ArticlePDF Available


Globally, there is an increasing prevalence of non-communicable diseases. The morbidity and mortality from these conditions confer a greater economic societal burden. Epidemiological research associates insulin resistance in the etiology of these diseases, but there is limited evidence for the mechanism of damage. Emerging research suggests that hyperinsulinemia, a symptom of insulin resistance, may cause these pathological changes, and therefore be an independent contributor to these diseases. This review shows that hyperinsulinemia, or excessive insulin secretion, should be considered independently to insulin resistance, defined as glucose uptake rate, even though the two conditions are intertwined and will co-exist under normal conditions. Hyperinsulinemia directly and indirectly contributes to a vast array of metabolic diseases including all inflammatory conditions, all vascular diseases, gestational and type 2 diabetes, non-alcoholic fatty liver disease, obesity and certain cancers and dementias. The mechanisms include increased production of: insulin growth factor-1; reactive oxidative species and advanced glycation end-products; and triglyceride and fatty acids. Hyperinsulinemia also directly and indirectly affects many other hormones and cytokine mechanisms including leptin, adiponectin and estrogen. There is limited research standardizing the hyperinsulinemia diagnostic process. Methodological concerns and lack of standardized reference ranges preclude the use of fasting insulin. Most research has also focused on insulin resistance and it is unknown whether these methods translate to hyperinsulinemia.
Corresponding Author, E-mail: 1Human Potential Centre & 2Biostatistics and Epidemiology, Auckland University of
Technology (AUT), PO Box 92006, Auckland 1142, New Zealand. Copyright: © 2015 The Authors. This is an open-access article
distributed under the terms of the Creative Commons Attribution License.
Catherine A.P Crofts*1, Caryn Zinn1, Mark C Wheldon2, Grant M Schofield1
Diabesity 2015; 1 (4): 34-43 doi: 10.15562/diabesity.2015.19
Globally, there is an increasing prevalence of non-communicable diseases. The morbidity and mortality from
these conditions confer a greater economic societal burden. Epidemiological research associates insulin
resistance in the etiology of these diseases, but there is limited evidence for the mechanism of damage.
Emerging research suggests that hyperinsulinemia, a symptom of insulin resistance, may cause these
pathological changes, and therefore be an independent contributor to these diseases. This review shows that
hyperinsulinemia, or excessive insulin secretion, should be considered independently to insulin resistance, defined
as glucose uptake rate, even though the two conditions are intertwined and will co-exist under normal
conditions. Hyperinsulinemia directly and indirectly contributes to a vast array of metabolic diseases including all
inflammatory conditions, all vascular diseases, gestational and type 2 diabetes, non-alcoholic fatty liver disease,
obesity and certain cancers and dementias. The mechanisms include increased production of: insulin growth
factor-1; reactive oxidative species and advanced glycation end-products; and triglyceride and fatty acids.
Hyperinsulinemia also directly and indirectly affects many other hormones and cytokine mechanisms including
leptin, adiponectin and estrogen. There is limited research standardizing the hyperinsulinemia diagnostic process.
Methodological concerns and lack of standardized reference ranges preclude the use of fasting insulin. Most
research has also focused on insulin resistance and it is unknown whether these methods translate to
Hyperinsulinemia, hyperglycemia, type 2 diabetes, insulin resistance, secretagogue, syndrome x
Impaired insulin homeostasis encompasses
both hyperinsulinemia and hypoinsulinemia. Although
the latter is well recognised as type 1 diabetes, there is
little literature on the former, despite being first
hypothesised in the early 1920s.1 Currently, a close
approximation to hyperinsulinemia research is that
conducted on insulin resistance. Insulin resistance is
well-established as underpinning many significant
chronic health conditions including type 2 diabetes,
metabolic syndrome, cardiovascular disease, some
cancers and Alzheimer’s disease.2-5 This insulin
resistance is invariably accompanied by increased
demands for insulin so that the body can maintain
euglycemia. Excess insulin, termed hyperinsulinemia,
may be endogenous from bodily compensation, or
exogenous via modern medicine. In this paper we
contend that hyperinsulinemia, in concert with insulin
resistance, should be considered as an important
independent health risk. We exclude isolated
hyperinsulinemia, such as that caused by an
It is well recognised that earliest detection of
any disease state allows for the best possible
outcomes. It is agreed that hyperinsulinemia precedes
hyperglycemia, by up to 24 years.3, 4, 6 There is a strong
argument that hyperglycemia indicates pancreatic β-
cell attrition; essentially end-stage organ damage.3, 7 We
contend that the under-recognition of
hyperinsulinemia is an important clinical issue because
there are no standard diagnostic reference values, is
most accurately diagnosed with dynamic glucose and
insulin testing, and has few (pharmaceutical)
management options. This review will discuss
pathophysiology and diagnosis of hyperinsulinemia.
Hyperinsulinemia was first theorised in 19241,
but it was not until the 1960’s that direct insulin
measurements became possible.8 Since then, there has
been a wealth of research in the field of insulin
resistance with a small amount of research into
hyperinsulinemia. Therefore, we highlight the disease
states that are both directly and/or indirectly
associated with hyperinsulinemia. We also discuss the
availability and limitations of current diagnostic
Hyperinsulinemia: A unifying theory of chronic disease?
A unifying theory of hyperinsulinemia Catherine Crofts et al.
Diabesity 2015; 1(4): 34-43. doi: 10.15562/diabesity.2015.19
methods for hyperinsulinemia and why further
investigations are needed.
For this narrative review, literature was reviewed on
hyperinsulinemia and insulin resistance, targeting full-
text English language studies. There was no date
criterion. Articles were selected on the basis of having
a minimum of both a plausible biological mechanism
and established clinical association. Initially, the
academic database search included EBSCO, Medline
and Google Scholar, using variants of the terms
hyperinsulinemia, insulin resistance, metabolic
syndrome, and syndrome x, individually and
conjunction with non-communicable disease,
mechanism, atherosclerosis, and cardiovascular
disease. As subsequent metabolic diseases and/or
mechanisms were eluded to in the initial search, search
terms were widened so that no disease state was
excluded. Subsequent metabolic diseases included, but
were not limited to, conditions such as non-alcoholic
fatty liver disease, cancer, dementia. The final
selection of references was based on the authors’
judgment of relevance, completeness, and
compatibility with clinical, epidemiological,
pathological and biochemical criteria.
There is no precise definition of
hyperinsulinemia. It is often described as ‘more insulin
than normal to achieve euglycemia; essentially the
same as insulin resistance. Where a reference range is
available, it is normally based on fasting levels and
include 5-13 µU/mL9, ≤ 30 µU/mL10, and 18-173
pmol/L (3-28 µU/mL)11 However, there are very few
studies where a normal level of insulin is defined as
many studies define hyperinsulinemia based on
quantiles.12-14 Few studies have been more specific.
Both a fasting serum insulin of ≥12.2 µU/mL in the
presence of euglycemia15 and a range of 8-11 µU/mL
between meals and up to 60 µU/mL after meals16
have been proposed. There are also practical,
methodological issues with determining insulin
resistance under the World Health Organization
(WHO) conditions that will be discussed later in this
The etiology of hyperinsulinemia is not yet
fully elucidated. Although there are several theories,
further research will likely show a multimodal
pathology. What can be deduced from physiological
principles is:
1. Healthy cells are subjected to acute hyperglycemia.
2. Although many cells can absorb glucose without
using insulin (GLUT1 transportation) hyperglycemia
causes insulin to be released from pancreatic cells to
facilitate absorption, especially in muscle and adipose
cells (GLUT 4 transportation).17 3. Insulin binds to
cellular insulin receptors and facilitates translocation of
GLUT4 to the cellular surface. During this process the
insulin and its receptor are absorbed into the cell to be
replaced from the internal pool of insulin receptors.18
4. This acute insulin resistance is of no consequence as
long as the cell has viable GLUT4 on the cellular
surface. However, GLUT4 have a relatively short half-
life.19 5. If hyperglycemia persists, the pancreas
maintains insulin secretion. This may deplete the
insulin receptors faster than they can be replaced. 6.
During this period where the cells are replacing their
insulin receptors, moderately elevated blood glucose
levels, (such as that immediately found after a normal
meal) may need slightly higher than normal insulin
levels to restore normoglycemia. This moderate
hyperinsulinemia may delay the return to normal
insulin receptor function (acute insulin resistance).7
This state of insulin resistance due to down-regulated
insulin receptors is reversible should the person not be
subjected to further episodes of hyperglycemia. It does
not matter whether this is via high, but acute, blood
glucose elevations, or moderately elevated glucose
levels over a prolonged period. 8. Prolonged impaired
insulin signaling impedes GLUT4 translocation to the
cellular surface thus causing impaired glucose uptake
and prolonging hyperglycemia, causing a positive
feedback cycle. This will both aggravate and prolong
the insulin resistance, potentially turning it from a
transitory state to a persistent or chronic state.
The complexity of the insulin receptor
regulation, combined with the availability of GLUT4
and factors that influence insulin secretion mean that
it is impossible to generalize whether insulin resistance
precedes or follows hyperinsulinemia. It is more
plausible that different individuals have different
triggers in the cycle. These triggers may include
genetic factors, excessive carbohydrate, corticosteroids
(endogenous or exogenous), free fatty acids, leptin, or
certain medications; each of these are discussed below.
Fructose: Fructose is metabolized in liver into ATP
and/or triglycerides in a process that is competitive
with, and preferential to, glucose. If excessive fructose
is consumed, glucose will not be metabolized causing
hyperglycemia and subsequent hyperinsulinemia.20, 21
Excessive fructose also results in hyperuricemia which
A unifying theory of hyperinsulinemia Catherine Crofts et al.
