate portrayal of the

effect of stress on blood glucose. Hence, this

methodological study was successful in helping to clarifying

the nature of the inconsistencies in the literature.

Comparison to the Wing Study: Nondiabetic Controls

The present study essentially replicates the results of

the Wing et al. (1985) study showing that acute

psychological stress delays the peak glucose response in

nondiabetic subjects following a glucose load (Figure 4 and

Figure 5). However, the design of the present study, which

allowed for more frequent, painless blood sampling, revealed

additional information regarding the shape of the blood

glucose curves. For example, in the nondiabetic group blood

glucose peaked at time = 20 on the control day. If the same

measurement times as in the Wing study were used, this

earlier glucose peak would have been missed. Similarly, the

glucose peak on the stress day occurred at time = 45 in the

present study, whereas Wing et al. (1985) did not pick up

the peak until time = 60 as they did not measure blood

glucose at time 45. The additional information gleaned from

more frequent blood glucose measurement particularly during

the stress phase becomes even more important when comparing

the two control groups and is crucial when assessing blood

glucose change in the IDDM and NIDDM groups.

Unlike the Wing et al. (1985) study, which used only

young, lean subjects, the present study included nondiabetic

subjects to match the NIDDM subjects who tended to be older

and heavier. Although the general pattern of response to

the experimental manipulation was similar, the nondiabetic

subjects matched to the NIDDM subjects in general attained a

higher blood glucose level and slower return to near

baseline levels (Figure 7). The differences in the blood

glucose curves are likely due to the impairment of glucose

tolerance with age and obesity (Jackson, 1990). When

analyzing the blood glucose data of the nondiabetic group by

dividing the subjects by age (> 40 years) and then by BMI (>

26), a significant difference was noted for age but not for

BMI. Hence, the age variable is likely to be more powerful

in accounting for the difference observed in the nondiabetic


According to a recent study by Jackson (1990), there is

a progressive reduction of glucose tolerance with age.

Jackson reports that age-related glucose intolerance is a

specific phenomenon distinct from obesity and NIDDM.

Impairments in glucose-induced insulin secretion and insulin

action are characteristic. The defect in insulin action,

after glucose ingestion, is in the delayed suppression of

hepatic glucose production and a delayed rise in insulin

mediated glucose uptake. The most predominant disturbance

appears to be impaired glucose uptake with skeletal muscle

as the principal site of this defect. Because insulin

receptors are unchanged with age, the impairment in insulin

action is primarily due to a postreceptor defect.

In nondiabetic subjects, acute psychological stress

appears to delay the peak glucose response by approximately

25 minutes following a Sustacal load (Figure 4). It appears

that stress alters the subject's ability to absorb a liquid

meal. There were no differences in the maximum plasma

glucose levels attained; thus stress did not raise or lower

the ultimate blood glucose peaks, but rather caused a

temporal shift in the glucose curve. As proposed in the

Wing et al. (1985) study, this shift may be due to slower

absorption of glucose. It is likely that the stress

affected blood glucose levels by causing a delay in gastric

emptying, and therefore a delay in the peak glucose

response. This hypothesis is supported by a study by

Thompson, Richelson, and Malagelada (1983) which

demonstrated that a 20 minute period of cold stress delayed

gastric emptying of a liquid meal relative to a control

condition due to inhibition of gastric motility. The design

of the study and the results, as shown in Figure 12, are

strikingly similar to the present study. The graph shows

rates of meal delivery into the duodenum for each condition.

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Inhibition of gastric motility by acute stress may occur

because of increased sympathetic nervous activity, either by

a direct catecholamine effect or indirectly via sympathetic

stimulation of glucagon release. Thompson points out that

the changes in the autonomic nervous system activity are

qualitatively similar to those resulting from other forms of

stressful stimulation, including predominantly psychic

stimuli such as mental arithmetic.

According to the activities of the sympathetic nervous

system on hormone pathways (refer to Figure 13), it is

expected that stress may stimulate glucose production by the

liver. Such a production is not clearly evident in the

results obtained from the controls. It may be that if

hepatic glucose production was increased as a result of the

stressor, nondiabetics possess such a tight regulatory

system that the secretion of insulin counteracted the

effects. In addition to responding to glucose, the islet

cells in the pancreas respond to a variety of other

nonglucose signals (e.g., catecholamines) (Unger & Orci,

1977). In nondiabetics the insulin response to these other

signals is modulated by the prevailing glucose level. This

regulatory effect of glucose is referred to as potentiation.