Diabesity 2015; 1(4): 34-43. doi: 10.15562/diabesity.2015.19
is associated with reduced endothelial nitric oxide
causing vasoconstriction, endothelial dysfunction and
insulin resistance.21
Hyperglycemia: Hyperglycemia alone can aggravate
insulin resistance.22 Along with excessive carbohydrate
ingestion, other mechanisms for this mechanism
include hepatic insulin resistance. Increased plasma
insulin slows hepatic gluconeogenesis but this process
can be impaired by hepatic insulin resistance leading to
peripheral hyperglycemia and further insulin
Corticosteroids: It is known that corticosteroids,
especially endogenous cortisol, cause a down
regulation of GLUT-4 receptors, thus preventing
glucose uptake and provoking hyperinsulinemia in the
presence of hyperglycemia. Long-term courses of
exogenous corticosteroids, such as prednisone, are
known to cause ‘drug-induced’ type 2 diabetes, which
may resolve after the medication is discontinued. Not
every patient on long-term corticosteroids will develop
drug-induced diabetes. Therefore, it is plausible that
the patient’s degree of insulin resistance at baseline
influences disease development/progression. Given
that stress causes a temporary rise in cortisol levels, it
is also plausible that prolonged stress may be another
cause of hyperinsulinemia.24
Leptin: Appetite control is mediated from the
hypothalamus in response to a balance between leptin
and insulin controlling neuropeptide Y expression.25
This balance is believed important to manage caloric
intake over longer periods of time when meals can
vary in size, frequency and composition. Leptin
secretion is slow to change as it is influenced by total
body fat mass and total caloric intake, while insulin
secretion is highly responsive to food ingestion and
will change quickly with every meal. Leptin is also
highly influenced by insulin as it is released from fat
stores by mechanisms that appear to involve glucose
flux.25 Experimental evidence shows that reducing
insulin secretion reduces leptin resistance, suggesting a
relationship between hyperinsulinemia and
hyperleptinemia.26 It is not yet clear whether
hyperleptinemia is causative of hyperinsulinemia
beyond the association of obesity and an increase in
free fatty acids.
Medication-induced: There are a number of medications
known or suspected to cause hyperinsulinemia and/or
contribute to insulin resistance. Exogenous
corticosteroids (prednisone) and exogenous insulin
and insulin secretagogues (sulphonylureas) have had
their mechanisms discussed. Other medications
include the antipsychotics (e.g. clozapine), and
statins.27 The mechanisms for these medications
causing hyperinsulinemia are currently unknown.
Due to the nature of insulin receptor
regulation, it is also plausible that insulin sensitivity of
the cells can be restored. This would require the
absence of both hyperinsulinemia and hyperglycemia.
Case studies indicate that a carbohydrate restricted diet
may facilitate this effect.10
Overall, it should be recognized that
hyperinsulinemia is independent to insulin resistance:
Hyperinsulinemia is excessive insulin secretion, while
insulin resistance is impaired glucose uptake. This
review investigates the both the mechanistic and
epidemiological evidence that links hyperinsulinemia
to metabolic disease. Although there is good quality
research mechanistically linking hyperinsulinemia to
subsequent pathologies, there is a paucity of good
epidemiological evidence. Given the intertwined
nature between insulin resistance and hyperinsulinemia
as depicted above, it can be assumed that the majority
of people with insulin resistance are also
hyperinsulinemic. Therefore, if no epidemiological
data was available, this review used epidemiological
research based on insulin resistance as a proxy for
Direct effects of hyperinsulinemia
As shown in Table 1, hyperinsulinemia can be
mechanistically and epidemiologically linked to
metabolic syndrome, gestational and type 2 diabetes
and therefore, cardiovascular and other diseases with
an increased prevalence in those with metabolic
syndrome.2-4, 28 It is also an independent risk factor for
a number of other diverse conditions including diet-
induced obesity, osteoarthritis, certain cancers,
especially breast and colon/rectum, and Alzheimer’s
disease and other dementias.5, 6, 29-32
Other conditions that may be associated with
hyperinsulinemia, via either epidemiological evidence
or potential mechanism of action, include gout,
tinnitus, schizophrenia and autism.33-36 Further
research is needed to confirm these associations.
Pathophysiological mechanisms
Hyperinsulinemia affects the body via five
main mechanisms: Increased reactive oxidative species
and advanced glycation end-products; increased
insulin-like growth factor-1 (IGF-1); hyperglycemia;
increased fatty acid/triglyceride production; and by
affecting different hormones and cytokines.
Reactive oxidative species
Reactive oxygen species is a collective term that
includes both oxygen radicals and non-radical
A unifying theory of hyperinsulinemia Catherine Crofts et al.
Diabesity 2015; 1(4): 34-43. doi: 10.15562/diabesity.2015.19
Table 1. Biological systems and disease states affected by hyperinsulinemia, and associated mechanisms of action
Direct or
of action
Increased insulin-like growth factor IGF-1 enhances cellular
growth and proliferation.
(5, 48)
Enhanced glucose uptake and utilization enhances cellular
growth and proliferation.
Increased production of reactive oxidative species causes
derangement of DNA and enzymes involved with repair
mechanisms (enhanced by hyperglycemia).
(2, 37, 38)
(2, 37, 38)
Increased sex-hormone production and decreased sex
hormone binding globulin causes increased cellular growth
and proliferation (enhanced by obesity).
Arterial wall damage caused by inflammation, increased
proliferation and migration of arterial smooth muscle cells.
Stimulation of the mitogen-activated protein kinase pathway.
(28, 40)
(28, 47, 63,
Microvascular disease, including changes to capillary
permeability, microaneurysm formation, vasoconstriction and
(65, 66)
(65, 66)
Increased myocardial fibrosis by increased reactive
oxidative species, deranged collagen production.
Diabetic neuropathy causes changes to catecholamines, which
further impairs myocardial function.
Vasoconstriction and pro-atherosclerotic effects from
decreased nitric oxide bioavailability and action and
increased thromboxane.
(2, 41, 67)
Enhanced by increased reactive oxidative species and
advanced glycation end-products.
Hyperinsulinemia causes increased fibrinolysis while
hyperglycemia causes increased blood coagulability
Pre-existing insulin resistance and increased demand for
Prolonged insulin resistance eventuating in beta-cell failure.
Down-regulation of glucose transporter-4.
(3, 69, 70)
Increased triglyceride production.
(43, 71)
Fatty acid production exceeds distribution capacity.
Aggravated by inflammation and oxidative stress.
Stimulation of mitogen-activated protein kinase pathway;
glycemic variability; hyperglycemia and/or obesity
influences increased cytokine production.
(40, 48)
Decreased lipolysis.
Lack of appetite suppression.
(25, 26)
Endothelial dysfunction resulting in microvascular disease,
metabolic disturbances and neuronal damage.
(2, 67, 77)
(30, 78, 79)
Increased blood coagulability and/or fibrinolysis cause
multiple thrombotic events.
(42, 80)
A unifying theory of hyperinsulinemia Catherine Crofts et al.
Diabesity 2015; 1(4): 34-43. doi: 10.15562/diabesity.2015.19
Changed regulation of beta-amyloid and tau protein
(Alzheimer's disease).
(77, 81)
Decreased synaptic plasticity caused by dysregulated PSA-
NCAM interactions (Alzheimer's disease).
Increased production of reactive oxidative species and
advanced glycation end-products enhanced by
(2, 41)
(64, 82)
Insulin resistance in the dorsal root ganglion neurons.
Hyperglycemia and endothelial dysfunction contribute blood-
retinal barrier breakdown. Aggravated by excess advanced
glycation end-products.
(41, 64, 84)
(41, 64, 84)
Increased reactive oxidative species and/hyperglycemia
cause collagen breakdown, impairs new collagen synthesis
and compromises mensenchymal cells.
Microvascular disease, including changes to capillary
permeability, microaneurysm formation, vasoconstriction and
(67, 85)
(64, 86)
Increased production of reactive oxidative species and
advanced glycation end-products enhanced by
(41, 87)
*While cancer is not typically classified as a “biological system”, due to its recognition and impact as a key chronic disease, it was decided that it warrants a
classification on its own, rather than be integrated into individual biological systems. PSA-NCAM-polysialic acid - neural cell adhesion molecule.
oxidising agents such as hydrogen peroxide.37 Reactive
oxidative species are also produced during, and
involved in, many metabolic processes including
enzymatic reactions, gene expression and signal
transduction.37 Generally, the actions of intracellular
reducing agents such as antioxidants prevent reactive
oxidative species-mediated damage. However, a
number of factors can contribute to excessive
production of reactive oxidative species including
excessive calorie consumption and the presence of
various pro-inflammatory mediators, including tumor
necrosis factor-α.37 Once produced, reactive oxidative
species can interact with numerous cellular
components including DNA, lipids, and amino acids.
Damage to DNA is likely to be the underlying
mechanism for reactive oxidative species being
associated with cancer and early aging.38
Polyunsaturated fatty acids are considered very
susceptible to reactive oxidative species damage,
triggering lipid peroxidation, which can affect cell
membrane fluidity and integrity, potentially being the
mechanism for endothelial damage.37 Amino acids
such as cysteine and methionine are very susceptible to
reactive oxidative species damage. Changes to these
amino acids are implicated in the development of
Alzheimer’s disease.39
Hyperinsulinemia is associated with increased
reactive oxidative species, although the exact
mechanism is disputed. Hyperinsulinemia is
mechanistically linked to excessive serum glucose and
free fatty acids. Either substrate can cause increased
reactive oxidative species production.2 Insulin has also
been demonstrated to have some inhibitory effects on
reactive oxidative species production that may be
independent of its effects on glycemia.40 However,
reducing insulin-stimulated nutrient uptake into the
cell is also believed to decrease reactive oxidative
species production.2 Further research is required to
better understand these mechanisms.
Over-nutrition is also thought to be
responsible for the formation of advanced glycation
end-products via non-enzymatic glycation and
glycooxidation processes.41 Defective renal excretion
of advanced glycation end-products, as seen with
diabetic nephropathy, and consumption of exogenous
advanced glycation end-products increases plasma
advanced glycation end-product levels. Advanced
glycation end-products are believed to contribute to
changes in the microvascular systems and also
promote changes to inflammatory, oxidative and other
degenerative processes of various chronic diseases
including neuropathies.41
Growth factors (IGF, vascular endothelial growth
Insulin, IGF-1 and other substances such as
vascular endothelial growth factor (VEGF) can
stimulate the growth and division of many cells.
Insulin can mediate cellular division but may also
stimulate cancer cell proliferation and metastasis.29
Most importantly, insulin increases the bioavailability
of IGF-1, thus insulin is indirectly implicated in all
IGF-1 mediated processes. These processes include
changes to vascular structures, increases to cellular
division and prevention of apoptosis
A unifying theory of hyperinsulinemia Catherine Crofts et al.
Diabesity 2015; 1(4): 34-43. doi: 10.15562/diabesity.2015.19
Hyperglycemia commonly follows
hyperinsulinemia3 but there is little information to
suggest whether fasting glucose, peak glucose, or area-
under-the curve (AUC) have the most adverse health
impact. Cancer cells have a continuously high glucose
uptake, which enhances cellular growth and
proliferation29; hyperglycemia augments this process.
Hyperglycemia allows IGF-1 to stimulate vascular
smooth muscle proliferation, which is a hall-mark of
both cancer and atherosclerosis. Blood coagulability is
also increased by hyperglycemia irrespective of insulin
Increased fatty acid and triglyceride production
Hyperinsulinemia influences both free fatty
acid and triglyceride production.43 While the processes
that occur during hepatic de novo lipogenesis are not
disputed, there is debate as to whether
hyperinsulinemia precedes, or are a consequence of
fatty liver.44 Nevertheless, elevated triglyceride levels
are recognized to be a key component of metabolic
syndrome (Table 1) while fatty liver may be considered
a hepatic manifestation of metabolic syndrome and
may progress to cirrhosis or hepatocellular cancer.44
Elevated triglyceride levels may also further impair
leptin resistance.20, 45
Hormone/cytokine production (sex hormones,
inflammation, obesity)
Hyperinsulinemia is involved with adiposity
via increased appetite and triglyceride production,
thereby increasing adiposity.46, 47 Adipose tissue is now
well-established as an endocrine organ and produces
both hormones and cytokines that are used for cellular
communication. Hypertrophic adipose tissues activate
inflammatory and stress pathways and decreases
insulin response. This results in increased cytokine
production including TNF-α, vascular endothelial
growth factor and leptin, while adiponectin expression
is decreased.48 These actions contribute to decreased
glucose and lipid uptake, leading to further reductions
to adiponectin secretion and adipogenesis as well as
contributing to further insulin resistance. Decreased
glucose uptake means there is less glycerol within the
adipocyte to esterify free fatty acids, allowing them to
infiltrate and accumulate in other tissues.
Adiponectin decreases proliferation of cell
types including adipocytes, endothelial cells and cancer
cells.48 The role of leptin is yet to be fully understood,
but it is accepted that hyperinsulinemia and
hyperleptinemia results in central leptin resistance, and
consequent prevention of appetite suppression and
promotion of further obesity.25, 26, 49 Hyperleptinemia
is also linked to increased inflammatory cytokines,
changes in nitric oxide, and further endothelial
Hyperinsulinemia is also believed to elevate
plasminogen activator inhibitor type-1 (PAL-1) levels,
with associated increased fibrinolysis and increased
risk of thrombosis. When combined with the
increased coagulation from hyperglycemia, this may
explain why over 80% of people with type 2 diabetes
have a thrombotic death.42
Diagnosing hyperinsulinemia is challenging
partly because the health effects of insulin resistance
and hyperinsulinemia have been conflated. Further
challenges arise when interpreting the available
literature. As previously discussed, fasting insulin
levels have been assessed as a means of diagnosing
hyperinsulinemia with differing results. But it is not
just the insulin level alone that is problematic. How
and when sampling occurs will also cause variation to
results. Insulin levels are higher in serum compared to
plasma samples meaning that studies reporting serum
insulin cannot be compared directly to plasma
insulin.50, 51 Insulin secretion is pulsatile leading to
significant levels in plasma insulin in a short space of
time. It is recommended that the mean of three
samples taken at five minute intervals be used if a
fasting insulin level is required52, however this rarely
seem to happen in practice. Single fasting insulin
samples can have a coefficient of variation of 25-
50%.53 This variation decreases testing sensitivity and
is perhaps why fasting insulin is not recommended to
be used clinically.54
It is unknown whether insulin resistance
testing can be used to diagnose hyperinsulinemia. The
gold standard for measuring insulin resistance is the
hyperinsulinemic-euglycemic clamp test. The lowest
quartile of glucose uptake rate defines insulin
resistance for that study population. Figures for this
lower quartile have ranged from < 4.7mg/kg ·min to
6.3M·mU-1·L-1, however differences in insulin
infusion rates, glucose disposal rate calculations, and
background populations under investigation means
that there are limits to the generalizability of these
results.15, 55-58 Furthermore, given the complexity of the
procedure, the hyperinsulinemic-euglycemic clamp
test has little to no clinical application.15
A further complication to using the clamp test
to assess hyperinsulinemia is that the high dose
infusion of insulin will confound any effects of
endogenous insulin secretion. As theorized above, the
damage associated with hyperinsulinemia is due to the
A unifying theory of hyperinsulinemia Catherine Crofts et al.
Diabesity 2015; 1(4): 34-43. doi: 10.15562/diabesity.2015.19
continuous action of insulin in the tissues. The
amount of insulin normally present in the tissues
cannot be measured during the clamp process. It is
unknown whether glucose uptake rates correlate with
insulin secretion.
A number of tests have been developed that
are validated against the hyperinsulinemic-euglycemic
clamp that has more clinical applicability. Those based
on fasting insulin include homeostatic model
assessment (HOMA or HOMA2), McAuley Index,
and the quantitative insulin sensitivity check index
(QUICKI).15, 56, 59 Although HOMA has since been
refined to the HOMA2 model, both are modelled on
the combination of fasting insulin to fasting glucose.
The original HOMA has a 89% sensitivity and 67%
specificity compared to hyperinsulinemia-euglycemic
clamp.57 The McAuley index is calculated from fasting
insulin and fasting triglyceride levels with 61%
sensitivity and 85% specificity.15
Another insulin resistance test, the oral
glucose sensitivity index (OGIS), is modelled on the
results derived from an oral glucose tolerance test.56
OGIS uses both blood insulin and glucose levels at
baseline, 120 min and 180 min. A spreadsheet is
recommended for the calculations (available from The
OGIS is validated against the hyperinsulinemic-
euglycemic clamp assessments for insulin resistance,
but as previously stated, the generalizability of clamps
is limited.
Both the OGIS and tests based on fasting
insulin levels have more clinical applicability for
assessing insulin resistance compared to the
hyperinsulinemic-euglycemic clamp test. However,
insulin resistance testing has never translated to
improvements in disease risk calculations. The WHO
definition for insulin resistance means that one in four
people would be diagnosed with insulin resistance; a
figure that may be unrelated to their actual health
risks.60 Analysis from the Women’s Health Initiative
Biomarkers study showed that although HOMA-IR
had a positive association with cardiovascular risk, this
was became non-significant after adjusting for other
risk factors such as HDL cholesterol.61 There is an
argument that HOMA-IR should be used in
combination with HOMA-%B for assessing insulin
Emerging research now suggests that insulin
response patterns following an oral glucose load may
determine hyperinsulinemic status. Kraft7,10
demonstrated the variability of insulin response to a
100 g glucose load over 3-5 hours, especially with
respect to timing and magnitude of the insulin peak
and rate of response decline. Five main insulin
response patterns are clearly identifiable, with pattern I
being considered normal insulin tolerance. From this
research Kraft concluded that the most accurate
means of assessing hyperinsulinemia was a 3-hour oral
glucose tolerance test with insulin levels assessed at
baseline, 30, 60, 120, and, at minimum, 180 minutes
but 240 and 300 minute insulin levels could also be
considered. This study was cross-sectional and there
are no long-term outcomes.
Hayashi and colleagues62 have shown that the
insulinemic pattern produced from sampling every 30
minutes during a 2-hour OGTT can predict the
development of type 2 diabetes. An insulin peak
delayed beyond 60 minutes being associated with
poorer health is common to both Kraft and Hayashi
patterns. Further research is required to understand
how to apply these patterns to clinical practice.
Collectively these studies show that there is a
paucity of research for diagnosing hyperinsulinemia.
Most studies focus on insulin resistance testing, but it
remains unknown whether insulin resistance correlates
with insulin secretion.
Concluding remarks
This review clearly demonstrates that not only
is hyperinsulinemia involved with the etiology of all of
the symptoms of metabolic syndrome, it is also
implicated in many other conditions; some of which
have previously been considered to be idiopathic, such
as tinnitus. This raises many questions with both
clinical and research implications. Firstly, what is the
prevalence of hyperinsulinemia? Given its association
with metabolic syndrome and fatty liver disease, this
warrants investigation. Could early detection and
careful management of hyperinsulinemia decrease the
need for medical interventions later in life? Would
managing hyperinsulinemia improve to both quantity
and quality of life? Yet there are currently too many
questions regarding diagnosis. A reliable and
repeatable result when sampling insulin is still a
challenging task. There is no agreed upon reference
range, and there are only associations between
quantiles and ongoing disease risk. Insulin response
patterning may answer some of these questions, but
patterning requires more resources than a fasting level.
Given the global concerns about the ‘epidemic’ of
metabolic diseases, this research needs to be urgently
Conflict of interest
None Declared.