The results of the study are contradictory to studies

reported recently in IDDM literature which found no evidence

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that acute psychological stress has adverse metabolic

effects (Kemmer et al., 1986, Delameter, Bubb, Kurtz, Smith,

White, & Santiago, 1988; Gilbert et al., 1989), even when

stress produced significant increases in cardiovascular

responses, subjective ratings of anxiety and significant

increases in stress hormone levels. As clearly shown in

Figure 8, group blood glucose data for IDDM subjects drops

significantly during the stressor period compared to the

control condition. This drop is followed by a rapid

increase upon completion of the stressor and then a gradual

return to near baseline levels by the end of the study

period. The pattern may be explained by a combination of

the following factors: the insulin injection administered

20 minutes prior to the glucose load; slowed gastric

emptying causing delayed glucose absorption; and the effects

of sympathetic nervous system activation on hormonal


It appears that the injected insulin initially causes

the blood glucose levels to drop. This lowering of blood

glucose levels may be accentuated by slowed gastric emptying

which delays the absorption of glucose into the blood. As

discussed above, slowed gastric emptying can be expected as

a result of the stressor. In response to the stressor and

perhaps the sharp drop in blood glucose, counterregulatory

hormones (epinephrine and cortisol) or "stress hormones" may

be triggered. These "stress hormones" are released into the

blood stream by the adrenal glands. In response to these

hormones a number of events may occur which influence the

metabolism of carbohydrates and are relevant to circulating

glucose level (refer to Figure 13). Glucagon is released

into the blood stream by the pancreas, increasing hepatic

glucose production (glycogenolysis and gluconeogenesis) and

causing glycogen to be converted to glucose by the liver and

released into the blood stream. Each of the effects of

these stress hormones would tend to raise blood glucose

levels. Therefore, a combination of the ingested Sustacal

ultimately being absorbed (upon completion of the stressor),

and the effect of the stress hormones due to psychic stress

and possibly due to a rebound may cause an abrupt rise in

the blood glucose level. The severity of the drop and the

general shape of the curve for individual subjects are

likely to be a function of type and dosage of insulin

injected. This important variable may also help explain the

great variability in the blood glucose data for IDDM


On the nonstress day, only a small initial dip in blood

glucose level after ingestion of the glucose load is

observed. This may be due to the fact that the injected

insulin has an available glucose load to act on. Blood

glucose slowly rises as ingested glucose is absorbed, levels

off and gradually decreases to below baseline level.

A number of studies (e.g., Halter, Beard, & Porte,

1984) show that endogenous epinephrine release or exogenous

epinephrine infusion results in exaggerated glycemic

response in diabetic patients. This is believed to result

from enhanced cortisol and epinephrine-induced glucagon

secretion, increased hepatic responsiveness to epinephrine

and lack of increased pancreatic insulin secretion. This

observation may contribute to the blood glucose

increases--particularly in the NIDDM subjects.

These subjects appear to have a slower absorption of

ingested glucose compared to the nondiabetics on the control

day (refer to Figure 9). This effect may be due to the

group's higher mean age and BMI and/or the increased

likelihood of gastric stasis with diabetes. However, these

subjects ultimately reach a significantly higher blood

glucose level and return only halfway to baseline levels at

the end of the study. On the stress day their blood glucose

level is higher during the stress phase, and peaks at a time

earlier than the control day.

This pattern can be explained by the following: unlike

the IDDM subjects and nondiabetics, NIDDM subjects do not

have a readily available amount of usable insulin to

counteract the effects of blood glucose increases due to the

stress response described above. Islet cell function

(insulin secretion) in NIDDM is characterized by diminished

responses to acute glucose stimulation. Studies show (e.g.,

Halter & Porte, 1981) that the acute insulin secretary

response to IV glucose is markedly impaired in fasting NIDDM

patients. In addition, there is an impairment of the

potentiating effect of glucose on insulin responses to

nonglucose stimuli (e.g. stress hormones). Therefore

patients with NIDDM may not be able to augment insulin

secretion normally to compensate for the hyperglycemic

effects of catecholamines and other stress hormones.

Additionally, catecholamines antagonize the ability of

insulin to increase glucose utilization (increased insulin

resistance) by the peripheral tissues. In other words,

these hormones inhibit insulin release from the pancreas and

have inhibitory effects on tissues which result in increased

resistance to insulin. Thus, the increased blood glucose

caused by the sympathetic response to stress may not be

utilized by the peripheral tissues until the termination of

the stressor. Additionally, there is substantial evidence

to support the notion that increased adrenergic sensitivity

is a characteristic of NIDDM (Surwit & Feinglos, 1988).