A unifying theory of hyperinsulinemia Catherine Crofts et al.
Diabesity 2015; 1(4): 34-43. doi: 10.15562/diabesity.2015.19
1. Harris S. Hyperinsulinism and dysinsulinism. Journal of
the American Medical Association. 1924;83:729-33.
2. Ceriello A, Motz E. Is oxidative stress the pathogenic
mechanism underlying insulin resistance, diabetes, and
cardiovascular disease? The common soil hypothesis
revisited. Arterioscler Thromb Vasc Biol.
3. Weir GC, Bonner-Weir S. Five stages of evolving beta-
cell dysfunction during progression to diabetes.
Diabetes. 2004;53(suppl 3):S16-S21.
4. Zavaroni I, Bonini L, Gasparini P, Barilli A, Zuccarelli A,
Dall'Aglio E, et al. Hyperinsulinemia in a normal
population as a predictor of noninsulin-dependent
diabetes mellitus, hypertension, and coronary heart
disease: The Barilla factory revisited. Metabolism.
5. Pollak M. Insulin and insulin-like growth factor signalling
in neoplasia. Nat Rev Cancer. 2008;8(12):915-28.
6. Dankner R, Chetrit A, Shanik MH, Raz I, Roth J. Basal
state hyperinsulinemia in healthy normoglycemic adults
heralds dysglycemia after more than two decades of
follow up. Diabetes Metab Res Rev. 2012;28(7):618-24.
7. Kraft JR. Diabetes epidemic and you. 2nd ed. Victoria,
BC: Trafford; 2011.
8. Yalow RS, Berson SA. Immunoassay of endogenous
plasma insulin in man. J Clin Investig. 1960;39(7).
9. Labtests. Reference Intervals 2012 [cited 2013 January
29]. Available from:
10. Kraft JR. Detection of diabetes mellitus in situ (occult
diabetes). Laboratory Medicine. 1975;6(2):10-22.
11. Waikato District Health Board. Laboratory test reference
guide Hamilton2015 [cited 2015 September 16].
Available from:
12. Lan-Pidhainy X, Wolever T. Are the glycemic and
insulinemic index values of carbohydrate foods similar
in healthy control, hyperinsulinemic and type 2 diabetic
patients? Eur J Clin Nutr. 2011;65(6):727-34.
13. Nilsson P, Nilsson JÅ, Hedblad B, Eriksson KF,
Berglund G. Hyperinsulinaemia as long-term predictor
of death and ischaemic heart disease in nondiabetic
men: The Malmö Preventive Project. J Intern Med.
14. Laakso M. How good a marker is insulin level for insulin
resistance? Am J Epidemiol. 1993;137(9):959-65.
15. McAuley KA, Williams SM, Mann JI, Walker RJ, Lewis-
Barned NJ, Temple LA, et al. Diagnosing insulin
resistance in the general population. Diabetes Care.
2001 March 1, 2001;24(3):460-4.
16. Iwase H, Kobayashi M, Nakajima M, Takatori T. The
ratio of insulin to C-peptide can be used to make a
forensic diagnosis of exogenous insulin overdosage.
Forensic Sci Int. 2001;115(12):123-7.
17. Wilcox G. Insulin and insulin resistance. Clinical
Biochemist Reviews. 2005;26(2):19-39.
18. Grunberger G, Taylor SI, Dons RF, Gorden P. Insulin
receptors in normal and disease states. Clin Endocrinol
Metab. 1983 Mar;12(1):191-219.
19. Schnurr TM, Reynolds AJ, Komac AM, Duffy LK,
Dunlap KL. The effect of acute exercise on GLUT4
levels in peripheral blood mononuclear cells of sled
dogs. Biochemistry and Biophysics Reports. 2015
20. Farooqui AA, Farooqui T, Panza F, Frisardi V.
Metabolic syndrome as a risk factor for neurological
disorders. Cell Mol Life Sci. 2012 Mar;69(5):741-62.
21. Johnson RJ, Perez-Pozo SE, Sautin YY, Manitius J,
Sanchez-Lozada LG, Feig DI, et al. Hypothesis: Could
excessive fructose intake and uric acid cause type 2
diabetes? Endocr Rev. 2009;30(1):96-116.
22. Vuorinen-Markkola H, Koivisto VA, Yki-Jarvinen H.
Mechanisms of hyperglycemia-induced insulin
resistance in whole body and skeletal muscle of type I
diabetic patients. Diabetes. 1992 May 1,
23. Hundal RS, Krssak M, Dufour S, Laurent D, Lebon V,
Chandramouli V, et al. Mechanism by which metformin
reduces glucose production in type 2 diabetes.
Diabetes. 2000 December 1, 2000;49(12):2063-9.
24. Björntorp PE, Rosmond R. Hypothalamic origin of the
metabolic syndrome x. Ann N Y Acad Sci.
25. Porte D, Baskin DG, Schwartz MW. Leptin and insulin
action in the central nervous system. Nutr Rev.
26. Lustig RH, Sen S, Soberman JE, Velasquez-Mieyer PA.
Obesity, leptin resistance, and the effects of insulin
reduction. International Journal of Obesity & Related
Metabolic Disorders. 2004;28(10):1344-8.
27. Taylor D, Paton C, Kerwin R, editors. The Maudsley
prescribing guidelines. 9th ed: Informa Healthcare;
28. Stout RW. Insulin and atheroma: 20-yr perspective.
Diabetes Care. 1990 June 1, 1990;13(6):631-54.
29. Giovannucci E, Harlan DM, Archer MC, Bergenstal RM,
Gapstur SM, Habel LA, et al. Diabetes and cancer: A
consensus report. CA Cancer J Clin. 2010;60(4):207-
30. Feng L, Chong MS, Lim WS, Lee TS, Collinson SL,
Yap P, et al. Metabolic syndrome and amnestic mild
cognitive impairment: Singapore Longitudinal Ageing
Study-2 findings. J Alzheimer's Dis. 2013;34(3):649-57.
31. Yan W, Li X. Impact of diabetes and its treatments on
skeletal diseases. Front Med. 2013 Mar;7(1):81-90.
32. Mehran Arya E, Templeman Nicole M, Brigidi GS, Lim
Gareth E, Chu K-Y, Hu X, et al. Hyperinsulinemia
drives diet-induced obesity independently of brain
insulin production. Cell Metab. 2012;16(6):723-37.
33. Monzo HJ, Park TI, Dieriks VB, Jansson D, Faull RL,
Dragunow M, et al. Insulin and IGF1 modulate turnover
of polysialylated neuronal cell adhesion molecule (PSA-
NCAM) in a process involving specific extracellular
matrix components. J Neurochem. 2013;136(6):758-70.
A unifying theory of hyperinsulinemia Catherine Crofts et al.
Diabesity 2015; 1(4): 34-43. doi: 10.15562/diabesity.2015.19
34. Meyer U, Feldon J, Dammann O. Schizophrenia and
autism: Both shared and disorder-specific pathogenesis
via perinatal inflammation? Pediatr Res. 2011;69:26R-
35. Kraft JR. Hyperinsulinemia: A merging history with
idiopathic tinnitus, vertigo, and hearing loss.
International Tinnitus Journal. 1998;4(2):127-30.
36. Fam AG. Gout, diet, and the insulin resistance
syndrome. J Rheumatol. 2002;29(7):1350-5.
37. Bayir H. Reactive oxygen species. Crit Care Med.
38. Wiseman H, Halliwell B. Damage to DNA by reactive
oxygen and nitrogen species: Role in inflammatory
disease and progression to cancer. Biochem J.
39. Eto K, Asada T, Arima K, Makifuchi T, Kimura H. Brain
hydrogen sulfide is severely decreased in Alzheimer's
disease. Biochem Biophys Res Commun. 2002
40. Monnier L, Hanefeld M, Schnell O, Colette C, Owens D.
Insulin and atherosclerosis: How are they related?
Diabetes Metab. 2013;39(2):111-7.
41. Chilelli NC, Burlina S, Lapolla A. AGEs, rather than
hyperglycemia, are responsible for microvascular
complications in diabetes: A “glycoxidation-centric” point
of view. Nutr Metab Cardiovasc Dis. 201323(10):913-9.
42. Stegenga ME, van der Crabben SN, Levi M, de Vos
AF, Tanck MW, Sauerwein HP, et al. Hyperglycemia
stimulates coagulation, whereas hyperinsulinemia
impairs fibrinolysis in healthy humans. Diabetes.
43. Olefsky JM, Farquhar JW, Reaven GM. Reappraisal of
the role of insulin in hypertriglyceridemia. The American
journal of medicine. 1974;57(4):551-60.
44. Vanni E, Bugianesi E, Kotronen A, De Minicis S, Yki-
Järvinen H, Svegliati-Baroni G. From the metabolic
syndrome to NAFLD or vice versa? Dig Liver Dis.
45. Banks WA, Coon AB, Robinson SM, Moinuddin A,
Shultz JM, Nakaoke R, et al. Triglycerides induce leptin
resistance at the blood-brain barrier. Diabetes. 2004
May 1, 2004;53(5):1253-60.
46. Bugianesi E, McCullough AJ, Marchesini G. Insulin
resistance: A metabolic pathway to chronic liver
disease. Hepatology. 2005 Nov;42(5):987-1000.
47. Folsom AR, Szklo M, Stevens J, Liao F, Smith R,
Eckfeldt JH. A prospective study of coronary heart
disease in relation to fasting insulin, glucose, and
diabetes: The Atherosclerosis Risk in Communities
(ARIC) Study. Diabetes Care. 1997;20(6):935-42.
48. Matafome P, Santos-Silva D, Sena CM, Seiça R.
Common mechanisms of dysfunctional adipose tissue
and obesity- related cancer. Diabetes Metab Res Rev.
49. Martin SS, Qasim A, Reilly MP. Leptin resistance: A
possible interface of inflammation and metabolism in
obesity-related cardiovascular disease. J Am Coll
Cardiol. 2008;52(15):1201-10.
50. Henderson JR. Serum-insulin or plasma-insulin ? The
Lancet. 1970;296(7672):545-7.
51. Feldman JM, Chapman BA. Radioimmunoassay of
insulin in serum and plasma. Clin Chem.
52. Wallace TM, Levy JC, Matthews DR. Use and abuse of
HOMA modeling. Diabetes Care. 2004;27(6):1487-95.
53. Mather KJ, Hunt AE, Steinberg HO, Paradisi G, Hook
G, Katz A, et al. Repeatability characteristics of simple
indices of insulin resistance: Implications for research
applications. The Journal of Clinical Endocrinology &
Metabolism. 2001;86(11):5457-64.
54. Samaras K, McElduff A, Twigg SM, Proietto J, Prins JB,
Welborn TA, et al. Insulin levels in insulin resistance:
Phantom of the metabolic opera? Med J Aust.
55. Samaras K, McElduff A, Twigg SM, Proietto J, Prins JB,
Welborn TA, et al. Insulin levels in insulin resistance:
Phantom of the metabolic opera? Med J Aust.
56. Mari A, Pacini G, Murphy E, Ludvik B, Nolan J. A
model-based method for assessing insulin sensitivity
from the oral glucose tolerance test. Diabetes Care.
57. Tam CS, Xie W, Johnson WD, Cefalu WT, Redman
LM, Ravussin E. Defining insulin resistance from
hyperinsulinemic-euglycemic clamps Diabetes Care.
2012 July 1, 2012;35(7):1605-10.
58. Diamond MP, Thornton K, Connolly-Diamond M,
Sherwin RS, DeFronzo RA. Reciprocal variations in
insulin-stimulated glucose uptake and pancreatic insulin
secretion in women with normal glucose tolerance. J
Soc Gynecol Investig. 1995;2(5):708-15.
59. Katz A, Nambi SS, Mather K, Baron AD, Follmann DA,
Sullivan G, et al. Quantitative insulin sensitivity check
index: A simple, accurate method for assessing insulin
sensitivity in humans. Journal of Clinical Endocrinology
& Metabolism. 2000 July 1, 2000;85(7):2402-10.
60. World Health Organization. Definition, diagnosis and
classification of diabetes mellitus and its complications.
Geneva: World Health Organization, 1999.
61. Schmiegelow MD, Hedlin H, Stefanick ML, Mackey RH,
Allison M, Martin LW, et al. Insulin resistance and risk
of cardiovascular disease in postmenopausal women: A
cohort study from the Women’s Health Initiative.
Circulation: Cardiovascular Quality and Outcomes. 2015
May 1, 2015;8(3):309-16.
62. Hayashi T, Boyko EJ, Sato KK, McNeely MJ, Leonetti
DL, Kahn SE, et al. Patterns of insulin concentration
during the OGTT predict the risk of type 2 diabetes in
Japanese Americans. Diabetes Care. 2013;36(5):1229-
63. Huxley R, Barzi F, Woodward M. Excess risk of fatal
coronary heart disease associated with diabetes in men
and women: Meta-analysis of 37 prospective cohort
studies. BMJ. 2006;332(7533):73-8.
64. Donnelly R, Emslie-Smith AM, Gardner ID, Morris AD.
ABC of arterial and venous disease: Vascular
complications of diabetes. BMJ. 2000;320(7241):1062.
A unifying theory of hyperinsulinemia Catherine Crofts et al.
Diabesity 2015; 1(4): 34-43. doi: 10.15562/diabesity.2015.19
65. Maisch B, Alter P, Pankuweit S. Diabetic
cardiomyopathy--fact or fiction? Herz. 2011;36(2):102-
66. Tarquini R, Lazzeri C, Pala L, Rotella CM, Gensini GF.
The diabetic cardiomyopathy. Acta Diabetol.
67. Rask-Madsen C, King GL. Mechanisms of disease:
Endothelial dysfunction in insulin resistance and
diabetes. Nature Clinical Practice Endocrinology &
Metabolism. 2007;3(1):46-56.
68. Kaaja R, Rönnemaa T. Gestational diabetes:
Pathogenesis and consequences to mother and
offspring. The review of diabetic studies: RDS.
69. Flores-Riveros JR, McLenithan JC, Ezaki O, Lane MD.
Insulin down-regulates expression of the insulin-
responsive glucose transporter (GLUT4) gene: effects
on transcription and mRNA turnover. Proceedings of
the National Academy of Sciences. 1993;90(2):512-6.
70. Scheepers A, Joost H, Schurmann A. The glucose
transporter families SGLT and GLUT: molecular basis
of normal and aberrant function. J Parenter Enteral
Nutr. 2004 September 1, 2004;28(5):364-71.
71. Medina-Santillán R, López-Velázquez JA, Chávez-Tapia
N, Torres-Villalobos G, Uribe M, Méndez-Sánchez N.
Hepatic manifestations of metabolic syndrome. Diabetes
Metab Res Rev. 2013.
72. Marchesini G, Brizi M, Morselli-Labate AM, Bianchi G,
Bugianesi E, McCullough AJ, et al. Association of
nonalcoholic fatty liver disease with insulin resistance.
The American journal of medicine. 1999;107(5):450-5.
73. Marques-Vidal P, Bastardot F, Känel R, Paccaud F,
Preisig M, Waeber G, et al. Association between
circulating cytokine levels, diabetes and insulin
resistance in a population-based sample (CoLaus
study). Clin Endocrinol (Oxf). 2013;78(2):232-41.
74. Choi SM, Tucker DF, Gross DN, Easton RM, DiPilato
LM, Dean AS, et al. Insulin regulates adipocyte lipolysis
via an Akt-independent signaling pathway. Mol Cell
Biol. 2010 November 1, 2010;30(21):5009-20.
75. Swinburn BA, Sacks G, Lo SK, Westerterp KR, Rush
EC, Rosenbaum M, et al. Estimating the changes in
energy flux that characterize the rise in obesity
prevalence. Am J Clin Nutr. 2009;89(6):1723-8.
76. Yu JH, Shin MS, Kim DJ, Lee JR, Yoon SY, Kim SG, et
al. Enhanced carbohydrate craving in patients with
poorly controlled Type 2 diabetes mellitus. Diabetic
Medicine. 2013;30(9):1080-6.
77. Humpel C. Chronic mild cerebrovascular dysfunction as
a cause for Alzheimer's disease? Exp Gerontol.
78. Razay G, Wilcock G. Hyperinsulinaemia and
Alzheimer's disease. Age Ageing. 1994;23:396-9.
79. Erol A. An integrated and unifying hypothesis for the
metabolic basis of sporadic Alzheimer’s. Journal of
Alzheimer’s Disease. 2008;13:241-53.
80. Barkhof F, Fox NC, Bastos-Leite AJ, Scheltens P.
Vascular dementia. Neuroimaging in Dementia. Berlin:
Springer; 2011. p. 137-76.
81. Qiu WQ, Folstein MF. Insulin, insulin-degrading enzyme
and amyloid- beta peptide in Alzheimer's disease:
Review and hypothesis. Neurobiology of Aging.
82. Sadosky A, Schaefer C, Mann R, Bergstrom F, Baik R,
Parsons B, et al. Burden of illness associated with
painful diabetic peripheral neuropathy among adults
seeking treatment in the US: results from a
retrospective chart review and cross-sectional survey.
Diabetes, metabolic syndrome and obesity: targets and
therapy. 2013;6:79.
83. Kim B, McLean LL, Philip SS, Feldman EL.
Hyperinsulinemia induces insulin resistance in dorsal
root ganglion neurons. Endocrinology.
84. Poulaki V, Qin W, Joussen AM, Hurlbut P, Wiegand SJ,
Rudge J, et al. Acute intensive insulin therapy
exacerbates diabetic blood-retinal barrier breakdown via
hypoxia-inducible factor-1 betaand VEGF. J Clin
Investig. 2002;109(6):805-15.
85. Kang D-H, Kanellis J, Hugo C, Truong L, Anderson S,
Kerjaschki D, et al. Role of the microvascular
endothelium in progressive renal disease. J Am Soc
Nephrol. 2002 March 1, 2002;13(3):806-16.
86. Hamer RA, El Nahas AM. The burden of chronic kidney
disease: Is rising rapidly worldwide. BMJ.
87. Forbes JM, Coughlan MT, Cooper ME. Oxidative stress
as a major culprit in kidney disease in diabetes.
Diabetes. 2008 June 1, 2008;57(6):1446-54.
This work is licensed under a Creative Commons Attribution-Non Commercial-No Derivatives 4.0 International
License. To view a copy of this license, visit
... In addition, other important analytical pitfalls of insulin measurements in blood are related to hemolysis (may result in falsely low insulin values) and circulating anti-insulin antibodies (resulting in low insulin levels in some assays and high insulin levels in others) [45]. Insulin displays pulsatile secretion and insulin concentrations in blood oscillate with a periodicity of 5-15 min per oscillation, leading to significant changes in levels of plasma insulin in a short period of time [47,48]. Therefore, it is recommended to calculate the mean of three blood samples taken at 5 min intervals when a reliable fasting insulin level is required [48,49]. ...
... Insulin displays pulsatile secretion and insulin concentrations in blood oscillate with a periodicity of 5-15 min per oscillation, leading to significant changes in levels of plasma insulin in a short period of time [47,48]. Therefore, it is recommended to calculate the mean of three blood samples taken at 5 min intervals when a reliable fasting insulin level is required [48,49]. However, this is rarely performed in clinical practice and epidemiological studies [48]. ...