The delayed gastric emptying mechanism may not have

nearly as powerful an effect for NIDDM subjects due to the

following factors: slowed gastric system in general compared

to nondiabetics (Sninsky, 1989); hypersensitivity to

catecholamines compared to nondiabetics thereby producing

more glucose by the liver (Halter et al., 1984; Surwit &

Feinglos, 1988); inhibition of insulin response during

stress superimposed on an already impaired insulin response

to increased blood glucose (Halter et al., 1984). Therefore,

slowed gastric motility in response to stress may not be as

an important variable for NIDDM subjects for nondiabetic and

IDDM subjects.

Conclusions and Future Research

In addition to direct means of affecting blood glucose

levels (by the modification of diet, exercise, and

medication), it is evident that psychological stress (via

the autonomic nervous system) is important in the regulation

of carbohydrate metabolism. However, there is not a simple,

linear relationship between stress and blood glucose levels.

Paradoxical findings regarding blood glucose levels during

stress relates to the complex homeostatic regulation of

blood glucose. Briefly, the glucose reducing effects of

insulin are opposed by the action of glucagon,

catecholamines, and cortisol. This process is affected

differentially by the presence of IDDM and NIDDM.

Superimposed on this regulatory mechanism are the effects of

food intake, gastric motility, insulin (type, dosage, and

time of administration), age, and carbohydrate metabolism,

each of which may change blood glucose substantially.

All of the above factors contribute to the variability

of the results in the literature. For example, the results

of the present study may have been very different if there

was a change in the placement of the stressor in relation to

the glucose load. In a post-absorptive state, delayed

gastric emptying under stress would not have the marked

effect it has on blood glucose when the stress occurs just

after a meal. Additionally, the availability of insulin at

the time of the stressor is another extremely influential

variable which would determine blood glucose direction. For

example, a different effect would be expected for IDDM

subjects if the stressor occurred before insulin

administration or before the liquid meal. Perhaps IDDM and

NIDDM glucose data would look more similar if insulin was

withheld from the IDDM group the morning of the study.

These factors may explain the negative results found in

the fairly recent, relatively well-designed studies

assessing lab stress on IDDM subjects. Kemmer et al. (1986)

and Edwards and Yates (1985) found no significant change in

blood glucose reactivity to stress for IDDM subjects. These

subjects took their usual morning doses of insulin at 6 a.m.

and ate a standard meal at about 2 p.m. before beginning the

stress induction procedure approximately 2 hours later.

Perhaps the presence of a post-absorptive state and adequate

insulin levels is optimal for blood glucose stability during

stress and therefore does not disturb glycemic control.

However, Delameter et al. (1988) found similar results

studying IDDM subjects in the morning after an overnight

fast prior to insulin administration. Although subjects

administered their regular insulin dose the night before and

the morning of the experimental session, no information

regarding meal times or study times were provided in the

Gilbert et al. (1989) study. This possibly uncontrolled

factor may have contributed to the variability of the

results. Additionally, blood glucose was only measured

twice, before and after the study. The lack of report of

important variables (e.g., time of last meal, measurement of

recent insulin dose) in addition to the extremely

methodologically flawed designs prevented proper evaluation

of stress effects in the early studies (e.g., Vandenbergh et

al., 1966, 1967). It is obvious that future research

varying the temporal placement of the stressor in relation

to the last meal and the insulin injection is needed to

clarify the nature of these influences. It appears that the

stress effect may be much more prominent when it occurs

immediately after a meal.

A study on normal subjects by Hamburg, Hendler, and

Sherwin (1980) revealed that moderate increases in

epinephrine infusion had minimal effect on fasting blood

glucose, but had a very strong potentiating effect on blood

glucose increase subsequent to a 100 gm oral glucose load.

Levels of glucose increased by 30 to 60 mg/dl above saline

control values. These data suggest marked sensitivity to

the insulin antagonistic effects of epinephrine. The

researchers conclude that evidence suggests that epinephrine

has its most powerful effect on insulin action (not insulin

secretion) and especially insulin facilitated glucose

uptake. In 1952, Hinkle and Wolf, noted that glucose

ingestion in a diabetic patient already experiencing stress

led to a glucose curve that is "higher and more prolonged

than in the absence of stress."

In examining the relationship between stress and

diabetes, the effects of possible modifying and mediating

variables must be considered. Individual differences, both

psychological and physiological (in addition to the insulin

variable) may account for the variability in the impact of

the stress. It is useful to consider individual differences

in studies of stress reactivity since blood glucose

increases and decreases would cancel each other out when

combining group data, possibly obscuring specific stress

effects in some patients. In a report of preliminary data,

Carter, Gonder-Frederick, Cox, Clarke, and Scott (1985),

found blood glucose changes with stress (mental arithmetic)

to be idiosyncratic but reliable in a sample of adult IDDM

subjects. Delameter and his colleagues' results (1988)

support their observation, with a high consistency of blood

glucose change observed across the three stress conditions.