... Therefore, it is recommended to calculate the mean of three blood samples taken at 5 min intervals when a reliable fasting insulin level is required [48,49]. However, this is rarely performed in clinical practice and epidemiological studies [48]. After each meal, insulin secretion shows a short-lived peak [30]. ...
Full-text available
For many years, the dogma has been that insulin resistance precedes the development of hyperinsulinemia. However, recent data suggest a reverse order and place hyperinsulinemia mech-anistically upstream of insulin resistance. Genetic background, consumption of the "modern" Western diet and over-nutrition may increase insulin secretion, decrease insulin pulses and/or reduce hepatic insulin clearance, thereby causing hyperinsulinemia. Hyperinsulinemia disturbs the balance of the insulin-GH-IGF axis and shifts the insulin : GH ratio towards insulin and away from GH. This insulin-GH shift promotes energy storage and lipid synthesis and hinders lipid breakdown, resulting in obesity due to higher fat accumulation and lower energy expenditure. Hyperinsuline-mia is an important etiological factor in the development of metabolic syndrome, type 2 diabetes, cardiovascular disease, cancer and premature mortality. It has been further hypothesized that nutritionally driven insulin exposure controls the rate of mammalian aging. Interventions that normal-ize/reduce plasma insulin concentrations might play a key role in the prevention and treatment of age-related decline, obesity, type 2 diabetes, cardiovascular disease and cancer. Caloric restriction, increasing hepatic insulin clearance and maximizing insulin sensitivity are at present the three main strategies available for managing hyperinsulinemia. This may slow down age-related physiological decline and prevent age-related diseases. Drugs that reduce insulin (hyper) secretion, normalize pulsatile insulin secretion and/or increase hepatic insulin clearance may also have the potential to prevent or delay the progression of hyperinsulinemia-mediated diseases. Future research should focus on new strategies to minimize hyperinsulinemia at an early stage, aiming at successfully preventing and treating hyperinsulinemia-mediated diseases.
... The resulting compensatory hyperinsulinemia and IR are strongly linked to T2DM, cardio-renal metabolic syndrome [including dyslipidaemia, inflammation, coagulopathy, hypertension, non-alcoholic fatty liver disease (NAFLD)] and other conditions such as cancer and neurological disorders (17). Systemic IR plays a crucial role in the pathogenesis of DMCM causing systemic metabolic perturbations which in turn cause impairment of insulin signaling and cardiac IR (17,18). ...
... The resulting compensatory hyperinsulinemia and IR are strongly linked to T2DM, cardio-renal metabolic syndrome [including dyslipidaemia, inflammation, coagulopathy, hypertension, non-alcoholic fatty liver disease (NAFLD)] and other conditions such as cancer and neurological disorders (17). Systemic IR plays a crucial role in the pathogenesis of DMCM causing systemic metabolic perturbations which in turn cause impairment of insulin signaling and cardiac IR (17,18). ...
... Cardiac IR may develop independent of systemic factors contributing to systemic IR such as obesity and overnutrition, increase reactive oxygen species (ROS), neurohormonal and/or cytokine activation and the development of cardiac IR (17,19). ...
Full-text available
Elevated blood glucose levels, insulin resistance (IR), hyperinsulinemia and dyslipidemia the key aspects of type 2 diabetes mellitus (T2DM), contribute to the development of a certain form of cardiomyopathy. This cardiomyopathy, also known as diabetic cardiomyopathy (DMCM), typically occurs in the absence of overt coronary artery disease (CAD), hypertension or valvular disease. DMCM encompasses a variety of pathophysiological processes impacting the myocardium, hence increasing the risk for heart failure (HF) and significantly worsening outcomes in this population. Low fat (LF), calorie-restricted diets have been suggested as the preferred eating pattern for patients with HF. However, LF diets are naturally higher in carbohydrates (CHO). We argue that in an insulin resistant state, such as in DMCM, LF diets may worsen glycaemic control and promote further insulin resistance (IR), contributing to a physiological and functional decline in DMCM. We postulate that CHO restriction targeting hyperinsulinemia may be able to improve tissue and systemic IR. In recent years low carbohydrate diets (LC) including ketogenic diets (KD), have emerged as a safe and effective tool for the management of various clinical conditions such as T2DM and other metabolic disorders. CHO restriction achieves sustained glycaemic control, lower insulin levels and successfully reverses IR. In addition to this, its pleiotropic effects may present a metabolic stress defense and facilitate improvement to cardiac function in patients with HF. We therefore hypothesize that patients who adopt a LC diet may require less medications and experience improvements in HF-related symptom burden.
... Increased fragility fractures are well documented in patients with type 2 diabetes mellitus (T2DM), a condition of chronic hyperinsulinaemia [3][4][5][6][7]. Decreased skeletal bone mineral density (L-BMD) is the phenotype of "classical" osteoporosis [8,9]. ...
... Hyperinsulinaemia drives the pathogenesis of T2DM, which may precede hyperglycaemia by up to 24 years [6,16]. Hyperinsulinaemia decreases osteoblastogenesis and propagates poorer-quality collagen production, a problem further compounded by hyperglycaemia increasing glycation damage on new or existing bone collagen. ...
Full-text available
Patients with type 2 diabetes mellitus (T2DM) and/or cardiovascular disease (CVD), conditions of hyperinsulinaemia, have lower levels of osteocalcin and bone remodelling, and increased rates of fragility fractures. Unlike osteoporosis with lower bone mineral density (BMD), T2DM bone fragility “hyperinsulinaemia-osteofragilitas” phenotype presents with normal to increased BMD. Hyperinsulinaemia and insulin resistance positively associate with increased BMD and fragility fractures. Hyperinsulinaemia enforces glucose fuelling, which decreases NAD+-dependent antioxidant activity. This increases reactive oxygen species and mitochondrial fission, and decreases oxidative phosphorylation high-energy production capacity, required for osteoblasto/cytogenesis. Osteocytes directly mineralise and resorb bone, and inhibit mineralisation of their lacunocanalicular space via pyrophosphate. Hyperinsulinaemia decreases vitamin D availability via adipocyte sequestration, reducing dendrite connectivity, and compromising osteocyte viability. Decreased bone remodelling and micropetrosis ensues. Trapped/entombed magnesium within micropetrosis fossilisation spaces propagates magnesium deficiency (MgD), potentiating hyperinsulinaemia and decreases vitamin D transport. Vitamin D deficiency reduces osteocalcin synthesis and favours osteocyte apoptosis. Carbohydrate restriction/fasting/ketosis increases beta-oxidation, ketolysis, NAD+-dependent antioxidant activity, osteocyte viability and osteocalcin, and decreases excess insulin exposure. Osteocalcin is required for hydroxyapatite alignment, conferring bone structural integrity, decreasing fracture risk and improving metabolic/endocrine homeodynamics. Patients presenting with fracture and normal BMD should be investigated for T2DM and hyperinsulinaemia.
... Chronic hyperinsulinemia is a characteristic of insulin resistance; therefore, every cell in the body is influenced by the microenvironment created by this condition. 43 ...
Full-text available
Background: Chronic hyperinsulinemia is a hallmark of insulin resistance that affects a diversity of cells, including leukocytes modifying the expression of some genes involved in insulin signaling. Purpose: The aim of this study was to evaluate how hyperinsulinemia affects the expression of genes involved in the proximal insulin signaling pathway in leukocytes from 45 young individuals grouped: normal weight with not insulin resistance (NIR), with insulin resistance (IR) and with obesity (OB-IR). Methods: qPCR was performed to analyze the expression of insulin receptor (INSR), insulin receptor substrate 1 and 2 (IRS-1 and IRS-2), neutrophil elastase (NE), alpha 1 antitrypsin (A1AT), glucose transporters 1, 3 and 4 (GLUT-1, GLUT-3 and GLUT-4) by the 2-ΔCt method, and the correlation between the genes was determined by Spearman's test. Results: The mRNA expression analysis of all genes between NIR and IR individuals revealed no differences. However, when comparing NIR and IR individuals with OB-IR, an increase in NE and A1AT expression and a clear trend towards a decrease in IRS-2 expression was observed, whereas the comparison of IR and OB-IR showed a decrease in GLUT-3 expression. Overall, the correlation analysis showed that in the IR group there was a positive correlation only between NE with IRS-1 (r = 0.72, p = 0.003), while in the OB-IR group, there was a positive correlation between the NE and A1AT with INSR (r = 0.62, p = 0.01 and r = 0.74, p = 0.002, respectively) and with IRS-2 (r = 0.74, p = 0.002 and r = 0.76, p = 0.001, respectively). Conclusion: These results suggest that hyperinsulinemia and obesity are associated with changes in the expression of genes in leukocytes involved in the insulin pathway that are related to NE and A1AT.
... In addition, it is recognized that IR plays a major role in the pathophysiology of all of the metabolic diseases, cardiovascular disease, some neurodegenerative diseases, and selected cancers [22,157]. Insulin resistance is therefore considered to be the main driver for many diseases and makes a significant contribution to the chronic disease epidemic [158]. Nevertheless, being able to vary the sensitivity and physiological action of insulin is thought to have conferred a significant adaptive survival role in many animals throughout evolutionary history [146,159]. ...
Full-text available
Polycystic ovary syndrome (PCOS) is increasingly recognized as a complex metabolic disorder that manifests in genetically susceptible women following a range of negative exposures to nutritional and environmental factors related to contemporary lifestyle. The hypothesis that PCOS phenotypes are derived from a mismatch between ancient genetic survival mechanisms and modern lifestyle practices is supported by a diversity of research findings. The proposed evolutionary model of the pathogenesis of PCOS incorporates evidence related to evolutionary theory, genetic studies, in utero developmental epigenetic programming, transgenerational inheritance, metabolic features including insulin resistance, obesity and the apparent paradox of lean phenotypes, reproductive effects and subfertility, the impact of the microbiome and dysbiosis, endocrine-disrupting chemical exposure, and the influence of lifestyle factors such as poor-quality diet and physical inactivity. Based on these premises, the diverse lines of research are synthesized into a composite evolutionary model of the pathogenesis of PCOS. It is hoped that this model will assist clinicians and patients to understand the importance of lifestyle interventions in the prevention and management of PCOS and provide a conceptual framework for future research. It is appreciated that this theory represents a synthesis of the current evidence and that it is expected to evolve and change over time.
... Hyperinsulinemia can be present without significant insulin resistance and is an important independent predictor of type 2 diabetes [63]. Hyperinsulinemia and insulin resistance should therefore be considered independently, even though they are closely intertwined and usually coexist [64]. ...
Full-text available
The increasing burden of obesity plays an essential role in increased cardiovascular morbidity and mortality. The effects of obesity on the cardiovascular system have also been demonstrated in childhood, where prevention is even more important. Obesity is associated with hormonal changes and vascular dysfunction, which eventually lead to hypertension, hyperinsulinemia, chronic kidney disease, dyslipidemia and cardiac dysfunction—all associated with increased cardiovascular risk, leading to potential cardiovascular events in early adulthood. Several preventive strategies are being implemented to reduce the cardiovascular burden in children. This paper presents a comprehensive review of obesity-associated cardiovascular morbidity with the preventive diagnostic workup at our hospital and possible interventions in children.
... Once we understand the processes by which insulin is secreted in both the basal and bolus states in a healthy person, we can begin to unravel the pathologies whereby these processes are dysregulated, such as in type 2 diabetes mellitus (T2DM), cardiovascular disease (CVD), certain cancers and dementias [6]. Upon entry into beta cells, glucose is phosphorylated to glucose-6-phosphate by glucokinase (GK), an isozyme of hexokinase [12]. ...
Full-text available
Unlike bolus insulin secretion mechanisms, basal insulin secretion is poorly understood. It is essential to elucidate these mechanisms in non-hyperinsulinaemia healthy persons. This establishes a baseline for investigation into pathologies where these processes are dysregulated, such as in type 2 diabetes (T2DM), cardiovascular disease (CVD), certain cancers and dementias. Chronic hyperinsulinaemia enforces glucose fueling, depleting the NAD+ dependent antioxidant activity that increases mitochondrial reactive oxygen species (mtROS). Consequently, beta-cell mitochondria increase uncoupling protein expression, which decreases the mitochondrial ATP surge generation capacity, impairing bolus mediated insulin exocytosis. Excessive ROS increases the Drp1:Mfn2 ratio, increasing mitochondrial fission, which increases mtROS; endoplasmic reticulum-stress and impaired calcium homeostasis ensues. Healthy individuals in habitual ketosis have significantly lower glucagon and insulin levels than T2DM individuals. As beta-hydroxybutyrate rises, hepatic gluconeogenesis and glycogenolysis supply extra-hepatic glucose needs, and osteocalcin synthesis/release increases. We propose insulin’s primary role is regulating beta-hydroxybutyrate synthesis, while the role of bone regulates glucose uptake sensitivity via osteocalcin. Osteocalcin regulates the alpha-cell glucagon secretory profile via glucagon-like peptide-1 and serotonin, and beta-hydroxybutyrate synthesis via regulating basal insulin levels. Establishing metabolic phenotypes aids in resolving basal insulin secretion regulation, enabling elucidation of the pathological changes that occur and progress into chronic diseases associated with ageing.
... Insulin resistance, a cause and consequence of hyperinsulinemia, 89 leads to type 2 diabetes and is associated with other adverse outcomes, such as myocardial infarction, chronic pulmonary disease, and some cancers, 90,91 and may also be indicated in diabetic nephropathy. 92 Despite the 3 scenarios described earlier, it is commonly believed that obesity leads to hyperinsulinemia. ...
Full-text available
Importance Obesity is associated with a number of noncommunicable chronic diseases and is purported to cause premature death. Objective To summarize evidence on the temporality of the association between higher body mass index (BMI) and 2 potential mediators: chronic inflammation and hyperinsulinemia. Data Sources MEDLINE (1946 to August 20, 2019) and Embase (from 1974 to August 19, 2019) were searched, although only studies published in 2018 were included because of a high volume of results. The data analysis was conducted between January 2020 and October 2020. Study Selection and Measures Longitudinal studies and randomized clinical trials that measured fasting insulin level and/or an inflammation marker and BMI with at least 3 commensurate time points were selected. Data Extraction and Synthesis Slopes of these markers were calculated between time points and standardized. Standardized slopes were meta-regressed in later periods (period 2) with standardized slopes in earlier periods (period 1). Evidence-based items potentially indicating risk of bias were assessed. Results Of 1865 records, 60 eligible studies with 112 cohorts of 5603 participants were identified. Most standardized slopes were negative, meaning that participants in most studies experienced decreases in BMI, fasting insulin level, and C-reactive protein level. The association between period 1 fasting insulin level and period 2 BMI was positive and significant (β = 0.26; 95% CI, 0.13-0.38; I² = 79%): for every unit of SD change in period 1 insulin level, there was an ensuing associated change in 0.26 units of SD in period 2 BMI. The association of period 1 fasting insulin level with period 2 BMI remained significant when period 1 C-reactive protein level was added to the model (β = 0.57; 95% CI, 0.27-0.86). In this bivariable model, period 1 C-reactive protein level was not significantly associated with period 2 BMI (β = –0.07; 95% CI, –0.42 to 0.29; I² = 81%). Conclusions and Relevance In this meta-analysis, the finding of temporal sequencing (in which changes in fasting insulin level precede changes in weight) is not consistent with the assertion that obesity causes noncommunicable chronic diseases and premature death by increasing levels of fasting insulin.
Type 1 diabetes (T1D)-induced osteoporosis is characterized by decreased bone mineral density, bone quality, rate of bone healing, bone formation, and increased bone resorption. Patients with T1D have a 2-7-fold higher risk of osteoporotic fracture. The mechanisms leading to increased risk of osteoporotic fracture in T1D include insulin deficiency, hyperglycemia, insulin resistance, lower insulin-like growth factor-1, hyperglycemia-induced oxidative stress, and inflammation. In addition, a higher probability of falling, kidney dysfunction, weakened vision, and neuropathy indirectly increase the risk of osteoporotic fracture in T1D patients. Decreased nitric oxide (NO) bioavailability contributes to the pathophysiology of T1D-induced osteoporotic fracture. This review discusses the role of NO in osteoblast-mediated bone formation and osteoclast-mediated bone resorption in T1D. In addition, the mechanisms involved in reduced NO bioavailability and activity in type 1 diabetic bones as well as NO-based therapy for T1D-induced osteoporosis are summarized. Available data indicates that lower NO bioavailability in diabetic bones is due to disruption of phosphatidylinositol 3‑kinase/protein kinase B/endothelial NO synthases and NO/cyclic guanosine monophosphate/protein kinase G signaling pathways. Thus, NO bioavailability may be boosted directly or indirectly by NO donors. As NO donors with NO-like effects in the bone, inorganic nitrate and nitrite can potentially be used as novel therapeutic agents for T1D-induced osteoporosis. Inorganic nitrites and nitrates can decrease the risk for osteoporotic fracture probably directly by decreasing osteoclast activity, decreasing fat accumulation in the marrow cavity, increasing osteoblast activity, and increasing bone perfusion or indirectly, by improving hyperglycemia, insulin resistance, and reducing body weight.
Vanillic acid (VA) is a flavoring and nutritional agent found in many fruits and vegetables. It is an antioxidant but its nutraceutical potential has not been studied in detail. In this study, the potential of VA against hyperinsulinemia mediated changes on redox status and mitochondria in HepG2 cells were investigated. Incubation of cells with 1 μM insulin for 24 hr was found to induce insulin resistance using the inhibition of Glut2 and glucose uptake (51.9%). Hyperinsulinemia caused depletion of superoxide dismutase, glutathione, glutathione peroxidase and generation of reactive oxygen species (68%). It also caused overexpression of the receptor for advanced glycation end products (120%) and a decreases of dolichyl-diphospho-oligosaccharide-protein glycosyltransferase non-catalytic subunit (34%). Mitochondria were affected with alterations in mitochondrial transmembrane potential, aconitase activity, mitochondrial fission and fusion, biogenesis (AMPK, Sirt1 and PGC-1α) and bioenergetics (ATP and oxygen consumption). Co-treatment with VA decreased oxidative stress by reducing of reactive oxygen species and lipid peroxidation during hyperinsulinemia. Similarly, VA protected the mitochondria during insulin shock. VA also prevented glycation through the decrease of the receptor for advanced glycation end products expression. VA was found to act through the AMPK/Sirt1/PGC-1α pathway to obtain its beneficial activity. From the overall results it was concluded that VA is expected to be a potential nutraceutical which could be explored for the development of affordable nutraceuticals after detailed in vivo study.
Full-text available
Using sled dogs as exercise model, our objectives of this study were to 1) assess the effects of one acute bout of high-intensity exercise on surface GLUT4 concentrations on easily accessible peripheral blood mononuclear cells (PBMC) and 2) compare our findings with published research on exercise induced GLUT4 in skeletal muscle. During the exercise bout, dogs ran 5 miles at approximately 90% of VO2 max. PMBC were collected before exercise (baseline), immediately after exercise and after 24 h recovery.GLUT4 was measured via ELISA. Acute exercise resulted in a significant increase on surface GLUT4 content on PBMC. GLUT4 was increased significantly immediately after exercise (∼ 50%; p<0.05) and reduced slightly by 24 h post-exercise as compared to baseline (~ 22%; p>0.05). An effect of acute exercise on GLUT4 levels translocated to the cell membrane was observed, with GLUT4 levels not yet returned to baseline after 24 h post-exercise. In conclusion, the present investigation demonstrated that acute high-intensity exercise increased GLUT4 content at the surface of PBMC of sled dogs as it has been reported in skeletal muscle in other species. Our findings underline the potential use of peripheral blood mononuclear cell GLUT4 protein content as minimally invasive proxy to investigate relationships between insulin sensitivity, insulin resistance, GLUT4 expression and glucose metabolism.