Thus it is possible that there are subgroups of patients for

whom stress is associated with different patterns of

response. The reliability of individual patterns could have

been assessed in the present study by adding a third study

(stress) day to the experimental design. Of course the

confounding variable of a habituation effect would have to

be dealt with. A very important, relevant subgroup to study

would be patients with autonomic neuropathy (screened out in

the present study). Impairment in the stress hormone

responses secondary to autonomic neuropathy, could interfere

with epinephrine-induced increases in blood glucose. These

patients may have a very different response to stress.

Another important subgroups to study would be patients in

good vs poor control.

Cardiovascular research has suggested that individuals

with Type A behavior patterns may aggravate the endocrine

response to stress. Although no consistent results were

evident in past studies (Stabler, et al., 1988) additional

research examining differential responses of Type A and Type

B individuals may be interesting.

Along these lines, as discussed in the introduction,

different types of stressors may have different effects on

the neuroendocrine system and thus carbohydrate metabolism.

Research utilizing different types of stressors (e.g.,

active versus passive) in the present design would be

valuable. A design similar to the one proposed above (3

experimental days) using two different stressors in

counterbalanced order may provide a good start to assessing

the potential differences.

The time course of metabolic changes in relationship to

psychological stress and the strength of the stress response

necessary to disrupt glucose metabolism has to be defined.

For example, the fact that Delameter's study failed to show

catecholamine increases in response to stress may account

for the negative results. Further research varying the

intensity and duration of the stressor is necessary. It

would be very interesting to study whether a longer stressor

(which is more generalizable to the natural environment)

prolongs the delay in gastric emptying and accentuates the

stress effects noted in each group. Perhaps the blood

glucose curve would show prolonged hyperglycemia in the

NIDDM group and a prolonged or steeper decrease in the IDDM


Meal composition is another variable which needs to be

manipulated. High fiber foods which are digested more

slowly than the liquid Sustacal are likely to affect the

blood glucose curve differently. For example, a meal high

in fiber may actually exaggerate the initial decrease in

blood glucose noted in the IDDM subjects.

Another line of research involves identifying (or

confirming) the mechanisms responsible for the various

effects. Frequent sampling of indices of autonomic response

(e.g., catecholamines, cortisol, glucagon) as well as

measures of gastric emptying should be included. Recent

investigations utilizing a glucose/insulin infusion system

allows greater control of baseline levels. Chemical

infusion studies help demonstrate the direct effect of

stress hormones on blood glucose and insulin.

Lastly, research assessing the external validity of

these stress-induction studies is very important. Do the

psychological and physiological effects of the lab stressors

generalize to naturally occurring life events?

In addition to the numerous possible implications noted

above, this study has several practical implications. The

possible hypoglycemia and rebound observed in this study in

response to stress may explain the difficulty controlling

some IDDM patient's glucose levels during periods of stress.

However, due to the high baseline levels of blood glucose,

despite a precipitous drop during the stressor (up to 50

mg/dl), it was rare for a subject to actually attain a

hypoglycemic level. One IDDM subject started at a blood

glucose level of 74 mg/dl, dropped to approximately 56 mg/dl

within the first 10 minutes of the stressor, and eventually

"rebounded" to a level 25 mg/dl above baseline. An

awareness of this potential to become hypoglycemic

(particularly during a time when blood glucose levels are

already low as in the above subject) may necessitate meal

changes (composition and timing) or insulin changes (dosage,

type or timing). For example, in order to avoid a potential

drop in blood glucose and subsequent rebound, an IDDM

college student preparing for an early morning stressful

exam, may want to eat breakfast before insulin

administration to allow for some glucose absorption. A

hypoglycemic episode would surely affect test performance or

driving ability on the way to the test. Similarly, IDDM

patients stressed 4-6 hours after insulin administration,

when NPH peaks, may be more likely to experience a drop in

blood glucose.

A disruption in regimen adherence due to life stress

may potentiate the destabilizing effects of stress on

metabolic control. A behavior change (e.g., skipping a

meal) combined with the phenomenon described in this study

may prove to be dangerous for an IDDM individual.

Considering the effects of stress on NIDDM subjects,

stress reduction techniques which decrease sympathetic

nervous system activity may indeed have utility in the

treatment of NIDDM particularly during periods of stress.

The growing literature reporting the effects of relaxation

training in NIDDM patients discussed earlier are promising.

Hopefully, the interesting results and discovery of

crucial methodology revealed in the present study will help

to end some of the frustration and motivate additional

studies in this exciting research area in order to clarify

the role of psychological stress in diabetes control and

ultimately enhance the health status of individuals with



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