Full-text available
Insulin and insulin-like growth factors (IGFs) are well known as key regulators of energy metabolism and growth. There is now considerable evidence that these hormones and the signal transduction networks they regulate have important roles in neoplasia. Epidermiological, clinical and laboratory research methods are being used to investigate novel cancer prevention and treatment strategies related to insulin and IGF signalling. Pharmacological strategies under study include the use of novel receptor-specific antibodies, receptor kinase inhibitors and AMP-activated protein kinase activators such as metformin. There is evidence that insulin and IGF signalling may also be relevant to dietary and lifestyle factors that influence cancer risk and cancer prognosis. Recent results are encouraging and have justified the expansion of many translational research programmes.
Full-text available
Advanced glycation end products (AGE) excess is one of the most important mechanisms involved in the pathophysiology of chronic diabetic complications. This review first summarizes the role of these compounds in microvascular pathogenesis, particularly in the light of recently proposed biochemical mechanisms for diabetic retinopathy, nephropathy and neuropathy. Then we focus on the relationship between AGE and metabolic memory, trying to clarify the former's role in the missing link between micro- and macrovascular complications. An excessive AGE formation has been demonstrated in the newly disclosed biochemical pathways involved in the microvascular pathobiology of type 2 diabetes, confirming the central role of AGE in the progression of diabetic neuropathy, retinopathy and nephropathy. As shown by recent studies, AGE seem to be not "actors", but "directors" of processes conducting to these complications, for at least two main reasons: first, AGE have several intra- and extracellular targets, so they can be seen as a "bridge" between intracellular and extracellular damage; secondly, whatever the level of hyperglycemia, AGE-related intracellular glycation of the mitochondrial respiratory chain proteins has been found to produce more reactive oxygen species, triggering a vicious cycle that amplifies AGE formation. This may help to explain the clinical link between micro- and macrovascular disease in diabetes, contributing to clarify the mechanisms behind metabolic memory. The pathophysiological cascades triggered by AGE have a dominant, hyperglycemia-independent role in the onset of the microvascular complications of diabetes. An effective approach to prevention and treatment must therefore focus not only on early glycemic control, but also on reducing factors related to oxidative stress, and the dietary intake of exogenous AGE in particular.
Full-text available
Against a background of an ever-increasing number of patients, new management options, and novel imaging modalities, neuroimaging is playing an increasingly important role in the diagnosis of dementia. This up-to-date, superbly illustrated book aims to provide a practical guide to the effective use of neuroimaging in the patient with cognitive decline. It sets out the key clinical and imaging features of the wide range of causes of dementia and directs the reader from clinical presentation to neuroimaging and on to an accurate diagnosis whenever possible. After an introductory chapter on the clinical background, the available "toolbox" of structural and functional neuroimaging techniques is reviewed in detail, including CT, MRI and advanced MR techniques, SPECT and PET, and image analysis methods. The imaging findings in normal ageing are then discussed, followed by a series of chapters that carefully present and analyze the key imaging findings in patients with dementias. A structured path of analysis follows the main presenting feature: disorders associated with primary gray matter loss, with white matter changes, with brain swelling, etc. Throughout, a practical approach is adopted, geared specifically to the needs of clinicians (neurologists, radiologists, psychiatrists, geriatricians) working in the field of dementia, for whom this book should prove an invaluable resource.
In a number of cases, normal glucose tolerances were associated with abnormal insulin patterns. Such situations, in which the glucose tolerance was abnormal, were considered indicative of prediabetes or occult diabetes. In order to focus greater attention upon this, the earliest detectable phase of diabetes mellitus, the term 'diabetes mellitus in situ' was proposed and used interchangeably with occult diabetes. It is the primary purpose of this paper to review basic insulin patterns which develop in the course of standard glucose tolerance testing and indicate the significance of each.
Insulin resistance is associated with diabetes mellitus, but it is uncertain whether it improves cardiovascular disease (CVD) risk prediction beyond traditional cardiovascular risk factors. We identified 15 288 women from the Women's Health Initiative Biomarkers studies with no history of CVD, atrial fibrillation, or diabetes mellitus at baseline (1993-1998). We assessed the prognostic value of adding fasting serum insulin, HOMA-IR (homeostasis model assessment-insulin resistance), serum-triglyceride-to-serum-high-density lipoprotein-cholesterol ratio TG/HDL-C, or impaired fasting glucose (serum glucose ≥110 mg/dL) to traditional risk factors in separate Cox multivariable analyses and assessed risk discrimination and reclassification. The study end point was major CVD events (nonfatal and fatal coronary heart disease and ischemic stroke) within 10 years, which occurred in 894 (5.8%) women. Insulin resistance was associated with CVD risk after adjusting for age and race/ethnicity with hazard ratios (95% confidence interval [CI]) per doubling in insulin of 1.21 (CI, 1.12-1.31), in HOMA-IR of 1.19 (CI, 1.11-1.28), in TG/HDL-C of 1.35 (CI, 1.26-1.45), and for impaired fasting glucose of 1.31 (CI, 1.05-1.64). Although insulin, HOMA-IR, and TG/HDL-C remained associated with increased CVD risk after adjusting for most CVD risk factors, none remained significant after adjusting for HDL-C: hazard ratios for insulin, 1.06 (CI, 0.98-1.16); for HOMA-IR, 1.06 (CI, 0.98-1.15); for TG/HDL-C, 1.11 (CI, 0.99-1.25); and for glucose, 1.20 (CI, 0.96-1.50). Insulin resistance measures did not improve CVD risk discrimination and reclassification. Measures of insulin resistance were no longer associated with CVD risk after adjustment for high-density lipoprotein-cholesterol and did not provide independent prognostic information in postmenopausal women without diabetes mellitus. URL: Unique identifier: NCT00000611. © 2015 American Heart Association, Inc.
Cellular interactions mediated by the neural cell adhesion molecule (NCAM) are critical in cell migration, differentiation and plasticity. Switching of the NCAM-interaction mode, from adhesion to signalling, is determined by NCAM carrying a particular posttranslational modification, polysialic acid (PSA). Regulation of cell-surface PSA-NCAM is traditionally viewed as a direct consequence of polysialyltransferase activity. Taking advantage of the polysialyltransferase Ca(2+) -dependent activity, we demonstrate in TE671 cells that downregulation of PSA-NCAM synthesis constitutes a necessary but not sufficient condition to reduce cell-surface PSA-NCAM; instead, PSA-NCAM turnover required internalisation of the molecule into the cytosol. PSA-NCAM internalisation was specifically triggered by collagen in the extracellular matrix (ECM) and prevented by insulin-like growth factor (IGF1) and insulin. Our results pose a novel role for IGF1 and insulin in controlling cell migration through modulation of PSA-NCAM turnover at the cell surface. This article is protected by copyright. All rights reserved.
Aims: Although hyperphagia is a common manifestation of diabetes mellitus, data on food craving in patients with diabetes are limited. This study compared food craving in patients with Type 2 diabetes mellitus and a control group without diabetes. Methods: A total of 210 subjects (105 with Type 2 diabetes and 105 age-, sex- and BMI-matched control subjects) participated in two food craving surveys. The surveys were as follows: the General Food Cravings Questionnaire--Trait, which assesses the general trait of food craving; and the Food Cravings Questionnaire--State, which assesses the state of food craving or current desire for high-carbohydrate or high-fat foods in response to pictures of food. Follow-up Food Cravings Questionnaire--State surveys were administered approximately 3 months later to the subjects with diabetes. Survey results were analysed to assess relationships between food craving and glycaemic control. Results: The General Food Cravings Questionnaire--Trait scores in the group with Type 2 diabetes and the control group were not significantly different. The group with Type 2 diabetes had higher carbohydrate craving scores, but lower fat craving scores, than the control group. Carbohydrate craving scores in subjects with diabetes were positively correlated with HbA(1c). In follow-up surveys, carbohydrate craving scores declined in patients with improved glycaemic control. Conclusions: The surveys showed that patients with Type 2 diabetes had higher carbohydrate cravings and lower fat cravings than the age-, sex- and BMI-matched control group. Carbohydrate craving in patients with diabetes was associated with poor glycaemic control.
The relationship between insulin and atherosclerosis is complex. People with type 2 diabetes are affected by three main glycaemic disorders: chronic hyperglycaemia; glycaemic variability; and iatrogenic hypoglycaemia. In addition to this triumvirate, the diabetic condition is characterized by lipid disorders, chronic low-grade inflammation and activation of oxidative stress. All these associated disorders reflect the insulin-resistant nature of type 2 diabetes and contribute to the development and progression of cardiovascular (CV) diseases. By both lowering plasma glucose and improving the lipid profile, insulin exerts beneficial effects on CV outcomes. In addition, insulin has several pleiotropic effects such as anti-inflammatory, antithrombotic and antioxidant properties. Insulin per se exerts an inhibitory effect on the activation of oxidative stress and seems able to counteract the pro-oxidant effects of ambient hyperglycaemia and glycaemic variability. However, insulin actions remain a subject of debate with respect to the risk of adverse CV events, which can increase in individuals exposed to high insulin doses. Evidence from the large-scale, long-term ORIGIN trial suggests that early implementation of insulin supplementation therapy in the course of glycaemic disorders, including type 2 diabetes, has a neutral impact on CV outcomes compared with standard management. Thus, the answer to the question "What impact does insulin have on atherosclerosis?" remains unclear, even though it is logical to deduce that insulin should be initiated as soon as possible and that small doses of insulin early on are better than higher doses later in the disease process.